Man-Machine-Environment System Engineering

Purpose: The aim of the present study is to explore the relationship between media multitasking behavior and information processing depth among college freshmen, and analyze the impact of media multitasking behavior on college students’ information processing ability. Method: Using college freshmen as subjects, the media multitasking index was measured using a media usage questionnaire to analyze and compare the performance differences between the heavy media multitasking behavior group and the light media multitasking behavior group in deep laboratory processing tasks. Result: Compared to the mild media multitasking behavior group, the performance differences of the heavy media multitasking behavior group showed a decreasing trend under deep and shallow processing conditions. Conclusion: Long term media multitasking behavior can weaken individuals’ ability to deeply process information. Application: Guide media content production and dissemination strategies, optimize education and training design, and improve learning outcomes for learners.

(Purpose) The purpose is to explore the ways to enhancing intelligent command and decision-making abilities through analyzing the main features and present challenges. (Methods) The research utilized literature review and case analysis to examine the main embodiment of the abilities, employed comparative analysis to identify challenges in enhancing the capabilities, and used summarization and induction methods to propose relevant strategies. (Results) Based on this study, the authors identified the current weaknesses from four aspects and discussed strategies from three levels. (Conclusion) The research is based on the teaching practices of the team and the current development of intelligent technology. The issues identified are closely related to practical aspects, and the proposed strategies can actively promote the construction of the abilities. The research results have a certain theoretical significance for the development of improving intelligent command and decision-making abilities.

As the energy industry structure transforms, the role of urban industrial landscape changes, and the industrial heritage left behind has a significant value of protection and renewal reuse. Eye-tracking experimental techniques were used to analyze the visual characteristics of subjects in different industrial heritage, and to explore the similarities and differences between the visual characteristics of subjects in the revitalization landscape design of mechanical equipment and the revitalization landscape design of industrial buildings in industrial cultural heritage. The results of the study show that the subjects pay more attention to the equipment itself when focusing on the landscape design of mechanical equipment. When focusing on the landscape design of industrial buildings, they will pay more attention to whether the building itself has the contrast of color materials.

Objective: To explore the impact of attention allocation methods on subway dispatch safety monitoring behavior under different experience and load conditions. Method: A 3 × 2 × 2 eye movement experimental platform was designed based on an attention allocation model, with 3 attention allocation methods × 2 brain load × 2 experience levels. Brain load was induced using the N-BACK paradigm and monitored by collecting EEG physiological data. The average fixation duration of the subjects was analysed. Exploring the effects of attention allocation methods on subway dispatch safety monitoring behavior under different levels of experience and mental load using three eye movement indicators: average fixation frequency and pupil diameter. Result: (1) Participants underwent brain load induction using the N-BACK paradigm under different load states α Wave and β The P-values of the average power percentage of the waves are all less than 0.05, indicating significant differences; (2) Under different experience and load conditions, the time required for primary and secondary allocation to handle abnormal information is the shortest; Conclusion: Through monitoring of EEG physiological data, it has been demonstrated that the N-BACK paradigm is effective in inducing brain load. By analyzing various indicators of eye movement data, the reasonable allocation of visual attention is achieved, with higher universality of primary and secondary allocation and more reasonable attention allocation. This provides a reference for the human-machine optimization of subway safety monitoring interfaces.

To investigate the effects of personality traits on how the workers are motivated by psychological needs and find directions for personalization in on-site safety management, this study carried out the moderating analysis among personality traits, psychological needs and safety motivation. The results show that openness to experience can moderate the relationships between social identity and amotivation/intrinsic motivation, work autonomy and amotivation; neuroticism can change the associations of social identity and amotivation/intrinsic motivation. Personality traits can be a sign of how to use the relationships between psychological needs and different kinds of safety motivation people respond to. The findings of this study contribute to a better understanding of how personality traits explain the variations in the associations between psychological needs and safety motivation, as well as how these variations can be utilized in customizing safety interventions to enhance on-site safety management.

Head constitutes a vital component of the human body. Therefore, in activities such as cycling, aviation, and other driving operations, ensuring adequate protection for the head through helmet usage becomes paramount. In this study, the area covered by the helmet is divided into six regions, and the high-density head pressure pain thresholds (PPT) are obtained through 128 measurement points. As a result, the PPT in the frontal pole and temporal regions gains the lowest index while that in the central gains the highest. Additionally, the PPT is slightly higher in females than that in males, but there was no statistical difference. PPT is negatively related to the body fat ratio (BFR), while the primary correlation area in both males and females are the parietal and occipital regions. Therefore, the results can provide a better understanding of the pressure pain sensitivity of the human head and offer robust data support for the design and optimization of ergonomic helmet pressure distribution in the future.

The problem of stress management is a multi-dimensional space composed of several different dimensions, each dimension is very important to analyze the stress situation of grass-roots officers and soldiers. Therefore, it is of great significance to analyze the stress situation of grass-roots officers and soldiers from different dimensions and build a stress management model. Based on the domestic and foreign research on stress management theories, this paper constructs a stress management model for grass-roots officers and soldiers from two dimensions of individual and organization. The whole model consists of three modules: ‘the generation and mechanism of stress, individual dimension and organizational dimension’. The module of pressure generation and action mechanism mainly consists of three parts: the attribute of pressure source, the pressure box of officers and soldiers and the work performance. The individual dimension module consists of three parts: investigation of individual work stress, individual self-stress management and pressure interview. The organizational dimension module consists of four parts: stress source investigation and management system, stress survey scale and implementation system, stress warning mechanism, stress response training mechanism and stress guarantee mechanism.

The grass-roots troops are a fighting group carrying out special tasks with high requirements for their work tasks. The officers and soldiers of the grass-roots level have to endure not only the impact from society, but also the tempering of the troops, their spirit and will face more severe tests, and their demand for stress management is increasing. As a professional method to help others, group counseling has attracted more and more attention with the development of mental health education and mental health services. Group counseling for stress management among grass-roots officers and soldiers can promote their continuous observation, learning, experience, sharing and communication in the group, to help them further understand and accept themselves, know others, improve interpersonal relationships, develop new behaviors, and finally to be more flexible and resilient in the face of various life events. Therefore, for the officers and soldiers at the grass-roots level, to implement the stress management group counseling, it is necessary to design a specific program, improve the cadres’ stress management group counseling skills, and to do a good job in the assessment of stress management group counseling.

(Objective) By studying and analyzing the current situation of the weapon operation practice course for foreign trainees, this paper puts forward some suggestions and measures to optimize and improve the teaching quality and efficiency of the course. (Methods) Based on trainees’ cognition and curriculum characteristics, methods of research and analysis, case demonstration and inductive reasoning are mainly adopted for research and discussion. (Results) This paper summarizes the common problems from three aspects: theoretical teaching, practical operation and final examination, and probes into the effective measures to improve the course quality from five aspects: teaching plan, teaching content and so on. (Conclusion) The research in this paper is based on the practical thinking in foreign training teaching for many years, and objectively analyzes the learning situation. The suggestions and measures put forward for the deficiencies are feasible, which has a good reference value for improving the teaching quality and efficiency of this course.

Due to the complex transportation lines and complex tasks of urban rail transit, drivers have high work intensity, high physiological and psychological load, and heavy safety responsibility burden. However, there is no pre-employment mental health assessment specifically for urban rail transit drivers. In this way, ordinary interviews and psychological assessments alone cannot effectively guarantee the driver’s safe driving adaptability. In this regard, based on in-depth interviews with 40 professionals in urban rail transit, this article uses Grounded theory to conduct qualitative analysis, summarizes a 6-dimensional model of urban rail transit drivers’ psychological fitness state, and develops a measurement scale based on this. Reliability and validity were verified through large-scale questionnaire data collection. The results show that the measurement scale has high reliability and validity.

Purpose: Supervisor bottom-line mentality (SBLM) suggests that supervisors sacrifice other priorities (e.g. employee well-being) for achieving the bottom-line results in the business sector. Although similar phenomenon exists in the safety industries, little research has paid attention to it. This article explores why supervisors’ addiction to pursuit of safety outcomes would lead to unsatisfactory results. Method: In study 1, we text data was coded based on grounded theory to propose the initial safety perspective’s SBLM scale. In Study 2, we improved the safety perspective’s SBLM scale by using the Delphi method, reliability analysis, factor analysis, discriminant validity analysis and regression analysis based on multi-wave data (n = 746). Results: the final scale consisted of two dimensions and 8 items with shows ideal content validity (Cronbach’s α = 0.862), convergent validity (CMIN/DF = 2.652; RMR = 0.069; GFI, NFI, IFI, CFI > 0.9), discriminant validity, and predictive validity. Conclusion: The safety perspective’s SBLM scale is a valid tool to assess whether safety supervisors focused only on safety outcomes in their management process. The findings are expected to advance research related to safety management research to reconsider poor management practices.

Objective The pathogenesis and examination methods of motion sickness at home and abroad are discussed. Method Twenty-one pieces of relevant literature were collected using databases such as NCBI and CNKI. Result The pathogenesis of motion sickness was analyzed and the examination methods were summarized through theories related to sensory conflict theory, fluid transfer theory, and vestibular organ sensitivity theory combined with the principle of flight. Conclusions Mining the occurrence mechanism and examination method of motion sickness to provide theoretical support for flight man-machine ergonomics evaluation.

In order to strengthen the fatigue management ability for flight-line maintenance personnel and ensure the safe operation of civil aviation aircrafts, the paper identifies 19 correlation indexes related to the fatigue of line maintenance personnel by analyzing the questionnaire answers of 829 line maintenance personnel in China. Then the AHP-entropy method is used to determine the weighting system of fatigue indexes for line maintenance personnel. Based on this, a fatigue management model for line maintenance personnel is established with the recognition thresholds set up for different fatigue states. It is found out through verification that, the fatigue management model for line maintenance personnel established in this paper is over 80% accurate in recognizing fatigue, proving to be reliable in fatigue recognition. The study provides decision support for the fatigue management of line maintenance personnel, and enables airlines to develop management software that carries out the whole process fatigue management of line maintenance personnel.

This investigation seeks to elucidate the influence of monocular and binocular vision on shooting behaviors, with an emphasis on evaluating shooting precision, the rapidity of aiming responses, and two ocular metrics: the ratio of saccade duration and the mean peak saccade velocity. Findings reveal that monocular aiming surpasses binocular aiming in terms of shooting accuracy, as monocular aiming enhances the shooter's focus on target details. Binocular aiming has a shorter aiming response time in rapid response shooting at multiple targets. The proportion of saccade duration and the average of peak saccade velocities during monocular aiming are higher than those during binocular aiming, implying that monocular aiming might increase visual load and lead to visual fatigue more quickly. This research provides new insights into the cognitive load and visual fatigue during shooting under different visual conditions, offering significant guidance for shooting training and practical applications.

