Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE: Commemorative Conference for the 110th ... Notes in Electrical Engineering, 800) 9811659621, 9789811659621

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Lecture Notes in Electrical Engineering 800

Shengzhao Long Balbir S. Dhillon   Editors

Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of Man-Machine-Environment System Engineering

Lecture Notes in Electrical Engineering Volume 800

Series Editors Leopoldo Angrisani, Department of Electrical and Information Technologies Engineering, University of Napoli Federico II, Naples, Italy Marco Arteaga, Departament de Control y Robótica, Universidad Nacional Autónoma de México, Coyoacán, Mexico Bijaya Ketan Panigrahi, Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, Delhi, India Samarjit Chakraborty, Fakultät für Elektrotechnik und Informationstechnik, TU München, Munich, Germany Jiming Chen, Zhejiang University, Hangzhou, Zhejiang, China Shanben Chen, Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China Tan Kay Chen, Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore Rüdiger Dillmann, Humanoids and Intelligent Systems Laboratory, Karlsruhe Institute for Technology, Karlsruhe, Germany Haibin Duan, Beijing University of Aeronautics and Astronautics, Beijing, China Gianluigi Ferrari, Università di Parma, Parma, Italy Manuel Ferre, Centre for Automation and Robotics CAR (UPM-CSIC), Universidad Politécnica de Madrid, Madrid, Spain Sandra Hirche, Department of Electrical Engineering and Information Science, Technische Universität München, Munich, Germany Faryar Jabbari, Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA, USA Limin Jia, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Alaa Khamis, German University in Egypt El Tagamoa El Khames, New Cairo City, Egypt Torsten Kroeger, Stanford University, Stanford, CA, USA Yong Li, Hunan University, Changsha, Hunan, China Qilian Liang, Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA Ferran Martín, Departament d’Enginyeria Electrònica, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain Tan Cher Ming, College of Engineering, Nanyang Technological University, Singapore, Singapore Wolfgang Minker, Institute of Information Technology, University of Ulm, Ulm, Germany Pradeep Misra, Department of Electrical Engineering, Wright State University, Dayton, OH, USA Sebastian Möller, Quality and Usability Laboratory, TU Berlin, Berlin, Germany Subhas Mukhopadhyay, School of Engineering & Advanced Technology, Massey University, Palmerston North, Manawatu-Wanganui, New Zealand Cun-Zheng Ning, Electrical Engineering, Arizona State University, Tempe, AZ, USA Toyoaki Nishida, Graduate School of Informatics, Kyoto University, Kyoto, Japan Federica Pascucci, Dipartimento di Ingegneria, Università degli Studi “Roma Tre”, Rome, Italy Yong Qin, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China Gan Woon Seng, School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore Joachim Speidel, Institute of Telecommunications, Universität Stuttgart, Stuttgart, Germany Germano Veiga, Campus da FEUP, INESC Porto, Porto, Portugal Haitao Wu, Academy of Opto-electronics, Chinese Academy of Sciences, Beijing, China Walter Zamboni, DIEM - Università degli studi di Salerno, Fisciano, Salerno, Italy Junjie James Zhang, Charlotte, NC, USA

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Shengzhao Long Balbir S. Dhillon •

Editors

Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of Man-Machine-Environment System Engineering

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Editors Shengzhao Long Astronaut Research and Training Centre of China Beijing, China

Balbir S. Dhillon Department of Mechanical Engineering University of Ottawa Ottawa, ON, Canada

ISSN 1876-1100 ISSN 1876-1119 (electronic) Lecture Notes in Electrical Engineering ISBN 978-981-16-5962-1 ISBN 978-981-16-5963-8 (eBook) https://doi.org/10.1007/978-981-16-5963-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

In 1981, under the directing of the great scientist Xuesen Qian, an integrated frontier science—Man-Machine-Environment System Engineering (MMESE)— came into being in China. Xuesen Qian gave high praise to this emerging science. In the letter to Shengzhao Long, he pointed out, “You are creating this very important modern science and technology in China!” in October 22nd, 1993. In the congratulation letter to the commemoration meeting of the 20th anniversary of establishing the Man-Machine-Environment System Engineering, the great scientist Xuesen Qian stated, “You have made active development and exploration in this new emerging science of MMESE, and obtained encouraging achievements. I am sincerely pleased and hope you can do even more to make prosper development in the theory and application of MMESE, and make a positive contribution to the progress of science and technology in China, and even in the whole world” on June 26th, 2001. October 22nd, which is the day that the great scientist Xuesen Qian gave high praise to MMESE, was determined to be Foundation Commemoration Day of MMESE by the 2nd conference of the 5th MMESE Committee on October 22nd, 2010. On this very special day, the great scientist Xuesen Qian pointed out in the letter to Shengzhao Long, “You are creating this very important modern science and technology in China!”. The Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of MMESE & The 21st International Conference on MMESE will be held in Beijing, China on October 23–25 of this year; hence, we will dedicate Man-Machine-Environment System Engineering: Proceedings of The 21st International Conference on MMESE—the Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of MMESE to our readers. Man-Machine-Environment System Engineering: Proceedings of The 21st International Conference on MMESE—the Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of MMESE is the academic showcases of the Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of vii

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MMESE & The 21st International Conference on MMESE held by Beijing KeCui Academe of MMESE in Beijing, China. The Man-Machine-Environment System Engineering: Proceedings of The 21st International Conference on MMESE—the Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of MMESE is consisted of 120 more excellent papers selected from more than 600 papers. Due to limitations on space, some excellent papers have been left out, we feel deeply sorry for that. Crudeness in contents and possible incorrectness are inevitable due to the somewhat pressing editing time, and we hope you kindly point them out promptly, and your valuable comments and suggestions are also welcomed. Man-Machine-Environment System Engineering: Proceedings of The 21st International Conference on MMESE—the Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of MMESE will be published by Springer-Verlag, German. Springer-Verlag is also responsible for the related matters on index of Index to EI, so that the world can know the research quality and development trend of MMESE theory and application. Therefore, the publication of Man-Machine-Environment System Engineering: Proceedings of The 21st International Conference on MMESE—the Commemorative Conference for the 110th Anniversary of Xuesen Qian’s Birth and the 40th Anniversary of Founding of MMESE will greatly promote the vigorous development of MMESE in the world and realize the grand object of “making positive contribution to the progress of science and technology in China, and even in the whole world” proposed by Xuesen Qian. We would like to express our sincere thanks to Springer-Verlag, German, for their full support and help during the publishing process. July 2021

Shengzhao Long

Organization

Program and Technical Committee Information General Chairman Shengzhao Long

Astronuat Research and Training Center of China

Program Committee Chairman Balbir S. Dhillon

University of Ottawa, Canada

Technical Committee Chairman Enrong Mao

College of Engineering, China Agricultural University, China

Program and Technical Committee Members Yanping Chen Hongfeng Gao Michael Greenspan Birsen Donmez Xiangshi Ren Kinhuat Low Baiqiao Huang Baoqing Xia Chenming Li Fang Xie Guangtao Ma

University of Management and Technology, USA University of California, USA Queen’s University, Canada University of Toronto, Canada Kochi University of Technology, Japan Nanyang Technological University, Singapore System Engineering Research Institute of China State Shipbuilding Corporation, China Weapon Industrial Hygiene Research Institute, China The Quartermaster Research Institute of Engineering and Technology, China China North Vehicle Research Institute, China Shenyang Jianzhu University, China

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Haoting Liu Hongjun Xue Lijing Wang Long Ye Qichao Zhao Qing Liu Weijun Chen Xiaochao Guo Yongqing Hou Yanqi Wang Yinying Huang Yuhong Shen

Organization

University of Science and Technology Beijing, China Northwestern Polytechnical University, China Beijing University of Aeronautics and Astronautics, China Beijing Jiaotong University, China Beijing King Far Technology Co., Ltd., China Jinggangshan University, China Shanghai Maritime University, China Institute of Aviation Medicine, Air Force, China China Academy of Space Technology, China Weapon Industrial Hygiene Research Institute, China Agricultural Bank of China, China The Quartermaster Research Institute of Engineering and Technology, China

Contents

Pandect Man-Machine-Environment System Engineering and Its Historical Mission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shengzhao Long and Yinying Huang

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40-Year Development of Man-Machine-Environment System Engineering from Scientific Papers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiaochao Guo, Jian Du, Yu Pu, Qingfeng Liu, Yanyan Wang, and Jie Li

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Research on the Man Character Research on the Comprehensive Evaluation Method of Pilot Workload During Flight Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hongjiao Wu, Bao Lv, and Yi Jiao

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Investigating the Effects of Face Mask and Gender on Interpersonal Distance Judgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mingyue Wang and Yu-Chi Lee

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Analysis of the Degree of Information Exchange Among Team Members in a Ccontrol Cabin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Liping Pang, Yitong Ren, Chenyuan Yang, Ye Deng, and Xin Wang

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The Influence of Modafini on the Visual Function of 16-hour Simulation Flight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dawei Tian, Feng Wu, Xiaoquan Zhu, Kaibo Zhang, Wenge Wang, Peiyi Chen, Yunhan Liu, Lue Deng, and Yongsheng Chen Study on Changes of Visual Function Before and After 24 hours Simulated Flight Visual Fatigue Protection . . . . . . . . . . . . . . . . . . . . . . Dawei Tian, Fengfeng Mo, Xiaobin Yan, Yange Zhang, Feng Wu, Shan Chen, Xianliang Zhao, Jing Huang, and Lue Deng

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Research Status of Neck Pain in Ergonomic Area . . . . . . . . . . . . . . . . . Menglu Li, Hongyan Yi, Lixia Niu, and Jie Li Effects of 8-hour Simulated Flight on Cognitive Function and Performance of Volunteers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Feng Wu, Dawei Tian, Hua Ge, Andong Zhao, Xuan Li, Shuang Bai, Xueqian Deng, Quan Wang, and Lue Deng Study on Countermeasures of Psychological Tension During Electroencephalogram Examination of Pilot Selection . . . . . . . . . . . . . . Yongsheng Chen, Xinxin Shang, Xiaoquan Zhu, Haitao Zhang, Jianling Pang, Li Li, Xueqian Deng, Huiming Qi, and Dawei Tian Application of Fuzzy Mathematics Method in Sensory Evaluation of Military Ready-to-Eat Meat Sticks . . . . . . . . . . . . . . . . . . . . . . . . . . . Huiling Mu, Peng Du, Shuang Bai, Ximeng Chen, Peng Liu, Feng Li, Hongjiang Jing, Falin Li, and Ruoyong Wang Risk Factors Analysis and Health Management Countermeasures of Dyslipidemia of Flight Personnel in 2020 Annual Physical Examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Peng Liu, Shuang Bai, Ximeng Chen, Huiling Mu, Ruoyong Wang, Feng Li, Hongjiang Jing, and Peng Du Effect of Different Muscle-Enhancing Supplement Programs on Muscle Strength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Huiling Mu, Ruoyong Wang, Xichen Geng, Yan Xu, Shuang Bai, Ximeng Chen, Longmei Fang, Lili Zhang, Peng Liu, Feng Li, Hongjiang Jing, and Peng Du Effects of Muscle-Enhancing Nutrition Support on Anthropometric Indexes After Anti-G Physical Training . . . . . . . . . . . . . . . . . . . . . . . . . Peng Du, Ruoyong Wang, Xichen Geng, Yan Xu, Shuang Bai, Ximeng Chen, Longmei Fang, Lili Zhang, Xiaoli Zhang, Baohui Li, Peng Liu, Feng Li, Hongjiang Jing, and Huiling Mu

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Investigation on Dietary Structure and Nutritional Health Status of Cadets in Air Force Youth Aviation School . . . . . . . . . . . . . . . . . . . . 108 Longmei Fang, Guangyun Wang, Ruoyong Wang, Shuang Bai, Dongyun Fen, Bingqian Guo, Qiao Ye, Huiling Mu, Yuan Luo, Zhusong Mei, Ximeng Chen, and Peng Du Study on Biomechanical Response and Subjective Fatigue Symptoms of Human Body Wearing Personal Protective Equipments . . . . . . . . . . 116 Yuhong Shen, Chenming Li, and Ting Zou

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A Rapid Objective Method of Fatigue Detection for Air Traffic Controller Before Duty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Zhenling Chen, Jianping Zhang, Xiaoxia Zhou, Pengxin Ding, Yanzhong Gu, and Bo Wang Preliminary Development of Mental Health Checklist for Flight Personnel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Yan Zhang, Jingjing Gong, Yishuang Zhang, Yang Liao, and Liu Yang Preliminary Validity Analysis of Pilot Psychological Competence Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Yan Zhang, Yang Liao, Yishuang Zhang, and Liu Yang Identification of Mechanical Impedance Parameters of Human Upper Limbs Using Mechanical Perturbation Method . . . . . . . . . . . . . . . . . . . 141 Huaiwu Zou, Haoran Tao, Zhou Zhou, and Bingshan Hu Comparative Analysis Research of Occupational Mental Health Assessment Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Zhongxi Guan, Yanqiu Sun, Jianwu Chen, Jiexiong Zhou, Bin Yang, Pei Wang, and Zhili Wang The Form of Competency Model of Pilots by Job Analysis . . . . . . . . . . 155 Yang Liao, Yan Zhang, and Huamiao Song Psychological Health and Self-management During Epidemic Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Yu Luo, Jiang Shu, Qian Liu, Mengxi Li, and Xuechen Yao Research on Screening Methods for People Susceptible to Motion Sickness and Fatigue After Long Voyage . . . . . . . . . . . . . . . . . . . . . . . . 166 Shuang Nie, Dawei Tian, Yanan Huang, Tianyu Zheng, Jie Zhang, Peng Ding, Bohan Zhang, Hui Shen, and Fengfeng Mo A Retrospective Analysis of Dietary Pattern Changes of Chinese Aircrew from Year of 1963 to 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Ximeng Chen, Peng Du, Huiling Mu, Shuang Bai, Zhenyao Song, Peng Liu, Feng Li, Hongjiang Jing, Longmei Fang, Falin Li, and Ruoyong Wang Sensory Evaluation of Fuzzy Mathematics in Sticky Soup Food . . . . . . 179 Ximeng Chen, Peng Du, Huiling Mu, Shuang Bai, Zhenyao Song, Peng Liu, Feng Li, Hongjiang Jing, Longmei Fang, Falin Li, and Ruoyong Wang The Evaluation of Cognitive Control Ability Under the Variable Operation Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Yang Liao, Yishuang Zhang, Yan Zhang, Duanqin Xiong, Xueqian Deng, Juan Liu, and Liu Yang

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Correlation Between EEG Band Power and Behavioral Performance Based on Dichotic Listening Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 Yang Liao, Yuyang Zhu, Jian Du, Rong Lin, and Liu Yang Sensory Evaluation of Mixed Juice Drinks Based on Fuzzy Mathematical Evaluation Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Shuang Bai, Peng Du, Huiling Mu, Ximeng Chen, Longmei Fang, Juan Liu, Hua Guo, Feng Wu, Yubin Zhou, Dalong Guo, Dalong Liu, Feng Li, Hongjiang Jing, Ying Liu, Falin Li, and Ruoyong Wang Discussion on the Cultivation of Talents for Intelligent Warfare . . . . . . 204 Qian Liu, Jinxin Li, and Jiwen Sun Study on the Regular Changes of Training Effect of Autonomic Nervous Stability of Flight Personnel . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Jian Du, Yishuang Zhang, Duanqin Xiong, Qinglin Zhou, Yang Liao, Yan Zhang, Juan Liu, and Liu Yang Experiment and Evaluation of Occupant Cognitive State Based on Situational Awareness Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Fang Xie, Sijuan Zheng, Xiaoping Jin, Dongwei Zhao, and Chunlin Liu A Preliminary Research on Energy Expenditure Assessment with 24-hour Life Observation Method and Activity Recorder Method . . . 226 Feng Li, Huijuan Zhu, Hongjiang Jing, Ruoyong Wang, Shuang Bai, Huiling Mu, Ximeng Chen, and Peng Du Investigation on Psychological Service of Military Pilots . . . . . . . . . . . . 233 Yishuang Zhang, Yan Zhang, Yang Liao, Juan Liu, Xueqian Deng, and Liu Yang Research on Preventive Methods for Human Errors of Marine Nuclear Power Plant Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Chuan Wang, Ziying Wang, and Shenghang Xu Analysis of Ship Operator's Operation Ability and Research on Prevention of Human Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Chuan Wang, Xiao Han, Shenghang Xu, Guangjiang Wu, Xi Lu, Ziying Wang, and Zhongfeng Gao Fatigue Index of ATC in Number Recognition Task . . . . . . . . . . . . . . . 255 Qiuhong Piao, Xianggang Xu, Wei Fu, Jianping Zhang, Wei Jiang, Xiang Gao, Zhenling Chen, and Pengxin Ding Research on Situational Awareness of Crew Warnings Based on GDTA and FCM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260 Wang Lijing, Xiaonan Shi, Yu Zhu, and Yanzeng Zhao Research on a Fatigue Detection Method Based on Phoneme . . . . . . . . 268 Qian Zhang, Weining Fang, Jian Li, Haifeng Bao, and Xingdong Zhao

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Study on EEG Channel Selection for Visual Manipulation Tasks . . . . . 278 Hongquan Qu, Min Liu, Liping Pang, Hongbin Qu, and Ling Wang An Experimental Study on the Impact of Customer Feedback on the Performance of E-commerce Customer Service Personnel . . . . . . 285 Xiaofang Yuan, Ling Li, and Yuanhang Liang Research on the Machine Character Modular Cleaning Set Design Based on Ergonomics . . . . . . . . . . . . . . . 297 Xiaoxuan Zhao, Min Lu, and Runsen Wang Design and Research of Female Anti-mistaken Touch Alarm Based on Ergonomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 Xiaoxuan Zhao, Han Li, Yaning Zhu, and Min Lu Man-Machine Analysis and Design of Handheld Infrared Thermometer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Hangling Liu, Huiran Ye, and Qiao Guo Research and Practice on Renovation and Reuse of Historic Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322 Zhen Li, Heng Chen, and Fang Liu Optimization Design and Development of Working Face Support Selection System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 Zhenlong Lu Test Evaluation of Thermal Protection Performance of FlameRetardant Protective Clothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 Chenming Li, Yuhong Shen, Liying Liu, Mei Tong, and Feng Li The Research on the Efficiency of UAV Swarm Anti-UAV Swarm Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Hongyan Ou, Di Wu, Shuxin Wang, Junfei Wang, Jifeng Wang, and Yuming Huang Research on Operational Capability and Countermeasures of the U.S. UAV Swarm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Weixin Liu, Haijun Ma, Yanyan Ding, Hao Liu, Hongyan Ou, and Hao Jiang Research on Low Resistance Ventilation Handle of a Welding Torch Based on Numerical Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353 Youchun Wang, Jianwu Chen, Pei Wang, Bin Yang, and Dongwei Zhao Research on Cabin Load Evaluation of Two Types of Transport Aircraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361 Xuan Li, Zhigang Jiao, Jiakang Zhang, Hua Guo, and Feng Wu

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Intelligent Process Parameter Tuning of Laser Cleaning Based on Image Feature Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 Haoting Liu, Na Zheng, and Jiacheng Li The Improved Artificial Bee Colony Method and Its Application on UAV Disaster Rescue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Ming Lv, Haoting Liu, Yajie Li, Lixuan Li, and Yun Gao Using an Electrochemical Immunosensor Based on Polypyrrole Nanowire Arrays/Carboxyl Graphene Composite Modified Microelectrodes to Detect Periodontal Bacteria . . . . . . . . . . . . . . . . . . . 382 Zhenhua Pei Safety Design to Underwater Robotic Arm . . . . . . . . . . . . . . . . . . . . . . 389 Shang Huan, Jiangang Chao, Yan Zhang, Jiahong She, Liangliang Han, Jian Yang, and Deli Zhang The Perceived Recoil Force on Shooter During Rifle Shooting Using MFF Pressure Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 Yong Cheng, Yaping Wang, Long He, Xinrui Wang, and Yu Bai Analysis of Heat Transfer of a Multiscale Turbulence Model . . . . . . . . 407 Jianxin Yuan, Zhong Shi, and Lei Bai Numerical Investigation of Impinging Jets Flow Using a Multiscale Turbulence Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 Zhong Shi, Jianxin Yuan, and Lei Bai Research on the Fin Performance of Air-Oil Heat Exchanger for Aircraft Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419 Hang Zhang, Ying Wang, Liping Pang, and Zhe Xu Research on the Environment Character Safety Control of Gas Displacement in the Environmental System of Space Station Experiment Rack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 Dongcai Guo, Qiang Sheng, Liang Guo, and Qinglin Zhu Numerical Simulation of Mixing Unit Performance of Civil Aircraft Environmental Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 Yifei Yang, Chao Liu, and Shenghua Yang Modeling and Simulation of Supersonic Parachute Inflation in Mars Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 Miao Zhao, Sijun Zhang, Zhang Zhang, Qi Wang, Yu Liu, and Jian Li Investigation on Real Environment Simulation Method and Ground Test Technology of Lunar Landing and Ascending . . . . . . . . . . . . . . . . 452 Zhang Zhang, Mingzhang Tang, Zhihui Lv, Miao Zhao, and Yu Liu

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Research on Urban Financial Ecological Environment Assessment Based on Principal Component Analysis . . . . . . . . . . . . . . . . . . . . . . . . 459 Shuqi Wan Ergonomics Evaluation of Home Office Environment . . . . . . . . . . . . . . 466 Nuo Xu, Yanqiu Sun, Jianwu Chen, Zhili Wang, Zhenfang Chen, Bin Yang, Pei Wang, and Jiexiong Zhou Numerical Simulation on Diffusion Law of Welding Fume in a Welding Workshop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474 Xin Wang, Bin Yang, Jianwu Chen, Pei Wang, and Miao Zhang Research on Combined Ventilation Technology in Large Painting Workshop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Bin Yang, Jianwu Chen, Menghui Xiao, Lindong Liu, Yanqiu Sun, and Jie Xie Study on Toxic Control Technology of Combined Ventilation for Internal Painting of Large Work Pieces . . . . . . . . . . . . . . . . . . . . . . 488 Jianwu Chen, Zhaochun Yang, Bin Yang, Yanqiu Sun, Lindong Liu, and Menghui Xiao Development of Lighting Effect Evaluation Method for Hospital Ward . . . 496 Yajie Li and Haoting Liu Modeling and Simulation Analysis of Explosive Decompression Test for Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504 Fang Hu, Chen Yu, Xuewei Wang, Tengfei Ma, and Shouqing Huang Steady-State Optimization of the Configuration of the Air-Borne Liquid Cooled Vapor Cycle Refrigeration System . . . . . . . . . . . . . . . . . 511 Liping Pang, Desheng Ma, and Shuxin Li Research on the Man-Machine Relationship Research on Icon Layout of On-Board Information Interface Under the Influence of Driver’s Visual Resource Allocation . . . . . . . . . . . . . . . 521 Zhengjun Li and Hao Yu Research on Readability of Automotive Instrument Information Based on Vibration Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Zhengjun Li and Zhicheng Jian Research on Users’ Satisfaction of App Interface of Mobile Phone Business Hall Based on Kano Model and Eye Movement Tracking . . . . 536 Yuqing Deng, Hechen Zhang, Mengyang Ren, and Zhongxia Xiang The Usability of Guidance System at Intersections in Different Directional Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545 Danting Zhao, Jun Ma, Leibing An, and Bowen Wang

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Design and Analysis of Man-Machine System of Ticket Gate in Changzhou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555 Qianying Yang, Ziyan Liu, and Jiao Yang Influence of Human Factors on the Operation Performance of a Certain Type of Equipment and Countermeasures . . . . . . . . . . . . . 562 Hongyan Ou, Yanyan Ding, Lei Tang, Hao Liu, Weixin Liu, and Jiantao Liu Man-Machine Interface Design Analysis of Multi-function Printing (Copying) Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569 Fangzichun Chen, Xinyue Shao, and Ting Qiu Construction of Ergonomic Evaluation System for Display and Control Characteristics of Aircraft Cockpit Touch Panel . . . . . . . . 577 Lijing Wang, Yanzeng Zhao, and Yu Zhu Research on the Matching of Advertisement and Interface Background Color of Online Shopping App: Based on Eye Movement Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 585 Chunhong Zhang, Yunying Luo, Lingyun Wu, and Shaofeng Deng Analysis and Design Method of Ship Command Cabin Layout . . . . . . . 593 Aiguo Lu, Xiaoye Tong, Bo Dong, and Chao Yang Multi-channel Interactive Intelligent Fusion Technology in Shipborne Command and Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 600 Aiguo Lu, Xiaoye Tong, and Bo Dong Research on the Man-Environment Relationship Design and Optimization of Air Supply System to Satisfy the Thermal Comfort of Human Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609 Jue Qu, Hongjun Xue, Wei Wang, Sina Dang, and Xiaoyan Zhang Muscle-Force Prediction Using an Improve AlexNet Under the Simulated Microgravity Environment . . . . . . . . . . . . . . . . . . . . . . . 617 Yuan Wang and Haoting Liu Modeling Research of Solar Illumination for Automotive Head-Up Display Testing Based on Chinese Population’s Driving Postures . . . . . 624 Lipeng Qin, Shouxi Wu, Peiwen Zuo, Shuoying Lv, and Zhicheng Tang The Change of Brain Activity Under Lower Body Negative Pressure Condition Examined by Time-Frequency Analysis of EEG Signals . . . . 632 Yang Liao, Zhanghuang Chen, Yuyang Zhu, Yishuang Zhang, Yan Zhang, and Liu Yang

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Driving Behavior Analysis for Pedestrian Collision Avoidance Under Emergency Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 638 Quan Yuan, Qingkun Li, and Wenjun Wang Effect of Cognitive Load on Urban Spatial Discrimination: An Eye Movement Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 645 Ge Chen, Xu Dong, Jiaxiao Li, Fenling Liu, and Liangyu Mi Research on the Machine-Environment Relationship Influence of High Cold Mountain Environment on Vehicle-Mounted Charged Equipment and Countermeasures . . . . . . . . . . . . . . . . . . . . . . 655 Luan Cheng, Jinkuang Zhang, Wei Zhao, Yawen Chen, Yaqiong Li, Xiaolong Chang, and Mingjie Wan Research on the Impact of Ground Vortex on Wing-mounted Nacelle Drainage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 662 Jiawei Zheng and Lizhe Wang Research on the Overall Performance of Man-Machine-Environment System Study on the Evaluation Method of Aircraft Ergonomics Defect Consequence During Flight Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671 Hongjiao Wu, Haijing Song, and Yuqi Zhang Driving Safety Assessment on Standard Deviation of Lateral Position and Time Exposed Time-to-Collision Measures Under Driving in Left-Hand and Right-Hand Traffic Conventions . . . . . . . . . . . . . . . . 681 Feina Wen and Yu-Chi Lee Explore the Impact of Consumer Perception Product Attributes on the Household Appliance User Experience Based on Usability Testing . . . . 688 Jing Liang, Xin Xin, and Yue Lv Research on Functional Training of Combat Physical Fitness Generation of Special Operations Forces . . . . . . . . . . . . . . . . . . . . . . . . 698 Chunlai Wang Fire Risk Assessment and Application in Business Circle Based on ISM-BN Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 706 Qiquan Wang, Ziqi Bao, Yuze Cui, Hao Wu, Hongwen Yu, Chen Wen, and Fan Xu VR Technology and Its Application in Financial Mathematics Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 714 Shuqi Wan

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Research on Workflow of Safety Risk Management in Army Training . . . 719 Zhenguo Mei, Weifei Wu, Peng Gong, Qian Shen, and Kun Cao Research on Safety Management of Warfighting-Oriented Training . . . 726 Kun Cao, Zhenguo Mei, Peng Gong, and Yongzhou Tang A Hierarchical Decision-Making Design in Human-Machine Interaction for Intelligent Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 733 Peng Zhang, Baiqiao Huang, Pengyi Zhang, and Kunfu Wang Traffic Flow Prediction Model Based on Deep Learning . . . . . . . . . . . . 739 Bowen Wang, Jingsheng Wang, Zeyou Zhang, and Danting Zhao Research on Quantitative Method of Traffic Safety Credit Score Based on Ridge-Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 746 Bowen Wang, Jingsheng Wang, Benyu Wang, Runzheng Wang, and Xichu Xue Research on Training Method of Information Processing Ability of Military Pilots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 753 Liu Yang, Yishuang Zhang, Yan Zhang, Yang Liao, Jian Du, and Xichen Geng Research on Intelligent Support of Anti-aircraft Gun Based on Remaining Service Life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 760 Jinxin Li, Qian Liu, Binghai Zhang, and Jiwen Sun Test Pilot Selection for Human System Integration of Advanced Fighter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 766 Xiaochao Guo, Yanyan Wang, Qingfeng Liu, Duanqin Xiong, Jian Du, and Xueqian Deng Research on the Promotion Effect of Emotional Cues on Target Search . . . 773 Juan Liu, Shuang Bai, Lei Yang, Wei Pan, Han Li, Jian Du, Jiabo Ye, Yubin Zhou, Rong Lin, and Duanqin Xiong A Decoupling Simulation Method for Complex Multi-form Vehicle-Vulnerable Road User Crash Cases . . . . . . . . . . . . . . . . . . . . . . 780 Quan Yuan, Junwei Zhao, and Tiefang Zou Automated Driving Simulation Platform Design on Collision Avoidance Decision Making for Vulnerable Road Users . . . . . . . . . . . . 787 Xiang Si and Quan Yuan The Advantages, Difficulties and Countermeasures of MilitaryCivilian Integration to Improve Management Efficiency . . . . . . . . . . . . 792 Shenghang Xu, Xiaojun Wang, Chuan Wang, and Xiao Han Quantitative Research on the Complexity of Pilot Operation Procedures Based on TACOM Method . . . . . . . . . . . . . . . . . . . . . . . . . 798 Lijing Wang, Yu Zhu, and Yanzeng Zhao

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Research and Application on Quantitative Evaluation Method of Maintenance Ergonomics for Fighter Cockpit . . . . . . . . . . . . . . . . . . 805 Haijing Song and Jue Wang Service Design of Vehicle System Based on Ergonomics . . . . . . . . . . . . 812 Jiahe Zhang, Xiaoyu Kang, and Zhenming Wu Design of Man–Machine Cooperative Assembly Line Based on Mathematical Model and Simulation . . . . . . . . . . . . . . . . . . . . . . . . . 818 Chaoan Lai and Jianying Yao A Framework for Intelligent Fitness Guiding System . . . . . . . . . . . . . . . 826 Haohao Yang, Jin Chen, Lian Shen, Yuwei Liang, and Yu-Chi Lee Research on the Reliability of ANRINC429 Bus Based Cabin Pressure Regulation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 833 Ying Wang, Hang Zhang, Liping Pang, and Shunv Zhang Research on Text Visual Effect of Multimedia Courseware for Mobile Online Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 841 Zhendong Liu and Beihai Wang Classroom Teaching Details Design Adapted to the Characteristics of Equipment and Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 848 Jianfeng Li, Jinxin Li, Jiwen Sun, Junlong Guo, and Tao Li Study on Humanized Design of a Fire Control System . . . . . . . . . . . . . 854 Jiwen Sun, Heyuan Hao, Jinxin Li, Junlong Guo, JianFeng Li, and Tao Li Theory and Application Research Analysis and Design of Road Safety Protection Guardrail Based on Man-Machine-Environment System . . . . . . . . . . . . . . . . . . . . . . . . . . 861 Danlan Ye and Wen Zhang Interaction Design of Display and Control Equipment Based on Man-Machine-Environment System Engineering . . . . . . . . . . . . . . . . 869 Kunfu Wang, Jian Su, Peng Zhang, Baiqiao Huang, and Wei Feng Research on Design Method of Man-Machine- Environment System in Product Processing Based on MMESE . . . . . . . . . . . . . . . . . . . . . . . . 878 Wobo Zhang Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 885

Biography of Editors in Chief

Professor Shengzhao Long He is the founder of the Man-Machine-Environment System Engineering (MMESE), the chairman of the Man-Machine-Environment System Engineering (MMESE) Committee of China, the chairman of the Beijing KeCui Academy of Man-Machine-Environment System Engineering (MMESE), and the former director of Ergonomics Lab of Astronaut Research and Training Center of China. In October 1992, he is honored by the National Government Specific Allowance. He graduated from the Shanghai Science and Technology University in 1965, China, and in 1981, directing under famous Scientist Xuesen Qian, founded MMESE theory. In 1982, he proposed and developed Human Fuzzy Control Model using fuzzy mathematics. From August of 1986 to August of 1987, he conducted research in Man-Machine System as a visiting scholar at Tufts University, Massachusetts, USA. In 1993, he organized Man-Machine-Environment System Engineering (MMESE) Committee of China. He published “Foundation of theory and application of Man-Machine-Environment System Engineering” (2004) and “Man-Machine-Environment System Engineering” (1987) and edited “Proceedings of the 1st–20th Conference on Man-Machine-Environment System Engineering” (1993–2020). e-mail: [email protected] Dr. Balbir S. Dhillon He is a professor of Engineering Management in the Department of Mechanical Engineering at the University of Ottawa, Canada. He has served as a chairman/director of Mechanical Engineering Department/Engineering Management Program for over ten years at the same institution. He has published over 345 (i.e., 201 journal + 144 conference proceedings) articles on reliability, safety, engineering management, etc. He is or has been on the editorial boards of nine international scientific journals. In addition, he has written 34 books on various aspects of reliability, design, safety, quality, and engineering management published by Wiley (1981), Van Nostrand (1982), Butterworth (1983), Marcel Dekker (1984), Pergamon (1986), etc. His books are

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being used in over 85 countries, and many of them are translated into languages such as German, Russian, and Chinese. He has served as a general chairman of two international conferences on reliability and quality control held in Los Angeles and Paris in 1987. He has served as a consultant to various organizations and bodies and has many years of experience in the industrial sector. At the University of Ottawa, he has been teaching reliability, quality, engineering management, design, and related areas for over 29 years, and he has also lectured in over 50 countries, including keynote addresses at various international scientific conferences held in North America, Europe, Asia, and Africa. In March 2004, he was a distinguished speaker at the Conf./Workshop on Surgical Errors (sponsored by White House Health and Safety Committee and Pentagon), held at the Capitol Hill (One Constitution Avenue, Washington, D.C.). He attended the University of Wales where he received a BS in electrical and electronic engineering and an MS in mechanical engineering. He received a PhD in industrial engineering from the University of Windsor. e-mail: [email protected]

Pandect

Man-Machine-Environment System Engineering and Its Historical Mission Commemorating the 40th Anniversary of the Founding of Man-Machine-Environment System Engineering Shengzhao Long1(B) and Yinying Huang2 1 China Astronaut Research and Training Center, Beijing 100193, China

[email protected] 2 Head Office of the Agricultural Bank of China, Beijing 100005, China

Abstract. In 1981, under the direction of great Scientist Xuesheng Qian, ManMachine-Environment System Engineering (MMESE), a comprehensive marginal science, came into being in China. MMESE is a science that uses system science theory and system engineering method to correctly handle the relations among man, machine and environment and deeply research the optimal combination of man-machine-environment system. Great scientist Xuesen Qian spoke highly of this emerging science. He wrote to MMESE founder Prof. Shengzhao Long on October 22, 1993, saying, “It is in China that you have created this important modern science and technology!” To commemorate the 40th anniversary of the founding of the MMESE, this paper comprehensively and incisively discusses the MMESE in terms of the formation and development of the MMESE, the research content and implementation methods, characteristics and contributions, relations with some related disciplines, the application fields and the historical mission, so that readers can deeply understand and actively apply MMESE theories promote the progress of science and technology and the prosperous development of productivity in the world! Keywords: Man character · Machine character · Environment character · Man-Machine-Environment System · Man-Machine-Environment System Engineering

1 Formation and Development of MMESE The history of the development of human society is a history in which three elements of man, machine (including tools, machines, systems and technologies) and environment correlate with, restrict and promote each other (Fig. 1). Due to the influence of environment, higher primates evolved into mankind; the birth of mankind led to the emergence of machine; the emergence of machine produced a new environment; the new environment is affecting human life, work and survival. Today, when people are immersed in enjoying the social prosperity brought about by high technology, they have unconsciously fell into two pitfalls: First, when designing © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 3–20, 2022. https://doi.org/10.1007/978-981-16-5963-8_1

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Fig. 1. Schematic diagram of interaction among man, machine and environment

machine, due to ignoring the characteristics and requirements of people, the efficiency of the work system is reduced and accidents increased, causing serious impacts on social development; Second, when designing machine, due to ignoring the characteristics and requirements of the environment, not only is the performance of the machine itself adversely affected, but also serious environmental deterioration resulted, posing a major threat to human life, work and survival. Take the automobile as an example. On the one hand, the advent of automobile has greatly promoted the social progress, on the other hand, it has also brought disasters to societies, as there are about 250,000 people killed in road traffic accidents every year in the world; At the same time, it is also one of the main factors causing urban pollution. There are many other similar examples. Therefore, the top priority is to research and explore a set of scientific methods to research the operation law and the optimal combination of the three elements of man, machine and environment. It is by adapting to this social demand that MMESE embarked on the historical arena of science and technology! [1]. Strictly speaking, the emergence of MMESE as a theory and a science took place in the early 1980’s. However, the ancient roots of MMESE can be traced back to the early human activities. Therefore, the formation and development of MMESE has gone through a long historical stage. It can be considered that before 1940’s, MMESE was in its infancy; from 1940’s to 1970’s, MMESE was in its preparation. Therefore, the formation and development of MMESE has gone through a long historical stage. Since ancient times, human beings have continuously improved their labor tools generation after generation until large-scale use of machines, so as to improve their ability to conquer nature and transform the world. When human beings first used simple tools to do a lot of heavy manual labor, the issue of optimal combination of man–machineenvironment system was brought forward objectively. The first industrial revolution and subsequent energy revolution in the 18th and 19th century brought mankind into the machine age, where the labor people engaged in changed greatly in complexity and load, giving rise to complex relations among man, machine and environment. In early

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twentieth century, F.W. Taylor put forward the operation method for people research through the shovel experiment and developed a corresponding operation system, called the “Taylor System” [2]. Later, people began to conduct experimental research on the relations among man, machine and environment in an organized manner, and accumulated a lot of relevant data. In the 1940’s, especially during the Second World War, all kinds of new weapons appeared constantly, and their performance became more and more complex; In the 1950’s, the application of electronic computers developed rapidly; In the 1960’s, a breakthrough was made in manned spaceflight activities. All these made the research of the relations among man, machine and environment appear more prominent. Therefore, numerous discipline names such as Human Factors, Human Engineering, Engineering Psychology, Ergonomics, Human Factor Engineering and Man Machine System emerged in succession, and experimental data and experience of man, machine and environment were accumulated from different aspects and angles, thus creating conditions for the formation of MMESE theory. However, in this period, the focus of research work is how to make people adapt to machine and environment. Although there is some knowledge about how to adapt machine design to the characteristics and needs of human beings, and how to transform and control the environment, we lack a systematic, holistic viewpoint to comprehensively solve the problem of the interrelations among man, machine and environment. Although there are various kinds of data about human beings, machine and environment, how to use these data is still based on experience, thereby making it difficult to obtain the best effect. At the end of 1980, the National Academy of Sciences of the US formed a special committee at the request of the army, navy and air force to particularly analyze and research the current research status in this field, with a special report titled “Research Requirements for Human Factor” put forward in January 1983 [3]. The report admits that in the 1970’s, the slackening of basic research due to relying solely on the data of the past two decades led to a number of major design and development mistakes. Consequently, some adjustments were made to the arrangements for scientific research. However, due to the lack of advanced scientific theory as a guide, it has not yet got rid of the traditional constraints. In 1981, under the personal guidance of great scientist Xuesen Qian, Prof. Shengzhao Long put forward the scientific concept of MMESE, marking the formation of this emerging discipline [4]. MMESE is a science that uses the theory of system science and the method of system engineering to correctly deal with the relations among man, machine and environment and deeply research the optimal combination of man-machine-environment system. “Man” in the system refers to the person as the implementer of work (such as operators or decision makers); “Machine” refers to the collective term of all subjects (including tools, machines, systems and technologies) controlled by the person; “Environment” refers to the specific working conditions in which man and machine coexist. The basic goal of the optimal combination of man-machine-environment system is “safety, efficiency and economy”. “Safety” refers to absence of physiological harm or injury to human body and avoiding various accidents; “Efficiency” means that the whole system has the best working performance or the highest working efficiency;

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“Economy” means that the establishment of the system needs to be most cost effective while meeting the technical requirements of the system. Since the founding of MMESE, it has developed prosperously in China, and has been widely used in military and civilian fields. In October 1984, the Equipment Development Department of the Central Military Commission (formerly the State Commission of Science and Technology for National Defense Industry, the same below) established the MMESE Military Standardization Technical Committee; In May 1986, the Equipment Development Department of the Central Military Commission listed “weapon equipment MMESE research” as a key project of defense science and technology application and basic research; In April 1987, the Equipment Development Department of the Central Military Commission established the MMESE specialized group; In October 1993, the MMESE Specialized Committee of the Systems Engineering Society of China was established. From 1993 to 2008, the first to the eighth Chinese MMESE conferences were held respectively, publishing and issuing the 1st –8th volumes of MMESE Research Progress. All these efforts have greatly promoted the prosperous development of MMESE theory and application in China [5]. The birth of MMESE also caused good repercussions in the world. In October 1984, the paper Application of MMESE Theory in Aviation by Shengzhao Long et al. was read out at the 32nd International Congress of Aviation & Space Medicine, well received and recognized by scholars all over the world. Scholars believe that this paper is very enlightening in theory, and guiding the research work using MMESE theory is highly creative. At the same time, they also believe it is very necessary to consider the environment as a part of the whole system, which greatly concerns people’s work efficiency. Therefore, it is indeed pioneering to research man, machine and environment as a system entirety, which provides a new mode for practice. Portugal also included the paper in the military yearbook of that year; American and Japanese scholars also attached great importance to this scientific theory. They believe that this is a creation by Chinese people; A Mexican scholar taught MMESE to his students, which aroused their great interest; During his visit to China in 1985, Japanese scholar Ichiro Saito had academic exchanges and study tours with Chinese scholars regarding MMESE and published an article in the Japanese Journal of Aerospace and Environmental Medicine, praising the development of MMESE in China; In 1992, a paper Research on the Overall Analysis Method for Man-Machine-Environment System by Shengzhao Long et al. was presented at the 18th International Science Conference; In 1998, the paper MMESE Theory and Its Application by Shengzhao Long et al. was presented at the Sino-French Conference on Man and Automation. From 2009 to 2012, the 9th to 12th MMESE conferences were held, and the 9th to 12th Man-Machine-Environment System Engineering: Proceedings of the Conference on Man-Machine-Environment System Engineering was published and issued by Scientific Research Publishing, USA: From 2013 to 2020, MMESE international conference was held once a year, and the 13th–20th Man-Machine-Environment System Engineering: Proceedings of the International Conference on MMESE was published an disused by German publishing house Splinger, which has been subjected to core retrieval EI for 8 consecutive sessions. All of these also helped accelerate the go-global pace of MMESE theory [5].