(Objective) Based on the teaching experience and theoretical thinking of the course team, combined with the content characteristics of a certain kind of course, the paper puts forward some countermeasures to strengthen the ideological and political exploration of the course, which can provide reference for improving the effectiveness of the ideological and political education of the course, and provide reference for the talents training of military colleges. (Methods) In the process of writing this paper, the authors make a theoretical exploration of the ideological and political problems of a certain kind of course by the method of point statement, example and summary, and puts forward the concrete countermeasures from three aspects by using the empirical method. (Results) This paper probes into seven countermeasures to strengthen the ideological and political exploration of a certain kind of course from three aspects: seeking the ideological and political goals of the course, optimizing the ideological and political design of the course and doing well in the ideological and political implementation of the course. (Conclusion) Based on the teaching experience of the course team for many years, the countermeasures proposed in this paper can effectively improve the ideological and political effect of a certain kind of course, the research results of this paper have positive significance for promoting the innovation of ideological and political practice and improving the quality of talents training.

Achieving a high level of reliability in an environment full of volatility, uncertainty, complexity, and ambiguity is an urgent subject for industries like police, railway, and healthcare. During the period of COVID-19, the “heroic groups” and “the heroes in harm’s way” that emerged in our country have delivered the best answer. They shoulder the mission of the country, society, and people, and commit to translating the “impossible” into “possible” in every emergency time. By reviewing the current literature, related studies are mainly found in foreign, and they called the above-mentioned teams as high-reliability teams (HRTs), which can successfully respond to crises. However, there is lacking of systematic discussion in China. The main purpose of this study is to explore the connotations and characteristics of HRTs in the Chinese context. By combining the qualitative and quantitative methods, we have also developed a scale for further empirical research. The results indicated that there are four unique characteristics of HRTs and the scale has good reliability and discriminant validity. Our findings make a significant contribution to the safety management for high-reliability industries.

As a powerful army in the world, the US army has many advanced training concepts and methods in its military physical fitness training, and the US special forces are excellent representatives of the US army’s physical fitness training. The physical training of our army also has its characteristics and advantages, but there are some problems such as slow updating of some contents and insufficient adaptation to actual combat. As the main position of training future commanders, it is also necessary for military academies to learn from and absorb advanced training concepts and methods both inside and outside the army. This article through the literature reading, understanding of the US special forces in the concept of physical training, methods and characteristics, combined with the US special forces physical training methods, sums up the inspiration for our military Academy physical training.

The present study investigates the effect of sensation seeking and hazard types on hazard perception of young cyclists. A mixed design of 2 (sensation-seeking: high sensation seeking group, low sensation seeking group) × 2 (hazard type: overt hazard, covert hazard) was adopted. Twelve video clips were presented to 61 children aged 13 to 16 years and 185 adults aged 18 to 30 years. Cyclists were asked to answer three questions after each video clips turned into black screen. The results showed that the hazard perception ability of cyclists with different sensation seeking was affected by the hazard type Compared with covert hazard, the ability of the high sensation seeker to identify the location and predict the overt hazard was lower than that of the low sensation seeker. The findings has some practical value in developing interventions targeted at young cyclists’ hazard perception ability.

Smartphones, influencing the interplay between fitness and entertainment, may affect how exercise is performed and enjoyed. This study focused on the lesser-studied effects of non-musical smartphone features—video watching and gaming—on indoor cycling. Thirty young adults participated in three cycling sessions with varying entertainment: watching videos, gaming, and a control session without entertainment. Heart rate, distance, and calories burned were tracked to quantify exercise intensity, while enjoyment and fatigue were self-reported using a 5-point scale. Video watching did not alter exercise intensity but enhanced subjective enjoyment. Conversely, gaming slightly decreased intensity, yet improved enjoyment. These findings highlight that smartphone entertainment can modulate the physical and psychological aspects of exercise, providing valuable insights for developing more engaging fitness programs.

Past research suggests the “Wink” emoji is effective for sarcasm perception in English but its impact in Chinese contexts is unclear. Therefore, this study aims to explore how Chinese perceive sarcasm with the “Wink” emoji and its influence on social interaction in instant messaging. Findings indicate that in positive responses, the “Wink” emoji weakens sarcasm, aiding literal understanding, while in negative responses it enhances sarcasm, leading to ambiguity. Furthermore, the use of the “Wink” emoji with positive connotations also facilitates the promotion and maintenance of social relationships. Overall, our research reveals cultural differences in the interpretation of sarcasm through emojis in digital communication. Hence, further research is needed to identify emojis that serve as effective cues for sarcasm among Chinese users.

The objective of this research is to assess the body shape dissatisfaction among young Chinese women via using a new body image scale in Chinese version. Thirty-four female participants were recruited to evaluate the construct validity of the body image scale and collect the current body self-rating and ideal body self-rating for calculating the body dissatisfaction scores. The results reported a positive correlation between participants’ actual BMI and their current self-ratings based on the selections from this scale, suggesting a good construct validity. Additionally, the body dissatisfaction score of Chinese females revealed that approximately 85% expressed dissatisfaction with their own bodies and sought body size reduction for the young Chinese females. This study provided quantifiable data and initial effective measurements for Chinese female body image perceptions.

Depression is one aspect of mental health. Previous research has revealed that depression is linked to drivers’ driving behavior and has an impact on drivers’ cognitive processes, but no studies have been conducted to determine what type of driving behavior depression may cause. This study examines the effects of depression on bus drivers’ driving behavior and the factors that may contribute to bus drivers’ depression. The mental health test scale was used to choose 50 participants with high depression and 50 participants with low depression as the experimental and control groups, and the bus driver’s driving behavior scale was administered to them. The findings indicate that bus drivers’ depression is highly associated to the occurrence of error driving and lapse driving behavior, while age, marital status, and children’s status are potential risk factors for depression. According to the findings, bus drivers can be targeted to intervene, thereby improving road traffic safety and the quality of public transportation services.

Effective measures to enhance pilot safety attitudes are crucial in preventing accidents. This study identifies psychological resilience and cognitive flexibility as two factors potentially related to improving safety attitudes among pilots. Through path analysis of questionnaire data from 106 Chinese civil aviation pilots, this study systematically examines the relationship between these factors and safety attitudes for the first time. Results indicate significant positive correlations among variables. Moreover, cognitive flexibility not only serves as a mediator between psychological resilience and safety attitudes (explaining 39.811%) but also exhibits a moderating effect (t = –2.368, p < 0.05). This suggests that cognitive flexibility partially mediates the influence of psychological resilience on safety attitudes, with significant differences across individuals with varying levels of cognitive flexibility. This study offers valuable insights for designing interventions in aviation safety management, emphasizing targeted designs based on different levels of cognitive flexibility, and provides a new perspective on the psychological foundation of pilot safety attitudes.

Objective. To study the association between motion sickness and related genes. Method. By collecting Pubmed, CNKI and other databases, 17 relevant papers were investigated. Result. The associations between α2A adrenergic receptor (ADRA2A) gene, angiotensin-converting enzyme (ACE) gene, coagulation factor C homology (COCH) gene and other gene polymorphisms and motion sickness were analyzed. Conclusions. Providing theoretical research on genomics and proteomics through the study of polymorphisms in motion sickness related genes.

The application of solid oxide fuel cells (SOFCs) in vehicles can greatly alleviate the energy shortage and the environmental pollution caused by fossil fuel combustion. However, when the temperature of the SOFC system decreases, the conductivity of the cathode material will decrease and the polarization impedance will increase, which will reduce the stability and selectivity of SOFCs. In this paper, a cathode material, Ca3Co4O9-δ (CCO) with high performance for automotive applications was investigated. The crystal structure and microstructure were studied by XRD and SEM. The electrochemical performance shows that the total resistance of the cell was only 0.1 Ω cm−1. CCO exhibits great potencial as SOFC cathode. The application of new types of electrode materials can not only optimize the cell performance of SOFC, but also provide new ideas for the development of automotive fuel cell technology.

Due to complex types of traffic participants and large randomness of traffic behaviors, intersection has become a typical scenario of urban traffic accident and a severe challenge for the application of autonomous driving urbanization. This paper extracts typical cross shaped intersection conflict scenarios through theoretical derivation in the first place. Next, to evaluate if single vehicle multi-sensor information fusion technology is reliable at intersections, a high mileage real road test is conducted. Then the potential risks of this scheme at intersection scene are analyzed. Finally, a technical concept of automatic driving perception combining V2I and multi sensor information fusion at intersections is proposed.

The level of situational awareness of coal mining machine operators significantly affects operational performance, which in turn is influenced by emotions such as state anxiety. In order to investigate the influence of state anxiety level on the situational awareness of remote-driving extractor operators, the State Anxiety Scale and SART Scale were used to conduct a remote-driving extractor situational awareness evaluation experiment with 60 subjects in a simulated extractor operation scenario. The results showed that there was a significant difference in the level of situational awareness among subjects at different levels of state anxiety, and that subjects at low levels of state anxiety would have a higher level of situational awareness, reduce the time to complete the task, and reduce the number of errors; Low situational awareness at high state anxiety levels makes it easy to make wrong judgments, increasing the time to complete the task as well as the number of errors. The results of the study can provide a theoretical basis and management approach for coal mining companies to manage operators’ anxiety and improve their work efficiency.

In flight, any form of abnormal cognitive state in pilots could jeopardize flight safety, necessitating intervention in pilots’ abnormal cognitive states. This paper first identifies five types of abnormal cognitive states in pilots based on the CREAM theory, and establishes the PDA model framework for abnormal cognitive states based on the human information processing model. By comparing the dynamic interactions between humans, machines, and the environment, and following the domestic SPO concept for intervening with pilots, an auditory and visual channel integrated alarm intervention strategy is designed. The effectiveness of the intervention is evaluated in real-time for adjustments, thus forming a corrective feedback loop. Finally, the alarm is implemented using Python programming, and intervention strategy validation simulation experiments are conducted in the DCS World simulation environment. The intervention effectiveness exceeds 90%, achieving the purpose of intervening in abnormal cognitive states and holding significant research value for flight safety.

In order to reduce the damage of exercise fatigue to the human body and improve work efficiency, conducting research on exercise fatigue evaluation has important theoretical and practical value for the design, training, and prevention of occupational diseases in physical work tasks. This study designed and conducted a running experiment, analyzed the variation patterns of time-domain and frequency-domain indicators of surface electromyography (EMG) signals during the process of deepening fatigue, explored the relationship between EMG signals and exercise fatigue, and established a fatigue evaluation model based on EMG signals support vector machine. The results showed that the integrate electromyography (IEMG), root mean square (RMS), mean power frequency (MPF), and median frequency (MF) of EMG had good sensitivity to fatigue changes, and the constructed fatigue evaluation model based on support vector machine (SVM) had good accuracy and could effectively evaluate exercise fatigue.