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2 Research Content and Implementation Methods of MMESE 2.1 Research Content of MMESE The research content of MMESE consists of seven aspects (Fig. 2):

Fig. 2. Research contents of MMESE

1. Research of man character. It mainly includes research of working ability of man, test and evaluation of basic qualities of man, research of physical load, mental load and psychological load of man, research of human reliability, research of human mathematical model (control model and decision-making model), research of human body measurement technology, research of personnel selection and training, etc. 2. Research of machine character It mainly includes research of operability and maintainability of machine, the modelling technology of the controlled object dynamics, research of the error proofing design of machine, etc. 3. Research of environment character. It mainly includes research of environmental detection technology, environmental control technology and environmental modelling technology, etc.

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4. Research of man-machine relation. It mainly includes three aspects: static manmachine relation research, dynamic man-machine relation research and the application of multimedia technology in man-machine relation research. The research of static man-machine relation mainly includes the layout and design of operation domain; the research of dynamic man-machine relation mainly includes the research of function allocation between man and machine (comparative research of man and machine functions, research of method for function allocation between man and machine, artificial intelligence research) and man-machine interface research (research of display and control technologies, research of man-machine interface design and evaluation techniques), etc. 5. The research of man–environment relation. It mainly includes the effects of environmental factors on man, and research of individual protection measures, etc. 6. Research of machine–environment relation. It mainly includes the effects of environmental factors on machine performance and the effects of machine on environment. 7. Research of the overall performance of man-machine-environment system. It mainly includes the research of the overall mathematical model of the man-machineenvironment system, research of the full mathematical simulation, semi-physical simulation and full physical simulation techniques of the man-machine-environment system, and the analysis, design and evaluation of the overall performance (safety, efficiency and economy) of the man-machine-environment system. 2.2 Implementation Method of MMESE The implementation method of MMESE can be summarized as four sentences and 24 words [4], namely: Based on three theories (control theory, model theory and optimization theory), analyzing three elements (man, machine and environment), going through three steps (scheme decision-making, development and production, actual use) and realizing three goals (safety, efficiency and economy). 2.2.1 Based on Three Theories (Control Theory, Model Theory and Optimization Theory) The fundamental contribution of control theory is that it breaks the boundary between life and nonlife by using general concepts and terms such as system, information and feedback, allowing people to research the three subjects of man, machine and environment from a unified point of view and scale, which are completely different and unrelated in material properties, and to make them an inseparable organic whole. Model theory can provide a complete set of mathematical analysis tools for MMESE research. Obviously, MMESE requires not only qualitative but also quantitative depiction of the whole system’s law of motion. Therefore, it is necessary to introduce appropriate mathematical models for different objective subjects, and use mathematical language to clarify the objective laws of the real world through modeling, parameter identification, simulation and testing, among other steps. The basic starting point of optimization theory is that, in the optimal combination of man-machine-environment system, there are always many different methods and

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approaches, of which one or several must be best or better. Such a view and idea of seeking the optimal approach is exactly the essence of MMESE. The optimization theory is exactly the mathematical means to embody this essence. 2.2.2 Analysis of Three Elements (Man, Machine and Environment) The analysis of the three elements of man, machine and environment mainly looks into how to use these three elements to form a man- machine-environment system that we need and has specific functions. Generally, according to the performance characteristics and complexity of various systems, man-machine-environment systems can also be divided into three types: a. Simple man-machine-environment systems In such systems, an operator uses only one machine to work in a specific environment. b. Complex man-machine-environment systems A characteristic of this kind of systems is that one operator can operate more than two machines, or one or more machines can be used by several operators at the same time. c. Generalized (or large scale) man-machine-environment systems This kind of systems widely exists in various production departments. The top decision maker of each production department (i.e. “man” in the broad sense) implements unified management and scheduling of the production status of subordinate basiclevel units (i.e. “machine” in the broad sense) through a set of command/control systems, which is a typical kind of man-machine-environment systems in the broad sense. 2.2.3 Going Through Three Steps (Scheme Decision-Making, Development and Production, Actual Use) Scheme decision-making belongs to the category of theoretical analysis, and it is also the most critical step. In this stage, MMESE can provide a complete set of decision-making theories for the overall scheme design of man-machine-environment system, in which the most essential task is to establish respective mathematical models of man, machine and environment and the overall model of the system, and carry out the mathematical simulation and optimization calculation of the whole system with the help of computers, so as to determine the optimal parameters of man, machine and environment and the optimal combination scheme of the system. In the development and production stage, the task of MMESE is to determine the best way to achieve the optimal scheme. In this stage, it is always emphasized that people should be involved in the system as the implementer of work, the overall and local performance of the man-machine-environment system continuously analyzed and tested through semi physical simulation or full physical simulation, and the technical indicators of each subsystem coordinated to achieve the best state of the overall performance. In the actual use stage, the task of MMESE is to put forward opinions about giving full play to the existing system performance (such as the standards of operator selection and the scheme and plan of training operators) through the verification of actual use, so

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as to make full use of materials and personnel across the board, and put forward new suggestions for further improving the system performance. 2.2.4 Achieving Three Goals (Safety, Efficiency and Economy) Generally speaking, it is difficult and sometimes contradictory to meet the three targets of safety, efficiency and economy at the same time. Therefore, in order to use the system engineering method to achieve the three goals of safety, efficiency and economy for the man-machine-environment system we built, we must first assume several design schemes, and then use the full mathematical simulation, semi-physical simulation or full physical simulation method for each scheme to determine the optimal scheme. After studying the feasibility (or realizability) of the system scheme, the optimal scheme can be decided ultimately. The scheme so selected is an ideal one.

3 Characteristics and Contributions of MMESE 3.1 Three Characteristics of MMESE First, MMESE particularly emphasizes that the machine design should meet the characteristics and requirements of man. In the past, there was a misunderstanding that as long as the machine was designed, the system performance could be brought into play by selecting and training operators. In fact, if the machine design does not meet the characteristics and requirements of people, making people adapt to the characteristics of the machine simply through selection and training not only can not ensure the system performance, but also would lead to serious accidents. Therefore, MMESE first emphasizes that the machine design should conform to the characteristics of man, and then emphasizes adapting man to the characteristics of the machine through selection and training, so as to optimize the coordination between man and machine; Second, one of the fundamental differences between MMESE and other related disciplines is that environmental factors are no longer excluded from the system as a passive interference factor, but included in the system as a positive active factor and become an important part of the system. Practice has proved that only when the environment is regarded as a moving part of the system can we plan and control the environment comprehensively from the overall height of the system. Some can be eliminated, some can be protected, some can be reduced to the allowable limit, and some can obtain the optimal value, thus bringing the whole system into the optimal working state; Third, guided by the scientific methodology of materialist dialectics, MMESE particularly emphasizes the top-to-bottom, general-to-detailed systematic thinking, and follows the thinking process of systemization—restoration—re-systemization—rerestoration and even cyclic rise, organically combining the system view and restoration view. MMESE abandons the previous metaphysical view that as long as a single element is good, its overall performance will surely be good. Instead, according to materialist dialectics, from the overall height of the system, it researches the interrelations and the overall change law of the three elements of man, machine and environment, thus promoting the development of science and technology.

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3.2 Three Contributions of MMESE First, MMESE has made a new leap in understanding the world and transforming the world. Xuesen Qian once stressed, “MMESE is a very important work, because in the past we could only expound the issues of spirit and material, subjective and objective, people and weapons from the perspective of philosophy,. It seems that there is no way to materialize them, nor are there quantitative or strict scientific analyses. Although those words are right from the perspective of philosophy, they should be used concretely. For example, in the field of defense science and technology, it is not a scientific problem and cannot be solved using scientific methods, calculation methods, and analysis methods.……The MMESE you brought forward combines man, machine and the whole objective environment rather than considering man and environment individually. This is dialectics. It is comprehensive and dialectical. Therefore, the idea you brought forward - MMESE - is of far-reaching significance to defense science and technology” [4]. Practice has proved that it is quite difficult to realize the optimal combination of man, machine and environment. The reason is that the research of the three elements of man, machine and environment originally belonged to different disciplines, and their research methods and approaches are quite different. Now, in order to combine them into a complex, gigantic system, there must be a theory that can describe the performance, interrelations and operation law of man, machine and environment. Without such a theory as the guidance, there would be no in-depth research of the whole man-machine -environment system, let alone the optimal design of the whole system. The MMESE theory came into being exactly in response to this reality. Therefore, the birth of MMESE theory enables people to gradually transit from general qualitative description of the relations between spirit and material, subjective and objective and man and machine from the philosophical perspective to quantitative description based on the dialectical materialism principle of Marx and fully using the essence of modern science. There are not only the basis of scientific theory, but also the method of scientific recording, and more importantly the measures to give full play to people’s positive role. With its active application in various fields, people can make a new leap from qualitative to quantitative and from perceptual knowledge to scientific experimental research in their practical activities of understanding and transforming the world, thus allowing people’s practical activities to leap in three aspects: ➀ From experience to science; ➁ From unconsciousness to consciousness; ➂ From qualitative to quantitative. This can not only avoid a lot of rework of engineering technology and huge economic losses, but also greatly accelerate the process of understanding and transformation of the world. Second, MMESE provides scientific methods for the healthy and sustainable development of human society. As mentioned earlier, the history of the development of human society is a history in which man, machine (including tools, machines, computers, systems and technologies) and environment interrelate with, restrict and promote each other. Therefore, by using the theory of man-machine-environment system engineering,

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we can grasp the operation law and optimal combination method of man, machine and environment, thus ensuring the healthy and sustainable development of human society. Third, MMESE provides technical means for the development of social productivity. Generally, the philosophical definition of productivity is: “the combination of people engaged in the production of material means and the means of labor consisting mainly of production means and are used in production constitutes social productivity.” Obviously, productivity should be an organic combination of three elements of man (people engaged in material production), machine (production tools and machines) and environment (relevant working conditions in production places). Therefore, the use of MMESE method can optimize the relations among man, machine and environment across the board and promote the prosperous development of social productivity. As mentioned earlier, one century ago, that is, in 1898, Frederic W. Talor, a famous American scholar known as “father of management”, conducted a famous “shovel operation experiment. He shoveled the same pile of coal with four kinds of shovels with the same shape and different capacities (each weighing 5 kg, 10 kg, 17 kg and 30 kg respectively). Although the shovels of 17 kg and 30 kg are large, the experimental results show that the 10 kg shovel is more efficient in doing the job. Then he did many experiments, finally finding the best design and the most appropriate weight of every shovel in moving loose granular materials such as coal dust, iron chips, sand and iron ore, thus greatly improving the productivity of labor. In 1911, Taylor published the Principles of Scientific Management, which became an important literature in scientific management. Taylor’s shovel experiment is also the embodiment of the early budding thought of MMESE theory. Because MMESE theory especially emphasizes that machine design should conform to human characteristics, only in this way can labor productivity be greatly improved, an idea exactly proven by his experiments. Generally, in order to apply MMESE theory to corporate production activities, we must first start with the simplest man-machine-environment system, as shown in Fig. 3 [5]. As we all know, Marx’s Das Kapital starts from dissecting the most basic cell of capitalism—commodity, thus exposing the law of development of capitalist societies. Similarly, when we describe people’s production activities, we must also start from the most common and basic elements of production - simple man-machine-environment system. At the bottom of Fig. 3 is the most typical simple man-machine-environment system. On the basis of the research of the simple man-machine-environment system, followed by the research of the complex man-machine-environment system, and finally the research of social groups of production, namely generalized man-machine-environment system, only in this way can we fully reveal the operation law of social production activities, thereby laying a scientific foundation for comprehensively improving social productivity.

Man-Machine-Environment System Engineering and Its Historical Mission

13

Tiptop Decision-Maker

S1

S1

S2

S2

Si

Sm

Skeleton Administrant

Machine Operator

Production Envir.

S1

S2

Sn

Production Machine

Fig. 3. Relationship between productive forces and man, machine & environment

4 The Relation Between MMESE and Some Related Disciplines As mentioned earlier, the birth of MMESE is related to and drew rich nourishments from Human Factors, Human Factor Engineering, Ergonomics and Man-machine System…. but it is both associated with and different from these disciplines. It not only includes a wider range of contents (especially the consideration of environmental factors), but also particularly emphasizes dealing with problems from a higher level of the system as a whole. Newton once said, “If I can understand a little bit more than others, it is because I stand on the shoulders of giants” [6]. Similarly, the advent of MMESE is not to negate or replace other related disciplines, but to raise these roughly similar or complementary research categories to a higher level and a broader horizon for analysis and synthesis, so as to bring people’s understanding level to a whole new stage. This paper focuses on the connections and differences between MMESE and some well-known disciplines, such as ergonomics, man-machine system and environmental medicine. 4.1 Relations with Ergonomics Ergonomics is a science emerging after the Second World War. Ergonomics is a combination of the Greek words ergon (i.e., work or labor) and nomos (i.e., laws or rules).

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Therefore, ergonomics can be defined as a discipline of researching the working law of human beings. Its early research mainly focused on anthropometry and human biomechanics. Later, its research content was expanded. At present, it covers human ability, human limitations and so on. Moreover, Human Factors and Ergonomics have been used interchangeably in the United States. We can see from the research content of MMESE (see Fig. 2) that the research of man character is closely associated with the research content of ergonomics. Obviously, in order to analyze, design and evaluate the overall performance (safety, efficiency and economy) of man-machine-environment system, it is necessary to first develop a full understanding of man character, that is, it is necessary to conduct a comprehensive research of man character from the perspective of ergonomics or human factors. Only in this way can the basic goal of MMESE be achieved. The biggest difference between MMESE and ergonomics is that it deals with the relations among man, machine and environment from the perspective of the system entirety, rather than solely emphasize the optimization of human factors or ergonomics requirements. This is because, according to MMESE’s point of view, a good single factor can not guarantee the good overall performance of the system and that all elements of the system should be standardized according to the overall performance of the system, with some indicators even required to make some concessions. The design of Apollo lunar module is an obvious example [7]. In the initial design, two astronauts were sitting and even if four windows were opened, the view of astronauts in their seats was very limited. If they lowered to the moon in an inclined posture, the astronauts would not be able to directly see the landing site; If you want to land the moon vertically, you can’t even see the moon surface, so this design is neither safe nor efficient, and the lunar module is heavy. No ideal solution was found after two years of efforts thereafter, so everyone was frustrated and debates were fierce. One engineer complained that the astronauts’ seats were too heavy and occupied too much space! Another engineer immediately said that why had to be seated since it took only about an hour or less for the lunar module to descend from the mother-ship to the lunar surface. Can’t they stand through this short trip?! Unexpectedly, this complaint opened up a new way of thinking for a new design scheme, and immediately everyone agreed to the “standing” idea. In this way, astronauts can maintain their eyes close to the window, which not only reduces the window area, but also expands the field of vision, as well as reduced the weight of the whole cabin. This is truly a safe, efficient and economical design. This example tells us that a person does not have to be in the “best” working state and little concessions made in a one part of the system can be traded for great superiority of the whole system. But in this period, because of the absence of MMESE theory as guidance, people only met the requirements of human work from the perspective of human factors (ergonomics) without considering problems from the overall system, so the design work has taken a detour. Therefore, MMESE not only emphasizes obtaining all kinds of data about man character from the perspective of ergonomics (i.e. working law of man), but also more emphasizes using these data from the strategic perspective of the system, thus making the man-machine-environment system meet the comprehensive effectiveness of “safety, efficiency and economy”.

Man-Machine-Environment System Engineering and Its Historical Mission

15

4.2 Relations with Man-Machine System Man-machine system is a discipline of researching the interaction between man and machine. The research content of man-machine system overlaps that of man-machine relation in MMESE (see Fig. 2). However, there are huge differences between MMESE research and man-machine system research, mainly manifested in two aspects: First, MMESE research first particularly emphasizes that the design of machines (including tools, machines, systems and technologies) should meet the requirements of man (that is, “machine is suitable for man”), and then emphasizes that man should be enabled to adapt to machines through selection and training (that is, “man is suitable for machine”). However, the research of man-machine system mainly focuses on “man is suitable for machine”. The U.S. Defense Technology Program of 1996 pointed out: “The field of man-machine system technology gathers together human science, physiology, biology, behavioral science, bioengineering and other disciplines, involving all aspects of man in combat activities……Man-machine system technology provides the opportunities and skills needed to ensure proper selection, training, outfitting (equipment) and protection of all forces that can adapt to (operational) development trends” [8]. Obviously, the research focus of man-machine system is “man is suitable for machine”, rather than “machine is suitable for man”. Second, MMESE research particularly emphasizes that environmental factors are included in the system as a positive and active factor, and become an important part of the system; while man-machine system research places the environment as an interference factor out of the system, which will lead to serious consequences. For example, according to British media reports [9], in the autumn of 2001, the British army held a three-month military exercise codenamed “Fast Sword” in Oman to test its operational capabilities. The results are as follows: “Challenger II” tank broke down due to the filter being blocked by sand and dust after only 4 h of fighting, and half of the tanks had to withdraw from the fighting; “Lynx” helicopter’ rotating shaft blade has a working life of 500 h under European climate conditions, but only 27 h in the desert……Soldiers’ uniforms and boots melted and disintegrated due to the heat, and some other’s feet festered. Obviously, the excellent performance of the system can be ensured only when the three factors of man, machine and environment are considered together. Moreover, only by taking the environment as a moving part of the system can we plan and control the environment comprehensively from the overall height of the system in a way that some can be eliminated, some protected, some reduced to the allowable limit, and some given the best value, thus allowing the whole system to remain in the optimal working state. This fundamentally eliminates the passive situation of addressing issues by taking only stopgap measures and allows people’s production practice to always move forward along the scientific road. 4.3 Relation with Environmental Medicine Environmental medicine is a discipline of researching the effects of environmental factors on population health [10]. It takes the environment and population health as the subject, clarifies the factors harmful to human health and existing in the environment, reveals the formation conditions of environmental pollution, destruction and pathogenic factors,

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the law of action on human body, and the early reaction and harm of injury. It can be seen from Fig. 2 that the research content of environmental medicine is similar to that of man-environment relation in MMESE. However, there are two obvious differences between MMESE research and environmental medicine research. Firstly, MMESE research covers a wide range of environmental changes, and divides the effects of environmental factors on people into four limits: comfort limit, work efficiency limit, tolerance limit and safety limit. However, environmental medicine research is dedicated to seeking the pathogenic conditions of environmental factors and considers problems more within the limits of tolerance and safety. Therefore, MMESE can deal with the relation between man and environment from a higher angle and a wider scope. In addition, MMESE research particularly emphasizes the effects of composite environmental factors on man. As we all know, mankind always live in an environment in which multiple factors act at the same time or in succession; moreover, the effects of multiple environmental factors on human body would produce compound effects that can not be replaced by a single factor, mainly including interaction as the manifestation of compound effects (additive, synergistic, antagonistic) and human reactions. Therefore, the research of the composite effects of various environmental factors on human body is not only more in line with the objective existence but also has more practical application value for clarifying the relation between man and environment, the characteristics and laws of action of environmental factors on human body.

5 Application Fields of MMESE On October 22, 1993, Xuesen Qian pointed out in his letter to Prof. Shengzhao Long: “I have received the MMESE Research Progress (Volume I) edited by you and feel very happy after reading it. I put forward an idea in the autumn of 1985 (which refers to Xuesen Qian’s October 21, 1985 speech at the Institute of Aerospace Medical Engineering). Now eight years later, it has become a book of more than 500 pages! And the scope of research has far exceeded the original field of space, involving aviation, aerospace, weapons, electronics, energy, transportation, electricity, coal, metallurgy, sports, rehabilitation, management and other fields! It is in China that you pioneered this important modern science and technology” [4]. Xuesen Qian’s affectionate words depict a magnificent blueprint for the application fields of MMESE. MMESE believes that any work system with human participation can be defined as a man-machine-environment system. Moreover, according to the performance characteristics and complexity of various systems, the man-machine-environment system can be divided into three types: simple (or single person, single machine), complex (or multiperson, multi-machine) and generalized (or large-scale). Therefore, although MMESE is a new frontier technology science, it has penetrated into all fronts of the national economy. According to the application fields pointed out by Xuesen Qian above, Table 1 lists the characteristics of man-machine-environment system in each application field. In the practical application in various fields, the specific functions and connotations of humanmachine-environment system should be clearly defined according to the characteristics of specific application objects, so as to achieve the best application effect.

Man-Machine-Environment System Engineering and Its Historical Mission

17

Table 1. Schedule of MMESE application fields Application area National defense construction

Transportation

Application object

Three elements of man-machine-environment system Man

Machine

Environment

Aerospace

Astronaut

Spacecraft and equipment

Overweight, weightlessness, shock, loneliness

Aviation

Pilot

Aircraft and equipment

Overweight, shock, high temperature, hypoxia……

Navigation

Boatman

Ships, submarines and equipment

Harmful gas, vibration, noise, underwater high pressure

Weapon

Armored forces

Armored vehicles and equipment

High temperature, high humidity, vibration, noise, harmful gas

Operational command

Commander

Combat forces

Operational environment (terrain, features, climate,…)

…

…

…

…

Aircraft

Pilot

Civil aircraft

High temperature, hypoxia, noise……

Automobile

Driver

Car

Interior environment, road condition and climate……

Train

Driver

Train

Interior environment, road condition and climate

Shipping

Driver

Ship

Noise inside the ship, temperature and humidity, water condition outside the ship……

…

…

…

… (continued)

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S. Long and Y. Huang Table 1. (continued)

Application area Industrial production

…

Application object

Three elements of man-machine-environment system Man

Machine

Environment

Coal

Coal worker

Coal digging equipment

Vibration, noise, dust, high temperature, high humidity……

Steel

Steelmaker

Steel-making equipment

High temperature, noise……

Production management

Managers at all levels

Production groups

Internal and external environments of production (physical environment, marketing environment)……

…

…

…

…

…

…

…

…

6 Historical Mission of MMESE On June 26, 2001, great scientist Xuesen Qian pointed out in his congratulatory letter to the 20th anniversary of the founding of the man- machine-environment system engineering: “Over the past 20 years, you have actively explored in the emerging scientific field of man-machine -environment system engineering, and have made very gratifying achievements, for which I feel sincerely happy. I hope you will continue to work hard in the future to promote the vigorous development of the theory and application of man–machine-environment system engineering, and make positive contributions to the progress of science and technology in China and even the world!” [4]. In order to fulfill the historical mission of making positive contributions to the progress of world science and technology as proposed by Xuesen Qian, we should seriously do five aspects of work well: 6.1 Continuously Strengthen International Academic Exchanges to Make the World Know and Understand MMESE From 2013 to 2020, we have held the 13th–20th “International MMESE Conference” for 8 consecutive years, and the 13th-20th International MMESE Conference Proceedings published by Springer Publishing House of Germany has been subjected to EI core search for 8 consecutive sessions, which marks a solid step for MMESE to go global. In the future, we should redouble our efforts to fully demonstrate the features and style of MMESE with the help of “International MMESE Conference”, so that the world can know, understand and apply this scientific theory.

Man-Machine-Environment System Engineering and Its Historical Mission

19

In addition, we should also vigorously promote and disseminate MMESE theory by taking part in international conferences, publishing academic papers in journals, exchanging lectures or jointly training graduate students, and greatly accelerate the pace of MMESE going global. 6.2 Actively Enrich and Improve the Basic Theories As mentioned earlier, the advent of MMESE is not to negate or replace other related disciplines, but to raise some roughly similar or complementary research areas to a higher level and a broader horizon for analysis and synthesis, so as to bring the research level of this field to a whole new stage. Therefore, MMESE practitioners must constantly absorb and learn from the fruitful achievements of other related disciplines, draw rich nutrition from other related disciplines, and strive to explore, enrich and improve the basic theories of MMESE in order to continuously accelerate the maturity process of MMESE. 6.3 Comprehensively Strengthen Application Research On October 1993, Xuesen Qian wrote to Prof. Shengzhao Long, pointing out that: “the scope of (MMESE) research has far exceeded the original field of space, covering the fields of aviation, space, weapons, electronics, energy, transportation, power, coal, metallurgy, sports, rehabilitation and management!” These affectionate words depict an ambitious blueprint for MMESE application. We must strengthen its promotion and application in various fields. 6.4 Attach Great Importance to Laboratory Construction There is an old Chinese saying, “if you want to do something well, you must first sharpen your tools”. The basic task of MMESE is to correctly deal with and research the respective performance, interrelations and overall change law of man, machine and environment from the overall height of man-machine-environment system. In order to truly achieve this, we must have the corresponding experimental equipment and experimental base in place to provide necessary technical means for MMESE research. 6.5 Further Expand the Building of Talented Personnel There are two possible ways to expand the construction of talented personnel: The first is to train the scientific and technological workers engaged in MMESE theory and application research to become MMESE experts or MMESE engineers through professional training; the second is to train a group of key practitioners from colleges and universities, so as to lay a foundation for the formation of talented personnel.

7 Conclusions It can be firmly believed that, as long as we continue to take MMESE theory as the guidance, we can greatly promote the comprehensive application of MMESE in the world, thereby promoting the progress of science and technology and the prosperous development of productivity in the world!

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References 1. Chen, H., Long, S.: A summary introduction to man-machine-environment system engineering. Proceedings. Inst. Space Medico-Eng. 3 (1981). Also see: J. Nat. 8(1) (1985) 2. Taylor, F.W.: The Principles of Scientific Management (1911) 3. U.S. National Academy Press: Research Needs for Human Factors. U.S. National Academy Press, Washington, D.C. (1983) 4. Qian, X.: Xuesen Qian’s important discourse about man-machine-environment system engineering. In: Long, S. (ed.) Advance for Man-Machine-Environment System Engineering, vol. 5. Ocean Press, Lancing (2001) 5. Long, S., et al.: Foundation of Theory and Application of Man-Machine-Environment System Engineering. Science Press, Beijing (2004) 6. Li, D.: The “Secret” Of Success—The Scientific Invention. China Youth Publishing House, Beijing (1980) 7. Shang, P.: A word is broken—Apollo design fun talk. Space (3) (1981) 8. China National Defense Science and Technology Information Center. Department of Defense Technology Program (1996) 9. Li, Q.: British equipment is afraid to enter the desert. In: China Television News (International edn), no. 16 (2002) 10. Chai, H., Lu, S.: Environmental Medicine. China Environmental Science Press (1990)

40-Year Development of Man-Machine-Environment System Engineering from Scientific Papers Xiaochao Guo1(B) , Jian Du1 , Yu Pu1 , Qingfeng Liu1 , Yanyan Wang1 , and Jie Li2 1 Air Force Medical Center of FMMU, Beijing 100142, China 2 Liaoning Technical University, Liaoning, China

Abstract. There were totally 1749 scientific papers published in proceedings of conferences on Man-Machine-Environment System Engineering (MMESE) during 1993 to 2020 since the MMESE was founded in 1981 by guidance of Xuesen Qian with system engineering thought. The results were found by data analysis that 27.90%, 10.29%, 9.26%, 9.89%, 11.78%, 2.69%, 20.01% of the papers were in the subdomains of MMESE named as the Man Character, the Machine Character, the Environment Character, the Man-Machine Relationship, the Man-Environment Relationship, the Machine-Environment Relationship, the Overall Performance of Man-Machine-Environment System in addition to 7.66% under title of Theory and Application Research and 0.51% of Pandect. In the last decade, MMESE went much faster especially in 5.75% growth on the Machine Character, and trend was better and better for internationalization with efforts of main contributors such as the first authors of the papers, publishers, and MMESE committee of SESC. Keywords: Man-Machine-Environment System Engineering (MMESE) · System Engineering · The Man Character · The Machine Character · The Environment Character · The Man-Machine Relationship · The Man-Environment Relationship · The Machine-Environment Relationship · The Overall Performance of Man-Machine-Environment System · Ergonomics · Human factors

1 Introduction In 1978, the original Chinese system engineering thought was brought out by the famous scientist, Mr. Xuesen Qian, with integration of operation research, management science, systems analysis, systems research, and cost effectiveness analysis [1]. The ManMachine-Environment System Engineering (MMESE) was then founded in 1981 by guidance of Mr. Qian with system engineering thought [6], and divided into seven subdomains by Professor Shengzhao Long [2] (Fig. 1). The MMESE has been developing more and more robust for 40-years driven by the Man-Machine-Environment System Engineering Committee under System Engineering Society of China (SESC). The MMESE committee had held 8 conferences once two years © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 21–28, 2022. https://doi.org/10.1007/978-981-16-5963-8_2

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Fig. 1. Seven subdomains of MMESE research

from 1993 to 2007 and 12 conferences during 2009 to 2020 every year to publish totally 20 books showing the advances in MMESE domain [2–21]. The scientific papers in the books were investigated to discover the evolvement of MMESE in China and its internationalization in this paper.

2 Method 2.1 Scientific Papers on MMESE There were 1749 papers sampled from the 20 books published by Beijing Science and Technology publishing (1993, 1995, 1997) [2–4] in Chinese, China Ocean Press (1999, 2001, 2003, 2005) [5–8] in Chinese, Publishing House of Electronics Industry (2007) [9] in Chinese with bilingual contents and abstracts, Scientific Research Publishing USA (2009~2012) [10–13] in bilingual edition, and Springer (2014~2020) [14–21], which fell into the Man Character, the Machine Character, the Environment Character, the Man-Machine Relationship, the Man-Environment Relationship, the MachineEnvironment Relationship, the Overall Performance of Man-Machine-Environment System in addition to the other two parts titled as Theory and Application Research or rarely Pandect. The eBooks were also studied on publisher website such as www.springer.com for downloads. 2.2 Data Analyses The quantitative data were analyzed in statistics with SPSS software.

3 Results The distribution of scientific papers on MMESE was listed in Table 1.

40-Year Development of MMESE from Scientific Papers

23

Table 1. The paper data from proceedings of conferences on MMESE during 1993~2020 Year of conference

Seven subdomains and extra parts in proceedings 1

2

3

4

5

6

7

Total 8

0

1993

46

1

12

8

14

3

21

10

1

116

1995

32

2

9

8

9

1

14

7

0

82

1997

21

3

3

13

18

2

13

7

0

80

1999

22

1

3

7

18

1

16

4

1

73

2001

19

4

7

11

16

1

19

9

2

88

2003

32

2

5

2

19

1

21

7

2

91

2005

19

5

16

5

10

1

34

6

1

97

2007

16

6

6

10

5

3

20

12

1

79

2009

22

9

5

9

8

3

9

11

0

76

2010

34

7

8

8

10

5

23

11

0

106

2011

31

9

8

8

8

5

19

8

1

97

2012

23

13

7

8

6

3

16

3

0

79

2013

13

10

8

8

14

2

7

9

0

71

2014

17

5

4

4

10

3

6

3

0

52

2015

17

16

11

14

11

2

7

7

0

85

2016

20

8

8

8

4

1

17

4

0

70

2017

33

17

8

9

3

1

24

4

0

99

2018

13

16

5

9

9

3

24

4

0

83

2019

27

20

18

7

6

2

19

3

0

102

2020

31

26

11

17

8

4

21

5

0

123

Total

488

180

162

173

206

47

350

134

9

1749

Note1: 0-Pandect, 1-Research on the Man Character, 2-Research on the Machine Character, 3-Research on the Environment Character, 4-Research on the Man-Machine Relationship, 5Research on the Man-Environment Relationship, 6-Research on the Machine-Environment Relationship, 7-Research on the Overall Performance of Man-Machine-Environment System, 8-Theory and Application Research Note2: No paper was published under the MMESE committee from 1981 to 1992

4 Discussions 4.1 Development of MMESE in Subdomains The main within-subjects effect of MMESE Subdomains was significant with interaction of Subdomains * Stages as shown in Table 2, but the between-subjects effect of Stages did not be significant in statistics (P ≥ 0.73). It suggested that all the seven subdomains of MMESE and its theory and application research had been developing in 1993~2020,

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but there did be differences of research among the subdomains or parts even with some regional imbalance in different periods. Table 2. Tests of within-subjects effects for the paper data with stages in decade Source

df

F

8

52.52 0.05). The heart rate of the uneducated group increased and remained at the same level until the end of the examination, which was significantly different from that of the basal heart rate (P < 0.05). Conclusion: Video education and heart rate detection can effectively improve the students’ understanding and cooperation on the examination items, reduce psychological tension and fear, and enhance the reliability and effectiveness of the selection results. Keywords: Electroencephalogram (EEG) · Physical examination of pilot selection · Video education · Psychological tension · Heart rate

1 Introduction An electroencephalogram (EEG) test is a necessary test in the Air Force’s physical examination, which aims to screen students with epileptic brain dysfunction [1]. Because of the particularity of the examination EEG, it is necessary to place an electrode on the scalp of the students. A lot of students who have not experienced this examination © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 74–79, 2022. https://doi.org/10.1007/978-981-16-5963-8_10

Study on Countermeasures of Psychological Tension

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item before or do not know its purpose, meaning is easy to produce fear psychology, cause muscle tension, produce electromyographic “artifact” interference to the EEG of normal record. Fear also leads to failure to cooperate or disobey the command, seriously affecting the results of the examination. By video education before examination and heart rate monitoring during examination, this study evaluated the psychological tension and cooperation degree of the students, and provided the basis for the reliability and effectiveness of the EEG examination.

2 Subjects 2.1 Subjects From 2019 to 2020, 250 senior high school students were randomly selected, which were divided into non-education group and education group (self-control) 250. Age 17–21 years, average age 19.3 ± 3.4 years. Through the air force recruitment physical examination of the primary and check, good health, no history of nervous-mental system and medication history. According to the questionnaire survey, 98.8% of the students had never had a EEG examination before. 2.2 Method (1) Video education takes the whole process of EEG inspection into video teaching video and plays it to the students before the inspection in order to generate perceptual knowledge. (2) Subjective assessment of the students’ understanding and acceptability (or unacceptability or fear) of the post-education EEG examination items through a selfdesigned questionnaire, e.g. questions about the level of awareness: have you understood the process and significance of the examination EEG? Question about the degree of stress: do you feel scared by doing the program check? There are three options for awareness, “don’t understand”, “know something” and “don’t understand at all”. There are also three options for stress, “no fear”, “mild fear” and “severe fear”. Students can choose one of them to answer according to their actual situation. (3) The monitoring of heart rate is carried out by means of Bluetooth bracelet and ECG monitoring channel in EEG examination program. CM5 lead of ECG were recorded [2, 3]. In the program interface can monitor the students’ heart rate in real time. Heart rate monitoring was divided into two stages, the first stage, through Bluetooth bracelet to record the heart rate before and after the students’ education. At stage 2, the heart rate in the EEG examination was recorded. Separately record the beginning of the inspection, during the inspection (1 min after the start of the inspection), and the heart rate after the end of the inspection. (4) In the absence of education for the students, the examination procedure consists of a questionnaire survey and a EEG examination by a physician, followed by a video education by a physician, followed by a questionnaire survey and a EEG examination.

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(5) Assessment Criteria ➀ Questionnaire survey Based on recovered questionnaires, number of responses for each option, percentage (%) ➁ 2 Heart rate detection Based on Wei J, Poh MZ, Shields GS, etc. Study [2, 6, 8]. The heart rate ranges from 85–90 beats/min in no stress, 90–95 beats/min in mild stress, 95–100 beats/min in severe stress.

3 Results Calculate the percentage of the number of people who changed their psychological state before and after video education (%). The change of heart rate during EEG examination was analyzed by ANOVA, and the difference between groups before, during and after examination was tested by scheffe method. Before and after the education of the difference with t test. The total data were expressed as % or x ± s, and the statistical results were significant P < 0.05. 3.1 Impact of Education on the Level of Psychological Stress During EEG Examinations Issued 500 questionnaires, recovered 500, the recovery rate of 100. Before and after video education, the students’ awareness of EEG examination and the degree of fear are compared in Tables 1 and 2. A questionnaire survey of the effect of education shows that, Before education 220 people who don’t know about EEG inspection, 88%, Only about 25 people, 10%, Five people who don’t know anything, 2%. And after education There’s a total of 250 people, Zero if not understood or partially understood, It shows that the awareness rate after education is 100. An investigation into the level of fear, Before education No fear, only 43, 18.8%, There were 110 mild fears, 44%, There were 93 people in deep fear, 37.2%. And after education Of 245 people without any fear, 98%, There are only three and two people left with mild and severe fear, 1.2% and 0.8% respectively, Explained that after education, Psychological fear of EEG examination has declined significantly. Table 1. Effect of video pre- and post-education on level of awareness during EEG examination (n = 500, %) Subgroup (person)

Level of awareness I don’t know

Know something

Fully understood

Non-education (250)

88 (220/250)

10 (25/250)

2 (5/250)

Post-education (250)

0 (0/250)

0 (0/250)

100 (250/250)

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Table 2. Effect of video pre- and post-education on psychological stress during EEG examination (n = 500, %) Subgroup (person)

The degree of fear No

Light

Non-education (250) 18 (47/250)

Heavy

44 (110/250) 37.2 (93/250)

Post-education (250) 98 (245/250) 1.2 (3/250)

0.8 (2/250)

3.2 Heart Rate Changes During EEG Examination During the whole examination period, the students were able to keep the basic heart rate stable, and there was no significant difference before, during and after the examination. The heart rate of uneducated students remained at a high level during and after examination, 92.85 ± 3.23/min and 93.05 ± 3.03/min, were higher than the basic heart rate 86.65 ± 2.7/min, respectively. During the whole examination period, the heart rate of the education group was significantly lower than that of the non-education group, as shown in Table 3. Table 3. Changes in heart rate during EEG examination (x ± s, n = 500) Groups

Heart rate (min) Before examination

Examination

After examination

F

P

Non-education (250)

86.65 ± 2.37

92.85 ± 3.23a

93.05 ± 3.03bc

31.442

0.000

Post-education (250)

79.90 ± 3.54d

80.35 ± 2.78d

81.15 ± 2.30d

0.942

0.396

t

11.828

24.741

16.750

P

0.000

0.000

0.000

Note: Comparison between examination and pre-examination a P < 0.05, after examination compared with before examination b P < 0.05, after examination compared with the examination c P > 0.05, comparison between education and non-education d P < 0.05

4 Discussion EEG examination is an electrophysiological process in which weak intracranial electrophysiological signals (microvolt level, µV) are collected by placing electrodes on the scalp, amplified by the amplifier, and then displayed on the computer screen or stored on disk through the display and recording system. Period does not involve “power generation” or “discharge”. Because of the characteristics of EEG examination, it is necessary to place electrodes on the scalp of the subjects and fix them with rubber tendons and caps.

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The appearance and form are very similar to the process of ironing the head of the barber shop. A barbershop scalding is a process that connects a heating rod to an electrified clip, similar to holding a scalp electrode with a crocodile clip during an EEG test. This process causes misunderstanding and even fear among students who do not know or have never done the test, so that the students will ask in horror before the examination, “will it be electric to me?” Or “is this check electrified?” This kind of cognition increases the students’ fear, makes them unable to relax the body and cause a lot of EMG interference at the beginning of the examination, which seriously affects the stability and reliability of the examination results. By taking the whole process of EEG inspection into video and playing it to the students before the inspection, the fear psychology of the students can be effectively alleviated. The study found that the heart rate of all students who did not participate in the education remained at a high level throughout the examination. Student A, for example, before education, the basic heart rate is 85 beats/min to 90 beats/min, when entering the laboratory. At the end of the examination, there are still 88 beats/min;. After education, the heart rate of 85 beats/min can be maintained until the end of the examination. Individual missionary students also had lower than the basic heart rate during the examination. Explain that it is important for students to fully understand the EEG inspection process, understand the purpose of the inspection, and explain the importance of video education. Psychological research has shown that a person’s heart rate increases when he or she experiences mental stress such as fear [4–8]. Therefore, heart rate is a sensitive measure of psychological relaxation and tension. A large number of studies have shown that people develop psychological stress in unknown environments or in uncertain states of perception of the future. The most obvious physiological changes are breathing, rapid heartbeat, and elevated blood pressure [3, 5, 6]. Since then, with the gradual adaptation of the environment and familiarity with external events, psychological tension will decrease. At this point, breathing will become calm, heart rate and blood pressure will return to the basic level. When observing whether a person’s body is relaxed and his mind is calm, observing heart rate changes is often used. Moreover, psychological relaxation and stability were evaluated by observing the changes of heart rate when they completed a task. During the examination of EEG, the observed heart rate changes were the psychological relaxation after video education. The results of EEG examination after education are stable, the EMG interference is less, and the results of other artifact before education are greatly disturbed by EMG artifact. Even individual uncooperation leads to interruption of examination (having to repeat examination). The results of EEG examination before and after education in turn prove the effectiveness of education. Since the students come from all over the country and have little access to EEG examination, video education is essential before the inspection. Besides the preliminary perceptual cognition of the students through video education, it is also helpful to obtain the students’ good cooperation and improve the accuracy and effectiveness of the EEG examination. Acknowledgements. This work is supported by the Military Medical Research Foundation, China, No. BKJ18B033. Yongsheng Chen and Xinxin Shang contributed equally to this work.

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Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Rosenow, F., Klein, K.M., et al.: Non-invasive EEG evaluation in epilepsy diagnosis. Expert Rev. Neurother. 15(4), 1 (2015) 2. Wei, J., Luo, H., Wu, S., et al.: Transdermal optical imaging reveal basal stress via heart rate variability analysis: a novel methodology comparable to electrocardiography. Front. Psychol. 9(1), 98 (2018) 3. Rafigue, N., Lubna, I., Asoom, A.I., et al.: Comparing levels of psychological stress and its inducing factors among medical students. J. Taibah Univ. Med. Sci. 14(6), 488–494 (2019) 4. Russell, E., et al.: toward standardization of hair cortisol measurement: results of the first international interlaboratory round robin. Ther. Drug Monit. 37(1), 71–75 (2015) 5. Schoenthaler, A.M., Rosenthal, D.M.: Stress and hypertension. In: Berbari, A.E., Mancia, G. (eds.) Disorders of Blood Pressure Regulation. UHCP, pp. 289–305. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-59918-2_19 6. Poh, M.Z., Mcduff, D.J., Picard, R.W.: Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt. Express 18(10), 10762–10774 (2010) 7. Lovallo, W.R., Thomas, T.L.: Stress hormones in sychophysiological research: emotional, behavioral and cognitive implications. In: Cacioppo, J.T., Tassinary, L.G., Bernston, G.G. (eds.) Handbook of Psychophysiology, pp. 342–367. Cambridge University Press (2016) 8. Shields, G.S., Slavich, G.M.: Lifetime stress exposure and health: a review of contemporary assessment methods and biological mechanisms. Soc. Pers. Psychol. Compass 11(8), 123–135 (2017)

Application of Fuzzy Mathematics Method in Sensory Evaluation of Military Ready-to-Eat Meat Sticks Huiling Mu, Peng Du, Shuang Bai, Ximeng Chen, Peng Liu, Feng Li, Hongjiang Jing, Falin Li, and Ruoyong Wang(B) Air Force Medical Center, Beijing 100142, China

Abstract. Objective—To study the sensory quality of six kinds of military readyto-eat meat sticks by fuzzy mathematics method. Methods—Adopted the method of fuzzy mathematics with color, status, smell, texture and taste as evaluation factors, and carried out fuzzy mathematics judgment of the sensory quality of six kinds of military ready-to-eat meat sticks: Orleans pork, sauced pork tenderloin, original beef, black pepper beef, mellow beef and spicy beef. Results—The fuzzy comprehensive sensory evaluation scores of six kinds of military ready-to-eat meat sticks from high to low were original beef, mellow beef, black pepper beef, spicy beef, Orleans pork and sauced pork tenderloin. Conclusions—The fuzzy mathematics method can reflect the sensory quality more objectively and accurately, which provided a reference method for the comprehensive sensory quality evaluation of military ready-to-eat meat sticks. Keywords: Ready-to-eat meat sticks · Military food · Sensory evaluation · Fuzzy mathematics method

1 Introduction Military ready-to-eat meat sticks were made of pork or beef as the main raw material. It was processed by rolling, slicing, salting, smoking, cutting, packaging and high temperature sterilization and other processes. It is easy to eat and carry, and rich in nutrition. It suits for military use and its shelf life usually needs to be more than 2 years or even longer, which also puts forward higher requirements for the acceptability of sensory quality of military food. At present, fuzzy mathematics method had been widely used in food sensory evaluation [1–9].We also evaluated the sensory quality of military food such as military instant rice and ready-to-eat meatballs by fuzzy mathematics method [10, 11]. In this study, comprehensive fuzzy mathematics evaluation of six kinds of military ready-toeat meat sticks was carried out, which was selected color, status, smell, texture and taste as the evaluation factors of sensory quality of military ready-to-eat meat sticks, in order to evaluate the sensory quality of military ready-to-eat meat sticks objectively and accurately. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 80–87, 2022. https://doi.org/10.1007/978-981-16-5963-8_11

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2 Materials and Methods 2.1 Main Raw and Auxiliary Materials Beef, pork, salt, sugar, phosphate, nitrite mixed salt, five spice powder, white pepper, potato starch, water. 2.2 Sensory Evaluation Eighty-four healthy male volunteers with an average age of (33.1 ± 4.3) years were selected for sensory evaluation of six kinds of military ready-to-eat meat sticks samples. According to personal preferences, they evaluated the color, status, smell, texture and taste of the ready-to-eat meat sticks by the 9-point system and the sensory evaluation criterion of military ready-to-eat meat sticks (Table 1). The 9-point system included 9 levels: extremely like (9 points), very like (8 points), like (7 points), a little like (6 points), general (5 points), less like (4 points), not like (3 points), very dislike (2 points), extremely dislike (1 point), the more you like, the higher the score. Before sensory evaluation, the evaluators should be trained to understand the meaning and scoring standards of various sensory evaluation indexes. Each evaluation should be recorded by each evaluation personnel independently, without contact and communication with each other, and each sample evaluation should be rinsed with water. Table 1. Sensory evaluation criterion of military ready-to-eat meat sticks Indicator

Criterion

Preference

Score

Color (15%)

The color should be bright and luster

like–extremely like

7–9

The color is normal and slightly glossy

less like–a little like

4–6

Status (15%)

Smell (20%)

The color is abnormal and lusterless extremely dislike–not like

1–3

Complete shape, compact structure, like–extremely like elastic, visible fleshy fiber, no fascia

7–9

Complete shape, compact structure, less like–a little like a little, elastic, visible fleshy fiber, no fascia

4–6

Complete shape, compact tissue, hard, invisible fleshy fiber, with a small amount of fascia

extremely dislike–not like

1–3

With the unique aroma of meat sticks, which is strong

like–extremely like

7–9 (continued)

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H. Mu et al. Table 1. (continued)

Indicator

Texture (25%)

Taste (25%)

Criterion

Preference

Score

With the unique aroma of meat sticks, which is light

less like–a little like

4–6

With the unique aroma of meat sticks, which is not obvious

extremely dislike–not like

1–3

Chewy, moderate in hardness

like–extremely like

7–9

A little bit chewy, feels a little hard less like–a little like or soft

4–6

No chewiness, feeling hard or soft

extremely dislike–not like

1–3

Strong meat flavor, moderate salty and sweet, when chewing

like–extremely like

7–9

Light meat flavor, moderate salty and sweet, when chewing

less like–a little like

4–6

No meat flavor, salty or sweet, when chewing

extremely dislike–not like

1–3

2.3 Establishment of Fuzzy Mathematical Model (1) Determined the evaluation object set. Six kinds of military ready-to-eat meat sticks: Orleans pork, sauced pork tenderloin, original beef, black pepper beef, mellow beef and spicy beef, were numbered in turn, which were S1 , S2 , S3 , S4 , S5 , S6 respectively. The evaluation object set S = {S1 , S2 , S3 , S4 , S5 , S6 }. (2) Determined the factor set. The color, status, smell, texture and taste were selected as evaluation factors, U1 , U2 , U3 , U4 and U5 represented color, status, smell, texture and taste respectively. The factor set U = {U1 , U2 , U3 , U4 , U5 }. (3) Determined the comment set V = {V1 , V2 , V3 , V4 , V5 , V6 , V7 , V8 , V9 }, where V1 meant extremely like (9 points), V2 meant very like (8 points), V3 meant like (7 points), V4 meant a little like (6 points), V5 meant general (5 points), V6 meant less like (4 points), V7 meant not like (3 points), V8 meant very dislike (2 points), V9 meant extremely dislike (1 point). (4) Determination the weight set W = {W1 , W2 , W3 , W4 , W5 }. This experiment was based on sensory evaluation criterion of military ready-to-eat meat sticks (Table 1): color 15%, status 15%, smell 20%, texture 25% and taste 25% as the distribution basis of weight coefficients. The weight coefficients of color, status, smell, texture and taste were 0.15, 0.15, 0.20, 0.25 and 0.25 respectively, and the total was 1, the weight set W = {0.15, 0.15, 0.20, 0.25, 0.25}. (5) Determination fuzzy relation comprehensive evaluation set. The comprehensive evaluation set of fuzzy relation is Y = W · R, where Y is the comprehensive evaluation set, W is the weight set and R is the fuzzy evaluation matrix.

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3 Results and Analysis 3.1 Sensory Evaluation Results According to the sensory evaluation methods and criterion, six kinds of military readyto-eat meat sticks were evaluated. The results were shown in Table 2. Table 2. Sensory evaluation results of six kinds of military ready-to-eat meat sticks (n = 84) Sample code Indicator

Score 9

S1

7

6

5

16 24 21 11

9 2 1 0 0

Status (U2 )

15 20 24 14

6 4 1 0 0

Smell (U3 )

11 19 22 14 10 6 2 0 0 8 25 18 18

11 18 17 18 11 6 3 0 0

Color (U1 )

12 19 25 15

Status (U2 )

15 13 31 11 10 4 0 0 0

Smell (U3 )

12 13 24 17 12 6 0 0 0

S5

8 5 0 0 0

9 7 2 0 0

Taste (U5 )

12 10 21 22 10 7 2 0 0

Color (U1 )

24 32 13

9

5 1 0 0 0

Status (U2 )

24 30 14

9

6 1 0 0 0

Smell (U3 )

24 21 22 12

4 1 0 0 0

Texture (U4 ) 27 24 18 S4

8 5 2 0 0

Taste (U5 )

Texture (U4 ) 11 12 27 16 S3

4 3 2 1

Color (U1 )

Texture (U4 ) S2

8

7

5 3 0 0 0

Taste (U5 )

23 22 21 10

4 4 0 0 0

Color (U1 )

21 25 21

9

7 0 1 0 0

Status (U2 )

21 23 19 12

8 0 1 0 0

Smell (U3 )

17 23 18 15

9 1 1 0 0

Texture (U4 ) 18 21 20 12

9 3 1 0 0

Taste (U5 )

17 26 15 13

9 3 1 0 0

Color (U1 )

22 28 21

7

5 0 1 0 0

Status (U2 )

20 23 25 11

3 1 1 0 0

Smell (U3 )

21 22 23 12

5 0 1 0 0

Texture (U4 ) 24 25 19 12

2 1 1 0 0 (continued)

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H. Mu et al. Table 2. (continued) Sample code Indicator

Score 9

S6

8

7

6

5

4 3 2 1

Taste (U5 )

23 21 24 11

3 1 1 0 0

Color (U1 )

20 22 23 11

8 0 0 0 0

Status (U2 )

19 18 29

8

9 1 0 0 0

Smell (U3 )

18 21 23 11

9 1 1 0 0

Texture (U4 ) 18 20 22 12

7 3 2 0 0

Taste (U5 )

8 1 1 0 0

16 22 24 12

3.2 Establishment of Fuzzy Comprehensive Evaluation Set Divide the data in Table 2 by the total number of evaluators (84) to get six fuzzy evaluation matrices:    4/21 2/7 1/4 11/84 3/28 1/42 1/84 0 0     5/28 5/21 2/7 1/6 1/14 1/21 1/84 0 0      R1 = rij 5×9 =  11/84 19/84 11/42 1/6 5/42 1/14 1/42 0 0   2/21 25/84 3/14 3/14 2/21 5/84 1/42 0 0     11/84 3/14 17/84 3/14 11/84 1/14 1/28 0 0     1/7 19/84 25/84 5/28 2/21 5/84 0 0 0     5/28 13/84 31/84 11/84 5/42 1/21 0 0 0      R2 = rij 5×9 =  1/7 13/84 2/7 17/84 1/7 1/14 0 0 0   11/84 1/7 9/28 4/21 3/28 1/12 1/42 0 0     1/7 5/42 1/4 11/42 5/42 1/12 1/42 0 0     2/7 8/21 13/84 3/28 5/84 1/84 0 0 0     2/7 5/14 1/6 3/28 1/14 1/84 0 0 0      R3 = rij 5×9 =  2/7 1/4 11/42 1/7 1/21 1/84 0 0 0   9/28 2/7 3/14 1/12 5/84 1/28 0 0 0     23/84 11/42 1/4 5/42 1/21 1/21 0 0 0     1/4 25/84 1/4 3/28 1/12 0 1/84 0 0     1/4 23/84 19/84 1/7 2/21 0 1/84 0 0     R4 = rij 5×9 =  17/84 23/84 3/14 5/28 3/28 1/84 1/84 0 0   3/14 1/4 5/21 1/7 3/28 1/28 1/84 0 0     17/84 13/42 5/28 13/84 3/28 1/28 1/84 0 0     11/42 1/3 1/4 1/12 5/84 0 1/84 0 0     5/21 23/84 25/84 11/84 1/28 1/84 1/84 0 0      R5 = rij 5×9 =  1/4 11/42 23/84 1/7 5/84 0 1/84 0 0   2/7 25/84 19/84 1/7 1/42 1/84 1/84 0 0     23/84 1/4 2/7 11/84 1/28 1/84 1/84 0 0 

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  R5 = rij 5×9

85

   5/21 11/42 23/84 11/84 2/21 0 0 0 0    19/84 3/14 29/84 2/21 3/28 1/84 0 0 0   =  3/14 1/4 23/84 11/84 3/28 1/84 1/84 0 0   3/14 5/21 11/42 1/7 1/12 1/84 1/42 0 0     4/21 11/42 2/7 1/7 2/21 1/84 1/84 0 0 

r ij indicates the degree of subordination from the evaluation indexes of military ready-to-eat meat sticks to the evaluation results of the indexes. The comprehensive membership degree of samples were calculated by using matrix multiplication [7–9]. The result vector of the comprehensive sensory quality evaluation of military ready-to-eat meat sticks was as follows: Y1 =W · R1 = {0.15, 0.15, 0.20, 0.25, 0.25}    4/21 2/7 1/4 11/84 3/28 1/42 1/84 0 0     5/28 5/21 2/7 1/6 1/14 1/21 1/84 0 0    ·  11/84 19/84 11/42 1/6 5/42 1/14 1/42 0 0   2/21 25/84 3/14 3/14 2/21 5/84 1/42 0 0     11/84 3/14 17/84 3/14 11/84 1/14 1/28 0 0  Among them, y11 = 0.15 × 4/21 + 0.15 × 5/28 + 0.20 × 11/84 + 0.25 × 2/21 + 0.25 × 11/84 = 0.138, y12 = 0.15 × 2/7 + 0.15 × 5/21 + 0.20 × 19/84 + 0.25 × 25/84 + 0.25 × 3/14 = 0.252. Similarly, y13 = 0.237, y14 = 0.185, y15 = 0.107, y16 = 0.058, y17 = 0.023, y18 = 0, y19 = 0. Therefore, Y 1 = {0.138, 0.252, 0.237, 0.185, 0.107, 0.058, 0.023, 0, 0}. Similarly, Y 2 = {0.145, 0.154, 0.300, 0.200, 0.117, 0.072, 0.012, 0, 0}. Y 3 = {0.292, 0.298, 0.217, 0.111, 0.056, 0.027, 0, 0, 0}. Y 4 = {0.220, 0.280, 0.218, 0.148, 0.102, 0.020, 0.012, 0, 0}. Y 5 = {0.265, 0.280, 0.265, 0.129, 0.041, 0.008, 0.012, 0, 0}. Y 6 = {0.214, 0.246, 0.285, 0.132, 0.096, 0.016, 0.011, 0, 0}. The comprehensive scores of each sample were calculated according to the comprehensive score formula 1: Hi =

n 

jYi

(1)

j=1

H 1 = 9 × 0.138 + 8 × 0.252 + 7 × 0.237 + 6 × 0.185 + 5 × 0.107 + 4 × 0.058 + 3 × 0.023 + 2 × 0 + 1 × 0 = 6.863. Similarly, H 2 = 6.746, H 3 = 7.577, H 4 = 7.260, H 5 = 7.528, H 6 = 7.256. Therefore, the sensory quality of six kinds of military ready-to-eat meat sticks from high to low was S3 > S5 > S4 > S6 > S1 > S2 . Sensory evaluation results showed that the sensory quality of original beef samples was the best, and the sensory quality of sauced pork tenderloin samples was the worst. The comprehensive scores of original beef and mellow beef were between 7 and 8, closed to 8, indicating that the two kinds of ready-to-eat meat sticks preferred to very like between like and very like. The comprehensive scores of black pepper beef and spicy beef were between 7 and 8, closed to 7, indicating that the two kinds of ready-to-eat meat sticks preferred

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to like between like and very like. And the comprehensive scores of Orleans pork and sauced pork tenderloin were between 6 and 7, closed to 7, indicating that the two kinds of ready-to-eat meat sticks preferred to like between a little like and like.

4 Conclusions Food sensory analysis is a scientific method to perceive the characteristics or properties of food through vision, smell, taste and hearing. At present, the nine-point system is used to evaluate the sensory quality of military food, which can fully reflect the personal preferences, but there is subjectivity, the evaluation results will be significantly effected by the individual differences of the evaluation personnel. In this study, the sensory quality of six kinds of ready-to-eat meat sticks was evaluated by fuzzy mathematics sensory evaluation method with color, status, smell, texture and taste. The results showed that the fuzzy comprehensive sensory evaluation scores of six kinds of ready-to-eat meat sticks from high to low were original beef, mellow beef, black pepper beef, spicy beef, Orleans pork and sauced pork tenderloin. Fuzzy mathematics method overcame the influence of subjective factors, can reflect the sensory quality more objectively and accurately, and provided a reference method for the comprehensive sensory quality evaluation of military ready-to-eat meat sticks. Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Hu, X., Xia, Y.B.: An improved sensory comprehensive evaluation method for chopped hot pepper based on fuzzy mathematics. Food Sci. 32(1), 95–98 (2011) 2. Chen, S.M.: Improvement of the recipe of the okara walnut cake by fuzzy mathematic sensory evaluation. Cereals Oils 29(7), 66–69 (2016) 3. Fu, L., Zhang, Y., Gong, H., et al.: Formular optimization of starch in crystal shrimps based on the fuzzy mathematics evaluation. Sci. Technol. Food Ind. 38(11), 209–218 (2017) 4. Zhao, Z.X., Sun, Y., Guan, L.N., et al.: Study on the process optimization of sprouting brown rice based on fuzzy synthetical evaluation. Grain Process. 44(3), 28–38 (2019) 5. Cong, Y.J., Ma, R., Li, Y.T.: Fuzzy mathematical evaluation and sensory attributes analysis of plain yogurt. Dairy Ind. 48(12), 53–58 (2020) 6. Zhang, X., Xia, K., Wang, J., et al.: Sensory evaluation based on fuzzy mathematics for hypoallergenic nutritional meal package. J. Hebei Univ. Eng. (Nat. Sci. Ed.) 37(4), 105–112 (2020) 7. Xiong, D.G., Xian, X.F.: Improvement of fuzzy comprehensive evaluation method. J. Chongqing Univ. 26(6), 93–95 (2003) 8. Zhu, W., Fu, X.Z., Guan, T.Q., et al.: Sensory analysis on pinckled potherb mustard quality by fuzzy comprehensive evaluation. Food Sci. 28(11), 176–178 (2007) 9. He, X.Y., Ni, X.G., Li, L.H., et al.: Preparation and sensory evaluation of pepper wine. Liquor-Making Sci. Technol. 29(11), 101–103 (2009)

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10. Mu, H.L., Du, P., Bai, S., et al.: Study on sensory evaluation of military instant rice by fuzzy mathematics method. Farm Prod. Process. 18(8), 13–16 (2020) 11. Wang, R., Huiling, M., Peng, D., Chen, X., Liu, P., Bai, S.: Application of comprehensive preference and fuzzy mathematics method in sensory evaluation of ready-to-eat meatballs. In: Long, S., Dhillon, B.S. (eds.) MMESE 2020. LNEE, vol. 645, pp. 379–386. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-6978-4_45

Risk Factors Analysis and Health Management Countermeasures of Dyslipidemia of Flight Personnel in 2020 Annual Physical Examination Peng Liu, Shuang Bai, Ximeng Chen, Huiling Mu, Ruoyong Wang, Feng Li, Hongjiang Jing, and Peng Du(B) Air Force Medical Center, Beijing 100142, China

Abstract. Objective—To understand and analyze the prevalence and risk factors of dyslipidemia among flight personnel, so as to provide the basis for aviation health management. Methods—The physical examination data of flight personnel who participated in physical examination in 2020 were collected. The prevalence and risk factors of dyslipidemia in flight personnel were analyzed by statistical methods. Results—The risk of dyslipidemia increased with age and longer flight time. Flight crews with an overweight body mass index are more likely to have dyslipidemia. Conclusions—Comprehensive measures should be taken to prevent and control dyslipidemia from health education, diet and nutrition, and physical training for the key population. Keywords: Flight personnel · Dyslipidemia · Risk factors · Health management

1 Introduction Dyslipidemia, characterized by low density lipoprotein cholesterol (LDL-C) or total cholesterol (TC) elevation, is an important risk factor of atherosclerotic cardiovascular disease (ASCVD). Lowering LDL-C level can significantly reduce the risk of ASCVD morbidity and mortality [1]. Other types of dyslipidemia, such as increased triglyceride (TG) or decreased high-density lipoprotein cholesterol (HDL-C), were also associated with an increased risk of ASCVD [2]. Therefore, in order to understand the prevalence of dyslipidemia among flight personnel and the related risk factors, we collected the physical examination data of flight personnel in 2020 and made a statistical analysis of the data. The situation is reported as follows.

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 88–93, 2022. https://doi.org/10.1007/978-981-16-5963-8_12

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2 Objects and Methods 2.1 Subjects 450 male flight personnel who will come to our center for physical examination in 2020. 2.2 Methods SPSS21.0 software was used to analyze the data. Measurement data was expressed as (x ± s). Two independent samples t test was used to compare the differences between the two groups. Enumeration data was expressed as percentage, and the difference between the two groups was compared by the chi-square test. Spearman correlation analysis was used to investigate the correlation between the occurrence of dyslipidemia and age and flight time of flight personnel. Multivariate Logistic regression analysis was used to investigate the influence of factors such as age and flight time on the risk of pilots with dyslipidemia, and P < 0.05 was used to indicate the criteria for statistically significant difference. Diagnosis of dyslipidemia was carried out according to the guidelines for the prevention and treatment of dyslipidemia in adults in China (revised edition 2016) [3].

3 Results 3.1 Age Comparison of Pilots in the Dyslipidemia Group The mean age of pilots in the abnormal triglyceride group was (35.2 ± 7.3) years, which was significantly higher than that in the normal control group (30.3 ± 7.8) (P < 0.05) (Table 1). Table 1. Age distribution of different types of dyslipidemia groups 1 Dyslipidemia group (age) Normal group (age) (x ± s) (x ± s) Total cholesterol Elevated

30 ± 8.2

30.4 ± 7.4

Marginal elevation 34.5 ± 9.8 Triglycerides

Elevated

35.2 ± 7.3

30.3 ± 7.8

Marginal elevation 33.2 ± 7.0 LDL-C

Elevated

31.9 ± 10.1

Marginal elevation 33.5 ± 10.2

30.5 ± 7.4

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3.2 Comparison of Dyslipidemia Among Different Age Groups With the increase of age, the percentage of increased triglyceride, the percentage of marginal increase of total cholesterol and LDL-C gradually increased. Different groups elevated triglycerides percentage difference, total cholesterol and LDL - C borderline higher percentage of the difference was statistically significant (P < 0.05) (Table 2) Spearman correlation analysis results abnormal flight crew triglyceride, total cholesterol and LDL - C borderline elevated risk was positively correlated with age (P < 0.05). Table 2. Percentage of dyslipidemia in flight personnel of different age groups Group The Total cholesterol Triglycerides LDL-C HDL-C (years number Elevated Marginal Elevated Marginal Elevate Marginal To old) of cases elevation elevation elevation reduce 20 to 29

253

8 (3.2%) 25 (9.9%)

8 (3.2%) 13 (5.1%)

6 (2.4%)

23 (9.1%)

19 (7.5%)

30–39

151

3 (2.0%) 23 (15.2%)

19 (12.6%)

15 (9.9%)

2 (1.3%)

19 (12.6%)

15 (9.9%)

40 to 49

31

2 (6.5%) 6 (19.4%)

6 (19.4%)

2 (6.5%)

1 (3.2%)

5 (16.1%)

4 (12.9%)

50–57

15

6 (40%)

1 (6.7%) 2 (13.3%)

1 (6.7%)

5 (33.3%)

3 (20%)

3.3 Comparison of Dyslipidemia Among Different BMI Groups The percentage of increased triglycerides in the BMI 26–30 group reached 23.1%, and there were statistically significant differences in the percentage of increased total cholesterol, triglyceride and decreased HDL-C between the two groups (P < 0.05) (Table 3). Table 3. Percentage of abnormal blood lipids with different BMI BMI

The Cholesterol Triglycerides LDL-C HDL-C number Elevated Marginal Elevated Marginal Elevated Marginal To of cases elevation elevation elevation reduce

18.0–25.9 385

9 (2.3%) 48 (15.2%)

19 (4.9%)

26 to 30

4 (6.2%) 12 (18.5%)

15 10 (23.1%) (15.4%)

65

22 (5.7%)

9 (2.3%) 40 (10.3%)

27 (7.0%)

1 (1.5%) 12 (18.5%)

14 (21.5%)

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3.4 Results of Multivariate Logistic Regressive Analysis When other variables were fixed, the risk of dyslipidemia changed by 1.072-fold for each 1-year increase in the age of flight personnel (95% CI: 1.049–1.096, P < 0.05). Taking flight time < 1000 h as the reference, the risk of dyslipidemia in flight time 1000–2000 h was 1.997 times higher than that in flight time < 1000 h (95% CI: 1.5799–2.525, P < 0.05). The risk of dyslipidemia in flight duration > 2000 h was 2.664 times higher than that in flight duration < 1000 h (95% CI: 1.860–3.815, P < 0.05) (Table 4). Table 4. Comparison of the percentage of dyslipidemia among different flight duration groups Flight duration (hours)

The Cholesterol Triglycerides LDL-C HDL-C number Elevated Marginal Elevated Marginal Elevated Marginal of elevation elevation elevation cases

1000 or less

237

9 (3.8%) 23 (9.7%)

5 (2.1%)

1000–2000 116

1 (0.9%) 18 (15.5%)

2000–3000

53

>3000

44

11 (4.6%)

5 (2.1%) 23 (9.7%)

15 (6.3%)

18 11 (15.5%) (9.5%)

2 (1.7%) 12 (10.3%)

15 (12.9%)

2 (3.8%) 8 (15.1%)

3 (5.7%)

2 (3.8%) 5 (9.4%) 3 (5.7%)

2 (4.5%) 12 (27.3%)

6 3 (6.8%) 1 (2.3%) 12 (13.6%) (27.3%)

7 (13.2%)

7 (15.9%)

4 Discuss 4.1 Analysis of the Occurrence of Dyslipidemia in Flight Personnel Previous studies have reported that hyperlipidemia ranks the top 5 in the spectrum of diseases among flight personnel [4], the incidence was 10.96–20.79% [5]. This survey showed that the incidence of dyslipidemia in flight personnel was 10.44%, lower than the previous survey results, but the incidence of marginal elevation of blood lipids (total cholesterol, triglyceride, LDL-C) was 28%.The early clinical symptoms of hyperlipidemia are not obvious and easy to be ignored [6], the risk of hyperlipidemia awareness rate is not high, flight personnel do not take the initiative to accept medical intervention [7]. Therefore, sanitariums should carry out targeted disease research, refine health management measures, carry out physical examination, risk assessment, develop personalized programs, so as to achieve the purpose of disease prevention and treatment. 4.2 Age and Risk Analysis of Dyslipidemia in Flight Crew This survey showed that the average age of flight crew in the abnormal triglyceride group was 35.2 ± 7.3 years old, which was significantly higher than that in the control group

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(P < 0.05). The risk of abnormal triglycerides, marginal increase in total cholesterol and LDL-C was positively correlated with age, suggesting that the risk of high triglycerides increased with age, which was consistent with the physiological characteristics of lipid metabolism. This survey shows that the flight crew 40–49 high blood triglycerides prevalence is highest, so must strengthen the aircrew lipid control. For flight personnel with dyslipidemia combined with other metabolic diseases, should be measured every 3–6 months to establish a system of prevention of cardiovascular diseases. 4.3 Flight Time and Risk Analysis of Flight Personnel with Hypertriglyceridemia This survey showed that with the increase of flight time, the risk of flight personnel with hypertriglyceridemia increased. In 2009, the Institute of Medical Sciences of Civil Aviation University of China analyzed the influencing factors of hyperlipidemia among male civil aviation pilots, showing that there was a positive correlation between hyperlipidemia and cumulative flight hours [8]. Therefore, the high triglyceridemia of flight personnel may be related to the accumulation of the effects of flight environment on lipid metabolism, Therefore, it is necessary to strengthen the monitoring of blood lipid of flight personnel and actively carry out health education. 4.4 Analysis of BMI and Dyslipidemia The percentage of total cholesterol and triglyceride increased and the percentage of HDL-C decreased in the abnormally-increased BMI group were significantly different. Overweight and obesity are important risk factors for dyslipidemia. For flight personnel with abnormally high BMI, weight monitoring should be strengthened, dietary structure should be improved, physical activity should be increased, daily energy intake should be lower than body energy consumption, so as to control weight growth, control blood lipid and reduce the risk of dyslipidemia. In conclusion, the incidence of dyslipidemia in flight personnel, especially marginal elevation, is not optimistic. With the increase of age and longer flight time, the risk of dyslipidemia in flight personnel increases. Flight crews with an overweight body mass index are more likely to have dyslipidemia. Navigation who work for risk factors intervention, from disease, health education, diet and nutrition, diseases of physical training, psychological counseling, the respect such as discharge follow-up to take comprehensive measures, at the same time, strengthen the cohesion and flying unit, hospital, sanatorium, forces, hospital health security system, of working together to prevent disease, flight crew health maintenance, extend the life of the purpose of flight. Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Baigent, C., Keech, A., Kearney, P.M., et al.: Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of prospective data from 90, 056 participants in 14 randomised trials of statins. Lancet 366, 1267–1278 (2005) 2. Ren, J., Grundy, S.M., Liu, J.: Long-term coronary heart disease risk associated with very-lowdensity lipoprotein cholesterol in Chinese: the results of a 15-Year Chinese Multi-Provincial Cohort Study (CMCS). Atherosclerosis 211, 327–332 (2010) 3. Zhu, J., Gao, R., Zhao, S., Lu, G.P., Zhao, D., Li, J.J.: Guidelines for the prevention and treatment of dyslipidemia in adults in China (2016 revised edition). Chin. J. Circ. 31(10), 937 (2016) 4. Xu, X., Fu, Z., Yin, X., et al.: Analysis of hospitalized disease spectrum of fighter pilots. Chin. J. Aerosp. Med. 16(2), 135 (2005) 5. Wang, Y., Bruce, L., Liu, D., et al.: Changes of disease spectrum in recuperating flight crews from 1984 to 2013. Chin. J. Health Care Med. 16(4), 309 (2014) 6. Liu, J., Li, Z., Liu, M., et al.: Analysis of symptoms in annual medical examination of flight personnel. J. Aerosp. Med. 23(3), 199 (2012) 7. Zhou, J., Han, L.: Correlation between hyperlipidemia and metabolic disease in naval pilots. Chin. J. Aerosp. Med. 26(2), 103 (2015) 8. Wang, X., Chen, W., Zhang, T., et al.: Analysis of serum lipids and hyperlipidemia in male pilots of civil aviation. Environ. Occup. Med. 26(1), 8 (2009)

Effect of Different Muscle-Enhancing Supplement Programs on Muscle Strength Huiling Mu, Ruoyong Wang, Xichen Geng, Yan Xu, Shuang Bai, Ximeng Chen, Longmei Fang, Lili Zhang, Peng Liu, Feng Li, Hongjiang Jing, and Peng Du(B) Air Force Medical Center, Beijing 100142, China

Abstract. Objective—To observe the effect of different muscle-enhancing supplement programs on muscle strength and guide pilots to carry out reasonable nutritional supplement in anti-G physical training. Methods—Ten healthy male volunteers were randomly divided into the experimental group and the control group. The subjects were trained according to the anti-G muscle strength training program and got different muscle-enhancing supplement programs for 16 weeks. The muscle strength indexes of the subjects were measured before and after the experiment. Results—Compared with before the experiment, the 10RM and 3RM of barbell squat, leg bend and pull, and maximal leg strength in the experimental group and the control group were significantly increased (P < 0.01), and the 10RM and 3RM of barbell push in the experimental group and the control group were significantly increased (P < 0.05). After muscle-enhancing supplement, the proportion of muscle strength improvement in the experimental group was higher than that in the control group. Conclusions—The muscle-enhancing supplement program of experimental group was better than the control group. Keywords: Muscle strength · Muscle-enhancing supplement · Anti-G physical training

1 Introduction It is a consensus in aviation medical field that enhancing muscle strength can improve +Gz tolerance [1]. Reasonable nutrition supplement can enhance muscle strength, which is recognized as an effective method to enhance muscle endurance and explosive power in sports nutrition field [2]. However, this effective method has not been widely used in anti-G physical training for pilots at present. In this study, the subjects were trained according to the anti-G muscle strength training program and got different muscleenhancing supplement programs for sixteen weeks. The muscle strength indexes of the subjects were measured before and after the experiment to observe the effect of different muscle-enhancing supplement programs on muscle strength, which has a certain guiding significance for pilots to carry out reasonable nutritional supplement in anti-G physical training.