Objective. Research on the etiology and assessment techniques of visual fatigue based on flight-controlled visual terminals at home and abroad. Method. 34 pieces of related literature were collected using databases such as NCBI and CNKI. Result. Analyzed the pathogenesis of visual fatigue and summarized the assessment methods by studying the etiology of visual fatigue. Conclusions. To explore the occurrence mechanism and assessment method of visual fatigue, and to provide reference data for further research on visual function characteristics and visual fatigue improvement of flight crew.

In response to the problem of scheduling weekly training plans for aerospace special practitioner under multi-resource constraints, a mathematical model for solving this problem is proposed. Based on the 1 + 1 Evolution Strategy, an adaptive modified evolutionary strategy based on simulated annealing algorithm is designed. The main operators and fitness function of the evolution strategy algorithm are elaborated in detail, and an automated scheduling program is developed using Python. The application of this program to actual examples shows that the proposed algorithm strategy has good convergence and convergence speed, and the resulting schedules are reasonable and feasible, which is benefited to improve the efficiency of aerospace special practitioner training plan scheduling in practical work.

This paper studies the method about analysis and evaluation for human actions with the potential to postulate initiating events which are regarded as Type B human actions in nuclear power plants. It develops a useful and effective flow diagram in the analysis and assessment of human actions with potential initiating events. It mainly includes the selection of scenarios, qualitative analysis and quantitative analysis. Through the detailed analysis, key steps of human actions could be picked out and the human error probability of the task could be calculated. The influence of the human actions for the whole task could be assessed. As an effective method of human reliability analysis, it provides a systematic assessment method for analyzing human error in the tasks and contributes for the overall safety of the nuclear plants. Besides, fuel mis-loading was chosen as a typical Type B human actions activity to be analyzed and assessed by this method.

In order to reduce the safety accidents caused by civil aviation passenger unsafe behavior, collect civil aviation passenger unsafe behavior in recent years, build based on the Security System Theory passenger unsafe behavior explanation model, using fishbone diagram analysis tool to identify risk, using the GAHP of civil aviation passenger unsafe behavior risk of “human, material, environment, management” four elements to build a risk evaluation system. The results show that the passenger abnormal behavior is the biggest influence factors of civil aviation passenger unsafe behavior, and put forward to build big data intelligence mechanism, the introduction of civil aviation facilities and equipment digital management system, build safety performance oriented aviation safety management system, in order to promote the development of civil aviation safety management of high quality.

This paper describes Russia's main hypersonic weapons and examines their usage in the Russo-Ukrainian conflict. It analyzes and summarizes the operational methods of Russian hypersonic weapons from various aspects such as strategic deterrence, targeted selection, rapid breakthrough, long-range precision strikes, and joint operations, etc., which has certain reference significance for understanding future hypersonic weapon operations.

With the large-scale use of stealth aircraft in penetrating strike, the confrontation between air defense forces and stealth aircraft is bound to become a key link in determining the victory or defeat of the war. This paper focuses on system optimization, considers the joint use of target search radar and tracking guidance radar to detect and track stealth aircraft, establishes a corresponding model based on queuing theory, and studies the method and principle of radar against stealth aircraft. The application of radar power in anti-penetrating strikes is explored.

At present, China's agricultural machinery is transforming to green, and actively promoting the realization of the dual carbon goal of the agricultural system. In view of the lack of systematic guidance on tractor fuel consumption in China, the unclear spatial and temporal distribution of fuel consumption in tractor operating systems, and the insufficient design to support the endurance of new energy agricultural machinery, the fuel consumption data of tractor ploughing and large-load operation in northern China/field management with small load operation period were investigated, and the fuel consumption time characteristics were analyzed on a monthly basis and the spatial characteristics of fuel consumption were analyzed on a regional basis. The results show that the tractor work includes ploughing, sowing, suppression, managing, subsoiling, land preparation, transfer and other links, throughout the agricultural operation throughout the year, a single fuel consumption has the characteristics of “concave”, in the ploughing and subsoiling links with large loads and other links in the peak of the wave, in the small load of the link fuel consumption in the peak valley. According to the survey data, the average fuel consumption per mu of large tractors is about 8L, and the work efficiency is about 15 mu/day (medium tractors are about 6 mu/day), assuming that they work 28 days per month. In the Northeast and Central Plains, the fuel consumption of high-power tractor is similar, with a peak value of about 3300L/unit/month and a valley value of about 1200 L/unit/month; In the Northeast and the Central Plains, the peak fuel consumption of high-power tractor is similar, about 1100 L/unit/month, and the valley value is slightly different, about 600–800 L/unit/month; The number of main working months is about 5 months.

Human comfort dictates stricter temperature and velocity requirements in the passenger cabin and flight deck. Uneven or excessively high airflow from the ventilation control system may cause discomfort to passengers due to strong drafts. In this study, a parametric CFD model, augmented with a genetic algorithm, is developed to optimize the temperature and velocity within aircraft ventilation buffer chambers, incorporating the shape and size of a novel curved ventilation plate. This endeavour aims to enhance airflow uniformity from the ventilation control system vents, thereby improving passenger comfort within the cabin. Results demonstrate that outlet airflow uniformity has been significantly enhanced through automated optimization design, providing a more adaptable solution for designing airflow comfort in aircraft.

With the rapid development of satellite technology, synthetic aperture radar and optical satellites play an increasingly important role in maritime reconnaissance. Among them, staring satellites in geostationary orbit can obtain more dynamic information than traditional satellites in low orbit, which has important influence on real-time acquisition of ocean situation and mastery of strategic initiative. To improve the efficiency of tracking marine target in staring sequence images, this paper combines the optimized frame difference method with the correlation filtering method, to track ship targets in GF-4 staring satellite image sequence. The result shows that, the study improves the tracking rate of ship targets significantly, and provides reference for target tracking of staring sequence images.

Out-of-distribution detection is an important task in image processing and plays an important role in AR Teaching image recognition. However, when the out-of-distribution data input into deep learning networks, the results tend to have a uniform distribution across various label categories, so it is difficult to detect out-of-distribution data using DNN. We propose a method that the intermediate layer outputs of neural networks are used as features for re-input into the neural network for the recognition of out-of-distribution data. Experimental results demonstrate that by training with a small amount of out-of-distribution data, the proposed method improves the AUROC metric by 9%.

Geostationary orbit (GEO) satellite remote sensing is becoming more and more important in the field of remote sensing because of its wide scan, real-time continuous observation and rapid operational response, and it has great application potential in ocean monitoring as well. In this paper, a pre-processing method of GEO satellite image data is proposed to realize sea-land segmentation and cloud masking of GEO satellite image. Taking GF-4 satellite image as the object of study, distinguish the sea surface, cloud layer and land in the image with the spectral characteristics of different reflectance firstly; then detecte the ocean area by water body index; the binary image is processed by block operation according to the difference of density distribution of ship, cloud and land, and the regions of interest are extracted at last.

Objective. To develop a multi-color photic EEG induced flash device for pilots of carrier-based aircraft. The flash can simulate the color of the guidance cursor of an aircraft carrier landing, and provide an identification method for selecting pilots of carrier-based aircraft who are sensitive to color light and may induce potential epilepsy. Methods. The lamp body of the device was designed as length × width × thickness = 35 × 8 × 3 cm, and the material was a 3mm thick plexiglass cuboid. Only the front side was transparent, and the other sides were opaque. There are 4 rows of high-brightness light-emitting diodes (LED) in the body of the lamp, which can emit light in 4 colors: red, yellow, green and orange. The colors of red, yellow and green each contain 36 LED, and the colors of orange contain 18 LED. In the 4 rows of LED, the spacing of each row of lLED is 1.0 cm. Under the control of EEG flashing program, the four color LED of the device can light up in the order of red, yellow, green and orange colors. At the same time, each color can flash at 3, 6, 8, 10, 13, 14, 15, 20 and 30 Hz. The duration of each color flash is 5 s, and the interval is 5 s. The bracket is designed to be foldable and retractable. During the inspection, the flash light is placed 15 cm in front of the subject’s eyes through a retractable folding arm. The control box circuit consists of a Darlington transistor connected to emit electrical signals from the brain and control the flash of the lamp body. Results. The comparative application of the device showed that the effect of color light on epileptoid brain dysfunction was not significantly different from that of conventional flash light (ordinary light). Conclusion. The device can make up for the deficiency of clinical flash induction method, and can be used in the selection and identification of pilots with color photosensitive epilepsy risk.

Aircraft carrier is a symbol of national military strength, the number of carrier-based aircraft carried by aircraft carriers and the sortie rate are the basic indicators to measure their combat capability, and the deployment of carrier-based aircraft on the flight deck has an important impact on the sortie of carrier-based aircraft. In this paper, for the purpose of designing the aircraft carrier aircraft deployment and sortie scheme, the aircraft carrier flight deck environment and ship surface station setting are analyzed, the sortie process and dispatch time of the carrier-based aircraft are studied, and the mission-oriented layout model is formed. By drawing on the latest technological achievements such as intelligent algorithms and genetic algorithms at home and abroad, combined with the layout model, a carrier-based aircraft deployment scheme based on genetic algorithm is formed, which solves the problem of carrier-based aircraft deployment on the aircraft carrier deck, improves the command and decision-making level of aircraft carrier transportation and support, and enhances the overall combat capability of the aircraft carrier.

Based on the triangular fuzzy number, FreeFta is used to construct an accident tree for qualitative and quantitative analyses, to determine the possible risks in the road transport of lithium batteries, and according to the probability of the impact of accident-causing factors, it proposes measures such as strengthening the safety training and establishing an effective quality supervision system of lithium batteries, to provide technical support for the prevention of lithium battery fires in road transport.

As a typical complex cabin, the aircraft fairing area has a coupling relationship among multiple parameters such as equipment operating state, surface temperature and cabin environment, which makes it difficult to obtain the accurate cabin temperature of aircraft fairing area based on a single simulation method. This paper proposes a one-dimensional and three-dimensional co-simulation analysis method for aircraft fairing area, and verifies the accuracy of simulation analysis method based on fairing area temperature test data of an aircraft. The results show that the average deviation between test temperature and simulated temperature is 5.8 °C, and the calculation accuracy can meet the engineering application. The analysis method has high accuracy and value for engineering application.

Fire accidents occurs frequently with the rapid popularization of electric bike and resulted in 41 persons killed as well as 157 persons wounded even in single year of 2021 according to National Fire and Rescue Administration. Therefore it is significant to trace the potential risk and provide specific measure to prevent fire accident. The study constructed the evaluation index system of the fire risk factors based on hierarchical analysis and fuzzy comprehensive evaluation methods. Research shows that the main factors for the fire accidents include flying line charging, indoor corridor charging, over-charging and aging of power lines. It is suggested to take targeted prevention and control measures such as setting up special charging area, intelligent charging management system and convenient charging device. These measures provide new perspectives and tools to help in the understanding and management of electric vehicle fire risk, and provide scientific reference for fire accident prevention and control.