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 94–98, 2022. https://doi.org/10.1007/978-981-16-5963-8_13

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2 Subjects and Methods 2.1 Material Whey protein, sucrose, glucose, maltodextrin, whey protein fortified solid beverage. 2.2 Subjects and Groups Ten healthy male volunteers, the average age was (19.00 ± 1.15) years old, the average height was (170.90 ± 1.29) cm, the average weight was (63.38 ± 3.60) kg. The subjects were randomly divided into two groups: the experimental group (group A) and the control group (group B). Five people in each group. On the basis of anti-G muscle strength training, muscle-enhancing supplement programs were carried out for sixteen weeks in both group A and B. All subjects did not take muscle-enhancing supplement in five weeks before the experiment [3]. During the whole experiment period, the subjects ate in accordance with the requirements. If any adverse event or unexpected event is found at any time, the trial can be stopped. 2.3 Methods 2.3.1 Muscle-Enhancing Supplement Programs Group A and B were given different muscle-enhancing supplement programs for sixteen weeks. Before and during training, group A was given 20 g sucrose and 10 g glucose, mixed with purified water, and took them in several times. Within 30 min after training, group A was given 30 g whey protein powder, 10 g sucrose, 10 g glucose and 10 g maltodextrin, mixed with purified water. Before and during training, group B was took pure water. Within 30 min after the training, group B was given 40 g whey protein fortified solid beverage, mixed with purified water. The amount of drinking water in the two groups was not limited during the training. 2.3.2 Anti-G Muscle Strength Training Program Using barbell, dumbbell, sitting and pedaling training device, neck training device, waist training device and other strength training equipment, the strength training of lower limb muscle, waist and abdominal muscle, chest and back muscle, neck muscle, respiratory muscle and other anti-G muscle groups was carried out, and the breathing mode of HP anti-G movement was integrated into the training movement. Each movement practiced three groups, 8–12 times in each group. A total of sixteen weeks of training was carried out. Both of the groups trained from Monday to Friday in the afternoon and rest on Saturday and Sunday.

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2.3.3 Test Index The muscle strength was measured before and after the experiment, including barbell squat strength, barbell push strength, leg bend and pull strength, maximal leg strength. 1. Barbell squat strength test: the subjects’ feet were separated, and the position of “hip joint width, sole parallel” was adopted. Under the protection of squatting frame, the subjects carried out the squatting action of shouldering barbell, repeated 10 times of squatting and standing up action and 3 times of squatting and standing up action respectively. The weight they could load was muscle endurance (10RM) and maximum strength (3RM) of barbell squatting respectively. 2. Barbell push strength test: the subjects were asked to lie on the bench and perform the push. They repeated the push for 10 times and 3 times. The weight they could load was muscle endurance (10RM) and maximum strength (3RM) of barbell push respectively. 3. Leg bend and pull strength test: the subjects’ feet were separated, and the position of “hip joint width, sole parallel” was adopted. The subjects carried out the action of leg bend and pull, repeated for 10 times and for 3 times respectively. The weight they could load was muscle endurance (10RM) and maximum strength (3RM) of Leg bend and pull respectively 4. Maximal leg strength test: the subjects sat on the tester seat with their feet on the pedal, the angle between thigh and calf was about (120 ± 10)°, pushed the pedal as hard as possible and kept it for at least 5 s. The maximum average pedal force of each subject’s legs was recorded. The maximal leg strength of each subject’s legs was recorded. 2.3.4 Statistical Method All data were expressed by means and standard deviation (x±s). SPSS 22.0 software was used for data processing. Independent sample t-test was used for inter group comparison, and paired sample t-test was used for intra group comparison. P < 0.05 was considered as significant difference.

3 Results and Analysis The measurement results of muscle strength are shown in Table 1. Compared with before the experiment, the results showed that the 10RM and 3RM of barbell squat, leg bend and pull, and maximal leg strength in group A and B were significantly increased (P < 0.01), and the 10RM and 3RM of barbell push in group A and B were significantly increased (P < 0.05). In group A, the 10RM of barbell squat, barbell push, leg bend and pull were increased by 69.23%, 37.78%, and 84.62%, respectively; the 3RM of barbell squat, barbell push, leg bend and pull were increased by 61.76%, 30.91%, and 75.38%, respectively; the maximal leg strength of left leg and right leg were increased by 24.21%, 24.38%, respectively. In group B, the 10RM of barbell squat, barbell push, leg bend and pull were increased by 52.83%, 20.83%, and 82.69%, respectively; the 3RM of barbell squat, barbell push, leg

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bend and pull were increased by 46.97%, 19.30%, and 67.19%, respectively; the maximal leg strength of left leg and right leg were increased by 19.85%, 19.92%, respectively. After muscle-enhancing supplement, the proportion of muscle strength improvement in group A was higher than that in group B. From this point of view, the muscle-enhancing supplement program of group A was better than group B. Table 1. The measurement results of muscle strength Index Barbell squat strength

10RM

Before the experiment (0w)

After the experiment (16w)

Proportion of change (%)

A

52.00 ± 4.47

88.00 ± 10.95**

69.23

53.00 ± 4.47

81.00 ± 7.42**

52.83

A

68.00 ± 5.70

110.00 ± 12.25**

61.76

B

66.00 ± 6.52

97.00 ± 13.04**

46.97

45.00 ± 3.54

62.00 ± 9.75*

37.78

B

48.00 ± 2.74

58.00 ± 5.70*

20.83

A

55.00 ± 3.54

72.00 ± 13.04*

30.91

57.00 ± 4.47

68.00 ± 8.37*

19.30

A

52.00 ± 2.74

96.00 ± 11.40**

84.62

B

52.00 ± 2.74

95.00 ± 11.18**

82.69

A

65.00 ± 3.54

114.00 ± 11.40**

75.38

B

64.00 ± 4.18

107.00 ± 13.04**

67.19

214.00 ± 20.43

265.80 ± 21.26**

24.21

B

207.60 ± 61.85

248.80 ± 62.03**

19.85

A

202.60 ± 20.59

252.00 ± 23.46**

24.38

212.80 ± 62.10

255.20 ± 62.80**

19.92

B 3RM

Barbell push strength

Group

10RM 3RM

A

B Leg bend and pull strength

10RM 3RM

Maximal leg strength

Left Right

A

B

# /## compared with the control group (P < 0.05/0.01), * /** compared with the initial value of this

group before the test (P < 0.05/0.01).

4 Conclusions Reasonable nutrition supplement can enhance muscle strength, and different muscleenhancing supplement programs have different effect on muscle strength. The time and type of nutrient supplement will affect the growth of muscle strength [4–7]. Supplement of carbohydrate during or after exercise can increase the secretion of insulin and reduce the loss of protein [8–10]. Supplement of carbohydrate and protein after exercise can help the body build protein, increase the cross-sectional area of muscle fiber, and promote the development of muscle [11]. In this study, the experimental group was given sucrose and glucose before and during training, and given sucrose, glucose, maltodextrin and whey protein powder within 30

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min after training; while the control group was only given whey protein fortified solid beverage within 30 min after training. Compared with before the experiment, the results showed that the 10RM and 3RM of barbell squat, leg bend and pull, and maximal leg strength in the experimental group and the control group were significantly increased (P < 0.01), and the 10RM and 3RM of barbell push in the experimental group and the control group were significantly increased (P < 0.05). After muscle-enhancing supplement, the proportion of muscle strength improvement in the experimental group was higher than that in the control group; the muscle-enhancing supplement program of experimental group was better than the control group. This study observed the effect of different muscle-enhancing supplement programs on muscle strength and can guide pilots to carry out reasonable nutritional supplement in anti-G physical training. Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Wang, J., Cao, X.S.: Complete book of aerospace medicine: aerospace physiology and psychology training and recuperation. Fourth Military Medical University Press, Xi’an: 63 (2013) 2. Yang, Z.Y.: Sports Nutritionist Course, pp. 223–238. People Sports Press, Beijing (2008) 3. Febbraio, M.A., Flanagan, T.R., Snow, R.J., et al.: Effect of creatine supplementation on intramuscular TCr, metabolism and performance during intermittent, supramaximal exercise in humans. Acta Physiol. Scand. 155(4), 387–395 (1995) 4. Zhang, L.H.: Effects on different types of protein powders’ muscle growth. J. Shenyang Sport Univ. 26(6), 48–49, 55 (2007) 5. Wen, A., Wang, Q., Fang, Z.L., et al.: Influence of single-bout resistance training and carbohydrate-protein supplementation on urine androgen metabolism of male boxers and bodybuilders. Chin. J. Sports Med. 31(9), 766–771 (2012) 6. Chen, L.W.: Analysis of muscle movement strength under high protein food intake. Bull. Sci. Technol. 30(9), 65–68 (2014) 7. Yu, M.C., Wei, B., Li, Q.G., Yang, Z.Y.: Effects of various muscle-enhancing supplements’ formulas on physical ability and corresponding metabolic parameters of athletes. J. Nanjing Sports Inst. 4, 41–49 (2019) 8. Haff, G.G., Koch, A.J., Potteiger, J.A., et al.: Carbohydrate supplementation attenuates muscle glycogen loss during acute bouts of resistance exercise. Int. J. Sport Nutr. Exerc. Metab. 10, 326–339 (2000) 9. Tipton, K.D., Rasmussen, B.B., Miller, S.L., et al.: Timing of amino acid-carbohydrate ingestion alters anabolic response of muscle to resistance exercise. Am. J. Physiol. Endocrinol. Metab. 281, 197–206 (2001) 10. White, J.P., Wilson, J.M., Austin, K.G., et al.: Effect of carbohydrate-protein supplement timing on acute exercise-induced muscle damage. J. Int. Soc. Sports Nutr. 5, 5 (2008) 11. Ivy, J.L.: Glycogen resynthesis after exercise: Effect of carbohydrate intake. Int. J. Sports Med. 19, 142–145 (1998)

Effects of Muscle-Enhancing Nutrition Support on Anthropometric Indexes After Anti-G Physical Training Peng Du, Ruoyong Wang, Xichen Geng, Yan Xu, Shuang Bai, Ximeng Chen, Longmei Fang, Lili Zhang, Xiaoli Zhang, Baohui Li, Peng Liu, Feng Li, Hongjiang Jing, and Huiling Mu(B) Air Force Medical Center, Beijing 100142, China

Abstract. Objective—To explore the effect of muscle-enhancing nutrition support on anthropometric indexes after anti-G physical training. Methods—Ten healthy male volunteers were randomly divided into experimental group and control group. Based on anti-G physical training, different muscle-enhancing nutrition support were used for 16 weeks. Anthropometric indexes were measured every two weeks. Results—The neck circumference, chest circumference, armpit upper arm circumference, upper arm circumference, upper arm minimum circumference and upper arm maximum circumference increased, while waist circumference, hip circumference and thigh circumference decreased in the experimental group and the control group. The body weight, fat free mass and muscle mass increased, while body fat percentage and fat mass decreased significantly (p < 0.05) in the experimental group. The body weight, boy fat percentage and fat mass increased while the fat free mass and muscle mass decreased in the control group. Conclusions—The results showed that the nutrition support in the experimental group could help improving muscle mass and reducing fat mass, and the effect was better than that in the control group. Keywords: Nutrition support · Anti-G physical training · BMI · Body composition · Body circumference

1 Introduction Researches showed that the increase of muscle strength in lower limbs, neck, respiratory muscle and other parts of the body could significantly improve the +Gz tolerance of the pilots [1–4]. Russian pilots must pass the pedaling force test of 280 kg for 30 s before conducting high-performance fighter flight training, otherwise they will be disqualified from flying [5]. It can be seen that enhancing muscle strength is of great significance to improve the anti-G endurance of pilots. Reasonable nutrition can not only eliminate muscle soreness, fatigue and other symptoms caused by strength training, but also promote muscle reconstruction and therefore effectively promote the growth of muscle strength. At present, reasonable nutrition combined with scientific training to increase muscle strength is widely used in competitive © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 99–107, 2022. https://doi.org/10.1007/978-981-16-5963-8_14

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sports, sports fitness and other fields [6], but few studies were reported on increasing the effect of flight physical training. In this study, the human experiment of muscleenhancing nutrition supports was carried out on the basis of anti-G physical training to observe there influences on anthropometric indexes, so as to evaluate the effect of nutrition support on muscle enhancing.

2 Subjects and Methods 2.1 Subjects Ten healthy male volunteers were included, with the average age (19.00 ± 1.15) years old, the average height (170.90 ± 1.29) cm and the average weight (63.38 ± 3.60) kg. The subjects were randomly divided into the experimental group (group A) and the control group (group B). Five people in each. All subjects did not take muscle-enhancing supplement in 5 weeks before the experiment. On the basis of anti-G muscle strength training, muscle-enhancing nutrition support were carried out for 16 weeks in both group A and B. Anthropometric indexes were measured every two weeks to evaluate the effect of nutrition support. During the whole experimental period, the subjects ate in accordance with the requirements. Any adverse event or unexpected event happen the trial would be stopped. 2.2 Methods 2.2.1 Muscle-Enhancing Nutrition Supports Group A and B were given different muscle-enhancing nutrition support for 16 weeks. Group A was given complex carbohydrate solution (20 g sucrose and 10 g glucose mixed with purified water) and took it in several times before and during training. Then within 30 min after training Group A took compound protein powder solution (30 g whey protein powder, 10 g sucrose, 10 g glucose and 10 g maltodextrin mixed with purified water) for once. Group B took purified water before and during the training, and commercially available products (whey protein fortified solid beverage 40 g mixed with purified water) within 30 min after the training. The amount of drinking water of group A and group B was not limited during the training. 2.2.2 Anti-G Physical Training Method Using barbell, dumbbell, sitting and pedaling training device, neck training device, waist training device and other strength training equipment, the strength training of lower limb muscle, waist and abdominal muscle, chest and back muscle, neck muscle, respiratory muscle and other anti-G muscle groups was carried out. Each movement practiced 3 groups and repeated 8–12 times in each group. The breathing mode of HP anti-G movement was integrated into the training movement. A total of 16 weeks of training was carried out. Both of the groups trained from Monday to Friday in the afternoon and rest on Saturday and Sunday.

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2.2.3 Anthropometric Indexes Anthropometric indicators, including body mass index (BMI), body circumference and body composition, were measured in the morning before breakfast after the subjects relieve themselves. BMI The height and weight of the subjects was measured. BMI was calculated according to Eq. (1). BMI =

Weight(kg)   Height 2 m2

(1)

Body Circumference According to the requirements of “Basic human body measurements for technological design”(GB/T 5703) [7] and “Human dimensions of Chinese male pilot population” (GJB 4856) [8], the subjects took a standing posture and measured the neck circumference (NC), chest circumference(CC), bilateral upper arm circumference [armpit upper arm circumference (AUAC), upper arm circumference (UAC), maximum upper arm circumference (UACMax), minimum upper arm circumference (UACMin)], waist circumference (WC), hip circumference (HC), bilateral thigh circumferences (TC). Body Composition JAWON X-Scan plus II body composition analyzer was used to measure the body composition of the subjects, including segmental analysis of the body muscle [muscle mass (MM), left upper limb muscle mass (LULMM), right upper limb muscle mass (RULMM), left lower limb muscle mass (LLLMM), right lower limb muscle mass (RLLMM), trunk muscle mass (TMM)], fat mass (FM), body fat percentage (BF%), fat free mass (FFM), body weight (BW), etc. The subjects were not allowed to take vigorous exercise before the test and couldn’t carry items such as metal stuff during the test. 2.3 Statistical Analysis All data were expressed by means and standard deviation (x±s). SPSS 22.0 software was used for data processing. Independent sample t-test was used for inter group comparison, and paired sample t-test was used for intra group comparison. p < 0.05 was considered as significant difference.

3 Results and Analysis 3.1 BMI As shown in Table 1, the BMI of the experimental group and the control group increased first and then decreased. Compared with before the experiment, the BMI of the experimental group and the control group increased slightly.

2w

21.66 ± 1.27

22.64 ± 1.51

0w

21.26 ± 1.15

22.14 ± 1.30

Group

A

B

22.80 ± 1.38

21.98 ± 1.20

4w 22.42 ± 1.33

21.54 ± 1.02

6w 22.53 ± 1.47

21.51 ± 1.17

8w 22.14 ± 1.59

21.42 ± 0.94

10w

Table 1. BMI of both groups (kg/m2 )

21.88 ± 1.61

21.34 ± 1.17

12w

22.22 ± 1.63

21.39 ± 1.09

14w

22.24 ± 1.84

21.38 ± 1.11

16w

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Group A B A B A B A B A B A B A B A B A B A B A B A B A B A B

0w 36.10 ± 1.34 36.01 ± 1.37 88.45 ± 3.81 90.89 ± 2.74 29.91 ± 1.47 30.31 ± 0.98 28.31 ± 1.35 28.95 ± 1.20 26.86 ± 1.44 27.27 ± 1.15 30.59 ± 1.64 30.82 ± 1.15 30.05 ± 1.55 30.83 ± 1.33 28.24 ± 1.70 28.88 ± 1.38 26.52 ± 1.44 26.78 ± 1.12 30.81 ± 1.67 30.78 ± 1.14 76.37 ± 1.11 78.78 ± 1.73 93.82 ± 2.67 97.99 ± 1.47 57.06 ± 2.18 59.64 ± 2.67 57.11 ± 1.90 59.77 ± 3.13

2w 36.44 ± 1.03 36.63 ± 1.57 88.37 ± 3.55 92.54 ± 3.33 30.57 ± 1.84 31.59 ± 1.22 29.19 ± 1.15 30.54 ± 1.48 27.55 ± 1.18 28.81 ± 1.51 31.24 ± 2.32 31.89 ± 1.12 30.86 ± 1.63 31.19 ± 1.29 29.98 ± 1.49 30.16 ± 1.28 27.98 ± 1.51 28.61 ± 1.12 31.92 ± 2.08 31.67 ± 1.14 75.65 ± 1.22 80.00 ± 2.49 94.35 ± 2.62 97.11 ± 2.71 58.53 ± 2.46 60.65 ± 2.38 57.91 ± 2.56 60.46 ± 2.47

4w 37.25 ± 0.98 36.59 ± 1.28 87.83 ± 5.76 91.02 ± 4.77 30.64 ± 1.42 31.25 ± 1.09 29.29 ± 1.39 30.24 ± 1.19 27.25 ± 1.80 28.28 ± 1.95 31.80 ± 1.54 31.79 ± 1.18 31.25 ± 1.78 31.04 ± 1.00 29.54 ± 1.29 30.04 ± 1.02 27.25 ± 1.58 28.34 ± 1.73 32.13 ± 1.68 31.57 ± 1.28 76.24 ± 2.30 77.89 ± 2.06 95.13 ± 1.66 98.01 ± 1.55 57.89 ± 2.31 59.03 ± 3.10 58.55 ± 2.25 59.43 ± 2.34

6w 36.57 ± 1.12 36.65 ± 1.49 88.71 ± 2.62 91.46 ± 1.58 30.71 ± 1.02 31.13 ± 0.83 28.97 ± 0.66 29.77 ± 1.07 26.46 ± 1.25 27.51 ± 1.23 32.12 ± 1.21 31.79 ± 0.92 30.79 ± 1.49 31.26 ± 0.82 29.36 ± 0.92 29.59 ± 1.07 26.97 ± 1.40 27.83 ± 1.25 32.51 ± 1.18 31.80 ± 0.88 75.93 ± 0.87 77.63 ± 2.34 91.90 ± 1.39 94.73 ± 2.83 55.43 ± 2.01 56.88 ± 2.82 55.79 ± 1.77 57.57 ± 2.73

Note: * /** Compared with the initial value before the experiment (p < 0.05/0.01)

Right TC

Left TC

HC

WC

Right UACMax

Right UACMin

Right UAC

Right AUAC

Left UACMax

Left UACMin

Left UAC

Left AUAC

CC

Index NC

8w 36.97 ± 0.48 36.68 ± 1.51 89.42 ± 4.27 92.08 ± 2.88 31.06 ± 2.78 32.81 ± 2.40 28.95 ± 1.09 30.04 ± 0.92 26.36 ± 1.09 27.32 ± 1.62 31.57 ± 1.95 31.80 ± 1.39 30.88 ± 2.64 31.98 ± 2.41 29.47 ± 1.59 30.08 ± 1.44 26.79 ± 1.24 27.34 ± 1.53 32.33 ± 2.20 31.56 ± 1.46 75.24 ± 1.18 78.22 ± 2.66 92.48 ± 2.29 95.51 ± 2.95 55.64 ± 2.12 57.83 ± 3.92 55.65 ± 2.13 58.31 ± 3.74

10w 36.57 ± 1.05 36.38 ± 1.95 88.07 ± 3.13 91.43 ± 2.09 30.89 ± 1.86 30.86 ± 1.62 29.47 ± 1.33 29.52 ± 1.45 26.93 ± 1.70 27.77 ± 1.50 31.68 ± 1.49 31.56 ± 1.59 31.30 ± 1.62 30.79 ± 1.83 29.29 ± 1.39 29.44 ± 1.42 27.19 ± 1.52 27.49 ± 0.96 31.93 ± 1.54 31.54 ± 1.50 74.09 ± 1.00 76.07 ± 1.87 91.29 ± 1.88 93.96 ± 2.43 55.03 ± 3.24 56.89 ± 4.28 55.24 ± 2.61 57.53 ± 3.79

Table 2. Body Circumference of both groups (cm) 12w 36.55 ± 0.91 36.29 ± 1.74 89.07 ± 5.02 91.40 ± 3.25 30.08 ± 1.50 30.00 ± 1.42 29.18 ± 1.52 29.51 ± 1.55 27.51 ± 1.77 27.29 ± 0.99 31.78 ± 1.66 31.57 ± 1.69 30.65 ± 2.03 29.80 ± 1.04 29.31 ± 1.61 29.18 ± 1.52 27.61 ± 1.36 27.48 ± 1.32 32.21 ± 1.90 31.29 ± 1.38 74.96 ± 1.63 76.45 ± 2.68 92.69 ± 1.77 94.97 ± 2.30 54.20 ± 2.09 55.99 ± 3.59 54.71 ± 2.54 56.48 ± 3.99

14w 37.00 ± 1.02 36.86 ± 1.67 89.14 ± 1.93 91.11 ± 3.02 30.87 ± 1.94 30.65 ± 1.08 29.46 ± 1.36 29.29 ± 1.17 26.96 ± 1.48 27.26 ± 1.63 32.03 ± 1.45 31.51 ± 1.43 31.47 ± 1.37 30.45 ± 1.28 29.56 ± 1.95 29.36 ± 1.06 27.03 ± 1.41 27.45 ± 1.48 32.27 ± 2.02 31.53 ± 1.31 76.30 ± 1.47 77.41 ± 2.50 93.21 ± 2.59 95.33 ± 3.01 54.09 ± 1.97 55.65 ± 4.00 54.35 ± 2.56 55.81 ± 3.87

16w 36.69 ± 0.97 36.59 ± 1.23 89.10 ± 1.90 91.59 ± 3.85 31.01 ± 2.13 30.69 ± 0.68 29.23 ± 1.66 29.25 ± 1.25 27.24 ± 2.14 27.41 ± 1.87 31.37 ± 1.56** 31.37 ± 1.20 30.71 ± 2.28 30.90 ± 1.10 29.38 ± 1.53** 29.47 ± 1.26 27.12 ± 2.06 27.38 ± 1.60 32.23 ± 1.76** 31.41 ± 0.95 74.12 ± 1.86* 77.98 ± 4.23 91.91 ± 2.65 94.44 ± 3.48* 54.70 ± 2.47 55.71 ± 4.32** 54.74 ± 1.88* 56.33 ± 4.11**

Effects of Muscle-Enhancing Nutrition Support 103

51.12 ± 1.33

3.48 ± 0.26

3.51 ± 0.12

3.45 ± 0.28

3.50 ± 0.13

9.76 ± 0.62

9.42 ± 0.32

9.56 ± 0.70

9.35 ± 0.27

25.73 ± 1.41

25.35 ± 0.54

50.50 ± 1.53

3.38 ± 0.23

3.37 ± 0.19

3.36 ± 0.25

3.31 ± 0.17

9.15 ± 0.62

9.61 ± 0.54

9.05 ± 0.63

9.32 ± 0.24

24.72 ± 1.05

24.89 ± 0.53

A

B

A

B

A

B

A

B

A

B

B

B

51.97 ± 3.13

7.77 ± 2.52

8.98 ± 1.91

A

10.94 ± 2.49

16.49 ± 2.71

15.74 ± 2.28

B

49.66 ± 2.65

12.17 ± 3.60

14.36 ± 2.68

A

10.22 ± 2.02

54.96 ± 1.55

54.26 ± 1.71

B

A

55.69 ± 3.26

53.30 ± 2.82

25.72 ± 0.45

26.05 ± 1.36

9.52 ± 0.19

9.75 ± 0.73

9.64 ± 0.21

9.82 ± 0.66

3.52 ± 0.14

3.52 ± 0.25

3.56 ± 0.13

3.56 ± 0.24

51.95 ± 0.98

52.68 ± 3.13

10.54 ± 2.68

7.99 ± 1.71

15.76 ± 3.12

12.36 ± 2.36

55.81 ± 1.20

56.48 ± 3.34

66.35 ± 3.77

64.47 ± 3.82

4w

25.32 ± 0.57

25.87 ± 1.60

9.34 ± 0.25

9.67 ± 0.69

9.41 ± 0.29

9.80 ± 0.85

3.43 ± 0.13

3.47 ± 0.26

3.48 ± 0.13

3.52 ± 0.27

50.97 ± 1.32

52.32 ± 3.62

10.49 ± 2.40

7.34 ± 3.10

15.96 ± 2.74

11.56 ± 4.71

54.77 ± 1.48

56.06 ± 3.72

65.26 ± 3.77

63.40 ± 3.09

6w

Note: * /** Compared with the initial value before the experiment (p < 0.05/0.01)

TMM (kg)

RLLMM (kg)

LLLMM (kg)

RULMM (kg)

LULMM (kg)

MM (kg)

FM (kg)

BF% (%)

65.90 ± 4.03

64.48 ± 3.60

B

A

63.46 ± 3.87

62.28 ± 3.64

A

BW (kg)

FFM (kg)

2w

0w

Group

Index

25.33 ± 0.66

25.56 ± 1.34

9.30 ± 0.29

9.42 ± 0.58

9.30 ± 0.30

9.43 ± 0.59

3.56 ± 0.13

3.49 ± 0.28

3.56 ± 0.13

3.52 ± 0.27

51.03 ± 1.49

51.40 ± 3.01

10.66 ± 2.42

8.24 ± 2.30

16.15 ± 2.72

12.93 ± 3.36

54.88 ± 1.70

55.12 ± 3.20

65.54 ± 4.06

63.36 ± 3.81

8w

24.95 ± 0.73

25.44 ± 1.47

9.07 ± 0.30

9.33 ± 0.63

9.12 ± 0.34

9.35 ± 0.63

3.47 ± 0.15

3.51 ± 0.24

3.48 ± 0.16

3.53 ± 0.25

50.09 ± 1.66

51.14 ± 3.17

10.65 ± 2.59

8.08 ± 2.22

16.37 ± 3.01

12.82 ± 3.34

53.83 ± 1.84

54.82 ± 3.34

64.48 ± 4.30

62.90 ± 3.41

10w

Table 3. Body composition of the two groups

24.95 ± 0.90

25.49 ± 1.92

9.14 ± 0.39

9.40 ± 0.87

9.17 ± 0.44

9.69 ± 1.05

3.42 ± 0.14

3.45 ± 0.31

3.44 ± 0.15

3.47 ± 0.31

50.10 ± 1.99

51.48 ± 4.41

10.14 ± 2.45

7.56 ± 2.65

15.71 ± 2.64

12.07 ± 4.07

53.84 ± 2.26

55.18 ± 4.63

63.98 ± 4.63

62.74 ± 4.10

12w

24.96 ± 0.72

25.34 ± 1.31

9.11 ± 0.35

9.33 ± 0.50

9.17 ± 0.30

9.34 ± 0.59

3.44 ± 0.14

3.45 ± 0.26

3.45 ± 0.13

3.46 ± 0.25

50.12 ± 1.59

50.90 ± 2.87

10.74 ± 2.76

8.39 ± 2.23

16.45 ± 3.16

13.27 ± 3.25

53.88 ± 1.81

54.61 ± 3.05

64.62 ± 4.50

63.00 ± 3.53

14w

25.07 ± 0.80

25.26 ± 1.29

9.19 ± 0.35

9.19 ± 0.53

9.24 ± 0.46*

9.45 ± 0.60

3.47 ± 0.15*

3.45 ± 0.30

3.48 ± 0.17*

3.48 ± 0.27*

50.44 ± 1.89

50.82 ± 2.91

10.52 ± 2.97

8.53 ± 2.00*

16.05 ± 3.33

13.47 ± 2.85*

54.22 ± 2.17

54.51 ± 3.12

64.74 ± 5.05

63.04 ± 3.93

16w

104 P. Du et al.

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3.2 Body Circumference As shown in Table 2, the NC, CC, AUAC, UAC, UACMin and UACMax of the experimental group and the control group were increased compared with those before the experiment; the left and right UACMax and UAC of the experimental group were significantly increased (p < 0.01); the right UAC of the control group was significantly increased (p < 0.01). The WC, HC and TC of the experimental group and the control group were decreased; the WC and right TC of the experimental group were significantly reduced (p < 0.05); the HC of the control group was significantly reduced (p < 0.05), and the left and right TC was significantly reduced (p < 0.01). 3.3 Body Composition As shown in Table 3, compared with before the experiment, the BF% and the amount of FM in the experimental group were significantly decreased (p < 0.05), and the amount of LULMM in the experimental group and the LULMM and RULMM as well as LULMM in the control group were significantly increased (p < 0.05). The BW of the experimental group and the control group increased, which was consistent with the result of BMI. The results showed that the TMM of the experimental group and the control group increased; the BF% and FM of the experimental group decreased significantly (p < 0.05), but the BF% and FM of the control group increased; the FFM and MM of the experimental group increased, but the FFM and MM of the control group decreased slightly; the LLMM of the experimental group increased, but the LLMM of the control group decreased.

4 Conclusions The size of body circumference can indirectly reflect the strength of muscle groups of limbs and trunk. In this study, the NC, CC, AUAC, UAC, UACMin, UACMax of the experimental group and the control group increased, while the WC, HC and TC decreased. The results showed that the nutrition support of the experimental group and the control group had a certain effect on improving body circumference. The possible reason for the decrease of WC and HC is that there are many influencing factors. Muscle thickness and subcutaneous fat thickness are two main factors, which reflect the comprehensive situation of muscle volume and subcutaneous fat volume of WC and HC [9, 10]. The body fat is not evenly distributed in the subcutaneous. WC and HC reflect the thickness of subcutaneous fat more, while NC, CC and LC reflect muscle slightly more [11, 12]. Therefore, the decrease of WC and HC may be related to the decrease of fat mass. Body composition indexes can further distinguish the changes of body muscle and fat [13]. In this study, the BW, FFM and MS of the experimental group increased, while the BF% and FM decreased significantly (p < 0.05); while the BW, BF% and FM of the control group increased, while the FFM and MM decreased. The results showed that after 16 weeks of strength training combined with nutrition support, both the experimental group and the control group achieved a certain weight gain. The nutrition support of the experimental group had a certain effect on the increase of MM and the decrease of FM,

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while the nutrition support of the control group had no effect on the increase of MM and the decrease of FM. It could be concluded that the experimental nutrition support is better than the control one. The disadvantage of this study is that the sample size is small, and due to the limitation of research cycle, no cross test was carried out, which leads to the test results have a certain trend of improvement, but the statistical difference is not significant. The sample size should be increased if some tests took later. Cross test should be carried out if the sample size of subjects is small and the research period permits, so as to further verify the effect of nutrition support. Acknowledgements. The work was supported by the Criteria Programme No BWS12B142.

Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Kobayashi, A., Kikukawa, A., Onozawa, A.: Effect of muscle tensing on cerebral oxygen status during sustained high +Gz. Aviat. Space Environ. Med. 73(6), 597–600 (2002) 2. Geng, X.C., Zhan, C.L., Chu, X., et al.: Respiratory muscle training and endurance. Chin. J. Aerosp. Med. 2(3), 133–136 (1991) 3. Burton, R.R.: Guidelines for a research and development (R&D) program for high sustain G. Physiologist 36(1(Suppl)), S94–S97 (1993) 4. Khomenko, M.N., Vartbaronov, R.A., Migachyov, S.D.: Prognostication of flyer’s +Gz tolerance on the base of static muscular strength endurance. Physiologist 35(1Suppl), S126–S129 (1992) 5. Li, L.H., Li, B.H., Geng, X.C., et al.: Study on the relationship between lower limb exertion and +Gz endurance. Chin. J. Appl. Physiol. 21(4), 417–418 (2005) 6. Beals, K., Darnell, M.E., Lovalekar, M., et al.: Suboptimal nutritional characteristics in male and female soldiers compared to sports nutrition guidelines. Mil. Med. 80(12), 1239–1246 (2015) 7. General Administration of quality supervision, inspection and Quarantine of the people’s Republic of China. GB/T 5703-2010. Basic human body measurements for technological design 8. General Equipment Department of PLA. GJB 4856-2003. Human dimensions of Chinese male pilot population 9. Mao, A.H., Wang, R.: Comparative study of five skinfold-thickness equations for predicting percentage body fat in obese children and adolescents. J. Shenyang Sport Univ. 34(1), 98–101 (2015) 10. Xu, G.C., Ma, C.D., Liu, N., et al.: Correlation between muscle mass and fat mass and limb circumference basis on electrical impedance in adults of He’nan Hui ethnicity. Acta. Anat. Sin. 47(1), 122–128 (2016) 11. Wang, J.J., Wang, J.H., Liu, J.S., et al.: The association between body mass index, waist circumference with body fat percent, and abdominal fat rate in overweight and obese pupils. Chin. J. Prev. Med 47(7), 603–607 (2013)

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12. Liu, L.J., Zhao, W.H., Rong, M.: Correlation analysis between thickness of abdomen fat and body mass index and waistline. Chin. J. Misdiagn. 9(31), 7577–7578 (2009) 13. Van Gaal, L.F., Maggioni, A.P.: Overweight, obesity, and outcomes: fat mass and beyond. Lancet 383(9921), 935–936 (2014)

Investigation on Dietary Structure and Nutritional Health Status of Cadets in Air Force Youth Aviation School Longmei Fang, Guangyun Wang, Ruoyong Wang, Shuang Bai, Dongyun Fen, Bingqian Guo, Qiao Ye, Huiling Mu, Yuan Luo, Zhusong Mei, Ximeng Chen, and Peng Du(B) Air Force Medical Center, PLA, Beijing 100142, China

Abstract. Objective— To investigate the dietary characteristics and nutritional health status of cadets in air force youth aviation school. Methods— The 24-h dietary survey was used to investigate the dietary structure. The body composition index and blood biochemical indexes were measured to evaluate their health status. Results— According to the dietary guidelines for Chinese residents, the intake of fruits was seriously insufficient, reaching only 53.48%–80.23%. The intakes of sodium, potassium and phosphorus were high, calcium, iron, zinc and iodine were low. Folic acid intake reached 50.58% of the recommended amount of Chinese residents. The energy supply for breakfast was 23.97%, which was lower than the recommended amount, while the dinner was higher. Carbohydrate provided 1163.6 kcal (39.80%), which was lower than standard recommended. The proportion of protein intake from animal origin was slightly higher than the upper limit (50%) recommended by military standard. Among the blood biochemical indexes, only VD (25-OH) was low. Conclusions— The dietary structure of the cadets is not reasonable, and the intake of minerals and the energy supply ratio of the three nutrients are unbalanced. The overall nutritional health status was good, individual students had malnutrition. Keyword: Cadets in air force youth aviation school · Dietary survey · Nutrition and health

1 Introduction In order to meet the needs of the army’s information construction and the generation of new quality combat effectiveness, the cadets of the air force youth aviation school, as a new type of flight talents in the field of military aviation, came into being [1]. At the same time, they also put forward higher requirements for the cultural quality, psychological quality and physical quality of the cadets. The cadets of this age group are in a critical period of physical development and ideological formation [2–4]. Reasonable diet and nutrition is the basis for their normal growth and development, and will also have a profound impact on their future dietary behavior and health [5–7]. At present, there are few reports about the nutritional and health status of this special group. This © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 108–115, 2022. https://doi.org/10.1007/978-981-16-5963-8_15

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study investigated the dietary structure and nutritional health status of the cadets of the air force youth aviation school, in order to provide the basis for guiding them to have a reasonable diet.

2 Objects and Methods 2.1 Objects By using the cluster random sampling method, cadets from an air force youth aviation school was randomly selected from a theater in 2019 for dietary survey and nutritional evaluation. The average age was (16.84 ± 0.69) years old and the average height was (1.75 ± 0.43) m. 2.2 Methods 2.2.1 Dietary Survey The “24-hour dietary survey review method” was used to review the type and quantity of all foods taken in the previous 24 h on the next day for 3 consecutive days. Based on the Chinese food composition Table 2, the collected data were input into the nutrition guidance software to calculate the average daily nutrient intake per person and so on. According to the dietary guidelines for Chinese residents, the recommended dietary intake of 14–18 years old residents [8], the nutrient supply standard for military personnel (GJB823b-2016) [9] and the food quantitative standard for military personnel (GJB826b2010) [10] as the evaluation basis, the food intake and nutrient intake should be within ±10% of the standard value, less than 90% is insufficient, and more than 110% is excessive [11]. 2.2.2 Assessment of Nutritional Status Body Mass Index (BMI), body fat rate, visceral fat rate and body water rate were measured by Japan belita MC-980Mas bioelectrical impedance analyzer. BMI classification standard accord to the Chinese adolescent nutritional status. Body fat rate ≤22%, visceral fat rate S3 > S4 . Sensory evaluation results showed that the sensory quality of cheese purple potato soup was the best, and the sensory quality of matcha wheat soup was the worst. The comprehensive scores of Cheese purple potato soup, gigan pumpkin soup and cocoa black bean soup were between 7 and 8, closed to 7, indicating that the three kinds of sticky soup food preferred to like between like and very like. And the comprehensive scores of matcha wheat seedling soup was between 6 and 7, closed to 7, indicating that matcha wheat seedling soup preferred to like between a little like and like.