Mechanical impedance is one of the most important parameters to characterize the biodynamic response of the hand-arm system. However, the mechanical impedance measurement of the hand-arm system may be affected by the measuring equipment. Similar problems exist in the mechanical impedance measurement of the hand-arm system of on-orbit hand-transmitted vibration. A typical mass cancellation method is applied to solve the influence of handle quality on measurement. The mechanical impedance of handle-only and handle-hand-arm system coupling is measured under microgravity simulation and calculated respectively. The results show that the mechanical impedance of the hand-arm system is consistent for different subjects under microgravity simulation. The frequency of the peaks and troughs of the mechanical impedance obtained is similar to the published mechanical impedance standard. Some of the differences in details may be due to the different working conditions of microgravity simulation and ground gravity conditions.

The process is detailed as follows. Firstly, the small data samples and their space points are obtained, and the quadratic elements are established to generate the projection transformation matrix with surface constraints. Secondly, a variety of construction factor transformations based on small data are obtained. Thirdly, the planar points are inversely projected into a sparse stereo point set, based on the F-norm distance domain, the correlation $$\vartheta$$ ϑ measure factor is set and the surface is generated by infinite approximation. Finally, the seed points expend to generate dense sets and are iterated into exact models. The experimental results show that this method is effective, especially for small data samples, with low computation and high visibility of reconstructed objects.

Lithium borohydride (LiBH4) has a high mass hydrogen storage density (18.5 wt%) and volume hydrogen storage density (121 kg/m3), which is a potential hydrogen storage material. However, its poor thermodynamic and kinetic properties and harsh reversible conditions limit the application of LiBH4. Using the nanoconfined method, the hydrogen storage performance of LiBH4 in porous carbon materials (PC) was studied. By means of melt impregnation, the most suitable impregnation amount of 80% LiBH4 was screened out in PC. The desorption temperature of LiBH4 in the nanometer confined domain is significantly lower than that of pure LiBH4, and the initial desorption temperature is reduced from about 300 ℃ to about 130 ℃, which effectively improves the thermodynamic properties of LiBH4. In addition, 1.4 wt% H2 can be released after nano-confined LiBH4 is kept at 160 ℃ for 100 min, and 8.4wt % H2 can be released after nano-confined LiBH4 is kept at 370 ℃ for 100 min. This is the amount of hydrogen release that pure LiBH4 cannot reach at the same temperatures, indicating that nano-confined LiBH4 also improves the kinetic properties of LiBH4.

China began to enter the aging society in 1999, and by 2021, it has turned to the severe aging society, which is the country with the largest number of elderly people, so the aging-friendly design has become a problem that must be considered by the Chinese society. By carrying out practical research, this thesis provides an in-depth understanding and analysis of the behavioral characteristics and needs of the elderly outdoor sitting and sitting, combines the emotional hierarchy theory to disassemble the user's needs, and applies the ergonomics content of the outdoor public seat to make a functional scale analysis to provide a solution and reference for the standardized design of the aging-friendly public seat, and improves the appearance of its local elements. The design results of this paper aim to effectively meet the needs of the elderly and improve their outdoor experience and quality of life.

(Purpose) this paper is based on the author’s learning interests and theoretical thinking, combined with the main characteristics and countermeasures of UAVs, to seek targeted countermeasures, providing theoretical references for informatized and intelligent air defense operations. (Method) In the process of writing the article, methods such as examples, comparisons, analyses, summaries, and inductions are used for theoretical exploration, and relevant countermeasures are proposed using speculative and empirical methods. (Result) The paper analyzes five main characteristics of UAVs, distinguishes three countermeasure difficulties, and proposes five countermeasures. (Conclusion) The characteristics, difficulties, and countermeasures of UAVs studied in this paper have a certain degree of credibility. The research in this paper is of great significance in promoting the research on countermeasures and air defense operations against UAVs.

With the increasing importance of education in society and the continuous improvement of students’ demand for quality of life, the redesign of campus public facilities has attracted much attention, among which the bathroom is closely related to each student. Through the combination of network search, field research, questionnaire survey, online interview and other practical methods, this paper uses ergonomics to study the space and design of university bathroom, and puts forward a series of design suggestions for university bathroom space, including optimizing the layout, improving the facility function and enhancing the safety, so as to improve students’ experience and ensure safety. Improve the aesthetic degree, so as to enhance students’ happiness.

During the airdrop test of a certain pod, the parachute system located at the tail provides deceleration function. The suspension point of the parachute system is an important part for transmitting loads during the descent process of the pod, and the transmission path of the suspension point load is related to the attitude stability of the Pod-Parachute-Combination (PPC) after parachute deployment. This article evaluates the attitude stability of the pod after parachute deployment by combining the flight path angle and the attitude angle of the PPC. Finally, the simulation results are verified by combining experimental images. The research results indicate that when using double suspension points, the attitude stability of the PPC is good, which can provide a reference basis for the suspension point design of subsequent pod airdrop tests.

In response to the problem of excessive fuel consumption of traditional agricultural machinery and unclear potential and benefits of electric agricultural machinery substitution in the process of facility vegetable cultivation, an analysis of the fuel consumption characteristics of facility vegetable agricultural machinery is carried out. The equivalent electricity demand formula of agricultural machinery is used to convert the electricity required by electric agricultural machinery, and then the contribution of electric agricultural machinery with multiple sources to carbon reduction and energy conservation in the power grid is predicted. The results show that the facility greenhouse is mainly powered by devices such as roller shutters and temperature controllers (with a constant temperature of about 25 ℃ and humidity of 76%), with an average monthly power consumption of 200 kWh/acre. Close to the municipal power grid, the basic conditions for electrification transformation are good. Generally, photovoltaic energy supply accounts for about 30%, wind energy accounts for about 70%, and battery energy storage accounts for about 60% in wind and solar complementary greenhouses; The predicted contribution rates of different usage levels (0, 25%, 75%, 100%) of electric tractors to carbon reduction are 0, 20%, 61%, and 81%, respectively; Equivalent power consumption is approximately 45 kW $$ \cdot $$ · h/hm2, Reduce carbon emissions by 12 kg/hm2(CO2), small and medium-sized greenhouses can reduce agricultural machinery carbon emissions by about 2464 tons (CO2), save electricity by 9.24 × 106 kW $$ \cdot $$ · h, or the electricity needed for 165 ventilation equipment to ventilate simultaneously all day, or the electricity needed for 5500 street lights to illuminate at night, or the electricity demand for 11 duty rooms throughout the year.

There are differences in the mechanical properties of high-performance fiber fabrics under dynamic tension and quasi-static conditions. In this paper, four high-performance fiber fabrics were selected for testing at tensile rates of 1 m/s, 5 m/s, 12 m/s, and 20 m/s, and the test results were compared. The experimental results show that as the stretching rate increases, the breaking strength of nylon, aramid, and polyethylene fabrics shows an upward trend, while the strain shows a downward trend. However, the changes in the parameters of fracture strength and strain are not linearly related to the experimental variable of tensile rate. The strain fracture strength curve indicates that, unlike the smoother curve under quasi-static tensile conditions, the tensile curve during dynamic stretching exhibits a clear unloading process, and the peak of unloading also increases with the increase of stretching rate.

This critical equipment undergoes complex external environments such as ground launch, high-altitude flight, and start-up work, making it difficult to low-cost verify its ability to withstand external environments through ground testing. In response to this situation, this article uses theoretical methods to analyze the main paths of heat transfer, and then establishes a mathematical simulation model to analyze the factors affecting the temperature of a certain electronic device. Finally, the results are verified with experimental data, and the simulation results are consistent with the experimental data. It can provide a reference for the thermal design of a certain electronic device for high-altitude parachute deployment in the future.

With the increasing competition in the market and the development of science and technology, the brand image design of mobile phones occupies a key position in the mobile phone industry. This paper analyses the role of sensory marketing on the development of brand image of major mobile phone brands, especially Apple, by analysing the sensory elements of vision, hearing, touch and taste. Through literature review and case studies, the text analyses how sensory elements interact with consumers’ emotional perceptions and enhance brand awareness and purchase decisions. This study adopts a combination of qualitative and quantitative aspects of analysis, including questionnaire survey, in-depth interviews, Spss reliability analysis, to prove the point of view through the collection and validation of data. The results show that sensory marketing plays an important role in the image development of mobile phone brands, especially the Apple brand. This study provides a new perspective for understanding the application of sensory marketing to user experience and modern brand management, and provides reference for the sensory marketing strategy of mobile phone brands.

In the process of filed test, a large number of test data are obtained, such as the data from internal trajectory, intermediate trajectory and ballistic end point of projectile. However, the emplacement data and the terminal ballistic end-point test data are less used each other although these data are interrelated in theory. For historical data, a digital deduction model of ballistic end point is established by using artificial intelligence algorithms such as deep learning and machine learning. This model can deduce the ballistic end-point test results, so as to realize the combination of digital signing and physical test, and provide theoretical support for the digital simulation of the same type of artillery prime mover and ammunition test.

To address the challenge of quickly locating multiple projectile explosion points on the ground during testing, this paper analyzes the optical characteristics of visible light, short-wave infrared, and medium to long-wave infrared target images of projectile explosions to select the most suitable optical shooting band. A test method is proposed based on the monocular camera of the space-based platform combined with ground control points to locate the coordinates of multiple explosion points. A complete set of automatic detection and location algorithms, such as image jitter correction, target image detection, and matching of the same named points, are provided. The feasibility and accuracy of the positioning method are verified by using the electronic detonation explosive experiment and the data acquisition method of the DJI UAV system. The experiment results show that the proposed method is not easy to be disturbed by fireworks, and the real-time processing error just is meter-level, and the post-processing test accuracy is in the decimeter level.

During live fire shooting, there is often the generation of UXO, which can cause potential safety issues. In the acoustic localization of dumbbell landing based on TDOA technology, the detection of the sound source is a key step in completing the localization, and the accuracy of the localization results is crucial. Based on the mixed basis decomposition of characteristic waveforms, this article studies a specific wavelet and other characteristics, and constructs a wavelet characteristic waveform basis function library that can be used for ground acoustic signal detection and time delay estimation. The effectiveness of this method was verified by detecting and locating weak sound sources when projectiles land under noisy background conditions.

The acoustic signal characteristics of multiple projectile explosions were analyzed, and a set of fusional localization method for multiple explosion points of salvo projectiles which was suitable for practical measurement environments was studied. This method firstly theoretically analyzes the characteristics of multiple explosion acoustic waves and the chaotic signal timing and adhesion, a microphone is deployed around the area of the explosion point to be tested, and a data processing model based on evidence theory is established according to the wave arrival time measured by the microphone, a sample dataset of explosion point coordinates is established, and the target is checked and eliminated based on multiple pieces of evidence, the evidence mainly includes spatial consistency, energy consistency, completeness of wave arrival time and target quantity. The method was applied to a certain salvo projectile combat test, and the processing results are consistent with the post test results, verifying the reliability and correctness of the method proposed in this article.

Spaceflight training simulator is the main place for astronauts mastering flight programs and skills on the earth. With the development of manned spacecraft astronautical engineering mission, spaceflight tasks become more complex and system function of simulator increase, which brings greater challenge to the development and maintenance of spaceflight training simulators. In this paper, characteristics of simulator software development were analysed and essential software development modes were contrasted. A software development mode based on multiple mode was proposed, which was successfully used in the software development of space station simulator and provided important reference for the follow-up work.

Fuzz testing is a powerful technique to discover software vulnerabilities by providing unexpected inputs to assess the behavior of the software under test. Feedback-driven fuzz testing tools like AFL have gained prominence in recent years, making feedback-based gray-box fuzz testing an effective method for vulnerability discovery. Specifically in the realm of network protocol testing, tools like AFLNET, State AFL, and SGfuzz have proven to be highly effective. This study examines the application of state-guided algorithms in recent research, particularly in feedback-driven protocol fuzz testing, offering a comprehensive comparison and valuable insights for future studies.

A cross-modality image transformation method using the Generative Adversarial Network (GAN) is proposed in this paper. First, the preprocessing methods are performed to the original image data. The computational steps include adjusting image size and suppressing image noises. Second, a kind of GAN is constructed. Both the generator network and discriminator network are created. Third, the GAN is trained and the back propagation optimization is performed continuously. Finally, the trained GAN can be used for data enhancement. To test the effects of computational steps above, the image transformation from the visible light image to other noise-contaminated image is performed. Lots of experiments have illustrated the correctness of our method.

Vascular skeleton extraction is one of the key steps in medical image analysis. However, during the acquisition process of forearm near-infrared vascular images, due to external factors, they are not clear enough, resulting in inaccurate extraction of vascular skeletons. After preprocessing the initial image, this paper uses the Zhang-Suen refinement algorithm to extract the forearm near-infrared vascular skeleton. This algorithm is an iterative algorithm that can accurately refine the object boundaries in an image into a pixel wide skeleton. The experimental results show that compared to other skeleton extraction algorithms, the Zhang-Suen refinement algorithm obtains smoother, more accurate, and clearer vascular skeletons.

This paper discusses the importance of visible-infrared imaging sensor in UAV cluster system and its application in post-disaster rescue. The technology is characterized by rapid deployment and flexible scheduling, which can quickly respond to disaster events and provide support. However, due to the differences between the two images, it is still a challenge to achieve their feature matching. Deep learning-based methods have become the mainstream research direction to solve this problem. This paper introduces a method based on local feature matching and Transformer to realize feature point matching of visible and infrared images. In this paper, ResNet-FPN structure is used to extract local features of the image, which can effectively obtain rich information and simplify the feature map. The extracted features will be sent to transformer to add location information and attention mechanism. And then feature point matching results can be obtained through coarse-grained and fine-grained matching. The effectiveness and performance of the proposed method are verified by experiments, and good results are obtained on multiple data sets.

With their affordability, agility, and stealth capabilities, unmanned aerial vehicles (UAVs) have become indispensable assets in modern warfare. However, developing an effective UAV cooperative hunting system that can counter enemy UAV intrusions at a reasonable cost is paramount. This paper aims to tackle the challenges of autonomous cooperative decision-making among multiple UAVs within such a system. Specifically, it proposes the utilization of the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to enable cooperative hunting among multiple UAVs. The results of experiments conducted demonstrate that the MADDPG algorithm effectively facilitates efficient hunting of enemy UAVs.

(Purpose) This paper analyzes the background and motivation of the further development of the short-range air defense weapon in the U. S. Army, and introduces the present situation of the short-range air defense weapon in the U. S. Army. (Methods) On this basis, the development trend of the short-range air defense weapons of the U. S. Army and the enlightenment to the development of the air defense equipment of the U. S. (Conclusion)Army are prospected, in order to provide reference for the construction and development of the air defense units of the U. S. Army.

(Purpose) By analyzing the threat of unmanned aerial vehicle (UAV) in the Palestinian-Israeli conflict, this paper draws the relevant enlightenment and thinking on how to conduct anti-UAV operations in the future battlefield. (Methods) The combat threat of UAVs in the conflict between Palestine and Israel was analyzed by the method of comparison. (Results) Based on the analysis of the use and threat of small and medium-sized UAVs in the conflict between Palestine and Israel, it is concluded that it is necessary to conduct reconnaissance and early warning of small UAVs in advance through various means. (Conclusion) In order to achieve the operational state of discovery and destruction, it is necessary to use multiple means such as multi-domain early warning exploration, high-energy directional weapon attack, electronic warfare complementation and multi-means interference, so as to achieve the operational objectives in future operations.

Deep learning is an essential technical means for the application of artificial intelligence in the field of perception, especially in the field of SAR target image recognition, which has shown excellent performance. Currently, deep learning heavily relies on data, and data quality is a key factor affecting SAR target image recognition. However, SAR images involved in the field of combat operations are difficult to obtain. To address the problem of insufficient data caused by this, it is crucial to generate effective SAR image data for model training and validation of artificial intelligence algorithms. This article proposes a framework for SAR target image simulation and generation tools, aiming to provide a data foundation for relevant artificial intelligence algorithm training and model performance verification work.

Deep reinforcement learning algorithms perform well in the field of control and artificial intelligence, but still face problems such as poor interpretability. Combined with the structural advantages of behavior tree, research on behavior tree generation and optimization based on reinforcement learning has become one of the ways to solve the problem. However, due to the high flexibility of behavior tree, the generation mechanism based on data-driven methods often has difficulties. Therefore, the paper mainly proposes a normalization method of behavior tree, which is applicable to the research of behavior tree generation based on multi-agent reinforcement learning. On this basis, combined with the classification tree model, the framework and algorithm of behavior tree generation for multi-agent systems are designed to provide a basis for the subsequent research on the interpretability of multi-agent reinforcement learning.

Deep learning has been applied to transfer learning. This deep transfer learning is based on learning transferable deep adaptive networks as a framework to reduce distribution differences between domains. Existing domain adaptive methods cannot use simple domain distribution matching information, so they cannot always compensate the algorithm performance degradation caused by domain offset. In this paper, we propose a joint multi-order domain distribution difference method (JDD), which uses Gaussian kernel functions to jointly unify the multi-order saturation domain distribution difference information, thereby learning more domain-invariant features end-to-end and solving the problem more significantly cross-domain alignment issues. The JDD method can be applied to actual migration tasks and is easy to train and implement. Experiments show that our method has better classification accuracy than existing adaptive methods.

To solve the problem of small sample data transfer learning in aircraft environment experiments, we propose a joint multi-order domain distributed difference method (JMDD), which uses Gaussian kernel function to combine and unify the distribution difference information of multi-order saturated domain, so as to learn more domain invariant features end-to-end and solve the cross-domain alignment problem more significantly. The JMDD method can be applied to the actual migration task and is easy to train and implement. It is solved that the existing domain adaptive methods cannot use simple domain distribution matching information, so they cannot always compensate the performance degradation caused by domain migration. This method can be applied to the transfer learning process of small data samples. This kind of deep transfer learning is based on a deep adaptive network that can learn to migrate, which effectively reduces the distribution difference between domains and compensates for the performance degradation caused by domain migration. Experiments on common data sets show that our method has better classification accuracy than the existing adaptive methods.

In the UAV distribution center, the use of unmanned vehicles as the UAV carrier platform can perfectly compensate for the short time that UAVs are in the air, while saving manpower and material resources, autonomously completing navigation and obstacle avoidance in known environments, and at the same time. With human-computer interaction function, it provides target tracking ability, which greatly facilitates the centralized and distributed management of UAVs. In this paper, slam and yolo algorithms are utilized to implement automatic visual tracking of autonomous unmanned aerial vehicles (UAVs) and to achieve collaboration between UAVs and unmanned aerial vehicles (UAVs) in a known experimental environment.

The identification of malfunctions within the electronic load systems of spacecraft is a crucial component of the spacecraft’s predictive maintenance and health monitoring framework. For the purpose of real-time anomaly detection in these systems, it is imperative to swiftly and precisely discern intricate electrical signals. In the field of fault diagnosis, various data-driven methods, which are mainly based on machine learning, have been utilized for the signal classification task. However, the traditional machine methods consisted of feature extraction algorithms and classification algorithms may extract unrepresentative features and take a long time to run. In this paper, a one-dimensional convolutional neural networks (1D-CNN) based multi-label spacecraft electrical signal classification method is proposed. First, during the preprocessing stage, the one-dimensional signals are processed by wavelet denoising and segmented into equal length. Then, a well-designed 1D-CNN model is trained to classify the 19-class electrical signal. An average classification of 99.69% is achieved, while the test time is much shorter than traditional methods. Furthermore, to insight into the internal operation and behavior of the proposed 1D-CNN model, a visualization method for 1D-CNNs is suggested to analysis the behavior of each filter in the network, and the visualization results show that the filters in different convolutional layers exhibit different behavior characteristics.

This research introduces a hybrid tracking system that integrates the YOLO (You Only Look Once) and KCF (Kernelized Correlation Filter) algorithms for enhanced automatic tracking and human identification. The study, conducted at Beihang University, addresses the limitations of the KCF algorithm in handling device offset and target loss by utilizing YOLO for initialization and re-calibration. The Offset Error Rate (OER) serves as a metric to decide when YOLO should update the KCF tracking frame. The proposed method demonstrates improved tracking accuracy and robustness, with potential applications in autonomous navigation and obstacle avoidance for unmanned vehicles. Future work will focus on optimizing the YOLO structure and KCF algorithm for higher efficiency. The research is supported by various foundations, including the Chinese National Natural Science Foundation.

Through the comparative investigation of the existing research on the UAV distribution center these years, our group selected unmanned vehicles as the carrier for the UAV distribution, used to collect and transport the UAV, and at the same time carried out functional splitting for the application workflow, realized the autonomous navigation and obstacle avoidance of the UAV, the UAV mobile object landed, the unmanned vehicle autonomous navigation, the obstacle avoidance, mobile object recognition, tracking and gesture recognition a total of five main functional modules. In this paper, the two modules of autonomous navigation, obstacle avoidance, and object detection of unmanned vehicles in a simulation environment are introduced. In particular, the paper focuses on the experimental methods and results of AirSim-based autonomous vehicle self-driving simulation through Deep Reinforcement Learning under the UE4 engine, analyzes the simulation results and puts forward the corresponding optimization ideas, and introduces the object detection method and concrete implementation details based on YOLO algorithm. A more complete solution is provided for the unmanned vehicle part of the UAV distribution center management dilemma. From the simulation results, the Deep Q Network itself and simulation environment used in this paper are suitable for verification of unmanned vehicle control, through a certain period of training, the neural network could make stable decisions for unmanned vehicles reaching the destination in a specific indoor simulation environment. The verification of the unmanned vehicle provides a solid foundation for the implementation of the technologies in the UAV distribution center.