4 Conclusions In this study, the sensory quality of four kinds of sticky soup food was evaluated by fuzzy mathematics sensory evaluation method with color, status, smell, texture and taste. The results showed that the fuzzy comprehensive sensory evaluation scores of four kinds of sticky soup foodfrom high to low were cheese purple potato soup, guggen pumpkin soup, cocoa black bean soup, matcha wheat soup. Fuzzy mathematics method overcame

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the influence of subjective factors, can reflect the sensory quality more objectively and accurately, and provided a reference method for the comprehensive sensory quality evaluation of sticky soup food. Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Huo, H.: Application of fuzzy mathematics in quality control method of food sensory evaluation. Food Sci. 25(6), 185–188 (2004) 2. Chen, Y.M.: Application of food sensory analysis technology in product development. Food Res. Dev. 28(2), 182–185 (2007) 3. Jin, S.K., Li, Y.: The application of fuzzy comprehensive judgment method in food sensory analysis. Meat Res. 25(1), 64–67 (2011) 4. Shi, B.L., Zhao, L., Wang, H.Y., et al.: The technical dynamic analysis of the performance evaluation of the sensory analysis and evaluation team and its members. Food Sci. 35(8), 29–35 (2014) 5. Zeng, X., Zeng, S.M., Long, W.Z.: The application and development of food sensory evaluation technology. Chin. Condiments 44(3), 198–200 (2019) 6. Mu, H.L., Du, P., Bai, S., et al.: Study on sensory evaluation of military instant rice by fuzzy mathematics method. Farm Prod. Process. 8, 13–16 (2020) 7. Chen, X.M., Du, P., Mu, H.L., et al.: Study on sensory evaluation of military freeze-dried fruits and vegetables by fuzzy mathematics method. Farm Prod. Process. 2, 50–53 (2021)

The Evaluation of Cognitive Control Ability Under the Variable Operation Conditions Yang Liao, Yishuang Zhang, Yan Zhang, Duanqin Xiong, Xueqian Deng, Juan Liu, and Liu Yang(B) Air Force Medical Center, Air Force Medical University, Beijing 100142, China [email protected]

Abstract. Cognitive ability evaluation is the main content of pilot psychological selection. Most of the existing cognitive ability assessment is based on a single cognitive ability assessment under normal condition, which does not consider the fluctuation of cognitive ability under the variable operation conditions. In this study, lower body negative pressure bucket was used to simulate accelerated stress, and digital Stroop task was used to evaluate the individual’s cognitive control ability. The results showed that the main effect of stimulus information type was significant (F = 22.96, P < 0.01), and the response time to conflict stimulus was significantly greater than that to consistent stimulus (P < 0.05). With the change of operation condition, the fluctuation of cognitive control ability is not completely consistent across subjects. The findings in the current study indicated that digital Stroop task can be applied as an assessment tool of cognitive control ability, and operation condition should be included as a variable in the evaluation of cognitive ability to comprehensively understand the level of individual cognitive ability. Keywords: Variable operation conditions · Psychological selection · Cognitive control

1 Introduction From the perspective of competency, pilot selection involves the evaluation of knowledge, ability, skills, personality and other characteristics. Among those factors, cognitive ability is the main content of ability. At present, the application of computer test to collect a single set of data is the common mode. Based on the group norm distribution, the percentage grade score or standard score could be obtained as the indicators of cognitive ability selection. However, the flight task is different from the ordinary operation task, pilots often face multiple stress during flight, which causes the change of operation condition. Such as acceleration (G overload) and hypoxia will affect the brain function and lead to the damage of job performance [1]. Due to the differences of physiological tolerance and self-regulation ability, the decline rate of work efficiency is different among individuals under the stress of the same parameters. Therefore, the psychological selection of pilots should not only be limited to a single set assessment of cognitive ability under the normal condition. Consideration of the decline of individual cognitive © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 186–191, 2022. https://doi.org/10.1007/978-981-16-5963-8_27

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ability under the variable operation conditions is needed, so as to avoid the selection of candidates with high cognitive ability under the normal state but great cognitive impairment under changed operation condition. This is of great importance for the accurate selection of pilots. According to the existing literature, the U.S. Air Force has designed G-performance assessment simulation system (G-PASS), a test tool for pilots’ cognitive ability under G overload [2]. It can display the curve of cognitive function changing with overload G per second, and find out the decline degree of cognitive function under the specific overload G curve. This study provides a good method for the evaluation of cognitive ability under different G conditions. The equipment needs to be used with manned centrifuge, which limits its wide use in personnel selection. In order to evaluate the effect of G overload on individual cognitive ability more conveniently, we can also use the lower body negative pressure (LBNP) equipment to simulate the cerebral ischemia after acceleration stress, so as to establish the stress gradient based on different negative pressure parameters, which can be used to evaluate the changes of individual cognitive ability under different operation conditions [3]. In the current study, lower body negative pressure bucket was used to simulate accelerated stress, and digital Stroop task was used to evaluate the individual’s cognitive control ability. By comparing the changes of cognitive control ability between baseline state and LBNP state, this paper attempts to provide data reference for establishing the evaluation method of cognitive control ability under variable operation conditions.

2 Method 2.1 Participants Eight young male subjects were recruited; they are all right-handed, with an average age of 20.75 years, ranged from 20 to 23 years. They are all in normal vision and with no history of brain injury. 2.2 Tools The subjects needed to complete two rounds of experiment: lower body negative pressure (LBNP) and baseline. During each round of experiment, the subjects performed a 5-min digital Stroop task in the supine position, the decompression parameter was – 50 mmHg during LBNP condition. There are 72 trials in digital Stroop task. Each trail start at the black cross fixation point in the center of the screen (lasting for 500ms), and then the digital stimulus is presented in the center of the screen. The presentation time range from 0 to 2500 ms, and the stimulus is automatically disappeared after subject pressed the response key. The stimulus is a group of digits, and the number of digits is ranged from 1 to 4, and the digits content is also composed of 1, 2, 3 and 4. There are two types of stimulus. Consistent stimulus is that the number of digits is consistent with the content of digits, such as “22”. The inconsistent stimulus is that the number of digits is inconsistent with the content of digits, such as “444”. The subjects were asked to ignore the interference of

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content of digits, only pay attention to the number of digits, and press the corresponding number key in keyboard. That is, press “1” for single digit, press “2” for double digit, and so on. Reaction time (RT) was recorded. After subjects press the key, a blank screen is displayed, and then the next trail would start (Fig. 1).

Fig. 1. Flow chart of digital Stroop task

2.3 Statistics Statistical package for the social sciences (SPSS 20.0) was used for statistic, and the significant level was 0.05.

3 Results 3.1 Comparison of Response Time of Different Types of Stimuli Repeated measures ANOVA showed that the interaction between operation conditions and stimulus type was not significant, F = 1.26, P = 0.30; the main effect of operation conditions was not significant, F = 1.87, P = 0.21; the main effect of stimulus type was significant, F = 22.96, P < 0.01. Pairwise comparison showed that the response time of inconsistent stimulus was significantly higher than that of consistent stimulus, indicating the existence of Stroop effect. It provides a basis for the next step to use the Stroop effect value of the task as an evaluation index of cognitive control ability (Table 1).

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Table 1. Comparison of response time of different types of stimuli RT of consistent stimulus (ms)

RT of inconsistent stimulus (ms)

Baseline

567.75 ± 76.97

622.98 ± 60.13

LBNP

554.42 ± 83.59

594.48 ± 80.76

3.2 Index Calculation of Cognitive Control Ability The RT of inconsistent stimulus was significantly higher than that of consistent stimulus, which confirmed that the experimental paradigm used in the current study could induce stable Stroop effect. Delta RT, the response time difference between inconsistent stimulus and consistent stimulus, was taken as Stroop effect quantity. The logarithm of 10 was taken as the base for delta RT, and then the reciprocal was calculated as the value of cognitive control ability. The higher the value reflects the higher level of cognitive control ability. In order to compress the value of cognitive control ability into the space of 0–1, when delta RT ≤ 10 ms, it is uniformly recorded as 10 ms (Table 2). Table 2. The difference of individual cognitive control ability in variable operation conditions Subject ID

Baseline

LBNP

Value of cognitive control

Rank

Value of cognitive control

Rank

1

0.47

8

0.55

7

2

0.52

6

0.85

1

3

0.52

7

0.58

6

4

0.65

3

0.70

3

5

0.60

4

0.54

8

6

1.00

1

0.69

4

7

0.57

5

0.65

5

8

1.00

1

0.71

2

Most of the subjects’ rank of cognitive control abilities between the baseline and lower body negative pressure condition were almost the same. However, there were still some subjects whose cognitive control ability fluctuated greatly after the change of operation conditions. For example, the cognitive control ability of subject 5 ranked the fourth at baseline, but the rank dropped to the last one in LBNP condition. On the contrary, subject 2 ranked sixth in cognitive control ability at baseline, and jumped to first in LBNP condition. It indicated that it is not accurate to evaluate the level of cognitive control ability only based on the baseline data, and the change of cognitive ability in different operation conditions needs to be included.

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4 Discussion Stroop task is a classic paradigm to assessment cognitive control ability. In the previous studies, color word Stroop task was used to evaluate cognitive control ability through the conflict between semantic information and color information [4–6]. In the current study, we use the digital Stroop task to evaluate cognitive control ability by the conflict between digital meaning and number of digits [7]. This change is used to similar to the daily operation task of pilots, the processing of the digital information displayed by instruments and screen display is important during flight. The results showed that the RT of inconsistent stimulus was significantly higher than RT of consistent stimulus both in baseline and LBNP conditions, indicating that Stroop effect existed, which provided reliable data support for the evaluation of cognitive control ability by digital Stroop task. In the current study, based on the reaction time difference of different type of stimulus, we calculated the index of cognitive control ability, and ranked the subjects’ cognitive control ability in different operation conditions. The results showed that the rank of cognitive control ability was not consistent in different operation conditions. While the operation condition changes, the influences on the cognitive control ability among the subjects are different. Some individuals with better cognitive control ability in the baseline may have a significant decline in the cognitive control ability under the stress of operation condition change. If they are selected in only based on the ability data of the baseline, it will cause potential risks. This suggests change of operation condition should be considered as a variable in the psychological selection of pilot, and then comprehensive evaluation of the individual cognitive ability data across different operation conditions would be helpful.

5 Conclusion In conclusion, the results of the current study found that digital Stroop task could also induce stable Stroop effect, indicating that the task can be used to assess cognitive control ability. It is worth noting that the differences of cognitive control ability of different subjects under the influence of operation condition change indicate that operation condition should be considered as a variable in the selection of cognitive ability. In the future study, the number of subjects and the gradient level of operation conditions should be increased to provide more sufficient evidence for the accurate selection of pilots by cognitive ability evaluation. Acknowledgements. This work is supported by the Youth Development Program of Medicine, No. 19QNP024.

Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Zhu, Y., Liu, X., Geng, X., et al.: Effect of acceleration on pilot operation in short-distance takeoff. Beijing Hangkong Hangtian Daxue Xuebao 44(8), 1748–1754 (2018) 2. O’Donnell, D., Moise, L., Schmidt, R. et al.: Measurement and Modeling of Human Performance Under Differing G Conditions. NTI, Inc., Dayton, OH (2003) 3. Whittaker, R., Bright, G., Driver, D., et al.: Changes in arterial cerebral blood volume during lower body negative pressure measured with MRI. Neuroimage 187, 166–175 (2019) 4. Scarpina, F., Tagini, S.: The stroop color and word test. Front. Psychol. 8, 557 (2017) 5. Zysset, S., Müller, K., Lohmann, G., et al.: Color-word matching stroop task: separating interference and response conflict. Neuroimage 13(1), 29–36 (2001) 6. Pan, Y., Han, Y., Zuo, W.: The color-word stroop effect driven by working memory maintenance. Atten. Percept. Psychophys. 81(8), 2722–2731 (2019) 7. Patria, F., Committeri, G., Daini, R., et al.: Brain activation for selective attention and cognitive interference using the digit-stroop paradigm. NeuroImage 11, s89 (2000)

Correlation Between EEG Band Power and Behavioral Performance Based on Dichotic Listening Task Yang Liao, Yuyang Zhu, Jian Du, Rong Lin, and Liu Yang(B) Air Force Medical Center, Air Force Medical University, Beijing 100142, China [email protected]

Abstract. Previous studies on personnel selection focused more on the cognitive processing of visual information, and it is urgent to pay more attention to auditory information. Ten young male subjects participated in a dichotic listening task, and 64 channel EEG data were recorded simultaneously. The correlation coefficients between delta, theta, alpha, beta, gamma band power and behavioral data in attention task were calculated. The results showed that the total distance and standard deviation of the reaction time of both ears are target stimulus, the left target and right non-target and the average reaction time were relatively larger. Delta and theta band power are dominant in frontal area, while alpha band power is dominant in temporal and occipital area. TP7-beta, CB2-alpha and O2-alpha were significantly correlated with the above three behavioral indicators (P < 0.05). In conclusion, the reaction time and the related EEG band power data in dichotic listening task could be used as potential indicators to evaluate auditory attention ability. Keywords: Dichotic listening · Auditory attention · Band power

1 Introduction Evaluation of cognitive ability is an indispensable part of personnel selection or training outcome evaluation. In particular, some special occupation, such as pilots, soldiers, police and so on, the requirements for the ability would be with higher standards. In the past, the strategy of “screen out” was often used in personnel psychological selection, aiming to use psychological scale to evaluate individual personality traits and mental health level, and eliminate individuals with personality defects and abnormal mental health. With the deepening of personnel psychological selection work on the needs of person post matching, gradually researchers began to pay attention to whether the ability of personnel can meet the requirements of job responsibilities. Ability assessment, especially cognitive ability assessment, began to play an important role in personnel selection. The psychological selection of personnel gradually turns into the strategy of “selecting in the best”. Taking pilot psychological selection as an example, air forces and civil aviation departments of various countries have developed many cognitive ability selection tests © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 192–197, 2022. https://doi.org/10.1007/978-981-16-5963-8_28

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to evaluate candidates’ abilities, such as attention allocation, working memory, reaction agility, hand eye movement coordination, etc. [1, 2]. These tests are based on computer software program, which realizes the standardization and automation of cognitive ability assessment, and greatly improves the efficiency of group testing. Most of the existing evaluation tests focus on the visual information processing, but pay less attention to the auditory channel. In fact, it is very important for pilots to accurately recognize the auditory command information of air traffic controller during takeoff and landing [3]. Therefore, it is of great importance to increase the assessment of cognitive ability of auditory channel. It is worth mentioning that behavioral indicators such as reaction time and accuracy are often used to evaluate cognitive ability in current tests, but time resolution and accuracy are not enough, and more sensitive indicators need to be explored. With the development of cognitive neuroscience, some indicators with higher temporal resolution and sensitivity, such as EEG, have attracted researchers’ attention. The current study intends to use dichotic listening task to evaluate the attention ability of individual auditory channel. The absolute power values of alpha and other frequency bands in the process of performing auditory attention task were obtained by EEG spectrum analysis. The correlation of EEG spectrum index and behavioral index was calculated, so as to provide data reference for establishing EEG indicators of auditory attention ability evaluation.

2 Method 2.1 Participants 10 young male subjects were recruited. The average age of was 25.80 years old, ranging from 23 to 30 years old. They are all with a bachelor’s degree and right handed. There was no history of visual impairment or brain injury. 2.2 Tools In the dichotic listening task, the left ear was the following ear and the right ear was the non following ear. A group of alphabetic sounds appeared at the speed of 2.5 s per letter in both ears at the same time. The subjects were asked to press the left mouse button to respond only when the target stimulus “A”, “B”, “C” and “Y” appeared in the following ear, but no reaction in other cases (Fig. 1). EEG data acquisition was using Neuroscan 64 channel amplifier and cap, with sampling rate of 1000 Hz and impedance less than 10 k . EEG data preprocessing as follows: • • • •

Re-reference: REF reference changed to mean reference of the whole brain; Filtering: 1–40 Hz; Eliminating bad segments and interpolating bad derivatives; Independent component analysis (ICA) was used to eliminate noise components such as electrooculogram (EOG) and electrocardiograph (ECG);

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Fig. 1. The scene of experiment

• Fourier transform is used to calculate the absolute power value and divide the frequency band as: delts band (1–3 Hz), theta band (4–7 Hz), alpha band (8–13 Hz), beta band (13–30 Hz), gamma band (31–40 Hz). The average power value of each electrode position was calculated. 2.3 Statistics MATLAB and EEGLAB were used for EEG data preprocessing, SPSS 20.0 was used for statistical test. The significance level is 0.05.

3 Results 3.1 Results of Behavioral Data According to the distribution of reaction time and accuracy rate in attention task, the full range of accuracy rate is narrow, the standard deviation is small, and the data distribution is relatively concentrated; while the full range and standard deviation of reaction time is larger, the distribution is relatively discrete. It shows that reaction time is more suitable to distinguish the behavioral performance level among the subjects, and can be used as indicators in the evaluation of cognitive ability (Table 1). Table 1. The distribution of subjects’ reaction time and accuracy in attention task Behavioral indicators

Range

Min

Max

Mean

SD

ACC. Both target

0.04

0.96

1.00

0.99

0.02

ACC. Left target, right non-target

0.09

0.91

1.00

0.95

0.03

ACC. Left non-target, right target

0.16

0.84

1.00

0.92

0.05

ACC. Both non-target

0.12

0.88

1.00

0.97

0.04

ACC. Average

0.08

0.91

0.99

0.95

0.02

RT. Both target

212.00 708.00 920.00 812.45 73.53

RT. Left target, right non-target

198.67 715.93 914.60 823.99 75.17

RT. Average

189.94 712.34 902.28 818.91 72.47

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3.2 Results of EEG Band Power According to the topographic map of EEG power spectrum, delta and theta band power are dominant in frontal area, while alpha band power is dominant in temporal and occipital area. The correlation analysis was conducted between delta, theta, alpha, beta and gamma band power of 62 electrode sites with the behavioral data in attention task. According to the significance level of correlation coefficient, the correlation matrix of behavioral data and EEG indexes were obtained, as shown in the table below (Fig. 2 and Table 2).

Fig. 2. EEG power spectrum topographic map

Table 2. Correlation matrix of behavioral and EEG indicators in attention task ACC. Both target None

ACC. Left target, right non-target

ACC. Left non-target, right target

AF4-beta

− 0.911**

PO7-gamma

− 0.678*

AF3-beta

− 0.896**

PO3-gamma

− 0.668*

FC4-beta

− 0.808**

PO5-gamma

− 0.651*

AF4-gamma

− 0.801**

FP2-beta

− 0.795**

ACC. Both non-target

ACC. Average

RT. Both target

C4theta

− 0.814**

PO6-delta

− 0.687*

TP7-beta

0.735*

AF4theta

− 0.799**

PO8-delta

− 0.677*

FC4-theta

− 0.709*

CP2theta

− 0.798**

C6-beta

− 0.666*

O2-theta

− 0.708*

F6theta

− 0.791**

FC6-beta

− 0.656*

T8-gamma

0.704*

CP4theta

− 0.770**

CB1-beta

− 0.645*

F5-delta

− 0.697*

RT. Left target, right non-target

RT. Average

(continued)

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ACC. Average

CB2alpha

− 0.637*

O2-alpha

− 0.667*

O2alpha

− 0.633*

F5-delta

− 0.665*

OZ-alpha

− 0.665*

CB2-alpha

− 0.645*

CB1-alpha

− 0.644*

RT. Both target

Note:* presents P < 0.05, ** presents P < 0.01

There were 36 EEG indexes significantly correlated with the accuracy of left and right non-target reactions, mainly in beta and gamma bands; 26 EEG indexes significantly correlated with the accuracy of both left and right non-target reactions, mainly in theta band; 8 EEG indexes significantly correlated with the average accuracy, mainly in beta band; 27 EEG indexes significantly correlated with both left and right non-target reaction time, mainly in beta band There were 7 EEG indexes significantly correlated with mean response time, mainly in alpha band. TP7-beta, CB2-alpha and O2-alpha were significantly correlated with the above three behavioral indicators of reaction time (all P < 0.05).

4 Discussion and conclusion The results showed that there was significant alpha band activity in the temporal occipital region. Previous studies have shown that significant alpha band activity can be observed in the O1 and O2 cites when the subjects open their eyes. The decrease of alpha synchronization is related to the enhancement of attention [4]. In order to keep the task close to the real task, the subjects were asked to keep their eyes open, but the screen remained black, so as to minimize the interference of visual information processing on EEG data. The obvious alpha band activity was also observed in the occipital lobe in the current study. It is suggested that alpha band power is not limited by channel of stimulus information, and could be used as a potential indicator to evaluate attention ability in auditory attention task. In the current study, theta band activity was found in the frontal lobe. Previous studies have shown that theta band activity increased with the increase of task difficulty load [5, 6]. In this study, the subjects need to selectively code the auditory stimulus of following ear for continuous attention processing, and make decision based on the stimulus type. The data showed that theta power of frontal lobe is significantly negatively correlated with the accuracy of auditory attention reaction. Therefore, theta band activity found in frontal lobe may be related to attention processing, and can also be used as a potential indicator for auditory attention ability evaluation. In order to select appropriate behavioral and EEG indicators for auditory attention assessment, it is necessary to screen these two type of indicators separately. Firstly,

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based on the discrete degree of behavioral indicators, the behavioral indicators with relatively discrete distribution were selected, including reaction time of total left and right target, reaction time of left target and right non-target, and average reaction time. Additionally, the EEG indexes which have the highest correlation with the selected behavioral indexes (i.e. the absolute value of correlation coefficient is the largest) are selected as the potential evaluation indicators of auditory attention ability. According to the data of correlation coefficient, TP7-beta, CB2-alpha and O2-alpha have the highest correlation coefficient with the three behavioral indicators respectively, so these three EEG indicators are selected as potential assessment indicators for auditory attention ability. Acknowledgements. This work is supported by the Foundation Enhancement Program No.2019JCJQ-ZD-119–01 and Youth Development Program of Medicine, No.19QNP024.

Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Kelley, S.: Relationship between Air Traffic Selection and Training (AT-SAT)) battery test scores and composite scores in the Initial En Route Air Traffic Control Qualification training course at the Federal Aviation Administration (FAA) Academy. Southeastern Oklahoma State University, Durant, OK (2012) 2. Grassmann, M., Vlemincx, E., Leupoldt, A., et al.: The role of respiratory measures to assess mental load in pilot selection. Ergonomics 59(6), 1–9 (2015) 3. Klaproth, W., Vernaleken, C., Krol, R., et al.: Tracing pilots’ situation assessment by neuroadaptive cognitive modeling. Front. Neurosci. 14, 795 (2020) 4. Klimesch, W.: Alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn. Sci. 16(12), 606–617 (2012)s 5. Jensen, O., Tesche, D.: Frontal theta activity in humans increases with memory load in a working memory task. Eur. J. Neurosci. 15(8), 1395–1399 (2002) 6. Wascher, E., Rasch, B., Sänger, J., et al.: Frontal theta activity reflects distinct aspects of mental fatigue. Biol. Psychol. 96, 57–65 (2014)

Sensory Evaluation of Mixed Juice Drinks Based on Fuzzy Mathematical Evaluation Method Shuang Bai, Peng Du, Huiling Mu, Ximeng Chen, Longmei Fang, Juan Liu, Hua Guo, Feng Wu, Yubin Zhou, Dalong Guo, Dalong Liu, Feng Li, Hongjiang Jing, Ying Liu, Falin Li, and Ruoyong Wang(B) Air Force Medical Center of FMMU, Beijing 100142, China

Abstract. In this study, four mixed juice beverages were evaluated using a fuzzy mathematical approach. The dimensions evaluated included color, aroma, taste and composition. Subjects scored each of these four dimensions. Using the obtained scores, a fuzzy mathematical comprehensive sensory evaluation model was developed. The results showed that the mixture of lemon and grapefruit juice scored the highest, followed by the mixture of pineapple and apple juice, and the mixture of strawberry and guava juice. The mixed juices of cherries and cranberries scored the lowest. Keywords: Mixed juice drinks · Preference · Fuzzy mathematics · Sensory evaluation

1 Introduction Sensory evaluation of mixed juice beverages is an important factor in determining product quality and popularity. Traditionally, sensory evaluation of foodstuffs relies entirely on human subjective perception, which has a large uncertainty and the obtained results are difficult to quantify. Fuzzy mathematical evaluation method has the characteristics of clear and systematic results [1], which can better solve the fuzzy and difficult to quantify problems, and has been more and more widely used in recent years to solve a variety of non-deterministic problems [2], such as optimizing food formulations, optimizing manufacturing processes, and comprehensively evaluating the sensory quality of food, etc. [3-7]. In this study, we use fuzzy mathematical methods to evaluate four kinds of mixed fruit juices, in order to make a more objective comparison of the sensory quality of mixed fruit juices and provide a reference for the comprehensive determination of the quality of mixed fruit juice drinks.

2 Materials and Methods 2.1 Main Raw and Auxiliary Materials Freshly squeezed juice, containing lemon juice, grapefruit juice, strawberry juice, guava juice, cherry juice, cranberry juice, pineapple juice, apple juice, water, fruit glucose syrup, potassium sorbate, sodium carboxymethyl cellulose. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 198–203, 2022. https://doi.org/10.1007/978-981-16-5963-8_29

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2.2 Preparation of Mixed Juice Drinks Process flow: collecting fruits → conveying and cleaning → first juice extraction → enzymatic digestion and stirring (adding pectinase) → second juice extraction → filtration → centrifugation → adding ingredients and stirring → sterilization → aseptic filling → cooling → packing into cartons (outer packaging) → storage. 2.3 Sensory Evaluation The subjects were 50 male volunteers with a mean age of (31.9 years ± 4.7 years). They rated the color, aroma, taste and composition of the mixed juice drinks according to their personal perceptions (Table 1). The scale included 9 levels: extremely like (9 points), very like (8 points), quite like (7 points), somewhat like (6 points), general (5 points), dislike (4 points), quite dislike (3 points), very dislike (2 points), and extremely dislike (1 point). The more volunteers like it, the higher the score. Before starting the sensory evaluation of the juice mixture, the evaluation criteria were clearly explained to the subjects so that they could grasp the evaluation method. We did not allow the subjects to communicate with each other each time we scored the mixed juice drinks. Table 1. Sensory evaluation criteria for mixed juice drinks Indicator

Criterion

Preference

Score

Color (20%)

beautiful color, appetizing

extremely like ~ quite like

7–9

color fails to impress

somewhat like ~ dislike

4–6

Aroma (20%)

Taste (50%)

unpleasant colors

quite dislike ~ extremely dislik 1–3

aroma to promote appetite

extremely like ~ quite like

7–9

scent fails to impress

somewhat like ~ dislike

4 –6

unpleasant scent

quite dislike ~ extremely dislik 1–3

delicious

extremely like ~ quite like

7–9

taste fails to impress

somewhat like ~ dislike

4 –6

unpleasant taste

quite dislike ~ extremely dislik 1–3

Composition (10%) suitable components, appetizing extremely like ~ quite like

7 –9

composition fails to impress

somewhat like ~ dislike

4 –6

unpleasant composition

quite dislike ~ extremely dislik 1–3

2.4 Establishment of Fuzzy Mathematical Model We referred to the National Standard of the People’s Republic of China(GB/T 31121– 2014 Fruit & Vegetable juices and fruit & vegetable beverage) and chose color, aroma, taste and composition as indicators for sensory evaluation. Set 9 levels, extremely like (9 points), very like (8 points), quite like (7 points), somewhat like (6 points), general (5

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points), dislike (4 points), quite dislike (3 points), very dislike (2 points) and extremely dislike (1 point) as the comment sets. Based on the sensory evaluation results, nine single-factor evaluation matrices were established and analyzed by fuzzy mathematical evaluation methods. (1) Determined the evaluation object set. Four kinds of mixed juice drinks: mixture of lemon and grapefruit juice, mixture of pineapple and apple juice, mixture of strawberry and guava juice, mixture of cherries and cranberry juice, the above mixed juice drinks were numbered individually, which were S1, S2, S3, S4 respectively. The evaluation object set S = {S1, S2, S3, S4}. (2) Determine the factor set. The factor sets U = {U1, U2, U3, U4, U5}. Color (U1), aroma (U2), taste (U3), and composition (U4) were selected as evaluation factors. (3) Determined the comment set. V = {V1 , V2 , V3 , V4 , V5 , V6 , V7 , V8 , V9 }, where V1 meant extremely like (9 points), V2 meant very like (8 points), V3 meant quite like (7 points), V4 meant somewhat like (6 points), V5 meant general (5 points), V6 meant less like (4 points), V7 meant not like (3 points), V8 meant very dislike (2 points), V9 meant extremely dislike (1 point). (4) Determine the weight set. The weight set W = {0.2, 0.2, 0.5, 0.1}. Determine the weights of each factor, according to Table 1: color 20%, aroma 20%, taste 50%, composes 10%. (5) Determination fuzzy relation comprehensive evaluation set. Y = W·R, where Y is the comprehensive evaluation set, W is the weight set and R is the fuzzy evaluation matrix.

3 Results and Analysis 3.1 Sensory Evaluation Results The subjects evaluated the four juice mixes according to the sensory evaluation method and the results are shown in Table 2. Table 2. Sensory evaluation results of four kinds of mixed juice drinks (n = 50) Sample code for mixed juice drinks

Indicator

S1

Score 9

8

7

6

5

4

3

2

1

color (U1 )

15

18

9

6

2

0

0

0

0

aroma (U2 )

17

21

7

4

1

0

0

0

0

taste (U3 )

17

19

8

6

0

0

0

0

0

(continued)

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Table 2. (continued) Sample code for mixed juice drinks

S2

S3

S4

Indicator

Score 9

8

7

6

5

compose (U5 )

20

22

7

1

0

color (U1 )

13

16

10

5

4

aroma (U2 )

16

19

8

6

1

taste (U3 )

13

16

9

7

compose (U5 )

15

21

7

4

color (U1 )

12

15

9

aroma (U2 )

11

13

taste (U3 )

11

16

compose (U5 )

17

color (U1 ) aroma (U2 ) taste (U3 )

7

compose (U5 )

10

4

3

2

1

0

0

0

0

1

1

0

0

0

0

0

0

5

0

0

0

0

2

1

0

0

0

8

5

1

0

0

0

12

7

6

1

0

0

0

9

6

4

3

1

0

0

14

11

7

1

0

0

0

0

8

11

14

10

6

1

0

0

0

9

12

14

9

4

2

0

0

0

12

13

10

5

2

1

0

0

13

17

5

4

1

0

0

0

3.2 Establishment of Fuzzy Comprehensive Evaluation Set The data in Table 2 were divided by the number of evaluators (50) respectively to obtain four fuzzy evaluation matrices:

  R1 = rij 4×9

  R2 = rij 4×9

  R3 = rij 4×9

   15/50 18/50 9/50 6/50 2/50 0 0 0 0     17/50 21/50 7/50 4/50 1/50 0 0 0 0    =   17/50 19/50 8/50 6/50 0 0 0 0 0   20/50 22/50 7/50 1/50 0 0 0 0 0 

   13/50 16/50 10/50 5/50 4/50 1/50 1/50 0 0     16/50 19/50 8/50 6/50 1/50 0 0 0 0  =  0 0 0   13/50 16/50 9/50 7/50 5/50 0  15/50 21/50 7/50 4/50 2/50 1/50 0 0 0     12/50 15/50 9/50 8/50 5/50 1/50 0 0 0     11/50 13/50 12/50 7/50 6/50 1/50 0 0 0    =   11/50 16/50 9/50 6/50 4/50 3/50 1/50 0 0   17/50 14/50 11/50 7/50 1/50 0 0 0 0

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rij indicates the degree of affiliation from the evaluation indicator to the evaluation result of that indicator. It is known that the set of weights for the sensory evaluation indicators of mixed juice drinks is W = {0.2, 0.2, 0.5, 0.1}, The comprehensive membership degree of four kinds of mixed juice drinks were calculated by using matrix multiplication [4–6]. The comprehensive sensory quality evaluation result vectors of samples are as follows: Y 1 = W ·R1 = {0.2, 0.2, 0.5, 0.1}·

Among them, y11 = 0.2 × 15/50 + 0.2 × 17/50 + 0.5 × 17/50 + 0.1 × 20/50 = 0.338, y12 = 0.2 × 18/50 + 0.2 × 21/50 + 0.5 × 19/50 + 0.1 × 22/50 = 0.39. Similarly, y13 = 0.158, y14 = 0.102, y15 = 0.012, y16 = 0, y17 = 0, y18 = 0, y19 = 0. Therefore, Y 1 = {0.338, 0.39, 0.158, 0.102, 0.012, 0, 0, 0, 0}. Similarly, Y 2 = {0.276, 0.342, 0.176, 0.122, 0.074, 0.06, 0.004, 0, 0}. Y 3 = {0.236, 0.3, 0.196, 0.134, 0.086, 0.038, 0.04, 0, 0}. Y 4 = {0.158, 0.238, 0.276, 0.186, 0.098, 0.034, 0.01, 0, 0}. The composite scores of the four kinds of mixed juice drinks samples were calculated according to the composite score formula 1: Hi =

i j=1

jYi

(1)

H 1 = 9 × 0.338 + 8 × 0.39 + 7 × 0.158 + 6 × 0.102 + 5 × 0.012 + 0 + 0 + 0 + 0 = 7.94. Similarly, H 2 = 7.914, H 3 = 8.77, H 4 = 8.254. Therefore, the sensory quality of the four kinds of mixed juice drinks from high to low was S1 > S2 > S3 > S4 . Sensory evaluation results showed that the sensory quality of the mixture of lemon and grapefruit juice was the best, and the sensory quality of the mixed juices of cherries and cranberry juice was the worst. The mixture of pineapple and apple juice ranked second, and the mixture of strawberry and guava juice ranked third.

4 Conclusions The fuzzy mathematical evaluation method is suitable for processing subjective information, and the reliability and accuracy of its processing results depend on the following two points: (1) whether the evaluation indexes are reasonable; (2) whether the weights of the evaluation indexes are reasonable. In this study, color, aroma, taste and composition were used as evaluation factors to quantify the sensory evaluation of fruit juices using fuzzy mathematical method, and the superiority and inferiority levels of sensory evaluation of four blends of fruit juices were determined. The conclusions drawn by the fuzzy mathematical method can provide a reference for the sensory quality evaluation of mixed juice beverages.

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Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Jin, S.K., Li, Y.: Application of fuzzy integrated judgment method in food sensory analysis. Meat Res. 2011(01), 64–67 (2011) 2. Principles and Techniques of Food Sensory Evaluation. China Light Industry Press (USA) Harry T. Lawless, (USA) HildegardeHeymann (2001) 3. Huo, H.: Application of fuzzy mathematics in food sensory evaluation quality control methods. Food Sci. (2004)(06), 185–188 (2004) 4. Jin, S.K., Li, Y.: The application of fuzzy comprehensive judgment method in food sensory analysis. Meat Res. 25(1), 64–67 (2011) 5. Zeng, X., Zeng, S.M., Long, W.Z.: The application and development of food sensory evaluation technology. Chin. Cond. 44(3), 198–200 (2019) 6. Mu, H.L., Du, P., Bai, S., et al.: Study on sensory evaluation of military instant rice by fuzzy mathematics method. Farm Prod. Process. 8, 13–16 (2020) 7. Chen, X.M., Du, P., Mu, H.L., et al.: Study on sensory evaluation of military freeze-dried fruits and vegetables by Fuzzy Mathematics Method. Farm Prod. Process. 2, 50–53 (2021)

Discussion on the Cultivation of Talents for Intelligent Warfare Qian Liu, Jinxin Li, and Jiwen Sun(B) Army Academy of Artillery and Air Defense, Zhengzhou Campus, Zhengzhou 450052, China

Abstract. Combat talents for intelligent warfare have the basic characteristics of professional complementarity, sophisticated skills, compound knowledge, innovative thinking, and intelligent decision-making. This paper analyzes the situation and tasks faced by the development of intelligent combat talents through the development of information technology, the midwifery by evolution of warfare, the preemptive development of powerful countries and the urgent needs of weak countries for leapfrog development. This paper puts forward some measures on how to cultivate talents adapting to intelligent warfare, such as insisting on taking combat needs as the traction and promoting transformation by updating ideas; highlighting the key points of institutional mechanism and optimizing the system structure to promote transformation; focusing on intelligent simulation training and promoting transformation through innovative training methods; persisting reform and innovation driven and promoting transformation through innovative support models. Keywords: Intelligentization · Warfare · Talents · Cultivation

The future war will start with intelligent warfare with a high probability. If you master the intelligent warfare, you will have the opportunity to win the future. Successful cultivation of personnel for intelligent operation will be conducive to the victory of the intelligent warfare. It is the development tendency and construction goals for armed forces of different countries to accelerate the development of military intelligentization and improve the joint operational capability as well as all-domain operational capability based on the network information system. Military intelligentization is an overall operation description of the force system composed of personnel, weapons and equipment as well as combat modes. It is upgrading, updating and remodeling in multi-directions and all-domains such as weapon platforms, command control systems and operational terminals, so as to form a new military system featuring unmanned platform, man-in-the-loop, intelligence-led and cloud brain operation. In intelligent warfare, the role of artificial intelligence is increasingly prominent, which will leap from potential, indirect and local combat capability to realistic, direct and global combat capability. New military talents with intelligence accomplishment are always the masters of intelligent warfare [1-3].

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 204–208, 2022. https://doi.org/10.1007/978-981-16-5963-8_30

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1 The Basic Characteristics of Talented Personnel for Intelligent Operation The intelligent warfare presents features such as complexity, advancing and humanization, and the operational process has the characteristics of indistinct division of labor, the composite talents structure, high-end skills operation, research-based operate mode as well as undifferentiated forward and rear position. As there are new requirements for cultivation of talents, basic characteristics of intelligent combat personnel should be accurately grasped so as to lay a solid foundation for establishing a scientific talents quality model [4]. 1.1 Knowledge Complexity The knowledge-based military is booming in the era of knowledge economy. ‘The battlefields in future will be intelligent warfare fought by knowledgeable warriors, and it will be a knowledge warfare with new meaning’. With the information-based, intelligent and integrative development of weapons and equipment, a variety of operational elements are highly integrated, promoting an increase in comprehensive demand for specialty coverage and knowledge capability of military personnel by the army posts. Intelligent military personnel are required to realize the integration of technology and command on the scientific and cultural as well as high and new tech platform, and promote spiral integration of overall quality among technology, command and management, so as to transform from single-skill, traditional, professional talents to interdisciplinary, intelligent and multi-skilled type talents. 1.2 Innovative Thinking The battlefield situation of intelligent operation is complex, and main combat elements such as operational pattern, time, area and space are rapidly changing, which requires the intelligent combat personnel to have long-term accumulated knowledge, well-honed quality, supernormal and forward thinking that innovate with courage, dare to seek difference, good at change, and be able to rapidly capture and timely restructure the battlefield information, then creatively analyze, process and use information so as to create new ideas, new strategies and new operational art to win the battle. 1.3 Intelligent Decision-Making Military decision is a game of human wisdom. Intelligent operations have efficient and joint characteristics of integrality, precision, diversity and coordination. As the command control means are highly automatic and intelligent, the role and value of command group’s knowledge, wisdom and tactics have become even more prominent, thus the intelligentization of military decisions will be an inevitable choice to transform the warfare pattern and win the future war, while the artificial intelligence will be the new growth point of command decision scientization and core military capabilities enhancement.