In order to accurately monitor human emotions during work, we develop a deep learning model based on electrocardiogram (ECG) data. First, we set up an ECG data acquisition system and generate standard data set. Second, a model combining convolutional neural network (CNN), Long Short-Term Memory (LSTM) and attention mechanism is used for training and testing. Finally, the recognition results are evaluated using evaluation metrics such as Precision, Recall and F1 Score. Experimental results show that the Precision of the model to identify abnormal emotional states is 85.48%, the Recall is 92.16%, and the F1 score is 88.68%. The development of this technology provides a new tool for emotional monitoring in workplace, which promises to improve productivity and safety through timely interventions.

Airship envelope material is the material used to manufacture the main structure of stratospheric airships and is one of the key technologies for stratospheric airships. Due to the special working environment of stratospheric airships, it is necessary to consider and study the impact of stratospheric environment on airship materials. This paper introduces the environmental characteristics of the stratosphere, analyzes the impact of environmental factors such as temperature, ozone, and ultraviolet radiation on the materials of stratospheric airship envelope materials, and conducts environmental adaptability design of airship materials. Through the analysis of the environment and the adaptive design of airship envelope materials, it is shown that the performance of airship materials in the stratospheric environment can be guaranteed through the structural design of the materials, and aging tests and evaluation systems can be used as input for design, improving the comprehensiveness of the design and serving as references for the design of stratospheric airship materials.

In order to improve the control performance of the underwater manipulator and significantly reduce drive torque required for joints, the problem that how to carry out whole arm neutral buoyancy design economically and efficiently is researched and solved. Methods Starting from the aspects of balancing goals, the selection of design schemes, load balancing, arm balancing, and joints balancing, an integrated shaping balancing method is proposed. Conclusion By combining methods such as virtual decoupling, adjusting the buoyancy center to match the center of gravity, virtual adjacent joint spaces, and integrated shaping process, buoyancy and gravity of each component are in equilibrium. Therefore, regardless of how the posture of the underwater manipulator changes, its buoyancy center and gravity center relative positions coincide and maintain the neutral buoyancy state. From balance design simulation, underwater component balance testing, to whole arm motion testing, the results all indicate that the balance method of wrapping buoyancy modules is effective, in line with economic and efficient principles, and achieves the excepted goals. The underwater manipulator has been put into use, with stable control performance and successfully completed the underwater support task during the construction period of the space station.

Aiming at the problems of unknown multi-dimensional innovative utilization mode of new energy agricultural equipment power supply, limited cross-domain efficiency and unclear benefit emergence prediction, based on the principle of system engineering, facing the scene of green cycle farm, the application mode of agricultural machinery power supply in production-living-ecology integration under the view of “Three-life” is analyzed. Innovative construction of power source cross-domain energy storage, energy dissipation, energy consumption and integration mode based on shared value, analysis of value network economic benefits, and put forward the implementation path of “one source and multiple uses” of new energy power system for agricultural equipment, help solve the problem of multi-dimensional development mode of new energy agricultural machinery modernization.

In the context of the increasingly serious traffic congestion, it will be an imperative research direction to enhance the interactive experience of cyclists in the cycling environment. By considering the situation in China, this paper analyzes the preference of cycling facility attributes and the characteristics of cyclists. A multivariate mixed logit model for cycling preference evaluation was established based on the questionnaire. And a quantitative method for solving the index weight is given by using the maximum likelihood estimation. The study can be applied to the planning and design of cycling environment, personalized cycling route recommendation and other directions, and provide a reference for similar preference evaluation research.

With the continuous improvement of the research on automotive intelligent and internet-connected technologies, the road test mileage of intelligent driving vehicles has increased. Active safety and intelligent driving performance testing and evaluation for vehicles are becoming more and more important. However, considering that the vehicle intelligent technology is not perfect enough, and the domestic and foreign related policies are delayed and the limitation of the testing area is not enough to carry out the evaluation of the performance advantages and disadvantages of intelligent vehicles in the whole area. Therefore, we follow the actual situation of China’s road traffic and conduct an open-road testing study of intelligent vehicle advanced assisted driving system (ADAS) with natural scenarios. This study is based on open road test scenarios, using high-precision positioning scene acquisition technology for testing and performance evaluation of vehicles equipped with intelligent systems. Based on the test results, the active safety and assisted driving technologies of domestic intelligent vehicles are analyzed and evaluated.

This study aims to utilize virtual reality technology to build a highly realistic metaverse battlefield based on Cesium for Unreal and Unreal Engine 5. By leveraging 3DGS rendering, Open-Sora 1.0 object-driven, and NLP multimodal interaction technologies, it achieves virtual reality multi-agent tactical confrontation decision-making deduction. The MADDPG algorithm demonstrates excellent performance in multi-agent confrontation tasks, with a win rate consistently above 95%. This research provides an efficient human-computer interaction interface (HCI) and immersive experience, holding significant application value for enhancing the tactical decision-making capabilities of military personnel.

With the development of technology, the application of manned/unmanned formation is becoming more widespread. When executing decision-making tasks, the officer has excessive work-load and slow speed. Therefore, there is an urgent need to develop human-machine function allocation strategies to improve decision-making efficiency. This study was based on the OODA loop theory and adopted the level of automation division method to set up multi-level schemes for four stages. Different schemes were combined to ensure that officer was in the loop. The strategies for completing decision-making tasks were generated, and a method for optimizing the human-machine function allocation strategy was established to achieve efficient decision-making in manned/unmanned formations.

Prognostics and Health Management (PHM) systems facilitate the efficient management and operation of mechanical equipment. Despite their importance, there has been limited research has focused on designing user interfaces for PHM systems. Digital twin technology offers new perspectives for PHM system implementation due to its real-time capabilities and virtual-physical consistency. This paper utilizes the Quality Function Deployment (QFD) method to translate technical terms into design terms. An interactive interface is designed, developed, and iteratively optimized using the wind turbine drivetrain test rig as the experimental object. Eye-tracking experiments are conducted to validate how different design elements affect user experience and information acquisition during the human-machine interaction process of digital twin-based PHM systems. Experimental results demonstrate that the rational optimization of interface design elements can improve the efficiency of human-computer interaction and the accuracy of information acquisition, which provides an important reference for the further improvement of the digital twin PHM system.

Based on the principles of ergonomics, analysis, and design were conducted on the dimensions, layout, and partitions of the self-service pickup units at Hohai University’s rookie stations. Research methods including the AEIOU observation method, in-depth interviews, and data collection were utilized to analyze the issues existing in the product dimensions, human-computer interaction methods, spatial layout, etc. Subsequently, design improvement proposals were put forward to reduce the occurrence of congestion during human-computer interaction. In addition, relevant design strategies are proposed.

While large display-based interaction has gained increasing popularity, its user experience is usually assessed by self-reporting measure and subject to bias. This study proposed an alternative approach by modeling user experience of large display-based interaction with physiological indicators and machine learning techniques. Twenty-four participants attended an experiment where they were asked to interact with a large display under varied body postures and interaction distances. Both self-reporting user experience (i.e., perceived usability and workload) and electromyography measures during task performance were collected and trained by three different machine learning models, out of which the best model could predict over 70% of the variance of user experience. Several electromyography measures were identified as effective indicators for user experience. The study demonstrates the feasibility of modeling user experience with physiological indicators and machine learning techniques in large display-based interaction.

In the activities of intelligent combat command and decision-making, the human-machine integration issue has become a key constraint affecting the improvement of command decision-making efficiency. This paper, based on the basic process of intelligent combat command and decision-making activities, explores the problems existing in the human-machine integration during the decision-making process. It conducts an in-depth analysis of the human-machine integration issues from the technical level, cognitive level, and rule system aspects, and studies strategies and methods to solve the human-machine integration problems. The research conclusions provide effective methods for solving human-machine integration issues in intelligent combat command and decision-making, offering theoretical references for enhancing the efficiency of intelligent combat command and decision-making.

：This paper explores the design of human-machine interfaces for combat task planning based on situational awareness theory. It first introduces the basic concepts and development of situational awareness theory, and analyzes the framework and elements of the interface of tactical-level combat task planning systems. Based on this, key points for designing human-machine interfaces for task planning based on situational awareness are proposed. These points aim to provide guidance for the design of task planning interfaces, making them more in line with task requirements, and improving the effectiveness and decision-making capabilities of commanders in combat.

This paper takes a cognitive psychology perspective, firstly analyzing the cognitive load issues in combat data visualization interfaces. Secondly, through methods of user experience and interview statistics, based on the cognitive load causal model, the cognitive load issues in combat data visualization interfaces are analyzed and summarized in terms of cognition and task aspects from the evaluation dimensions. Eleven relatively common factors are selected through frequency statistics, determining the cognitive load types corresponding to each factor, and assessing the cognitive load level of each factor through Paas scale scoring. Finally, based on the Balanced Cognitive Load Theory, five principles for the design of combat data visualization interfaces are proposed: hierarchical information display, simplified data presentation, clear chart meanings, mission-oriented design, and personalized customization for users.

The main control room of nuclear power plant is shifting from traditional analog control to advanced digital control. The iterative design of human-machine interface makes the presentation of the information diverse, and the cognitive behavior pattern of the operator changes accordingly. This study adopts the method of work domain analysis to sort out the information hierarchy of the second-loop interface of the nuclear power plant, clarifies the relationship between the purpose and means of each information element in the interface, analyzes the interface information demand and the information presentation mode based on the cognitive decision theory, builds the corresponding design principles for the optimal design of the digital interface, and assists the operator to make decisions by optimizing the presentation mode of the interface information.

To alleviate the workload of medical personnel and enhance the convenience of rapid thrombus detection for patients, this study designs and implements a self-service thrombus detection system based on the Jetson Nano platform. The system utilizes near-infrared light and an industrial camera to detect blood vessels in human forearm during disease diagnosis. This paper focuses on the human-computer interaction design of this system, enabling users to autonomously operate the detection system through scripting, allowing for tasks such as patient information collection and medical image acquisition via a single button. The research findings demonstrate that the system is stable, reliable, and user-friendly, meeting the demand for patient-initiated detection.

As the main control rooms of the new generation of nuclear power plants have fully implemented centralized, automated, and precise digital control systems, there is an inherent conflict between the vast amount of digital visual information and the operator’s limited cognitive processing capacity and attentional resources. Based on a survey of current research both domestically and internationally, this paper proposes the use of dynamic highlighting symbols to capture the operator’s attention, making the presentation of information in the digital human-machine interface of nuclear power plants more aligned with human cognitive and behavioral patterns. Psychological behavioral response experiments were conducted to support this proposition. The results indicate that dynamic highlighting symbols can effectively enhance the operator’s search and understanding efficiency, reduce cognitive load, and decrease the risk and likelihood of human errors. This, in turn, contributes to improving operational efficiency and human reliability in nuclear power plant operations.

In the context of monotonous highway driving, simulated experiments were carried out to evaluate various emergency takeover prompts for autonomous vehicles. A total of 30 participants (21 males, 9 females) were recruited, with an average age between 23 and 35 years (mean = 26.3, SD = 1.7) and an average driving experience of 3 to 10 years (mean = 4.2, SD = 1.3). EEG measurement technology was used to gather EEG signals and emotional characteristics, allowing the assessment of emotional changes in users under different takeover prompts. The results showed that in a monotonous highway driving environment, incorporating seat vibration with visual and auditory prompts could more quickly and effectively awaken drivers’ emotions. Hence, combining multiple prompting methods is more effective for supervising autonomous driving.

In order to reasonably assess the effectiveness of the existing AR-HUD interface indication icon design, a cognitive assessment method of interface icon based on EEG signals is proposed. It is found that there is a dominant relationship between different interface icons and the amplitude of N100, and the larger the amplitude, the higher the visual attention and attractiveness of the interface icon elements.

In-depth research on how to improve the thermal adaptation ability of special operations team members in desert environments is of great significance for enhancing their overall combat effectiveness Thermal adaptation refers to the natural adaptation and regulatory mechanisms of organisms to the thermal environment, which involves a series of complex biological physiological processes. However, cultivating the adaptability of special operations personnel in sustained high-temperature environments remains a challenge. This study adopts a literature review approach to establish a continuous systematic training program for thermal adaptation of cardiovascular function, to provide scientific and effective theoretical and practical support for physical training of special operations personnel in high-temperature environments such as deserts. At the same time, the research results are also expected to provide theoretical updates and methodological innovations for modern military training, thus promoting the scientific, standardized, and systematic training mode of special forces.

In order to quantify the degree of fatigue of oil and gas exploration workers in high-altitude special operation areas, based on the mature fatigue scale FASA, combined with the special low-oxygen operation environment at high altitude, and the fatigue scale for workers in the high-altitude oil and gas exploration industry was compiled. Field research was conducted by personnel of China National Petroleum Corporation (CNPC) and Oriental Geophysical Exploration Company Limited (OGE). Based on the field research conducted by the personnel of China National Petroleum Corporation (CNPC) and Oriental Geophysical Exploration Company Limited (OGECL), 102 valid samples of the pre-test scale and 512 valid samples of the formal scale were obtained. The validity of the scale was examined by Exploratory Factor Analysis (EFA), and the validity of the structure of the scale was examined by Confirmatory Factor Analysis (CFA). The results showed that the fatigue scale developed for high-altitude oil and gas exploration workers has good reliability and validity, and can effectively quantify the personal fatigue of high-altitude oil and gas exploration workers, and the formal scale consists of three dimensions (Physical fatigue, Mental fatigue, Situational fatigue) and 15 items.

Accurate prediction of the temperature drop in aircraft main landing gear brakes is crucial for improving aircraft landing safety and reducing aircraft turnaround time. A rapid method for verifying this temperature drop using computational fluid dynamics (CFD) and thermal equilibrium analysis is employed to investigate the environmental factors affecting the heat dissipation rate of brake discs in the air. A response surface model of the heat transfer coefficient of the brake disc is established, considering environmental factors such as brake disc temperature, air pressure, and external temperature. Dynamic simulations and modeling are conducted to analyze the variation in brake temperature drop throughout the entire process from takeoff to aircraft landing. Validation through multiple sets of flight test data indicates that the calculated brake temperature deviates from the measured temperature by no more than 10 ℃ throughout the flight process. This validates the accuracy and feasibility of the simulation model in predicting brake temperature before landing, providing a crucial reference for enhancing the reliability of aircraft design.

For thermal comfort assessment of three different cushion-lined tactical vests, sweating thermal manikin were employed to test the thermal resistance and evaporative resistance of the tactical vests, and the Heat Strain Decision Aid (HSDA) model was used to predict the core body temperatures and maximum working times at various work intensities in warm and humid as well as hot and dry conditions. The results indicated that the tactical vest with a polymer sponge cushion strip was more adaptable to warm and humid environments, the tactical vest with EVA compression film cushioned was more suitable for hot and dry environments, and the tactical vest with a strip fabric cushion layer had the longest maximum working time under all intensities and environments, proving to be the most adaptable to various conditions.

The project team conducted ergonomic experiments for multi-channel interactive input to analyze the effect of cabin lighting and noise environment on multi-modal interaction performance. The simulated experiment environment of the operator task was constructed, and the attention and physiological response of the subjects were compared in a typical scene of a special vehicle. Through the experimental analysis, the brightness change has an impact on the attention and physiological emergency of mechanical interaction, voice interaction and touch interaction. The attention and physiological emergency were the smallest in the moderate noise environment, and the attention and physiological stress were increased in the small and large noise environment. This study can provide experimental basis for vehicle man-machine control design.

This study analyzes the factors related to the internal design of train cars, including seating layout, door clear width, and the driver’s cab evacuation passage, and their impacts on passenger evacuation capability, with the aim of providing recommendations for reasonable subway train car design from the perspective of evacuation. The research results indicate that the seating layout and door clear width have significant impacts on evacuation. Simultaneously, when evacuating through the driver’s cab, the width of the evacuation passage affects the overall evacuation time.

The radar electronic shelter is the core equipment of the task execution, and it is an important place for human-computer interaction. How the cabin thermal environment affects the thermal comfort of human body has become a topic of concern in the experimental research of thermal environment design at present. Therefore, based on the environmental factors (temperature, wind speed) and personal factors (physiological, psychological, human skin temperature distribution) that affect human thermal comfort, this paper designs two kinds of human thermal comfort experiments (transient thermal comfort experiment and steady-state thermal comfort experiment) for experimental research on the influence of thermal environment on human thermal comfort. Through the experimental study, it can be seen that the existing thermal environment cannot meet the thermal comfort needs of operators, and it is necessary to improve the air supply parameters and the design of the air supply outlet. The experimental research in this paper can be applied to the thermal environment optimization of the control chamber to provide a more comfortable working environment for the operator.

The aim of this study is to simulate the cockpit vibration environment and explore the impact of vibration amplitude on the range of eye control errors under the fixed point task paradigm. Through experimental research, it was found that as the vibration amplitude increases, the range of eye control error increases; When the target gaze time is 0.5 s, the range of eye control error is the largest; The range of eye control error varies among different characters, and as the graphic area increases, the range of eye control error decreases. Therefore, when using eye control interaction design in fighter cockpit, the influence of vibration amplitude should be considered, and the optimal time for staring at the target should be set to 0.5 s, and the effective eye control range should be set according to the character size. The research results can provide reference suggestions for the application of eye controlled human–machine interaction in the vibration environment of fighter cockpit.

Temperature uniformity is a critical technical parameter in thermal vacuum testing. This study involves creating a geometric model of small-scale mixed refrigerant vacuum test equipment (SMRVTE) and using the steady-state thermal analysis module in Ansys Workbench to simulate temperature fields of various test products under different conditions. Concurrently, thermal vacuum tests were conducted under conditions identical to those in the simulation. The analysis revealed that the presence of heat sink openings adversely affects product temperature uniformity. Introducing copper plates coated with black paint to block the heat sink openings was found to enhance temperature uniformity during both heating and cooling processes. Based on these findings, recommendations are provided for conducting thermal vacuum tests using SMRVTE.

Aiming at the Safety of the Intended Functionality (SOTIF) of the Visual Landing System (VLS) in the nonlinear coupled operation scenario, a hazard analysis method combining fuzzy theory with Decision-Making Trial and Evaluation Laboratory (DEMATEL) is proposed. Firstly, this paper analyses the VLS’s function and system architecture and identifies the SOTIF causal factors associated with man-machine-environment. Subsequently, the Fuzzy-DMATEL method is employed to quantify the centrality and causality scores of each causal factor. Finally, the risk mitigation measures for key causal factors are given. The results show that the proposed method can effectively perform hazard analysis and overcome the ambiguity and uncertainty of expert evaluation, which provides a reference for the safety design of VLS.

(Purpose) The purpose of this paper is to improve the effectiveness of UAV reconnaissance operation by analyzing the formation cooperative operation composed of multi-function UAV. (Methods) In the process of writing this paper, the reconnaissance capability of single UAV and the cooperative reconnaissance capability of multi-function UAV are compared and analyzed. The conclusion is that single UAV’s payload is limited, and multi-function UAV can make up for its reconnaissance payload defect. (Results) Based on the research in this paper, the characteristics and operational application of multi-function UAV cooperative reconnaissance were analyzed, and the development trend of UAV cooperative reconnaissance in the future was summarized. (Conclusion) Theoretical research proves that multi-type UAV cooperative reconnaissance can make up for the disadvantages of single UAV reconnaissance, improve the effectiveness of UAV reconnaissance, and provide certain theoretical support for future UAV combat.

The purpose of this study is to explore how to better integrate man-machine in intelligent combat command to meet the needs of future intelligent combat command. The research method is to analyze the influence of artificial intelligence technology widely used in the military field to combat command, and find the new needs of combat command from the aspects of combat theory, command system, information system and command activities. The result of the research is to find out the changes in the combat command system, command mode and command means through the analysis. The research conclusion is that in the future, we should grasp the development direction of man-machine hybrid intelligence, correctly understand the man-machine advantages, and speed up the research of intelligent technology and intelligent combat command theory in the field of command.

Modern battlefields are changing rapidly and cannot be separated from the support of information. The rapid development of information technology has led and promoted profound changes in war form, combat ideology, power structure and combat mode. Information technology not only leads the military reform, but also promotes the transformation of combat effectiveness generation mode to information-led . Information has become an important support in the components of combat capability and plays a leading role. The core position, controlling effect and decisive role of “information-led” have become increasingly prominent. It is a great practical significance for winning future wars to deeply discuss the essential connotation, operational embodiment and implementation points of “information-led”.

Remote collaboration has become an important approach to assemble cross-temporal human resources to collaboratively solve problems for complex tasks in industrial production. Groupware systems are a significant factor affecting the efficiency of remote collaborative tasks. This study first surveyed the types of information shared and the needs for groupware interaction functionalities in remote collaboration for complex operational tasks. Secondly, integrating advanced human-computer interaction technologies, a method for visualizing user gaze points in a MR environment was proposed. Based on this, a design framework for a cognitive enhancement-oriented remote collaboration groupware application was constructed. Finally, case studies were conducted to verify the effectiveness of the proposed method in reducing cognitive load during collaborative processes and enhancing the usability of groupware systems.