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2 The Situation Confronted by the Personnel Development for Intelligent Operation With the rapid development of information technology and the wide application of intelligent weapons and equipment in the military field, the future battlefield will be a new concept intelligent battlefield integrating land, sea, air, sky and network, in which various elements are highly integrated, interdependent, transparent, three-dimensional and flowing. For training intelligent combat personnel, we should survey the situation and tasks confronted by intelligent operation from the perspective of human society evolution and military revolution in the world [5]. 2.1 The call of Development of Information Technology In the sight of new round of industrial revolution, the Internet of Things, machine learning, VR/AR (virtual reality/augmented reality), smart chips, wearable devices and other industries are all supported by artificial intelligence technology. Human society is moving towards an "intelligent era" with man-machine coordination, cross-border integration and all things intelligent. "Science and technology are the most active and revolutionary factors in military development, and every major scientific and technological progress and innovation will cause profound changes for warfare pattern and operational mode." Therefore, we can judge that the next warfare pattern will be intelligent warfare. The personnel training for intelligent operation in our army must conform to the situation and catch up forthwith. 2.2 The Midwifery by Evolution of Warfare The evolution of warfare has always been the forerunner of development and reform for backward armies. Some people predict that "the future information warfare will mainly use intelligent weapons. Whoever scores a success in the field of artificial intelligence will have the initiative in military confrontation of the 21st century." This view is a bit equipment-oriented, however, it reflects the development trend of equipment. At present, intelligent operation has taken shape in many battlefields such as Iraq and Syria, and its advantages have appeared. The Nagorno-Karabakh Conflict has refreshed the cognition of different countries on this new warfare pattern. The military struggle carried out in the future is likely to be integrated joint operations under intelligent conditions. The evolution of warfare requires all countries to accelerate the pace of personnel training for intelligent operation. 2.3 The Preemptive Development of Powerful Countries The "Third Offset Strategy" launched by the United States is marked by intelligent army, independent equipment and unmanned warfare, and its development direction is to build an intelligent operational system. At present, military powers in the world have been racing to control the strategic commanding pointing of artificial intelligence, and the time window that the development circuit of the era and the competition curve of powers leave to developing countries is extremely limited.

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2.4 The Urgent Needs of Weak Countries for Leapfrog Development In general, the armed forces of developing countries are improving their command systems such as integrated command platforms and information-based command control systems. Digital weapons and equipment such as unmanned aerial vehicles and new radars are being deployed constantly, and the construction of intelligent military barracks such as digital barracks, smart military camps and smart national defense is starting. Compared with the situation and tasks, the powerful foreign armies, the construction goal of first-class armies as well as the demand for intelligent combat personnel, there is still a large gap. Therefore, it is urgent for developing countries to promote personnel training for intelligent operation.

3 Measures to the Personnel Training for Intelligent Operation Standing at the new historical starting point, we should objectively examine and solidly promote the personnel training for intelligent operation in our army. We should improve our ideological position, find out the quality structure of talents, accurately grasp the situation and tasks we faced with, take extraordinary measures, innovate the training mode, and strive to cultivate a large number of sophisticated and excellent talents who are competent in intelligent operation in a relatively short time. 3.1 Insisting on Taking Combat Needs as the Traction and Promoting Transformation by Updating Ideas The main equipment in future war will be intelligent weapons and equipment, and the prominent feature of the entire battlefield operation is a high degree of intelligence. The integrity of combat forces, the accuracy of battle plans, the diversity of operation mode and the coordination of operations will be stronger. In terms of personnel development, "the future army relies on intelligent talents for construction, the cutting-edge technologies and equipment depend on intelligent talents for operating, and operations rely on intelligent talents for planning. "At present, we should closely focus on urgent needs for formation of information offensive and defensive capability, system wreck capability and joint operation capability under intelligent condition, and demarcate the direction and goal of the personnel training transformation by new military capability requirements with a forward-looking vision and advancing thinking. We should build up the new idea of military personnel training adapted to intelligent warfare, and accelerate the transformation of personnel training target, object, mode and mechanism from traditional type to intelligent type. 3.2 Focusing on Intelligent Simulation Training and Promoting Transformation Through Innovative Training Methods We should deeply study characteristics and rules of the personnel training for intelligent operation, actively explore the reference frame, focal point and road map for the transformation of personnel training, and establish the personnel training system for intelligent

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operation. The urgent need at present is to build a smart simulation training battlefield so as to simulate the future battlefield environment, especially create a complex battlefield environment approximating actual combat. Focusing on requirements of the joint operation, joint training as well as joint command, we should conduct intelligent and joint training for all specialties and practical elements, and break new and better paths for personnel training for intelligent operation by practice and innovation.[6]. 3.3 Persisting Reform and Innovation Driven and Promoting Transformation Through Innovative Support Models Adapting to the basic requirements of personnel training for intelligent operation and carrying out the construction of horizontal joint support resources. Adhering to the unified standards, system and regulations, and doing a good job in the integration and upgrading of existing resources. Strengthening the system support and comprehensive integration for the support resources of colleges and troops, and building a joint support mode of interdependence, resource sharing and multi-dimensional integration among colleges, troops, research institutions and social resources, so as to realize the synchronous and coordinated development of the personnel training theory, mechanism as well as organizational leadership for intelligent operation.

References 1. Verheij, B., Wiering, M. (eds.): BNAIC 2017. CCIS, vol. 823. Springer, Cham (2018). https:// doi.org/10.1007/978-3-319-76892-2 2. Chongliang, P.: Intelligent Warfare. Shanghai Academy of Social Sciences Press, Shanghai (2017) 3. Congrong, L., Yuqiang, Z.: Intelligent Unmanned Combat System. National University of Defense Technology Press, Changsha (2008) 4. Hanwen, C.: Some considerations on promoting the talent team development for intelligent warfare (2020) 5. Li, M.: Winning mechanism of the intelligent warfare. Frontiers (2019) 6. Peng, W.: Grasping the characteristic and rules of intelligent warfare and promoting innovative development of intelligent training. Defense Science and Technology (2019)

Study on the Regular Changes of Training Effect of Autonomic Nervous Stability of Flight Personnel Jian Du, Yishuang Zhang, Duanqin Xiong, Qinglin Zhou, Yang Liao, Yan Zhang, Juan Liu, and Liu Yang(B) Air Force Medical Center of FMMU, Beijing 100142, China [email protected]

Abstract: Objective. To study the characteristics of the regular changes of autonomic nervous stability training for flight personnel, and provide scientific and application basis for clarifying the training methods, procedures and objective evaluation of the effects. Method 101 military pilots were selected as the subjects. Three phases of autonomic nervous stability training for the pilots before and after the three times of heart rate variability (heart rate variability, HRV) index, including time domain and frequency domain index data and combined with frequency of 0.1 Hz for recording and analysis on order to probe the regular changes of heart rate variability in autonomous nervous stability training of flight staff. Results After autonomous nervous stability training: (1) Time domain index: SDNN index increased, and reached the highest value in the third training; RMS-SD index decreased; SDSD and PNN50 showed a downward trend (P < 0.05). (2) Frequency domain indexes: TP, LF, LF/HF and LFnorm were significantly increased, and TP reached the highest value in the third training; VLF and HFNorm significantly decreased. (3) HRV power spectrum at 0.1 Hz was enhanced before and after training of pilots, and the difference was significant (P < 0.01). Conclusions Through the regular changes of HRV indexes after autonomic nervous stability training of pilots, the results showed that the overall level of autonomic nervous function of pilots was increased after the training, and the stress level is mobilized to a more suitable working state, and the best effect is achieved in the third training. Keyword: HRV · Autonomic nervous stability · Military pilots · Psychological training

1 Introduction Due to the particularity of flying personnel career, there are many obvious effects on the body’s physiological and psychological function of the factors in combat training, such as aviation operation environment of high altitude, low oxygen and low temperature, and the individual stress, fatigue, facing the situation of stress can lead to heart autonomic nervous function disorder symptoms [1–3]. Neurological dysfunction may lead to hypertension, coronary heart disease, arrhythmia, insomnia, depression, anxiety © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 209–218, 2022. https://doi.org/10.1007/978-981-16-5963-8_31

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and other physical and psychological problems [4]. Improving the ability of autonomic nerve regulation to maintain stable and coordinated state will be helpful to keep good combat effectiveness, physical and mental health, which is of great significance to the improvement of combat psychological effectiveness of flying personnel. In the early stage, our research group proved the effectiveness of autonomic stability training for flying personnel through control group experiments. The autonomic stability training can effectively regulate the balance of sympathetic and vagal nerve functions of military flying personnel, which is conducive to maintaining good job performance [5, 6]. However, the regular changes of autonomic stability training have not been effectively studied. In this paper, a large sample regularized field applied experiment was used to study the regular variation characteristics of heart rate variability of pilots after autonomous stability training, so as to provide research basis and objective evaluation scheme for the effect, methods and procedures of autonomic nervous stability training for pilots.

2 Objects and Methods 2.1 Objects The study involved 101 military pilots recently trained in aviation medical identification. The general condition of the subject: all male; Average age 33.70 ± 9.34 years (range 22 –57 years); Average flight time 2670.87 ± 2069.93 h (range 120 –1110 h). Flight types include fighters, transport planes, helicopters, etc. 2.2 Methods 2.2.1 Test Equipment The research group conducted field tests in a medical evaluation training center and sanatorium of the Air Force, and applied the Self-Generate Physiological Coherence System (SPCS) as a tool for autonomic nerve stability training and HRV data acquisition. This system collected and recorded the HRV indexes of the subjects through an ear worn information collector. By means of biofeedback, HRV index changes of subjects during training were fed back through the picture, so that the subjects could feel the changes of autonomic nerve activity and consciously adjusted them. 2.2.2 Experiment Design and Training Methods The effects of autonomic nervous stability training of subjects were analyzed by using self-control before and after the training, and the differences of psychological training effects before and after the 3 stages of training were compared. Three-stage autonomic nervous stability training was carried out by using the three-step method of autonomic balance and relying on SPCS equipment. The first stage of training is represented by 1 (before the first training, that was the original state without training), followed by 2 (after the first training), 3 (before the second training), 4 (after the second training), 5 (before the third training), and 6 (after the third training).

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(1) First stage training: ➀ the subjects were instructed to learn the three-step method of self-balancing. Step 1: Focus on the heart, and imagine the heart as a command center, while sending commands to the brain and other organs of the body. Step 2: Breathe evenly through your heart, keep your attention focusing on your heart. Exhale—imagine taking out the extra breath, inhale—imagine the oxygen filling your heart. Then, the mind will become clearer, pay attention to control the tempo between exhale and inhale while keep even and deep breathe. Step 3: Keep doing the same as before 2 steps, and focus on experiencing positive emotions and the pleasure of good feeling. ➁Subjects were fitted with an ear-wearing information collector. They sat in a relaxed state with their arms naturally flat at their sides. HRV index was automatically collected by the system with “state test” of 3-min. They tried to keep their head clear without considering any problems and keep breathing naturally. (3) In the training center, the “Pudi Tree” training module was used to guide the subjects to conduct “easy-medium-hard” training for 3 times. (4) Return to the status assessment interface, the subjects were instructed to recall the use of the training method in the status assessment, and feedback the learning effect to the subjects according to the score from system. (2) In the second stage of training, the process was repeated from step ➁ to ➃, in which the subjects were reminded to use the training method during the status assessment before and after training. (3) The third stage of training: repeat the process (➁ ~ ➃), and collect the HRV index after the training stage as the training effect data. 2.2.3 Collection Indexes (1) Time-domain indexes: SDNN: standard deviation of RR interval of all sinus heart beats (NN interval for short), reflecting the overall status of autonomic nerve function. SDSD: the standard deviation of the difference between adjacent NN, reflecting the sympathetic tension. RMS-SD root mean square of successive difference between adjacent NN intervals, reflecting the vagal nerve tension; PNN50: the standard deviation of the continuous RR interval > 50 ms between adjacent NN, reflecting the vagal tone. (Vagal excitation predominated in people under quiet conditions; but in the excited, tense condition, then the sympathetic nerve is dominant). (2) Frequency domain indicators: TP: total power, reflecting the overall level of neural function; VLF: extremely low frequency power, reflecting the level of sympathetic nerve function; LF: Low frequency power, mainly reflecting the dual influence of sympathetic and parasympathetic nerves; HF: High frequency power, reflecting the level of parasympathetic function; LF/HF: low frequency power/high frequency power, reflecting the balance of sympathetic and parasympathetic functions; LFnorm (low frequency normalized values for LF/TP-VLF): reduces the VLF on the influence of LF and HF components in the analysis, and takes more emphasis on the level of sympathetic nerve function: low frequency power calibration. HFnorm (normalized value of high frequency, HF/TP-VLF): high frequency power calibration, reduces the VLF on the influence of LF and HF components in analysis, and takes more emphasis on the vagus nerve functional level. Both reflect the coordination state of psychological energy.

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2.3 Statistical Analysis SPSS22.0 statistical software was used for data analysis. Measurement data were expressed as ± s, and non-parametric multi-match pair Test (Friedman Test) was used for comparison in groups. Non-parametric signed rank difference Test (Wilcoxon Test) was used for comparison between groups. P < 0.05 was considered for the statistically significant differences.

3 Results 3.1 Comparison on Time Domain Indexes of HRV Before and After Autonomic Nerve Stability Training 3.1.1 Friedman test was conducted on the time-domain indexes before and after training, as shown in Table 1, which showed that the time-domain indexes of the subjects before and after the third training were statistically different (P < 0.05). Table 1. Comparison on time domain indexes of HRV of before and after autonomic nerve stability training for 101 pilots Index

First training 1(1 times before)

Second training 2(After 1 time)

3(2 times before)

Third Training 4(After 2 times)

5(3times before)

6(After 3 times)

X2 value

P value

SDNN

73.62 ± 40.90

76.49 ± 35.58

77.63 ± 36.21

75.10 ± 36.49

87.20 ± 48.53

82.41 ± 47.91

1.597

0.041

RMS-SD

69.10 ± 50.89

56.77 ± 34.49

60.09 ± 44.22

52.84 ± 45.94

73.01 ± 70.53

63.44 ± 67.27

17.917

0.003

SDSD

55.10 ± 45.54

43.02 ± 30.73

45.39 ± 38.41

38.32 ± 39.36

57.74 ± 65.55

48.9. ± 60.01

17.543

0.004

PNN50

19.24 ± 15.06

18.97 ± 14.35

19.87 ± 14.35

17.93 ± 14.54

21.25 ± 15.14

18.22 ± 14.08

13.721

0.017

3.1.2 We further conducted pairwise comparison (Wilcoxon test) for each time of domain index before and after 3 training sessions, and the results showed that SDNN: 1/2, 1/5, 2/5 and 4/5 of; RMS-SD: 1/4, 1/6, 2/4, 3/4, 4/5, 4/6, 5/6; SDSD: 1/4, 1/6, 2/4, 3/4, 4/5, 4/6, 5/6; PNN50: 3/4, 3/6, 4/5, 4/6. There were significant differences among the above indexes in pairwise comparison (P < 0.05). 3.1.3 The Following Line Chart Showed the Variation Rule of Frequency Domain Indexes Before and After Three Training Sessions (Fig. 1)

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Fig. 1. Frequency domain indexes before and after three training sessions line chart.

3.2 Comparison on Frequency Domain Indexes of HRV Before and After Autonomic Nerve Stability Training 3.2.1 Friedman test was conducted on the frequency domain indexes before and after training. As showed in Table 2, the time-domain indexes of the subjects before and after the third training showed statistical differences (P < 0.05). 3.2.2 We further conducted pairwise comparison (Wilcoxon test) for each time domain index before and after three training sessions, and the results showed that 1/2, 1/3, 1/4, 1/5, 1/6, 4/5 in TP;VLF 1/2, 1/4, 1/5, 1/6, 2/3, 2/5, 3/4, 4/5;LF 1/2, 1/3, 1/4, 1/5, 1/6;2/5, 3/4, 4/5, 5/6 in HF;LF/HF in 1/2, 1/3, 1/4, 1/5, 1/6, 3/4, 3/6, 4/5, 5/6;LFnorm: 1/2, 1/3, 1/4, 1/5, 1/6, 2/3, 3/4, 3/6, 4/5, 5/6;HFNorm: 1/2, 1/4, 1/5, 1/6, 2/3, 2/5, 3/4, 4/5;There were significant differences among the above indexes in pairwise comparison (P < 0.05). 3.2.3 The Following Figure Showed the Variation Rule of Time Domain Indexes Before and After Three Training Sessions Through Broken Line Chart (Fig. 2)

846.66 ± 965.48

133.90 ± 283.48

631.40 ± 666.95

81.36 ± 144.74

15.78 ± 15.72

88.03 ± 10.90

11.97 ± 10.90

1 (before the first training)

626.47 ± 916.93

198.06 ± 375.94

328.73 ± 442.41

99.68 ± 167.41

5.97 ± 4.55

78.58 ± 13.72

21.42 ± 13.72

TP

VLF

LF

HF

LF/HF

LFnorm

HFnorm

15.66 ± 14.80

84.34 ± 14.80

13.75 ± 16.53

89.95 ± 124.22

603.13 ± 695.82

152.49 ± 243.92

845.57 ± 929.46

Second training 3(2 times before)

2(After 1 time)

First training

Index

10.90 ± 11.21

89.10 ± 11.21

20.79 ± 22.76

70.73 ± 194.63

631.00 ± 737.43

98.77 ± 124.23

800.50 ± 875.02

4(After 2 times)

14.58 ± 13.67

85.15 ± 13.67

12.50 ± 10.57

105.73 ± 145.40

647.05 ± 551.25

139.05 ± 219.69

891.84 ± 756.14

5(3 times before)

Third Training

11.99 ± 12.15

88.01 ± 12.15

20.00 ± 21.63

101.70 ± 239.93

679.12 ± 851.16

141.91 ± 207.92

922.73 ± 1146.45

6(After 3 times)

64.664

64.446

64.446

23.710

56.242

28.033

32.969

X2 value

Table 2. Comparison on frequency domain indexes of HRV before and after autonomic nerve stability training for 101 pilotsts

P value

0.000

0.000

0.000

0.000

0.000

0.000

0.000

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Fig. 2. Domain indexes before and after three training sessions through broken line chart.

3.3 Comparison of 0.1Hz Index Differences Before and After Training for Pilots Studies have shown that, when the body was in the state of autonomic coherence, the heart rate is close to the sinusoidal waveform, and the power spectrum of HRV will change significantly, adjusted to the resonance frequency of the baroreceptor feedback loop (about 0.1Hz) [7]. The results of this experiment (as shown in Table 3) showed that the 0.1 Hz index was increased, indicating that the stability of autonomic nerve was significantly enhanced and the training method was effective [8]. The difference of 0.1 Hz index before and after training was statistically significant (P < 0.01). Table 3. Friedman test results of 0.1 Hz index before and after three-stage training ( 0.1 Hz index

X2

±s) ± s)

p

Before the first stage(R1 )

0.2074 ± 0.1166 105.55 0.00**

After the first stage(R2 )

0.4689 ± 0.2278

Before the second stage(R3 ) 0.3960 ± 0.2367 After the second stage(R4 )

0.4976 ± 0.2453

Before the third stage(R5 )

0.4213 ± 0.2316

After the third stage(R6 )

0.4756 ± 0.2485

Note: **p < 0.01

3.4 Discussions Due to the special professional requirements, flying personnel in daily work and operational process are under high altitude hypoxia, acceleration, noise, radiation and other environmental factors caused by load [9], and often faces a particular task or emergency. To be in long-term nervous condition would cause fast increase of the heart rate, raise of

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blood pressure, muscle contraction, increased blood flow to the brain. While this reaction can reflectively improve the ability of effective stress of the body, but too strong stress is beyond the scope of the body’s physiological compensatory response, work performance and flight safety of flying personnel will be affected [10, 11] . The autonomic nervous system is an important part of the nervous system of the body, which is composed of two branches: sympathetic nerve and parasympathetic nerve. The heart is innervated by both sympathetic nerve and parasympathetic nerve. Under quiet conditions, excitability of the vagus nerve (parasympathetic nerve) is dominant while under the condition of excitement, tension, the sympathetic nerve is dominant. In short, the regulation of sympathetic and parasympathetic nerves in the autonomic nervous system can be quantitatively analyzed by measuring the index of heart rate variation [12]. HRV is a tiny fluctuation of RR interphase between successive heartbeats, which refers to the phenomenon of periodic change of the sinus heart rate during a certain period of time. HRV, which is a sensitive, noninvasive test indicators and reliable method, can objectively reflect the adjustment ability of the autonomic nervous system function and be more focused and researched [13]. In the analysis of HRV, the time-domain indicator SDNN reflects the overall status of autonomic nervous function. In this experiment, this indicator increased with the cumulative value of training times, indicating that HRV of pilots was increasing, that was, the regulation ability of nerve was enhanced. In the third training, HRV of pilots reached the highest value, indicating that the training effect in the third time was better, which have strengthened the training function; RMS-SD indicator is used to measure the level of vagal nerve tone. In this experiment, the overall trend of this indicator was decreasing, which showed the stress response of sympathetic nervous function excitation and parasympathetic nervous function weakening. It is indicated that the pilot’s excitement is enhanced after training. TP of the frequency domain is used as the evaluation standard of the influence of autonomic nervous system on the cardiovascular system, and TP value can also reflect the general trend of HRV [14]. In this study, with the increase of the number of autonomic nerve training, TP value showed an upward trend, indicating that the overall nerve level of pilots increased, which was consistent with the conclusion of SDNN in the time domain index. It reached the highest value in the third training, which furtherly indicated that the optimal number of training was three times, and LF/HF can be used as a quantitative indicator to evaluate the balance of sympathetic and parasympathetic heart [15]. In this study, the value of LF/HF was significantly increased, indicating that the balance of sympathetic and parasympathetic nerve functions was improved, that is, the overall regulation level of autonomic nerve was increased. Compared with the indexes before training, the values of TP, LF, LF/HF and LFNorm of pilots were significantly increased after training, while VLF and HFNorm were significantly decreased (P < 0.05 or 0.01). It is indicated that the overall regulation level of autonomic nerve is increased. The sympathetic nerve function is increased and the vagus nerve function is decreased, which is manifested as the enhancement of excitability. Compared with HRV power spectrum of the 0.1Hz frequency band, the enhanced power spectrum of 0.1Hz suggests that the physiological coherence state is improved and the autonomic nerve is in a coordinated excited state, that is, the pilot enters into the optimal mental

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energy region (excited but not nervous). At this time, the most appropriate operational performance can be achieved. The results of our study are consistent with the results of relevant studies [16]. Group USES the flight crew large sample of regularization applied field experiments, collect three times of autonomic nerve stability index of heart rate variability in the time domain and frequency domain before and after the training, analyzing the characteristics of the regular change of indicators, the flight crew in the autonomic nervous system regulation of sympathetic and parasympathetic nerve function, by adjusting the flight crew of the autonomic nervous system function, to a “excited and don’t overstrain” balance, will help to keep a good operational effectiveness and health of body and mind [17]. Experimental results showed that, neural function level of the pilot was improved, while sympathetic and parasympathetic nerve function balancing and mental energy coordination state was obviously enhanced, and the ability of the double control of the autonomic nervous system improved after the stability of the autonomic nervous training. Namely, psychological stability of pilots was enhanced so that stress level was activated to a more appropriate work. Through further discussion and research on the regular changes of various indicators, a mature training program, training methods and the best training times (three times is best) are finally formed, which has provided research basis and objective evaluation scheme for the effect, methods and procedures of autonomic nervous stability training for pilots. Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center of FMMU. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Li, M., Zhang, J., Meng, G., Li, J.: Changes of heart rate and heart rate variability in pilots of different simulated flight training subjects. Aerospace Med. Med. Eng. 26(2) (2013) 2. Yao, Y., Chang, Y., Wu, X., Sun, X.: Feasibility study on the correspondence between in- flight physiological parameters of fighter pilot and dynamic flight status parameters. Sci. Technol. Rev. 25(16) (Sum No. 238) (2007) 3. Wang, X.: The effect of biofeedback training based on SPCS on HRV and performance of young shooters, The Graduate School of henan Normal University, Master thesis (2017) 4. Chen, H., Wang, P., Zhou. Y., Wei, B.: Analysis of heart rate variability of military pilots transferring to another airport. J. Prev. Med. Chin. PLA 34(4), 493–497 (2016) 5. Yang, L., Zhang, Y., Dong, W.: Effect of autonomic nervous stability training on military flight personnel. J. Prev. Med. Chin. PLA 35(12), 15331536 (2017) 6. Zhang, Y., Zhang, Y., Peng, F., Liu, Y.: Study on autonomic nervous stability training of military pilots. In: Long S., Dhillon B.S. (eds.) Man-Machine-Environment System Engineering. MMESE 2020. LNEE, vol 645. Springer, Singapore (2020) 7. Miyata, M., Sano, Y., Suzuki, K., et al.: Evaluation of respiratory modulation on the pulse wave amplitude in low-birth-weight neonate. Biol. Sci. Space 16(3), 215–216 (2002)

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8. Meng, G.: Analysis on different flying mental stress correlation with flight performance ang personal factors. Medical school PLA, Master thesis (2014) 9. Wang, H., Wang, J.: The observation of the influence of biological feedback training on the variability of pilot heart rate. People ’s Military Surg. 59(9), 876–877 (2016) 10. Lin, L., Zhang, X., Zhu, M., Zhang, X.: The meta-analysis of the impact of the relaxation training on the index of the variability of the variability of the heart rate. J. Sports Sci. 39(2), 95–105 (2020) 11. Wu, M.: A study on HRV and influencing factors among different characteristic populations. Master thesis (2018)s 12. Taylor, M.K., Sausen, K.P., Potterat, E.G., Mujica-Parodi, L.R., Reis, J.P., Markham, A.E., et al.: Stressful military training: endocrine reactivity, performance, and psychological impact. Aviat. Space Environ. Med. 78(12), 1143–1149 (2007) 13. Yoshihara, K., Hiramoto, T., Oka, T., Kubo, C., Sudo, N.: Effect of 12 weeks of yoga training on the somatization, psychological symptoms, and stress-related biomarkers of healthy women. BioPsychoSocial Med. 8(1), 1 (2014) 14. Goessl, V.C., Curtiss, J.E., Hofmann, S.G.: The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis. Psychol. Med. 47(15), 2578–2586 (2017) 15. Liu, X.: Assessment study on multi-variables of physiology to emotional stability. Fourth Military Medical University For the degree of Ph, D. (2002) 16. Wang, W., Li, X., Chen, H.: Heart rate variability is a biological indicator of self-regulation. Psychol. Tech. Appl. 1, 16–19 (2015) 17. Chen, L., An, R., Zhang, Q., Zhang, X.: A study of mental Stress in recruits during parachute training based on heart rate variability. Med. PLA 36(4), 405–407 (2011)

Experiment and Evaluation of Occupant Cognitive State Based on Situational Awareness Theory Fang Xie1 , Sijuan Zheng1 , Xiaoping Jin2 , Dongwei Zhao2 , and Chunlin Liu1(B) 1 No. 51 Box 969, Beijing, China 2 China Agricultural University, Beijing, China

Abstract. In recent years, with the improvement of the automation level of special vehicles and the explosive growth of the information available on the battlefield, higher requirements have been put forward for occupants’ cognitive level and performance. The first problem is how to master the cognitive state law of the occupant of the special vehicle system in real-time, that is, how to solve the cognitive state recognition problem. In this paper, the representation methods of occupant’s situational awareness in physiological and performance aspects were studied by virtual simulation experiments, and the man-machine system of automated special vehicles was taken as the research object. The results show that the level of situational awareness and performance of special vehicle members are significantly increased under the condition of partial task automation; that is, the level of the cognitive state is improved. Keyword: Situational awareness · Cognitive · Evaluation

1 Introduction In recent years, the informatization level of Special vehicles has improved, the information has significantly increased, and the fighter aircraft is fleeting, which brings significant challenges to the design of special vehicles. The growth of battlefield data and complex combat systems makes it difficult for the occupants to recognize and process information, challenging to meet the requirements of rapid information perception in modern warfare. Therefore, the rational division of work between man and machine becomes the main issue to improve the occupant combat performance. The primary problem to solve the rational division of workload is to master the law of occupant cognitive state of the armored vehicle system, namely the cognitive state detection problem. At present, the widely accepted concept of situational awareness is the three-stage model proposed by Endsley, namely perception, comprehension and projection [1]. Endsley believes that situational awareness includes three levels of states (Fig. 2): level 1 (perception of the elements in the current environment), level 2 (understanding of the current situation), and level 3 (projection of the future). Only when a low level of situational awareness is achieved can a high level of situational awareness be achieved. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 219–225, 2022. https://doi.org/10.1007/978-981-16-5963-8_32

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Studies show [1–4] that the lack or insufficiency of situational awareness has been considered as one of the most important factors in accidents caused by human mistakes (Fig. 1).

Fig. 1. Situation awareness theory

At present, the evaluation methods of SA including Situation Awareness Global Assessment Technique (SAGAT), SART (Situation Awareness Rating Technique) scale, and eye movement measurement method. Among them, the main feature of the SAGAT method is the evoked representation of situational awareness [6], that is, the stop time of the task is designed at a fixed task time point, a blank screen is presented, and the participants are asked to give answers to the scenario-related questions designed based on recall. But this technique can be intrusive and can only be used on simulators. SART is a post-task test, which quantifies the situational awareness of the subjects in the way of subjective evaluation and is widely used [7]. The eye movement measurement method mainly measures the subjects’ eye movement information, such as the observation point, pupil diameter, eyelid opening, etc. The SART scale proposed by Taylor is widely used for subjective measurement of situational awareness. Relative to the specific events of the task, the SART scale pays more attention to the overall level of situational awareness, which is suitable for this experiment. The SART scale includes three dimensions of situational awareness, namely, demand on attentional resources (D), which is composed of environmental instability, environmental complexity, and environmental variability, and supply of attentional resources (S), which is composed of the subjects’ wakefulness, concentration, task allocation method, and psychological allowance. And understanding (U) is composed of information quantity, information quality, and situational familiarity. The total score of SART can be calculated with Eq. (1). SSART = U − (D − S)

(1)

S SART is the score of situational awareness level, U represents the score of situational understanding, D represents the score of attention resource demand, and S represents the score of attention resource supply.

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There have been many studies on the evaluation methods of situational awareness. This can provide a reference for cognitive state identification of special vehicles. Therefore, based on three indicators, including subjective evaluation, task performance, and eye movement information, this paper explored the expression mode of situation awareness of occupants of Special vehicleswith or without automation through experiments and then discussed and evaluated their cognitive state.

2 Methodology 2.1 Participant A total of 20 subjects participated in this experiment, with a mean age of 23.4 years (MIN = 22, MAX = 26, S.D = 1.07).All subjects were in good physical condition and had normal naked or corrected visual acuity. During the experiment, he was in good mental state. Before the experiment, he fully understood the experiment content and practiced for 45 min. 2.2 Testbed Experimental equipment includes a desktop computer, a keyboard and a SmarteyePro eye tracker. The eye tracker uses four infrared cameras to capture the facial state, pupil position and diameter of the subjects, and the sampling frequency is 60 Hz.The coordinate system is established by calibrating the subject’s head position and the measured screen position to complete the capture of the subject’s comment points and other information. The experiment scenario simulates the shock breakthrough task in the typical combat mission of assault equipment. The scene is mainly divided into three parts, that is, the view angle part of the gunner, the control part of the commander and the overhead view part. The circumferential lens of the commander is used to observe the surrounding environment, and it is the main basis to observe the appearance of the target when there is no information prompt. The commander’s console part is used to complete the series of operations carried out by the commander, and the overhead perspective part is used to simulate the helicopter’s monitoring perspective. The virtual scene of the experiment is shown in Fig. 2:

Fig. 2. Virtual experiment scenario

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3 Experiment 3.1 Variables The in-subject design was adopted in the experiment, and 20 subjects respectively completed the armored vehicle shooting task with the typical combat mission profile -shock breakthrough as the background (the experimental scene is shown in Fig. 2). The independent variables are divided into two levels, manual and automatic. Additional relationships of automation functions are shown in Tab 1. Each experiment was conducted for 10 min at each level. Each experiment was repeated twice. At the end of each level of the experiment, the subjects were asked to fill in the SART questionnaire in turn. Before the formal experiment, the subjects received about 45 min of experimental training to solve common problems in the experiment, such as unskilled operation methods and identification of the enemy and friendly forces. Table 1. Additional features for different automation level of special vehicle Variable

Meaning

Example

Manual

No information was supplied

(N/A)

Automation

The system acquire various information and push

(An enemy was detected at xxx)

3.2 Indicators The subjects’ main task performance is the survival time of the enemy, that is, the time required from the appearance of the enemy to being destroyed. The subtask of the subjects was the DRT task, and the average response time of the subjects was extracted as the performance index of the subtask. Average eyelid opening was used as an eye movement index according to the eye movement data. The SART questionnaire’s total score was used as the subjective evaluation index of situational awareness, and situational understanding, attention resource demand, and attention resource supply were used as additional evaluation indexes of situational awareness.

4 Results 4.1 Subjective Rating SART scale was adopted as the subjective evaluation method, which was mainly analyzed from the mean total score of the subjects’ SART and SART sub-indexes composed of demand on attention resource, supply of attention resource, and understanding (Fig. 3).

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Fig. 3. SART score.

As can be seen from Fig. 4, the SART score in the automated mode is significantly higher than that in the manual mode, indicating that the subjects’ situational awareness level in the automated mode under subjective evaluation is higher than that in the manual mode.

Fig. 4. Different dimension of SART.

It can be seen from Fig. 4, when the subjects was in manual mode, the supply of attention resource is lower than the automation mode (P = 0.003 < 0.05), the main reason lies in manual mode the participants need to complete the manual manipulation of the special vehicles to complete the search the enemy, identification, target, shooting to reload and DRT tasks, such as psychological allowance is less, cause for the low level of attention resource supply. In contrast, the automatic mode simplifies enemy search and identification tasks, and the subjects have higher retention of psychological allowance, so the level of attention resource supply is relatively higher. Due to manual operation requires participants to a larger effort, the subject need to focus more on the operation task, which lead to a higher score of understanding (P = 0.043 < 0.05). The understanding of automation mode is lower than manual mode, the main reason is that the information push contains the enemy position, so there’s no need for subjects’ constant search, the searching of the surrounding environment is affected, and the participants focus more on the monitoring task and DRT tasks, more difficult to detect changes in the environment. There was no significant difference was detected in the demand on attention resource (P > 0.05), in manual mode and automatic mode, which indicated that the increased information push in automatic mode did not cause significant interference to the subjects and proved the effectiveness of the advanced information.

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4.2 Task Performance Mission performance mainly includes primary mission performance and secondary mission performance, that is, the primary mission performance represented by the survival time of the enemy and the secondary mission performance represented by the DRT.

Fig. 5. Task Performance.

As shown in Fig. 5, the subjects’ main task performance in the automated mode was significantly higher than that in the manual mode (P = 0.000 < 0.05). The main task performance index can infer the level of situational awareness of the subjects according to the results, which is accurate to a certain extent. The higher the subjects’ main task performance, the higher the level of situational awareness of the subjects. In manual mode, the participants need to continue the search task, the location of the enemy in relative uncertainty, the search time is longer. At the same time, participants need to identify the camp of the target, if the enemy appeared in the remote location, the identification friend-or-enemy difficulty should increase, at the same time identification friend-or-enemy time increased. Therefore, the overall task time of manual mode is higher than that of automatic mode.

Fig. 6. Average DRT at different automation level

As a measure of mental allowance, the sub-task can reflect the level of attention resource supply of subjects from the side, and they represent the situational awareness of subjects. As can be seen from Fig. 6, compared with the manual mode, the automation mode removed the enemy search task, reduced the difficulty of the main task, increased the psychological margin of the subjects, reduced the average reaction time (P = 0.027 < 0.05), and significantly improved the performance of the secondary task. That is, it reflects the improvement of situational awareness of the subjects.

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5 Conclusion In this paper, the shock breakthrough task in a typical armored vehicle combat mission was taken as the experimental scenario, and the special vehicle occupant cognitive state detection experiment involving 20 subjects was carried out. By taking subjective evaluation, task performance, and eye movement information as indicators, the subjects’ situational awareness level was analyzed. The influence of manual mode and automation mode on occupant cognitive status of special vehicles was investigated. The following conclusions are drawn: (1) The situational awareness level of the occupants of special vehicles in the automated mode was higher than that in the manual mode. (2) Automation can significantly improve the performance of armored vehicle members’ primary and secondary tasks. (3) The eye movement data showed that the automated mode with monitoring as the main task did not reduce occupants’ situational awareness due to task dreary. (4) From the perspective of situational awareness, automation improves the cognitive state of the occupants of armored vehicles. Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of China North Vehicle Research Institute. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Hum. Factors 37(1), 32–64 (1995) 2. Winter, J.C.F.D., Happee, R., Martens, M.H., et al.: Effects of adaptive cruise control and highly automated driving on workload and situation awareness: a review of the empirical evidence. Transp. Res. Part F Traffic Psychol. Behav. 27(Part B), 195–217 (2014) 3. Zeng, Q., Zhuang, D., Ma, Y.: Mental workload and target identification. Chin. J. Aeronaut. 28(b08), 75–80 (2007). (in Chinese) 4. Wei, Z.: A multi-dimensional comprehensive evaluation model of mental workload for complex flight missions. J. Beijing Univ. Aeronaut. Astronaut. 46(7), 1287–1295 (2020). (in Chinese) 5. Baumgartner, N., Mitsch, S., Müller, A., et al.: A tour of BeAware – a situation awareness framework for control centers. Inf. Fusion 20(15), 155–173 (2014) 6. Endsley, M.R.: Errors in situation assessment: Implications for system design. In: Elzer, P.F., Kluwe, R.H., Boussoffara, P.F.: Human error and system design and management, pp. 15–26. Springer, London (2000) 7. Kahneman, D.: Attention and Effort. Prentice-Hall, Englewood C, liffs (1973)

A Preliminary Research on Energy Expenditure Assessment with 24-hour Life Observation Method and Activity Recorder Method Feng Li, Huijuan Zhu, Hongjiang Jing, Ruoyong Wang, Shuang Bai, Huiling Mu, Ximeng Chen, and Peng Du(B) Air Force Medical Center of FMMU, Beijing 100142, China

Abstract. Objective—To understand the daily energy expenditure of military personnel with different measurement method, so as to provide scientific basis for guiding the military personnel’ reasonable energy intake and dietary supply. Methods—67 male military personnel were included in the study. The total energy expenditure (TEE) was assessed by 24-hour life observation method and activity recorder (ActiGraph GT3X+) method. The results of these two different energy expenditure assessment methods were compared by paired t-test. Results— With the 24-hour life observation method the average energy consumption of various actions(ECVA) and TEE-24 were (3672.42 ± 829.78)kcal and (3839.26 ± 834.75) kcal respectively. Using Actigraph GT3X+ to measure their average energy consumption of physical activity(PA) and TEE-Actigraph were (1416.47 ± 615.17) kcal and (3251.68 ± 680.98) kcal respectively, and the mean difference between TEE-24 and TEE-Actigraph was (587.58 ± 540.16) kcal. There is a strong correlation between the measurement results of the two methods(r = 0.764, p < 0.001). Conclusions—The measurement result of activity recorder (ActiGraph GT3X+) method and 24-hour life observation method is highly related. The activity recorder (ActiGraph GT3X+) method is more objective and easier to be implemented for the military personnel. Further comparative studies should be performed to find more objective, accurate, reproducible, and maneuverable methods. Keywords: BEE · BMI · Energy expenditure · 24-hour life observation · Activity recorder method

1 Introduction In recent years, the training intensity of the military personnel had continued to increase, which has placed higher requirements on their physical energy balance. In order to understand the energy consumption of the military personnel during training, the author conducted a 24-hour life follow-up observation survey on 67 military personnel, and meanwhile used activity recorder (ActiGraph GT3X+) to monitor energy consumption of the same person. The measurement results of two different methods were compared to analyze and evaluate the total daily energy expenditure (TEE) of the military personnel, thus to provide a scientific basis for guiding the military personnel’ reasonable energy intake and dietary supply. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 226–232, 2022. https://doi.org/10.1007/978-981-16-5963-8_33

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2 Subjects and Methods 2.1 Subjects A total of 67healthymilitary personnel were recruited from 4 different units,with an average age of (27.64 ± 6.24) years, an average height of (173.15 ± 5.24) cm, and an average weight of (67.87 ± 7.68) kg. 2.2 Methods 2.2.1 24-hour Life Observation Method of Energy Expenditure According to the observation method, the subject was observed for 24 h. The daily life and work activities as well as the duration (min) of various actions were recorded, and then referred to the energy consumption calculation table to calculate the energy consumption of the day. Basic energy expenditure (BEE), energy consumption of various actions (ECVA) throughout the day, average body surface area (ABSA), thermic effect of food (TEF) and total energy expenditure (TEE) of each subjects were calculated [1, 2]. The relevant calculation formulas were as follows (1): ABSA = 0.00659 × H(cm) + 0.0126 × W(kg) − 0.1603 BEE = BMR

    kcal/(m2 • h × ABSA m2 × 24 TEF = BEE × 10%

ECVA = Time(min) × ECV



   kcal/(m2 • min × ABSA m2

TEE = ECVA + TEF

(1)

BMR: Basic metabolic rate (BMR), ECV: energy consumption value of daily activities (kcal/m2 •min). 2.2.2 Activity Recorder(ActiGraphGT3X+) Method of Energy Expenditure The Actigraph GT3X+ three-axis accelerometer was worn on the subject’s dominant wrists. The data sampling interval was 10s. Before the test, the test content, purpose and requirements were explained to the research subjects. After obtaining the consent, the subjects wore the activity recorder to monitor physical activity(PA) for 24 h. TEE of each soldier was calculated with the following formulas (2). TEE = PA + TEF + BEE

(2)

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2.2.3 BMI The height and weight of each subject were determined according to standard measurement methods, and subjects were required to take off their shoes and hats and wear light sports attire to complete the measurement. The height was measured in centimeters (cm) and the weight was measured in kilograms (kg), all accurate to two decimal places. BMI was calculated according to formulas (3). BMI =

Weight(kg) Height 2 (m2 )

(3)

2.3 Statistical Analysis SPSS 17.0 software was used for statistical analysis of the data, and the data were expressed as mean and standard deviation (Mean ± SD). The data were compared between TEE-24 and TEE-Actigraph by paired t-test, with p < 0.05 as the statistically significant. Test the correlation between Actigraph GT3X+ and 24-hour life observation measurement results by Pearson correlation analysis (correlation coefficient 0.8~1.0 means very strong correlation; 0.6~0.8 means strong correlation; 0.4~0.6 means moderate correlation; 0.2~0.4 means weak correlation; 0.0~0.2 Indicates very weak correlation or no correlation).

3 Results and Analysis 3.1 The Basic Situation of the Military Personnel The average BMI and body surface area of 67 military personnel were (22.60 ± 1.99) kg/m2 and (1.84 ± 0.12) m2 respectively. 3.2 Energy Consumption of the Military Personnel According to the above calculation method, it can be seen that the average TEF of the 67 subjects was (166.84 ± 11.27) kcal. With the 24-hour life observation method the average ECVA throughout the day and TEE-24 of the 67 subjects were (3672.42 ± 829.78) kcal and (3839.26 ± 834.75) kcal respectively. The results were shown in Table 1. Table 1. The energy expenditure of the 67 subjects with 24-hour life observation method (x ± s) TEF (kcal)

ECVA (kcal)

TEE-24h, (kcal)

166.84 ± 11.27 3672.42 ± 829.78 3839.26 ± 834.75

According to the above calculation method, the average BEE and TEF of the 67 subjects were (1668.37 ± 112.75) kcal and (166.84 ± 11.27) kcal respectively. With

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activity recorder method (Actigraph GT3X+) their energy consumption of PA can be measured as (1416.47 ± 615.17) kcal, so the average TEE-Actigraph can be obtained to be (3251.68 ± 680.98) kcal. The results were shown in Table 2. Table 2. The energy expenditure of the 67 subjects with activity recorder method (x ± s) BEE (kcal)

TEF (kcal)

PA (kcal)

TEE-Actigraph, (kcal)

1668.37 ± 112.75

166.84 ± 11.27

1416.47 ± 615.17

3251.68 ± 680.98

3.3 Differences and Correlations Between 24-hour Life Observation and ActiGraph Method of Energy Expenditure Paired t-test and pearson correlation analysis were used to analyze the relationship between TEE-24 and TEE-Actigraph. It can be seen the mean difference between the results of the two methods was (587.58 ± 540.16) kcal. Correlation coefficient was 0.764(p < 0.001). It shows that there is a strong correlation between the measurement results of the two methods. The results were shown in Table 3. Table 3. Differences and correlations between 24-hour life observation and Actigraph method of energy expenditure for the 67 subjects TEE-Actigraph

TEE-24h

Mean difference

Correlation coefficient

587.58 ± 540.16

0.764(p < 0.001)

4 Conclusions The three main ways of human energy consumption are basic energy expenditure(BEE), physical activity(PA) and thermic effect of food (TEF), which account for 60~70%, 20~30% and 10% of daily energy consumption respectively [1, 2]. PAis defined as any body activity that consumes more energy than the basal metabolic level caused by skeletal muscle contraction. It is not only the basis for the military personnel to complete daily training tasks, but also helps maintain their physical health. The energy consumption of BEE and TEF is relatively fixed. Therefore, the accurate measurement of the energy consumption of the military personnel’s PA is important to monitor theirPA level, and probe the dose-effect relationship between PA and health, meanwhile the scientific evaluation of the average total energy expenditure(TEE)and daily dietary energy intake are both very necessary to keep their health. Common TEE measurement methods are mainly

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divided into subjective measurement methods and objective measurement methods. Subjective measurement methods represented by PA questionnaires and activity logs, such as 24-hour life observation method,due to subjective bias caused by the subject’s recall bias and cognitive level, greatly affect the reliability of such methods [3]. Double standard water method, indirect calorimetry method, direct observation method, heart rate monitoring method and accelerometer (activity recorder) belong to the category of objective measurement methods [4]. Among them, the accelerometer is regarded as an effective measurement method and is widely used in the research of physical activity due to its convenient, objective and accurate characteristics [5]. Various developed countries have successively selected accelerometers as the objective standard for PA measurement in the nationwide sample survey of residents’ health [6–8]. Although accelerometer was not widely adopted for objective PA monitoring in our country, it has been generally adopted and applied by individual researchers [9, 10]. In addition, the most typical way to wear an accelerometer is to attach it to the waist to capture the overall movement of the whole body [11]. But low compliance is a problem that needs to be paid attention to when the waist is used as an accelerometer wearing part [12, 13]. Some foreign scholers demonstrated greater accuracy for PA classification when the device was placed on the wrist [13, 14]. The survey found that compared with wearing an accelerometer on the waist, subjects thought that wearing an accelerometer on the wrist was more comfortable and could reduce embarrassment [15]. Some studies also believe that the dominant wrist as the accelerometer wearing part is more accurate in predicting METs than the waist position [14, 16]. So the Actigraph GT3X+ three-axis accelerometer (ActiGraph), as a monitoring instrument for the level of PA in this study, was worn on the subject’s dominant wrists. The results showed thatwith the 24-hour life observation method the average ECVA throughout the day and TEE-24 of 67 military personnel were (3672.42 ± 829.78) kcal and (3839.26 ± 834.75) kcal respectively. Using Actigraph GT3X+ to measure their average energy consumption of PA and TEE-Actigraph were(1416.47 ± 615.17) kcal and (3251.68 ± 680.98) kcal. It is worth noting that the mean difference in the evaluation results of the two methods was (587.58 ± 540.16) kcal, so there is a strong correlation between the measurement results of the two methods (r = 0.764, p < 0.001). In conclusion, the two energy expenditure assessment methods used in this study have their pros and cons. The 24-hour life observation method needs to closely track the participants and can directly record the subject’s activity background, but it takes a long time and requires the active cooperation of the survey participants. Recording data is cumbersome, prone to human bias and recording errors. Especially with the increase in sample size, statistical data is also a heavy task. Military personnel have heavy training tasks nowadays and this method is only applicable for small sample research, not suitable forlarge-scale surveys to measureenergy expenditure. In the past, many military studies in China used this method for subjective evaluation of TEE [17, 18]. It is undoubtedly a very practical and common method when there are no objective measuring instruments such as accelerometers and indirect calorimetry and so on. Both the activity recorder and the 24-hour life observation method need to be compared with the “gold standard"double standard water method or indirect measurement method as a reference to obtain a suitable and accurate prediction equation to effectively test energy consumption. Due to

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limited conditions, this study did not yet carry out scientific demonstrations in this area. However, according to the effective information obtained above, the standard deviation of the data obtained by the 24-hour life observation method is larger(±834.75), and the data dispersion measured by the activity recorder is smaller(±680.98), so the latter may be more precise and accurate. If permitted, the best plan for determining the TEE of military personnel should be combined with a variety of measurement methods and a longer period of time, and further comparative studies should be found to find more objective, accurate, reproducible, and maneuverable energy expenditure measurement methods, so as to provide a scientific basis for guiding the military personnel’ reasonable energy intake and dietary supply. Acknowledgements. The work was supported by the Criteria Programme No BWS12B142.

Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air force Medical Center of FMMU. All subjects who participated in the experiment were provided with and signed an informed consent form.All relevant ethical safeguards have been met with regard to subject protection.

References 1. Gao, L.X., Guo, J.S., Guo, C.J.: Military Nutrition and Food Science. Military Medical Science Press, Beijing (2008) 2. Yang, Y.X., Ge, K.Y.: Encyclopedia of Nutrition Science, 2nd edn. People’s Medical Publishing House, Beijing (2019) 3. Trost, S.G.: State of the art reviews: measurement of physical activity in children and adolescents. Am. J. Lifestyle Med. 1(4), 299–314 (2007) 4. Yang, Y.X.: China Food Composition Tables-Standard, 6th edn. Peking University Medical Press, Beijing (2018) 5. Migueles, Jh., Cadenas-Sanchez, C.: Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports Med. 47(9), 1821–1845 (2017) 6. Troiano, R.P., Berrigan, D., Dodd, K.W., et al.: Physical activity in the United States measured by accelerometer. Med. Sci. Sports Exerc. 40(1), 181–188 (2008) 7. Canadian Health Measures Survey, 2007–2008: Detailed information for Spring 2007 to Spring 2009 (Cycle 1) (2008). http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSur vey&Id=10263 8. Rachel, C., Jennifer, M., Vasant, H.: Health survey for england-2008: physical activity and fitness-summary of key findings (2008). https://files.digital.nhs.uk/publicationimport/ pub00xxx/pub00430/heal-surv-phys-acti-fitn-eng-2008-rep-v1.pdf 9. Wang, C., Chen, P., Zhuang, J.: A national survey of physical activity and sedentary behavior of Chinese city children and youth using accelerometers. Res. Q. Exerc. Sport 84(Suppl. 2), S12–S28 (2013) 10. Huang, Y.X., Dai, J.S., Xu, K.: Research on the daily physical activities of middle school students based on acceleration sensor technology. J. Nanjing Inst. Phys. Educ.: Nat. Sci. Edn. 14(3), 18–22 (2015) 11. Mathie, M.J., Coster, A.C., Lovell, N.H., et al.: Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol. Measur. 25(2), R1–R20 (2004)

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12. Belton, S., O’brien, W., Wickel, E.E., et al.: Patterns of noncompliance in adolescentfieldbased accelerometer research. J. Phys. Act. Health 10(8), 1181–1185 (2013) 13. Fairclough, S.J., Noonan, R., Rowlands, A.V., et al.: Wear compliance and activity in children wearing wrist- and hip-mounted accelerometers. Med. Sci. Sports Exerc. 48(2), 245–253 (2016) 14. Crouter, S.E., Flynn, J.I., Jr, B.D.: Estimating physical activity in youth using a wrist accelerometer. Med. Sci. Sports Exerc. 47(5), 944–951 (2015) 15. Scott, J.J., Rowlands, A.V., Cliff, D.P., et al.: Comparability and feasibility of wrist-and hip-worn accelerometers in free-living adolescents. J. Sci. Med. Sport 20(12), 1101–1106 (2017) 16. Staudenmayer, J., He, S., Hickey, A., et al.: Methods to estimate aspects of physical activity and sedentary behavior from high-frequency wrist accelerometer measurements. J. Appl. Physiol. 119(4), 396–403 (2015) 17. Liu, Y., Xiong, W.X., Yu, L., et al.: Energy consumption survey of air force aviation pilots. Chin. Convalescent Med. 21(3), 200–202 (2012) 18. Song, G., Wang, L., Xiong, W.X., et al.: Investigation and analysis on energy consumption of pilots of a certain bomber in our army 33(9), 771–772 (2016)

Investigation on Psychological Service of Military Pilots Yishuang Zhang, Yan Zhang, Yang Liao, Juan Liu, Xueqian Deng, and Liu Yang(B) Air Force Medical Center, Fourth Military Medical University, Beijing 100142, China [email protected]

Abstract. Based on the investigation of the present situation of psychological service of military pilots, this paper points out that now the psychological service of pilots is not carried out frequently, and the methods&means are not targeted enough, then analyzes the military pilots’ characteristics of psychological stress and their demands for psychological service. It is considered that the psychological service of military pilots should be necessary to strengthen the mechanism construction, cultivate the professional and technical personnel of psychological service, and strengthen the propaganda of psychological knowledge among pilots, highlight the goal and significance of psychological service, in order to achieve the overall service of full coverage and follow-up of the whole process. At the same time, we should pay attention in scientific research, aim at the psychological service needs of pilots, combine with advanced psychological training and evaluation technology, and explore methods of psychological service for pilots with definite purpose and measurable effect. Keywords: Military pilots · Psychological service · Investigation on present situation

1 Introduction In the new era, military struggle requires not only superb military skills, but also excellent psychological quality [1]. In order to achieve the goal of building a strong army and building a first-class army, the army must plan to improve its psychological service ability while strengthening the practical training [2]. As an important part of military combat effectiveness, the mental health level of military pilots is directly related to flight safety. Relevant studies show that the operational errors of military pilots account for 40%~50%. When encountering the special situation threatening flight safety, the decline of mental health level is often the direct and main cause of accidents caused by operation errors if the physical health reasons are excluded [3]. Therefore, paying attention to the needs of psychological characteristics and service of military pilots in the process of training will help to perfect the content of psychological

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 233–238, 2022. https://doi.org/10.1007/978-981-16-5963-8_34

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service with professional pertinence, reduce the professional risk of military pilots, and enhance the combat effectiveness of our troops.

2 Objects and Methods 2.1 Objects The study involved 70 military pilots participated in combat training ormilitary recently. The general condition of the subject: all male; Average age 32.57 ± 4.42 years; Average flight time 1203.92 ± 527.73 h. The survey objects are widely distributed in age, position and flight time. 2.2 Methods The questionnaire method was used. The questionnaire was handed out to the pilots face to face by the investigators, explaining the way of filling in and collecting the questionnaire on site. The questionnaire mainly investigates the psychological service related problems of pilots in the new training mode, including the stress related situation of military pilots in flight operation, the types of psychological service often accepted, etc. 2.3 Statistical Processing Use EXCLE for data analysis. The response rate is used as the observation and evaluation index. Response rate =

Number of people who agree to this option × 100% Total number of people who answered this question

3 Results 3.1 Psychological Service for Pilots The types of psychological services that pilots had received before were investigated, and the results are shown in Table 1.

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Table 1. Types of psychological services received Number of answer

Number of agree

Response rate

Never

70

51

72.86%

1~2 types

70

17

24.28%

More than 3

70

2

2.86%

3.2 Main Stressors and Stress Degree of Military Pilots in Flight Operation The stress level and stressors felt by military pilots during flying commission were investigated. The results are shown in Table 2. Table 2. The stress level and stressors of military pilots

Stressors

Stress level

Number of answer

Number of agree

Response rate

Special flight environment

38

26

68.42%

Aviation safety pressure

38

23

60.53%

Fatigue

20

9

45.00%

Sleep rhythm disorder

20

8

40.00%

Rescue in distress

58

13

22.41%

Exercise subjects

58

16

27.59%

Others

58

4

6.90%

None

38

1

2.63%

Slight

38

6

15.79%

Moderate

38

22

57.89%

Serious

38

7

18.42%

Very serious

38

2

5.26%

3.3 Common Stress Reactions of Military Pilots Common stress reactions of military pilots during flying commission were investigated. The results are shown in Table 3.

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Emotional response

Physiological response

Cognitive response

Behavioral response

Number of agree 4

Response rate

Fear

36

11.11%

Lonely

36

5

13.89%

Anxious

36

22

61.11%

Angry

36

4

11.11%

Sad

36

0

0.00%

Numbness

36

6

16.67%

Others

36

5

22.22%

Fatigue

38

30

78.95%

Headache

38

4

10.53%

Dizzy

38

5

13.16%

Flustered

38

1

2.63%

Chest tightness

38

1

2.63%

Nausea

38

0

0.00%

Loss of appetite

38

10

26.32%

Muscle soreness 38

13

34.21%

Insomnia

38

5

13.16%

Sexuality decrease

38

6

15.79%

Others

38

1

2.63%

Distracted

37

12

32.43%

Memory decline 37

22

59.46%

Thinking slow

37

8

21.62%

Hard to make a decision

37

11

29.73%

Disorientation

37

2

5.41%

Others

37

3

8.11%

Change of living 37 law

16

43.24%

Social withdrawal

37

11

29.73%

Interpersonal tension

37

2

5.41% (continued)

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Table 3. (continued) Number of answer

Number of agree

Response rate

Work efficiency decline

37

19

51.35%

Excessive smoking

37

10

27.03%

Alcoholism

37

1

2.70%

Sleep disorder

37

11

29.73%

Ritualized behavior

37

5

13.51%

Others

37

2

5.41%

4 Conclusion Psychological service, means use of psychological principles, methods and techniques to maintain the mental health of officers and soldiers, which is an important link to improve the combat effectiveness [4], and has been highly valued by the multinational army in recent years [5–7].The literature shows that due to the imperfect psychological service mechanism in our army, the pilots’ psychological service is not carried out frequently, and the methods&means are not targeted enough [3]. In this survey, more than 70% of pilots consider that they have never received special psychological service, or think that psychological service is mental health test or simple relaxation exercise guidance. they are all lack of personal experience about the effect of psychological service methods. Compared with the single means of psychological service, there is a strong demand for psychological service. Military pilots often face multiple physical and psychological challenges due to their professional particularity. On the one hand, the overload caused by high intensity and long-time training mission, as well as various environmental factors like high altitude hypoxia, acceleration, noise, radiation and others; for another, the higher requirements for the combat training of pilots results by the constantly improving fighter performance [2], all above making them suffer more psychological stress [8]. The results showed that about 82% of pilots felt more than moderate stress during flight mission. The pressure mostly comes from the special flight environment (such as flight on the sea or at night, long-distance flight, etc.) and the anxiety of flight safety, at the same time, fatigue and sleep rhythm disorder are also important stressors in flight mission. This is basically consistent with the research results that the psychological problems exposed in training mainly focus on the bad psychology induced by flight fatigue and other reasons [9]. The main stress reactions of pilots are anxiety, fatigue, memory decline, change of life pattern and decreased work efficiency. These problems should be the focus of psychological service. In conclusion, the psychological service of military pilots should be more purposeful, scientific and targeted. On the one hand, it is necessary to strengthen the mechanism construction, cultivate the professional and technical personnel of psychological service, and strengthen the propaganda of psychological knowledge among pilots, highlight the

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goal and significance of psychological service, in order to achieve the overall service of full coverage and follow-up of the whole process; On the other hand, we should pay attention in scientific research, aim at the psychological service needs of pilots, combine with advanced psychological training and evaluation technology, and explore methods of psychological service for pilots with definite purpose and measurable effect.

Compliance with Ethical Standards. The study was approved by the Logistics Department for Civilian Ethics Committee of Air Force Medical Center, PLA. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Barrett, D.H., Boehmer, T.K., Boothe, V.L., et al.: Health-related quality of life of US military personnel: a population-based study. Mil. Med. 168(11), 941–947 (2003) 2. Mei, Y., Haiyan, T., Jie, C., et al.: Study on the correlation between mental health and personality characteristics of soldiers in field training. People’s Mil. Surg. 60(1), 6–8 (2017) 3. Mingxuan, Y., Junming, Z.: Study on psychological service of military pilots. J. Psychol. 14(17), 48 (2019) 4. Guolin, S., Mingxian, L., Bo, S.: Analysis of psychological stress medical support mode in actual combat training of military officers and soldiers. People’s Mil. Surg. 63(11), 1037–1040 (2020) 5. Bohua, C., Shanshan, L., Min, W., et al.: A brief introduction to the mental health support system of the US Navy. People’s Mil. Surg. 56(5), 527–528 (2013) 6. Shanshan, L., Jieying, W., Bohua, C.: Psychological support of Royal Norwegian Navy in military operations. People’s Mil. Surg. 59(8), 783–784 (2016) 7. Shanshan, L., Bohua, C., Xuxia, L.: Royal navy mental health support. J. Navy Med. 34(6), 438–440 (2013) 8. Yishuang, Z., Yan, Z., Fei, P., Yang, L., Liu Y.: Study on autonomic nervous stability training of military pilots (2020) 9. Wendong, H., Jin, M., Wenqiang, H.: Prevention and monitoring of flight fatigue. Chin. J. Clin. Rehabil. 8(3), 542–543 (2004)

Research on Preventive Methods for Human Errors of Marine Nuclear Power Plant Operators Chuan Wang1 , Ziying Wang1 , and Shenghang Xu2(B) 1 Naval Medical Center of PLA, Naval Medical University

(Second Military Medical University), Shanghai 200433, China 2 Naval Equipment Department, Beijing 100089, China

Abstract. Aiming at the problem of human error caused by the manipulation of marine nuclear power plants, this paper conducts research on prevention methods for human error of marine nuclear power plants from three perspectives: external factors, internal factors and stress factors. In the design stage, suggestions are made for the working environment, equipment and procedures, etc.; in the operation stage, suggestions are made for personnel training, work instructions, experience feedback, etc.; in terms of nuclear safety culture suggestions, it is recommended to strictly select operators and value people Suggestions on how to deal with the physiological laws, develop emotional management, and humanized system design. The research results are of great significance to strengthen the prevention of human error in marine nuclear power plants, reduce operation accidents, and improve the safety of operation. Keywords: Marine nuclear power plant · Operator · Human error · Prevention method

1 Preface Human error has been attached great importance from the domestic and foreign industries after the Three Mile Island in the United States and the Chernobyl nuclear accident in the former Soviet Union, and has been constantly invested in manpower and material resources in research. Human engineering field which is one of the four nuclear safety technologies has been established, which plays an important role in ensuring nuclear safety. According to public research results, abnormal events and accidents in nuclear power plants caused by human error accounted for 50%–85% of the total; and abnormal events and accidents caused by human error accounted for 60%–80% [1]. It has put forward higher requirements for the safe operation of nuclear power from the Fukushima nuclear power plant accident, and its impact was far-reaching [2]. Some scholars have analyzed the countermeasures for the improvement of human-caused incidents in nuclear power plants from the perspective of management [3], and some experts have provided suggestions on the elimination of human-caused errors from the perspective of safety culture construction [4]. In the case of great improvement of equipment technical reliability, the prevention of human error is considered to be one of the key aspects to ensure © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 239–246, 2022. https://doi.org/10.1007/978-981-16-5963-8_35

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nuclear safety. The personnel in nuclear power operation positions, as the direct performers of various operations of the nuclear power plant, are of uppermost priority in the prevention of human errors. Compared with nuclear power plants, marine nuclear power plants have a lower degree of automation, human factors account for a significant proportion of the entire system, and human factors in operating positions are more prominent. Therefore, carrying out human factors engineering research, analyzing the causes of human error, and taking scientific and effective preventive measures to reduce human error are of great significance for improving the efficiency of using the equipment and ensuring the safety of nuclear power plants [5]. Based on the combing and analysis of incidents caused by human errors of marine nuclear power plants, this paper conducts research on human error prevention of marine nuclear power plants from three aspects: external factors, internal factors and stress factors.

2 Preventive Methods for Human Errors Caused by External Factors 2.1 Working Conditions (1) Working environment design. It is recommended to pay attention to the design of the working environment for marine nuclear power plants. As far as possible, the working space of the operators should be spacious, comfortable, well-ventilated and moderately illuminated, so as to ensure that the operators are concentrated and the efficiency of the operators is guaranteed. In addition, the marine nuclear power plant needs to be well-designed to allow operators to avoid unexpected workloads other than the original tasks, such as various emergency repairs, equipment support, etc., thus reducing the potential workload of the operators. (2) If conditions permit, it is recommended to organize simple and flexible meeting before starting work. When carrying out various routine tasks in marine nuclear power plants, it is recommended to organize simple and flexible meetings before starting work if conditions permit. In order to complete the current work better before starting work, it is necessary for the operator to answer some necessary questions before work. According to the contents of the question, the information that the operator wants to know shall be deepened, so as to make the task more fully prepared and make the work to be carried out more smoothly. Therefore, the meeting before starting work is very necessary and important. It should be noted here that the following four aspects shall be specified in every meeting before starting work: ➀ The key link of the work task; ➁ The place where the worst situation may occur during the work and operation; ➂ The place where the possibility of human error is likely to occur during the work and operation; ➃ The barrier which can reduce human errors.

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It shall be guaranteed in the meeting before starting work that these four aspects are fully discussed, so as to effectively improve the work performance of individuals and organizations. 2.2 Work Instructions (1) Closed-loop communication. It is recommended to adopt closed-loop communication for the communications between marine nuclear power plant operators. In closed-loop communication, the sender is required to confirm the accurate instructions received by the receiver. The key point is that the sender is responsible for ensuring that the operators have a common understanding of the instructions. Closed-loop communication is an important means to prevent human errors and ensure work efficiency. It can ensure the consistency and accuracy of the communicated information, and prevent the recipient from misunderstanding the confirmed information. The principle of closed-loop communication is that the linguistic expression must be accurate, concise, complete and unique. It helps operators create a more understandable communication place to adopt closed-loop communication at work. (2) Preventive measures for operational errors. In order to prevent operational errors in marine nuclear power plants, the following suggestions can be considered: ➀ It is recommended to strengthen safety culture education for marine nuclear power plant operators; ➁ It is recommended to conduct root cause analysis of typical human error incidents in marine nuclear power plants. Superficially, the human error incident may appear to be an incident caused by misoperation. In fact, it may be that there may be a problem with the entire system of the marine nuclear power plant; ➂ The operators of marine nuclear power plant shall learn to use nuclear power plant related tools to prevent human error. Operators are regarded as independent individuals, and must truly become an effective barrier to marine nuclear power plants. (3) Preventive measures for procedural violations. In order to prevent operational errors in marine nuclear power plants, the following suggestions can be considered: ➀ Make efforts to improve the personal qualities and sense of responsibility of marine nuclear power plant personnel. Managers should have good working abilities, and can not only lead the operators to work corporately, but also deal with various human error events in a meticulous and serious manner; ➁ Plan a set of systematic and detailed implementation and management procedures. During the execution of the work, it is necessary to remind the operators to be vigilant to implement the regulations at all times;

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➂ Carry out strict management and control on relevant contractors or other cooperators. (4) Preventive measures for insufficient training. It is recommended to strengthen comprehensive management on the education and training for marine nuclear power plant operators, so as to improve the overall skills of all staffs. Attention should also be paid to the improvement of relevant education and training equipment and facilities for the marine nuclear power plants. 2.3 Equipment and Regulation Characteristics (1) Design of equipment. It is recommended to improve the design of related equipment of marine nuclear power plant in the design stage. This is a key factor for the safe operation of the marine nuclear power plant throughout its life cycle, and it is also a key factor for the prevention of human errors to the marine nuclear power plant. It can improve the basic safety of marine nuclear power plants by setting a series of design-related principles, so that the consequences of accidents will not be very serious and play a role in mitigating them. The main physical protective barrier of the marine nuclear power plant is the equipment of the marine nuclear power plant, and the equipment is also the most important protective measure to prevent the front-line workers of the marine nuclear power plant from making mistakes. The higher the reliability of the marine nuclear power plant equipment, the more accurately can the marine nuclear power plant system composed of equipment perform the functions expected by the operator, therefore, it can also prevent the occurrence of related accidents and mitigate the consequences of the accidents. (2) Design of regulations. It is recommended to avoid potential human errors as much as possible in the design of regulations for marine nuclear power plants. If the prevention of human error is not considered sufficiently during the design of regulations for marine nuclear power plants, or the operators are not well trained on the program upgrade information, it may induce human-caused accidents to the marine nuclear power plants.

3 Preventive Methods for Human Errors Caused by Internal Factors 3.1 Training of Personnel (1) Contents. It is recommended that marine nuclear power plant operators put forward training demands, and research institutes will research and customize training contents. The development of social environment and science and technology will create new requirements for training the marine nuclear power plant operators. The training content system of marine nuclear power plant operators can be summarized as basic training, professional training, skill training, psychological training, etc. Among

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which, basic training, professional training and skill training are traditional trainings for marine nuclear power plant operators; cognitive skills training is the content that needs to be studied and strengthened in the training of marine nuclear power plant operators; psychological training, special training and new technology training are the contents that need attention to adapt to the development of society and science. (2) Training with simulator. It is recommended to strengthen the training with simulator for marine nuclear power plant operators. The functions of trainings and drills with simulator for marine nuclear power plant operators have been generally recognized. Training with marine simulator is an important part of the training of marine nuclear power plant operators. The training effectiveness is directly related to the normal operation of the marine nuclear power plant. The items of training with simulator have significant advantages over other trainings for marine nuclear power plants. It can not only be used for general simulator operation training, but also can simulate the operations in various unforeseen conditions. For example, equipment failures, instrument and protection system failures can be simulated and reproduced, so that the operator has an immersive feeling. Training with simulator allows the operators to understand and proficiently use various operating regulations, and effectively grasp and respond to various situations. (3) Application of virtual reality technology. Proper application of virtual reality technology shall be considered in the training of marine nuclear power plant operators. 3D graphics in virtual reality technology can provide operators with realistic scenes or scene renderings. In education and training, virtual reality technology often has advantages and effects that are difficult to compare with other methods. Virtual reality technology will be applied to the training of marine nuclear power plant operators. It can not only save manpower and material resources, but also improve the effectiveness of training. 3.2 Experience Feedback It is recommended to provide feedback on the research experience of marine nuclear power plants. The experience feedback on the operation of marine nuclear power plants can be regarded as one of the most important methods to cope with human errors in marine nuclear power plants. It can be used to analyze and summarize the experience and lessons of operating marine nuclear power plants, and can be used to remind the operators themselves and timely discover hidden safety dangers, take the most effective and direct preventive measures and response methods before and after the occurrence of accidents. The self-evaluation of marine nuclear power plants is an important means to realize the experience feedback of marine nuclear power plants. Its purpose is to find out the problems in their work and production processes through self-inspection, evaluation and comparison of operators and managers, thereby improving the work efficiency and reduce the probability of human errors. Self-evaluation activities focus on preventing, identifying and correcting those that hinder the achievement of unit goals, especially the management of safety goals.

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3.3 Emotion Management It is recommended to consider studying the emotion management of marine nuclear power plant operators. Emotion management is a proper term for psychology. It refers to the study of individuals and groups’ awareness, coordination, guidance, interaction and control of their own emotions and the emotions of others, fully excavating and cultivating the emotional intelligence of individuals and groups, and cultivating the ability to control emotions, thus ensuring that individuals and groups maintain a good emotional state, thereby producing good management results. The analysis of emotion management has been carried out in foreign countries for nearly ten years, but China has insufficient personnel to study this field. Therefore, there isn’t sufficient technical reserve for the emotional management of the human error response methods of marine nuclear power plants. However, in the large-scale complex system such as a marine nuclear power plant, it is necessary to actively promote the emotion management of operators at work for reducing the occurrence of human errors caused by the personal emotions of operators. 3.4 Design of People-Oriented System In view of the heavy responsibility of the operators and the difficult working environment, the design of people-oriented system for operators shall be increased. It is recommended to provide operators with more effective organizational care and personalized individual development plans to ensure that each operator can deeply feel the concern from the organization, and be more responsible and enthusiastic to complete various tasks, thus avoiding personal negative emotions, and reducing potential human errors.

4 Preventive Methods for Human Errors Caused by Stress Factors 4.1 Strict Selection of Operators It is recommended to strictly select the operators for marine nuclear power plants. The marine nuclear power plant is a large and complex human-machine system, which requires operators not only to have extensive and solid scientific and technical knowledge and experienced professional skills, but also high physical and psychological quality. ➀ Requirements on physical and psychological quality Physical health, sensitive sensory organs (mainly eyes and ears), slow response, concentration, emotional stability and strong adaptability, especially mental calmness to work under stress. Physiological requirements mainly refer to the aspects such as health and sensitive sensory organs (mainly eyes and ears), slow response, concentration, emotional stability and adaptability. Requirements on psychological quality, especially require the ability to work calmly in a stressful environment, which is very important for operators of nuclear power plants.

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➁ Requirements on personality. Psychological research shows that introverts often think twice before acting and seldom act rashly, can control their emotions better, and act seldom impulsively and rationally. However, extroverts are active, impulsive and emotional, tend to act carelessly, do not act in accordance with the rules, have large emotional fluctuations, are susceptible to external influences, and show a tendency to induce accidents due to human errors. Therefore, after analysis, introverts should be chosen as direct operators of marine nuclear power plants. Of course, some special cases are not ruled out, but personality is a very important consideration in the selection of operators. ➂ Requirements on competence. Various information display instruments and controllers are scattered in the main control room of the marine nuclear power plant, and the state of the operating system is ever-changing, which determines that the operators should have good memory, comprehension, analysis and judgment capabilities. After the above requirements are integrated, that is, the most important requirement on the quality for the direct operators of marine nuclear power plant is the ability to make judgments and respond correctly to complex problems under abnormal or potentially dangerous conditions. 4.2 Pay Attention to Human Physiological Law ➀ Maintain a high level of awareness of operators. The operations in the main control room of the marine nuclear power plant include not only the mechanical activities that cause physical and physiological burdens, but also the mental burdens caused by visual information processing. Therefore, on the one hand, the operators of marine nuclear power plant should actively strive to maintain a high sense of work responsibility and create a good atmosphere of hard work; on the other hand, the operating time should be shortened appropriately. In addition to formulating various accident handling regulations as complete as possible in advance, and rehearsing in the simulator, each operation must be inspected in actual handling of problems to prevent misoperation. ➁ Pay attention to the influence of changes in human biological rhythm. Humans have a variety of biological laws. Among them, the laws of intelligence, emotions, and physical strength have the greatest impact on human behavior, which circulate regularly according to their respective curves. The first half of each cycle is positive, which promotes work, but the second half is negative, which will reduce the functional level of corresponding person. Human errors are more likely to occur on the critical day of phase change. Consider continuously storing the relevant data of operators in the computer, and print out the critical date of each personnel every week for reference by the monitor and individual, and promptly remind them to pay special attention to safety operating regulations, and conduct more strict supervision over their implementations. If necessary and possible, its work may be adjusted appropriately.

5 Conclusion In this paper, the research on prevention methods of human errors in marine nuclear power plants is carried out from three perspectives: external factors, internal factors and

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stress factors. In the design stage, suggestions are made for the working environment, equipment and procedures, etc.; in the operation stage, suggestions are made for personnel training, work instructions, experience feedback, etc.; in terms of nuclear safety culture suggestions, it is recommended to strictly select operators and value people Suggestions on how to deal with the physiological laws, develop emotional management, and people-oriented system design. The above suggestions are of great significance to strengthen the prevention of human errors in marine nuclear power plants, reduce operational accidents, and improve operation safety. Acknowledgements. This work is supported by the Weapon and equipment scientific research topics, No. 18A204.

References 1. Yang, M.: Development of human factor engineering. Chin. Eng. Sci. 4(8), 14 (2002) 2. Wang, C., Ma, Z.: Yuan T (2014) The enlightenment of Fukushima Nuclear Power Plant accident to China’s nuclear power development. Ind. Saf. Environ. Prot. 40(2), 83–85 (2014) 3. Zhao, W., Luo, Z.: Analysis of human factors events in nuclear power plants and improvement countermeasures. Safety 12, 26–28 (2011) 4. Hao, J., Hao, D.: Analysis on the causes of human liability accidents in substation. China Chem. Trade 10, 291 (2013) 5. Wang, C., Zhang, J., Yu, H., Dai, S.: Marine nuclear power plant human error analysis and protective measures. In: Long, S., Dhillon, B.S. (eds.) MMESE 2014. LNEE, vol. 318, pp. 33– 42. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44067-4_4

Analysis of Ship Operator’s Operation Ability and Research on Prevention of Human Error Chuan Wang1 , Xiao Han2 , Shenghang Xu2 , Guangjiang Wu2 , Xi Lu3 , Ziying Wang1 , and Zhongfeng Gao4(B) 1 Naval Medical Center of PLA, Naval Medical University

(Second Military Medical University), Shanghai 200433, China 2 Naval Equipment Department, Beijing 100089, China 3 Naval Staff Department, Beijing 100089, China 4 92330 PLA troops, Qingdao 266000, China

Abstract. Based on the theory of human error classification, combined with the characteristics of human error of ship control devices, through the analysis of memory, cognition and ability limits, the relevant ability restrictions of ship operators are correlated to analyze the impact of human error on ship control devices The factors are classified, mainly from the psychological state factors, the physiological state factors, the information in the memory, the individual’s quality and ability factors to analyze the impact of people’s work behavior. On the basis of influencing factors, the cognitive status of ship control devices under emergency conditions is analyzed according to actual conditions, and operational ability training indicators are proposed. The research results provide theoretical guidance for ship operators’ operational ability training subjects and methods, and have practical significance for the prevention of ship operators’ human errors. Keywords: Ship · Operator · Operational ability · Prevention of human error

1 Preface The reliability and operating environment of equipment continuously improve, and the proportion of accidents caused by equipment failure has been reduced to a relatively low level with the rapid development of modern science and technology, thus, human errors have become one of the main causes of major accidents [1, 2]. In fact, human is the key factor as well as the manager of system and equipment design, construction, operation and maintenance. From a basic point of view, all equipment defects can be attributed to human factors [3]. Therefore, the prevention and reduction of human errors are important issues to be solved to ensure the safe operation of the ship [4]. The ship operator’s cognitive ability is an important part of the operational ability [5]. Thus, this paper studies the ship operator’s operation ability from memory, cognition and ability, summarizes from characteristics and limits, discusses and studies the main contents by classification, and finally summarizes the limit characteristics of the ship operator’s memory, cognition and ability. In addition, this paper puts forward the operation ability training indexes, so as to provide solutions for the ship operator to control human errors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 247–254, 2022. https://doi.org/10.1007/978-981-16-5963-8_36

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2 Human Memory Limit 2.1 Human Memory Characteristics (1) Incomplete reliability People’s memory of knowledge, experience, events, objects, etc. is not intact over time. Some of the memory contents, forms or images may change and are deleted implicitly, so the memory information is not completely reliable. (2) Invisibility Memory is invisible and not intuitive. As long as people refuse to transcribe the contents recorded in their brains, or copy them by speaking or writing or other ways, the others will not be able to get it. (3) Speed limit Research found that the human brain can only remember four different data which are not very clear in 50 ms to half a second. The normal people brain can only remember some major aspects of interested knowledge, experience or events in a blink. (4) Short retention Some researchers analyzed the variation relationship between memory interval and syllable retention rate, and confirmed that most of the memory retention time is short. 2.2 Human Memory Limits (1) The sense registration in the processing model is instantaneous memory, which has a large capacity but short retention. It is generally believed that the content of instantaneous memory is 9–20 bits. (2) As the memory span we usually call, the short storage in the processing model is short memory, and the capacity of short memory is generally limited to 7 ± 2 items, i.e. 5–9 items. If it exceeds the capacity of short memory or other activities are inserted, the short memory will be easily disturbed and forgotten. We can use the block method to expand the capacity of short memory, that is, combine small memory units into a large unit to remember, and the latter is called block. (3) The long storage in the processing model is long memory. The capacity of long memory is infinite both in type and quantity of information, but it will be forgotten due to interference or natural decline.

3 Human Cognitive Limit 3.1 Human Cognitive Characteristics (1) Multidimensional There are different understandings in observing the same thing from different aspects, and multidimensional shall be considered for the formation of the complete cognition of things.

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(2) Relativity Everything can be divided into two, and it is advocated that the "dichotomy" shall be used to understand and deal with problems. In the real society, many things are composed of two relative parts, such as the male and female parts of animals, the differences between good and bad things, and the time divided by day and night. (3) Association Human cognitive activities are not only sensory activities, but also related to human experience and understanding ability, which includes the imagination and thinking elements of individuals, and is infiltrated by emotional factors. (4) Developmental nature The human cognitive function has its historical or developmental characteristics because cognitive activities are related to people’s knowledge structure, educational level and social and cultural environment. (5) Preemption In daily life, people’s cognitive activities or cognitive processes often have “the first dominates” phenomenon, or use the “first impression” to judge and solve problems, which is the preemption. (6) Integration The integration is defined as that the individual finally shows the overall cognition or understanding of something, which is usually obtained after integrating the psychological processes of perception, memory, thinking, understanding and judgment. 3.2 Human Cognitive Limits (1) Vision limit Human have a preference for left visual field. When the information received by the left visual field and the one of the right visual field are different, people are easily affected by the information from the left visual field. (2) Area limit When we recognize patterns and backgrounds, our cognitive system also has some tendency, such as small area parts are more easily recognized as patterns than large parts. (3) Color limit People’s cognitive speeds to color, text, etc., are different. Mutual interference occurs when these information appear together. (4) Time limit Human vision has the characteristics of constancy. The characteristics of the object remain unchanged in our brain even if the change of environment will make the color, size, etc., that we perceive change. (5) Delusion limit Cognitive illusion refers to the systematic errors and deviations that people often make in the processes of judgment, reasoning, decision-making and other intellectual activities. People often ignore or violate logic rules and statistical principles, such as ignoring the relevant information, influenced by unrelated information without basis, not integrate pieces of information that shall be considered, not consider

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the significance of sample size, overestimating or underestimating, believing they have foreseen the occurrence of events and the results without evidence, etc., to make systematic errors and deviations when they use information to engage in cognitive activities such as reasoning, judgment, decision-making, etc.

4 Human Ability Limit 4.1 Characteristics of Human Ability (1) Visual characteristics ➀ Visual field Visual field is defined as the range of space the eye can see when looking straight forward. The horizontal visual field is the binocular area which is about 60° to the left and right; people’s most sensitive visual acuity is in the range of 1° on each side of the standard line of sight; and the onocular visual field is 94° to 104° on each side of the standard line of sight. The visual field in the vertical plane is as follows: the maximum visual area is 70° below the standard line of sight, the color discrimination dividing line is 30° above the standard line of sight and 40° below the standard line of sight. In fact, people’s natural line of sight is lower than the standard line of sight. In general, the natural line of sight is 10° lower than the standard line of sight when standing, and 15° lower than the standard line of sight when sitting, and the natural line of sight and standard line of sight are 30° and 38° respectively when standing and sitting in a relaxed state. The best viewing area for the object is in the area 30° lower than the standard line of sight. ➁ Dark adaptation and light adaptation The time for light adaptation is shorter (0.5–1 min), and the time for dark adaptation is longer (about 30–50 min for complete adaptation). The transient "blindness" phenomenon of the human eyes is just the alternation process of pyramidal cells and rod cells when the environmental brightness changes. ➂ Glare Glare refers to the visual conditions that cause visual discomfort and reduce the visibility of objects due to unsuitable brightness distribution or extreme brightness contrast in space or time in the visual field. It is easy to have glare when the included angle between the light source and the horizontal direction of the line of sight is less than 45°, and it is easy to cause reflected glare when the included angle of the light reflected to the eyes by any smooth object surface is less than 40°. These are easy to cause visual fatigue or visual impairment. (2) Auditory characteristics ➀ The tone, intensity and timbre of sound The human ears can distinguish the sound with the frequency less than 500 Hz or more than 4000 Hz or at the frequency difference of 1% or at the frequency difference of 3% when the frequency is between 500 Hz to 4000 Hz. People can distinguish a sound only when its intensity is 26% higher than that of another sound. In the loudness contour, the hearing threshold indicates the minimum loudness limit that a person can hear.

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➁ Auditory adaptation and fatigue Most people’s hearing organs recover after 10 s or a few minutes after the sound stimulation stops. ➂ Human auditory characteristics Human auditory range, human auditory intensity, direction sensitivity and masking effect. (3) Skin sensation characteristics ➀ Tactile threshold Ideally, a displacement as small as 0.001 mm is enough to induce human tactile sensation. ➁ Temperature sensation The cold receptors produce nerve impulses when the skin temperature is lower than 30 °C, and the warm receptors produce nerve impulses when the skin temperature is higher than 30 °C. ➂ Pain sensation It makes the body produce a series of protective and adaptive responses. (4) Taste characteristics The taste sensitivity is the highest when the food temperature is 20–30 °C. 4.2 Human Ability Limits (1) Visual limit The difference between the impression and the actual situation is called optical illusion when people observe the shape, size, position and color of an external object. The main types of optical illusion can be summarized as shape illusion, color illusion and object motion illusion. (2) Auditory limit For a person with normal hearing, the lowest sound intensity of a pure tone corresponding to a given frequency is called the “auditory threshold” at the corresponding frequency. The limit sound intensity of a pure tone corresponding to a given frequency, which makes people begin to feel painful, is called the “pain threshold” at the corresponding frequency. The area surrounded by the two curves of auditory threshold and pain threshold is called the “auditory area”. Based on each frequency and its corresponding minimum sound intensity and limit sound intensity, the following can be known: ➀ There is no significant change in auditory threshold in the frequency range of 800–1500 Hz. ➁ The audible loudness decreases obviously with the decrease of frequency in the frequency range below 800 Hz. ➂ It reaches the maximum auditory sensitivity in the frequency range of 3000– 4000 Hz. If the auditory sensitivity measured at 1000 Hz is taken as the “standard sensitivity”, the auditory sensitivity can be as high as 10 times of the standard value within this frequency range.

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➃ The auditory sensitivity decreases again when the frequency exceeds 6000 Hz. The auditory sensitivity decreases to 1/10 of the standard value when the frequency is about 17000 Hz. ➄ The limit intensity making people painful is almost independent of the frequency except when there is a valley in the frequency range of 2000–5000 Hz. (3) Sensory limit The stimulation must reach a certain intensity before it affects the sensory organs. At the same time, the stimulation intensity shall not exceed a certain maximum limit, otherwise it will be invalid and damage the corresponding sensory organs. The range of stimulation intensity that can be felt by sensory organs is called sensory threshold or recognition threshold. (4) Attention limit Attention is a form of consciousness, and it is the concentration of people’s psychological activities to specific objects. The reason why people do this is because of the limit of energy resources. What people can process is limited in a single time, and it is impossible to process all objects at the same time. Another reason is that only the concentration of energy can make it possible to have a clearer understanding of the object. Due to the limit of resources, many opportunities are lost to grasp the object stimulation. (5) Thinking limit As an indirect, general and essential reflection of objective things, thinking is one of people’s complex psychological activities, which includes analysis, integration, comparison, abstraction and generalization.

5 Operation Ability Training Indexes and Prevention of Human Error Training the following eight operation ability indexes can help the ship operator control human errors. 5.1 Spatial Perception Training Focusing on lines of sight, such as looking at hands, looking at each other or objects on each other’s hands in two person games, looking at objects in the mirror, etc. 5.2 Working Memory Training Strengthen the training of reading breadth test: the participants are asked to read or listen to a sentence and judge whether the sentence is meaningful in the reading breadth test. Meanwhile, the participants are required to remember the words at the end of the sentence (for example, the subjects are asked to listen to the sentence: “the police spent half an hour in interrogating his trusted friend”, and then the subjects were asked to judge whether the sentence is meaningful, and to remember the words “trusted friend” at the end of the sentence at the same time). After reading or listening to a group of sentences (the number of sentences in each group increases from 2 to 6), the subjects are asked to recall the group of words at the end of the sentence they read or listen to. The recall result is regarded as the working memory capacity of the individual.

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5.3 Operation Stability Training The training adopts the method of speaking with finger indication, which is a kind of operation method to force attention through the directional centralized linkage of heart (brain), eyes, mouth and hands. This method has been a habit in many jobs, for example, people count money with fingers and mouth; the pharmacists count each kind of drug with fingers for checking and mouth for speaking the drug name. The method of speaking with finger indication can help to focus the operator’s attention, promote the operator to maintain a high or relatively high attention, enhance the operator’s concentration and stability, and force the operator to exclude all kinds of interference. 5.4 Time Perception Training Exercise of time estimation: let the operator select a certain routine operation, such as opening a local valve, and make the operator estimate how many minutes it will take, then start timing, and let the operator hear the sound of time ticking away. When it ends, stop the valve and tell him how many minutes and seconds it took. Practice many times every day so as to make the operator’s sense of time more and more accurate. 5.5 Attention Focusing Training The gaze training to improve attention: often gaze at something for a long time, such as a card, the branches outside the window, the pencil in hand, etc. After a long time of the training, the people’s scope of consciousness will gradually narrow, so as to achieve the purpose of attention focusing. 5.6 Simple Response Time Training Train and improve the operator’s peripheral vision: having keen awareness of what’s going to happen can make the operator have a quick response speed. The operator can pay more attention to their peripheral vision in daily life, so as to improve their ability to perceive obstacles and flying objects. The operator will gradually develop the habit to pay attention to more objects in the peripheral vision by looking out of a window with a good view and focusing on distant objects, keeping looking at the object, and slowly paying more attention to the objects on both sides, and doing this exercise once a day and broadening the visual field a little bit each time. 5.7 Selective Response Time Training Carrying out the training for improving the selective response time for the common operation of ship control devices, for example, for an open valve and a closed valve, operator A gives the command to let operator B choose to open or close the valve. After a plurality of times of training, the two people exchange their roles. For a pressure sensor display value and a liquid level pressure sensor display value, operator A gives the command to let operator B choose to read the pressure sensor display value or liquid level pressure sensor display value, and the two people exchange their roles after a plurality of times of training.

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5.8 Training of Discrimination Response Time Train the operator for improving the discrimination response time for the common operation of ship control devices, for example, with the help of the simulator platform, set the value of the liquid level pressure sensor of a vessel, and let the operator identify the liquid level of the vessel as high, normal or bottom; and with the help of the simulator platform, set up some typical normal scenes and accident scenes of the ship control device, and let the operator identify the current working scene of the ship control device.

6 Conclusion Complex factors are involved in ship operation safety, which requires the operator to have good cognitive ability and operation ability. This paper analyzes the ship operator’s operation ability from the aspects of human memory limit, human cognitive limit, visual limit, auditory limit, sensory limit, attention limit and thinking limit. In view of these limits, this paper puts forward the training subjects and methods of the ship operator’s operation ability, which has certain guiding significance and practical value for improving the operator’s prevention of human errors and reducing operation accidents. Acknowledgements. This work is supported by the Weapon and equipment scientific research topics, No. 18A204.

References 1. Yang, M.: Development of human factor engineering. Chin. Eng. Sci. 4(8), 14 (2002) 2. Wang, C., Ma, Z., Yuan, T.: The enlightenment of Fukushima Nuclear Power Plant accident to China’s nuclear power development. Ind. Saf. Environ. Prot. 40(2), 83–85 (2014) 3. Zhang, L., Chen, S., Qing, T., et al.: Analysis of human errors in severe accident of nuclear power plant based on cognitive model and fault tree. Nucl. Power Eng. 41(3), 137–142 (2020) 4. Wu, S., Zhang, L., Zou, Y., et al.: A study on the applicability of human error taxonomies in the context of continuous and rapid changes in operational tasks. J. Univ. South China Sci. Technol. 34(5), 23–28 (2020) 5. Yu, H., Xu, L., Hu, P., et al.: The change of crew’s cognitive ability under long voyage conditions. In: The 4th Nautical Hygiene Conference of the Navigational Medicine Branch of the Chinese Medical Association (2010)

Fatigue Index of ATC in Number Recognition Task Qiuhong Piao1(B) , Xianggang Xu1 , Wei Fu1 , Jianping Zhang2 , Wei Jiang3 , Xiang Gao1 , Zhenling Chen2 , and Pengxin Ding2 1 Civil Aviation Management Institute of China, Beijing, China 2 The Second Research Institute of CAAC, Chengdu, China 3 Civil Aviation General Hospital, Beijing, China

Abstract. Objective: The objectives of current study are to explore whether serious fatigue of Air Traffic Controller (ATC) exist in their duty, and to explore a sensitive fatigue index. Method: Number recognition task was used to explore ATC fatigue. Following results were found, firstly, significant fatigue effect was found in all 55 ATC. Besides, significant fatigue effects were only found in ATC in tower control area and terminal control area, but not in regional control area. Thirdly, only reaction time before and after ATC duty were found significant difference but not in accuracy. Conclusion: Fatigue effect really exist in ATC after their duty, and ATC in different work location suffer different work load. Finally, reaction time of number recognition task can be a very sensitive and reliable fatigue index. Keywords: Fatigue management · Air Traffic Controller (ATC) · Cognitive fatigue · Fatigue index

1 Introduction According to Bellenkes study [1], 70% of civil aviation accidents were related to human factors, thus supervision on ATCs’ (Air Traffic Controller) fatigue is significant for civil aviation safety. Human may have both physical and mental fatigue during work, among which cognitive fatigue refer to subjective tiredness when processing information. Many studies have demonstrated fatigue can influence human cognitive ability [2, 3]. There are many research methods on fatigue study and Psychomotor Vigilance Test (PVT) is one of the most practical method [4–6] in which participants should respond to target (letter or number) appearing on the screen as quickly as possible. Thus the number recognition task was used in current study to explore fatigue of ATC. One object of current study is finding a sensitive and exact fatigue index which may be the response time or the accuracy. If response time is longer or accuracy is lower after ATC duty than before their duty, then fatigue effect does exist in ATC.

2 Experiment Method One number (0–9) will appear on the computer screen randomly and the participants must press the same number key as quickly as possible. All 55 participants in current study © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 255–259, 2022. https://doi.org/10.1007/978-981-16-5963-8_37

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come from Air Traffic Management Bureau of somewhere in China, working in tower control area, terminal control area or regional control area. They all attend experiment fully informed and voluntarily after signing informed consent and all received enough compensation fee. Participants must finish the same number recognition task once before and after their air traffic control duty.

3 Result Response time of all ATC were analyzed, and response time before their air traffic control duty is pre-response time and that after duty is post-response time, the same as accuracy. As Table 1 shows, pre-response time is significantly longer than pre-response time, but no significant difference were found in accuracy. Table 1. Statistical results of all ATC Index name Test time Subject number Accuracy

Reaction time

Average value

Standard deviation

Before duty

55

0.99

0.02

After duty

55

0.99

0.03

Before duty

55

741.38

129.94

After duty

55

771.13

322.76

Correlation

Significance

−0.08

0.58

0.57

0, the increase of Ci value will increase the value of Cj ,

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and there is a positive causal relationship between them. If ωji < 0, the increase of Ci I will decrease the value of Cj . There is a reverse causal relationship between the two. If ωji = 0, the change of Ci will not affect Cj , and there is no causal relationship between them [6]. 1.4 The Process of Building SA Model Based on GDTA and FCM We need to establish GDTA model to obtain the key factors that affect situational awareness. At first, divide the main task into several subtasks. Then, for each subtask, the key decisions needed to complete the subtask are analyzed. Then, FCM is used to analyze the influence of the three situational awareness factors. Each influencing factor is regarded as a node in FCM. Assuming that there are n nodes C1 , C2 . . . . . . Cn , At is used to represent the conceptual value of the i node Ci at time t, then the conceptual value At+1 of the node at the next time can be expressed for: ⎛ ⎞ n  = f ⎝Ati + AtJ˙ ωji ⎠ (1.1) At+1 i j=1,j=i

According to the above formula, the state value of a node at the next moment is related to two factors, one is the current state value of the node, the other is the influence of other nodes on the node. Where, ωji is the influence coefficient of the Cj node on the Ci concept node. Thus we can build the matrix: ⎡ ⎤ 1 ω12 ω13 . . . ω1n ⎢ω ⎥ ⎢ 21 1 ω23 . . . ω2n ⎥ ⎢ ⎥ (1.2) W = ⎢ ω31 ω32 1 . . . ω3n ⎥ ⎢ ⎥ ⎣ ... ... ... 1 ... ⎦ ωn1 ωn2 . . . . . . 1 

Matrix At = At1 , At2 . . . . . . Atn represents the state of each nodes at time t, so it’s easy   to get: At+1 = f At ∗ W ,f (x) is conversion function, converting variable of arbitrary value to the interval [0,1]. We can set: f (x) = 1+e1−λx . 

Each nodes has initial state: A0 = A01 , A02 . . . . . . A0n , then after many times iter      ations, A1 = f A0 ∗ W , A2 = f A1 ∗ W ……At+1 = f At ∗ W , matrix A will be stable, the state value of each node in the iteration is the influence weight of each situational awareness influencing factor. For some tasks, it is necessary to determine the order of each subtask after subtask division. The problem can also be solved by FCM. f (x) selects the discrete function and takes each subtask as a section. By tracking the change of the state value of each node after each iteration, we can infer the order of each task.

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2 Example of SA Modeling for Crew Warning 2.1 GDTA Analysis of Task of Dealing with Warning The main task is to eliminate the alarm. Through sorting out the typical flight accident materials, aircraft flight manual, alarm related specifications and other materials, and communicating and discussing with experts, the GDTA hierarchy is divided and sorted out, and the key factors affecting the situational awareness are obtained [8]. Table 1. Levels of GDTA for dealing with alerts Main task

Subtasks

SA requirement Level 1

Dealing with faults that happen during the flight

Confirming the warning Information

Level 2

Getting warning information

Understanding warning Knowing warning information system

Level 3 Predicting contents of the warning information

Odd meter/Interface Display State of Fault Indicator Confirming the reason of the fault

State of the airplane

Understand the state of each part Odd states of each and system part and system

Predicting reason of faults

Natural states of each part and system Some hint information on the interface Confirming the flight phase and important information

Information displayed on the Interface and meter

Understand the information

Predicting flight phase and critical information

Getting information from ground (continued)

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Main task

Subtasks

SA requirement Level 1

Determining Type and source operations to deal of warning with faults Rules on FCOM

Level 2

Level 3

Understand operation to deal with warnings

Predicting the operation to deal with alerts

Understand the state of each part and system

Judging whether the warning has been handled

Previous experience State and control methods of Each parts and systems Environment Inside and outside of the airplane Flight condition and related information Judging whether the warning has been handled

Whether flight condition and Parameters are natural Parts and systems natural or not Warning disappear or not State of fault indicator

2.2 FCM Analysis of Task of Dealing with Warning In this part, FCM is used to determine the sequence of each subtasks. Get the relationship matrix from the interviews with pilots and experts. 0 means the subtask hasn’t been executed; 1 means the subtask has been executed. From the iteration process, task 1 is completed firstly; 2 and 3 secondly and 4&5 last. After discussing with experts, the correct order should be: 1. 2. 3. 4. 5.

Determine the content of alarm information Determine the cause of the problem (failure) Determine flight phase and important flight information Determine the actions required to eliminate the alarm Judge whether the alarm has been eliminated

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After that, we need to analyze the impact of the situational awareness factors. The results are in the table below. Weights are above 0 and below. High weight means the factor is important for pilots to maintain good SA in relative subtask. Based on the table and analysis, for the pilot to deal with the alarm, the important information that needs to be obtained includes: obtaining the alarm information; abnormal instrument reading or interface display information; communication with the alarm Important flight parameters, alarm related components, system status, etc. In the design of cockpit interface, it is necessary to ensure that pilots can obtain these information at any time, so as to help pilots better maintain situational awareness, process alarm information and ensure flight safety. Table 2. Weight of each factors that influence Subtask

Important SA Factors

Weight

Confirming the warning information

Getting warning information

0.7740

Confirming the reason of the fault

Confirming the flight phase and important information

Knowing warning system

0.7382

Odd meter/Interface Display

0.7593

State of Fault Indicator

0.7528

State of the airplane

0.7655

Odd states of each part and system

0.8150

Natural states of each part and system

0.8147

Some hint information on the interface

0.7655

Information displayed on the interface and meter

0.7925

Getting information from ground Determining operations to deal with faults Type and source of warning

0.7299 0.8490

Rules on FCOM

0.8764

Previous experience

0.8256

State and control methods of each parts and systems

0.8383

Environment Inside and outside of the airplane

0.8020

Flight condition and related information 0.8511 Judging whether the warning has been handled

Whether flight condition and parameters 0.7814 are natural Parts and systems natural or not

0.7814

Warning disappear or not

0.7394

State of fault indicator

0.7292

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2.3 Verify the Rationality of the Model In order to test the rationality of the situational cognitive model, we select the new alarm scenarios to see whether the model is still applicable. By selecting a specific alarm task and comparing the established model with the contents in the operation manual, we can judge whether the established model is reasonable. Take Airbus A320 as an example. First, determine the type of alarm. Take the warning information “blue + yellow system low voltage” as an example to analyze. First of all, if the Yellow system fails due to low oil level or overheating, “hyd PTU fault” should appear. This is consistent with “received alert information” in the subtask “confirm alert information content”. What kind of operation should be carried out later should be analyzed in detail. In A320 process, the low pressure of the oil tank and the overheating of the oil tank will lead to the loss of the system, and the operations to be carried out in the two cases are different. Therefore, before handling the warning, we should first determine how the alarm is caused, which is in good agreement with the subtask “the problem that causes the alarm”. In A320 process, there are “relevant pump on”, “blue system electric pump auto”, “landing gear gravity release” and other requirements. This corresponds to the key factor in the subtask “understanding the status and control methods of related systems and components”. which correspond to the key factor “understanding flight conditions and relevant flight information”. Then, we need to judge whether the system is restored to normal, if not, we need to perform subsequent operations. This corresponds to the subtask “determine whether an alert is excluded.” It can be seen from the above content that the established model does not completely correspond to the “blue + yellow system low pressure” alarm processing program of Airbus A320, but it is roughly consistent. The items in the abnormal program can basically find the corresponding content in the scenario cognitive model. It can be considered that the rationality of the established alarm scenario cognitive model has been verified.

3 Conclusion This paper presents a method of combining GDTA with FCM to build a cognitive model of crew alarm situation. Referring to flight manual and some flight examples, the key factors that affect the situation awareness are analyzed by using GDTA. The FCM is used to analyze the expert data, and the influence of each factor and the steps to deal with the alarm are obtained. Then the established model is compared with the specific alarm scene, and the established model is basically consistent with the actual scene, so the rationality of the model is verified. The situational cognitive model can help to understand the information that pilots need to obtain when they deal with the warning information, and has a certain reference value for later design of cockpit interface which is more conducive to pilot identification and processing the warning information.

References 1. Jones, R.E.T., Connors, E.S., Endsley, M.R.: A framework of representing agent and human situation awareness. In: 2011 IEEE International Muti-Disciplinary, 226–233

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2. Modeling and Eye Movement Research on Cognitive Load of Maintenance Training. Beijing University of Posts and Telecommunications, Beijing (2014) 3. Kokar, M.M., Endsley, M.R.: .Situation awareness and cognitive modeling, Cyber-PhysicalSocial Systems, 91–96 (2012) 4. Jones, R.E.T., Connors, E.S., Endsley, M.R.: Incorporating the human analyst into the data fusion process by modeling situation awareness using fuzzy cognitive maps. In: 12th International Conference on Information Fusion, pp. 1265–1271 (2009) 5. Zhong, Y., Zheng, J.: Fuzzy Cognitive Map and Its Application. Beijing Normal University 6. Tao, X., Jun, G.: Research on ship maintenance risk assessment model based on fuzzy cognitive map. Ship Electronic Eng. (2), 129–132 (2015) 7. Yunyun, X., Keping, Z., Liyang, Y., Zhengong. Y.: Application of fuzzy cognitive map in mine safety assessment system modeling mining research and development, 27(6), 86–89 (2007) 8. Hongjun, L.: Research on Flight Safety Risk Prevention and Control and Countermeasures of China Eastern Airlines Based on Crew Factor Analysis. Fudan University, Shanghai (2013)

Research on a Fatigue Detection Method Based on Phoneme Qian Zhang1 , Weining Fang1(B) , Jian Li2 , Haifeng Bao1 , and Xingdong Zhao2 1 State Key Laboratory of Rail Traffic Control and Safety,

Beijing Jiaotong University, Beijing 100044, China [email protected] 2 Traffic Control Technology, Beijing 100070, China

Abstract. In order to effectively detect the fatigue status of train drivers and ensure the safety of train operation, in view of the limitations of existing methods in feature selection and model construction, a driving fatigue detection method based on phoneme spectrogram and convolutional neural network was proposed. According to the characteristics of the work tasks of the train driver, a fatigue speech database was constructed and the effectiveness of the database was verified; phonemes that can express fatigue information in a more detailed and intuitive manner were selected as the research object, and based on the speech signal processing theory and the deep learning theory, a driving fatigue detection model was established to achieve a more accurate and robust driving fatigue detection. The experimental results show that the precision, recall and accuracy (96.7%) of this method are better than the existing methods. The research on the train driver fatigue state automatic detection technology carried out in this paper not only has a wide application prospect in the intelligent rail transit industry, but also can provide theoretical and technical support for the research on human-machine adaptive interaction of trains. Keywords: Speech · Driver fatigue detection · Convolutional neural network · Phoneme

1 Introduction The railway transportation system has gradually realized the innovation from concept to practice with the rapid development of China’s rail transit industry. However, the transportation pressure is also increasing with the increasing passenger flow, which puts forward higher requirements for train safety. Ensuring the smooth operation of train and improving the monitoring and management level of train operation safety have become the top priority of railway departments. The train driver’s fatigue has become a universal phenomenon in rail transit [1, 2]. Evans [3] analyzed the rail transit accidents and found that human factors accounted for 74% of the various causes of accidents. The statistical results of Zhengzhou Railway Bureau on locomotive driving danger and above accidents for which the locomotive drivers were responsible during 1995–2000 show that the proportion of accidents caused © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 S. Long and B. S. Dhillon (Eds.): MMESE 2021, LNEE 800, pp. 268–277, 2022. https://doi.org/10.1007/978-981-16-5963-8_39

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by fatigue is 56.52% [4]. The serious railway traffic accidents on Yongwen Line and Jiaoji Line were both caused by human factors [5]. It can be seen that “man” has become the main factor of train operation safety in the “Man-Machine-Environment” system composed of people engaged in railway activities, railway vehicles, systems, equipment and railway operation environment. Among all participants in railway transportation, the role of the train driver is the most direct and prominent. Because fatigue is an important factor affecting safety performance, how to effectively monitor the driving fatigue status of the train driver and how to improve the operation level of the train driver have become urgent problems to be solved in railway safety management. Common fatigue detection technologies can be roughly divided into three types: the fatigue detection based on subjective questionnaire [6], the fatigue detection based on physiological indicators [7], and the fatigue detection based on behavioral characteristics [8]. The method based on subjective questionnaire is commonly used with low cost, simple operation and high surface validity, but it is greatly affected by subjective factors. Based on EEG, ECG and other physiological indicators, the accuracy rate is high, but the cost is also high, and it has a certain degree of invasion, which may interfere with the driver’s operation, resulting in the impact on driving. The method based on behavioral characteristics, such as yawn and blink frequency, is easily affected by the environment and noise, which affects the accuracy of monitoring. Therefore, it is necessary to find a method with high accuracy and no contact but more suitable for the driver’s working environment and characteristics. The driver is required to adopt standard response operation in the field of rail transit. The speech contains a lot of physiological and psychological information of human body, including fatigue state information. Whitmore and S. Fisher found that the pitch frequency and duration of speech segment obviously change with the deepening of fatigue degree during the fatigue degree detection experiment [9]. Milosevi proposed that the intensity, pitch, channel spectrum and articulation clarity of speech are related to fatigue [10]. Research by Harrison and Horn found that people’s pronunciation is incomplete in sleepiness and sleep deprivation [11]. By means of gray correlation analysis, Liu Zhonghua found that the feature of speech intensity can be used as a means of judging fatigue [12]. With experiment, Qian Jin found that the average amplitude change rate of speech has a high correlation with the average energy of human body’s fatigue degree, and the correlation of other factors is small [13]. Sun Ruishan found that when the human body is fatigue, the human response time becomes longer and the voice stability decreases [14]. Fu Jianmei found that with the increase of fatigue, the amplitudes of speech parameters in time domain and frequency domain increase by different degrees, in which the short-term average amplitude of speech signal increases most obviously, and the short-term zero crossing rate is the slowest [15]. All studies have shown that there is a high correlation between human fatigue state and speech signal, however, speech is a signal carrier rich in information, which includes not only the fatigue state information needed for research, but also the information of semantics, speaker, emotion, dialect, environment and equipment. In order to reduce the impact of these information on fatigue state analysis, complex and detailed analysis is needed. It is very difficult to make accurate classification by simply using the sound mechanism, the simple characteristics of the signal and artificial means.

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Therefore, this paper uses the spectrogram which reflects the fatigue state of human body [16], as well as the convolutional neural network which learns the nonlinear relationship between various kinds of information in the voice signal, to automatically extract the abstract features of depth hierarchy, and proposes a fatigue detection method based on the combination of spectrum and deep learning, so as to classify the train attendant’s fatigue states, in order to provide theoretical and technical support for reducing the train attendant’s fatigue risk and preventing human-factor accidents in railway operation.

2 Experiment Method 2.1 Speech Data Processing The unsteady speech signal was divided into several small segments of “quasi steady” signals with basically unchanged properties in order to reduce the noise of the environment for recording and the interference of the internal noise of the microphone, and to remove the influence of the lip radiation of human voice organs on the speech signal, so as to be convenient for the subsequent analysis of the speech signal. It is necessary to carry out speech enhancement, pre-emphasis and framing preprocessing on the recorded speech signal in turn. Because the recording environment was quiet and the noise signal was relatively stable, the spectral subtraction method with good noise reduction effect and less calculation was used to deal with the own noise of the equipment. The basic principle of the spectral subtraction is: assuming that the noise signal is stable and additive, calculate the power spectra of the original signal and noise signal respectively, and subtract the power spectrum of the original speech signal with the one of the noise signal to obtain a relatively clean speech signal power spectrum. The formula is as follows: x(n) = s(n) + t(n)

(1)

In Formula (1): x(n)—signal with noise; s(n)—noise signal; t(n)—signal without noise. Respectively carry out Fourier transform to x(n), s(n) and t(n) to get the complex spectrum: X (w) = S(w) + T (w)

(2)

The following energy spectrum with noise is obtained: |Y (w)|2 = |X (w)|2 + |N (w)|2 + X ∗ (w)N (w) + N ∗ (w)X (w) In addition, because the noise is not related to the pure speech signal, the power spectrum of the denoised signal is squared, and the complex spectrum of the denoised signal is obtained by using the phase information of the original signal, and then the following denoised signal is obtained by using the inverse Fourier transform: |T (w)|2 = |X (w)|2 − |S(w)|2

(3)

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Then use the first-order high pass digital filter to emphasize the high-frequency part of the speech signal, which makes the signal spectrum flat and convenient for subsequent analysis. The speech signal is taken as a unit pulse signal, and the transfer function H (z) is as follows: H (z) = 1 − µz −1

(4)

In Formula (4): µ—function coefficient; H(z)—transfer function. The range of µ value is 0.9–1, take µ = 0.98, and the speech signal is as follows after z transform: y(t) = x(t) − 0.98x(t − 1)

(5)

In Formula (5): x(t)—speech signal at time t; y(t)—signal at time t after pre-emphasis. Speech signal generation is an unsteady process with time-varying characteristics. Framing is to divide a speech signal into several segments of “quasi steady” signals with basically unchanged properties. Framing operation is realized by “windowing”. After being sampled, the speech signal can be considered as composed of numerous sampling points. Windowing operation is to multiply the sampled speech signal by a window function with limited length, which is convenient for the analysis of speech signal. Due to the frequency leakage caused by the direct truncation of the signal (with a rectangular window), this paper uses the Hamming window with larger side lobe attenuation with the frame length of 400, and the frame shift of 80 in order to improve the frequency leakage. yi (n) = w(n) ∗ x((i − 1) ∗ inc + n)

(6)

In Formula (6): x(·)—speech signal of time domain; yi (t)—signal at time t after pre-emphasis; L—frame length; inc—frame shift; fn—total number of frames after framing; w(n)—window function. 2.2 Characteristic Extraction Directly inputting a whole sentence may cause a large amount of redundant information, and then reduce the accuracy of recognition, while phoneme is the smallest phonetic unit divided according to the natural attributes of speech. One action constitutes a phoneme according to the analysis of the pronunciation action in the syllable. Extracting the sequence phoneme from the spectrum of input speech or audio is helpful to identify the

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weak information hidden in the speech, such as emotion, fatigue state, etc. Therefore, phoneme is selected as the analysis object in this paper. Spectrogram is a visual expression of time-frequency distribution of speech energy, which can not only show the gradual time evolution process of speech to meet the requirement of fatigue state changing with time, but also imitate the ability of human auditory system to perceive fatigue information. The 2D spectrum structure reflects the characteristics of harmonic wave and other excitation sources, and analyzes the characteristics of cepstrum, formants and other channels. It contains rich information, such as pitch period, formant, amplitude, MFCC, etc. In addition, it breaks through the singleness of traditional acoustic features, and is convenient to reflect the subtle differences between different sounds, with a certain generalization property, so it has stronger robustness. Divide a long original speech signal into frames and window, and then perform Fourier transform (FFT) on each frame. Finally, stack the result of each frame along another dimension to obtain a 2D signal form similar to a picture, which is called a spectrogram: ∞ x(m)g(n − m)e−jwn (7) X (n, w) = m=−∞

In Formula (7): x(m)—input signal; g(m)—window function; X(n, w)—2D function of time and frequency; S(n, w)—spectrogram of speech signal. 2.3 Model Construction The model is constructed by combining the convolutional neural network and the spectrogram, which can extract the high-level representation of the features effectively, and not only learn the time-frequency information in the speech signal, but also the frequencydomain information which is important to fatigue detection. The whole network has 16 layers that need training parameters, including 13 convolutional layers and 3 full connection layers. Among them, the convolutional layers mainly use convolutional operation to extract picture features, while the pooling layer selects the features obtained by the convolutional layers. Finally, the softmax layer is used to complete classification, and the VGG16 [17] architecture is basically used. Because of the large number of parameters of the model, the dropout mechanism [18] is added to the whole connection layer in order to prevent the over fitting phenomenon that the loss function is small but the prediction accuracy is high in the training data as well as the loss function is big but the prediction accuracy is low in the test data. Dropout is defined as follows: neural network units are temporarily discarded from the network according to certain probability in the training process of deep learning network. For the random gradient decline, two neurons may not present in one dropout network at a time due to random discarding. Thus, the weight updating no longer depends on the joint action of hidden nodes with fixed relationship, which prevents that some features are only effective under other specific features, forcing the network to learn more robust features, so as to effectively reduce the phenomenon of over fitting.

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3 Experiment 3.1 Experiment Data The reliable database is the key to the experiment. Because recording is not allowed, and it is inconvenient to detect the driver’s fatigue state under the actual train operation conditions, the fatigue induction was made under laboratory conditions. Twenty students were recruited, including 14 males and 6 females, with an average age of 23 ± 3. All the subjects were in normal physical condition, spoke clearly, and had no drinking or staying up late the day before, so as to ensure the smooth progress of the experiment. The time sequence process of the whole experiment is shown in Table 1, which mainly includes two performance analysis stages and one fatigue induction stage. Since the main workload source of the train attendant is mental workload, n-back paradigm [19] was used for fatigue induction. At the beginning and end of different experiment stages, the subjects were asked to read part of the standard terms of call response for four times each with normal volume and speed, including signal open, correct switch, station attention, benchmarking parking, no entrainment and speed code available, and these were used as the experimental data. Table 1. Process of fatigue induce experiment Rest

Record

Performance analysis

Record

Fatigue induced

Record

Performance analysis

Record

2 min

2 min

20 min

2 min

60 min

2 min

20 min

2 min

Fatigue state classification is the premise of fatigue state analysis, thus, subjective scoring data and performance data were combined to judge the subjects’ fatigue state in order to verify the effectiveness of fatigue induction. The scores of VAS-F fatigue scale [20], which can effectively reflect mental fatigue, were used to express the subjects’ subjective fatigue degrees. The subjective scores at the beginning and end of the fatigue induction task were used as the evaluation criteria of fatigue state. The subjects were fatigue when the VAS-F score was higher than 5. Two characteristics, namely, the response time and accuracy rate of 2-back fatigue task, were chosen for performance data analysis. The average values of response time and accuracy rate of all subjects in the first and third stages were calculated, and they were taken as the subjects’ performance data. The subjective data and performance data before and after the experiment were analyzed by paired sample t-test. The test results are shown in Table 2: Table 2. t test analysis results Data

Mean value

Variance

t

p

20.11

0.05

69.11

285.166

0.87

0.06

219.058

0.82

0.05

265.73

Subjective score (before experiment)

2.21

0.79

Subjective score (after experiment)

6.26

0.93

Reaction time (before experiment)

254.21

Reaction time (after experiment)

267.13

Accuracy (before experiment) Accuracy (after experiment)