By studying and analyzing the operational employment of unmanned aerial vehicle weapons and equipment in the Nagorno-Karabakh conflict, the article systematically summarizes the new characteristics of air raid operations. Through the introduction of Azerbaijan’s air raid forces and Armenia’s air defense forces, and the analysis of the technical and tactical application on both sides, it demonstrates the effectiveness of air raid and air defense operations on both sides in this local conflict, and focuses on systematically analyzing the distinctive characteristics of of using UAV to carry out air raid operations in the Nagorno-Karabakh conflict.

In the Russian-Ukrainian conflict, the Ukrainian army has achieved great results by using High Mobility Artillery Rocket System(HIMARS), reflecting the new features of future operations. The Russian army successfully intercepted HIMARS by using the Beech and other air defense missile systems and the multi-echelon configuration air defense system, which provided reference experience for countering the HIMARS operations. The effective countermeasures against HIMARS are put forward, which has certain reference value for the future combat against HIMARS.

This article provides a brief analysis of drone clusters by introducing the concept of drone clusters. Listed the development of drone cluster projects in several military developed countries and regions, extending to the combat style of drone clusters. By classifying and briefly analyzing the operational applications of existing foreign drone clusters, we can speculate on the future use of drone clusters under information technology conditions and their impact on the form of war. To predict and analyze the development trend of domestic drones based on this.

In recent years, the army has achieved remarkable results in the standardization of weapons and equipment and their operation and use, which has made a qualitative leap in the level of interconnection, interworking, interoperation and related technical support. However, there are many problems in the standardization of weapon and equipment safety management in the army, such as the lack of standardization management concept, the lack of understanding of standardization management, still based on experience management in safety management, and the lack of implementation of safety management standards of some military personnel. It is necessary to standardize the safety management of military weapons and equipment from the aspects of establishing the concept of standardized management, strengthening organizational leadership, doing a good job in planning and coordination, and strengthening training and education.

Human society is entering the era of intelligence, and the cognitive, interactive, and autonomous functions of intelligent agents are gradually increasing. Intelligent assistance is also gradually being applied in the aviation field. Aviation formation collaboration is one of the important combat methods in the future. However, existing drones are difficult to make accurate judgments and decisions independently, and cannot gain sufficient trust from operators during task execution, leading to frequent collaboration problems and negative impacts on work efficiency and mission results. At present, the mechanism of collaboration in aviation formations is still unclear, and higher levels of intelligence in aviation formations also need to be developed. This article starts with the transparency of information in aviation formation collaboration and elaborates on the impact of information transparency on aviation formation collaboration. In typical collaboration scenarios, an information transparency diagnosis system is established to timely discover the reasons for collaboration mismatch and provide solutions to improve collaboration efficiency and stability.

This essay proposes a digital twin interactive fusion architecture, which includes six elements: broad to use, fast to use, joint to use, stable to use, convenient to use and comfortable to use. The architecture realizes the complete integration of digital twin interaction through accurate virtual-real mapping, physical element collaboration, and virtual element linkage. The research aims to use this architecture to assist cognitive decision-making in the real world and to promote the close integration of digital twins and human-machine-environment. In the research process, the architecture was applied to the digital twin tea ceremony showcase system, which verified its effective fusion possibility and improved the intelligence level and interaction efficiency of the system. The conclusion shows that the proposed architecture is helpful in improving the comprehensive performance of digital twin technology in practical applications and indicates that it has a wide application prospect in many fields, such as intelligent manufacturing and smart cities in the future.

The comprehensive operational effectiveness evaluation of military mission can score the completion degree of the mission and provide reference for improving the execution of military mission. This study proposed a method for selecting key operational effectiveness indexes of military mission, decomposed military mission into operations through hierarchical analysis, selected equipment parameters that could reflect the completion degree of operations and task statistics index that reflect performance as key operational effectiveness indexes, and then proposed a comprehensive operational effectiveness evaluation method based on key effectiveness indicators to evaluate the comprehensive effectiveness of military missions. Finally, the method proposed in this paper is applied to extract key effectiveness indicators of air combat tasks, and a key operation effectiveness system including 22 parameters and 2 dimensions is constructed. Then the comprehensive effectiveness evaluation is carried out on the aircraft catapult-assisted take-off mission, indicating that the method is feasible for military mission effectiveness evaluation.

Simulation experiments precede combat, and experiments determine combat. Future warfare will no longer be a reproduction of history, but may be a reproduction of virtual battlefields in combat laboratories. For high-tech warfare under the conditions of informatization, due to factors such as venue, funding, and equipment, it is difficult for university laboratories to provide practical operation and exercise conditions that meet the needs of students. Virtual laboratories are not limited by the conditions of environment, venue, and real equipment, and can conduct collaborative experiments, making virtual laboratories an effective choice. This paper analyzes the Army air-defense forces equipment problems existing in the teaching, put forward the necessity of virtual laboratory construction is difficult, realized the function and structure, clear the air, the construction of the virtual laboratory should pay attention to the problem.

The purpose of this paper is to provide suggestions and references for the construction of army air-defense training evaluation laboratory. Firstly, from the aspects of training evaluation theory system construction, training evaluation method innovation and training development, the necessity of training evaluation laboratory construction of army air defense force is analyzed. Then, it puts forward the goal, principle and function of training evaluation laboratory construction, and plans the system structure and logical flow of the experiment platform according to the practice of training evaluation. On this basis, from the perspectives of enhancing practicability, interdisciplinary innovation and modularization of standards, some problems in laboratory construction are pointed out.

Objective Research on domestic and international technologies related to mixed reality and simultaneous motion simulation. Method National and international databases were used to search for 29 pieces of relevant literature. Result The analysis of the state of the art in kinematic analysis, the state of the art in control research, and the state of the art in mixed reality displays can be used to guide the modeling of small motion simulators. Conclusions The analog simulation flight platform built according to the kinematic inverse solution theory is small in size, low in cost, easy to maintain, and can either run alone through the upper computer software or linked with the flight simulation software.

The efficient operation of smart campuses is inseparable from good data governance, and data quality, as the core element of data governance, is crucial for the construction of smart campuses. Therefore, the article first designs a decision-making process framework based on feedback from the perspective of optimizing data quality, based on the smart service platform of colleges and universities; secondly, the article verifies the effectiveness of this framework in specific situations through simulation experiments, thereby verifying its feasibility; finally, the article proposes suggestions based on the conclusions of the experiments, hoping to contribute to the informatization development and smart campus construction of colleges and universities.

Radar electronic cabin is the main operation place for operators, and operators need to carry out various activities and operations in the cabin for a long time. Therefore, the evaluation and prediction of the thermal comfort of operators has become the premise for the design of the thermal environment in the cabin and the improvement of the efficient work of operators. Based on this, this paper studies the thermal comfort of operators of transient thermal environment, collect physiological parameters, psychological parameters and environmental parameters, use them as the index set of thermal comfort modeling, learn and train the index set data with BP neural network, establish the prediction model of human thermal comfort, compare the prediction results and obtain the correctness of the prediction model. The thermal comfort model established in this paper can be applied to the thermal comfort assessment and thermal environment optimization of radar electronic cabin operators.

The ship information display interface is an important medium for human-computer interaction. The presentation of information elements directly affects the process of perception, comprehension, and prediction, thereby influencing situation awareness (SA) of the crew. In order to analyze the relationship between SA and interface information elements more comprehensively, this study combined the process and outcome of SA to establish a theoretical model of SA based on information processing and cognitive activation state through qualitative analysis and quantitative calculation. To verify the validity of the model, twenty-three participants were recruited to conduct simulated maritime tasks in four different scenarios, and multi-dimensional data including task performance, scale, and eye movement were collected. The results of the correlation analysis presented high consistency between the prediction of SA model and the level of SA reflected by experimental data. The theoretical model of SA established in this study can be used for the ergonomic evaluation of interface design, thus optimizing the display interface in the ship system and improving the crew's SA.

UNESCO has listed psychology as one of the key disciplines for development and construction in the 21st century. Applied psychology is also a key area and hope for the development of psychology in the 21st century. Due to the widespread application of applied psychology in social life and its relationship with the healthy development and scientific status of psychology, the path and strategy of its development have attracted much attention in the field of psychology. This paper comprehensively elaborates on the historical mission that the applied psychology community should courageously undertake, from the research content of applied psychology and its relationship with theoretical psychology, the application fields of applied psychology, and the promotion of its application.

(Objective) Aiming at the typical air strikes by unmanned aerial vehicles (UAVs) in the recent Russian-Ukrainian conflict, this paper studies the possible threats and impacts of foreign military UAVs in future operations. (Methods) This article focuses on the operational characteristics of UAVs such as long endurance, low cost, and strong penetration capability, and adopts the illustrative method to sort out and summarize five main operational characteristics such as multi-dimensional reconnaissance and surveillance, and accurate and efficient firepower strikes. (Results) By combing and studying the possible threats of foreign military UAVs in future operations, it provides some reference for future anti-UAV operations. (Conclusion) Based on the frontier research of foreign military UAV operations by relevant scholars in recent years, this paper reflects the latest development trends of foreign military UAV operational application, and provides theoretical guidance for our military UAV and anti-UAV operations.

Subjective questionnaire surveys are one of the methodologies for identifying ergonomic issues. In response to previous shortcomings in survey comprehensiveness, user coverage, and in-depth data analysis, this study adopts a human-machine interaction framework to develop new questionnaires. A subjective survey was conducted among 24 individuals across different positions, yielding issues and suggestions related to operational control and other aspects of a specific complex system. This research offers fundamental data for the development of an ergonomic assessment index suite, as well as for subsequent design enhancements of complex systems.

The fundamental operational purpose of the nuclear power plant is the safe and effective generation of electricity keeping risk to the public, staff and the environment as low as reasonably practical. The concept of operations of advanced third-generation PWR Nuclear Power Plant is based on the existing second-generation nuclear power plant design, and puts forward the operation strategy and requirements for the overall operation goal of the third-generation nuclear power plant from the perspective of the top-level design of the power plant. It mainly includes the operation strategy under different operation modes of nuclear power plants, the operation strategy of human machine interface in control room, the working environment, the basic operation organization and the roles and responsibilities of operators. Good concept of operations can improve the level of plant safety control and monitoring in the control room, reduce the risk of human error of plant operators, promote the safe production of plants, and thus ensure nuclear safety.

For the safety and reliability of nuclear power plants (NPP), the design of NPP should meet the requirements of human factors engineering (HFE). Although HFE was considered in the design of NPP in the past, but mainly in the main control room, the consideration of HFE in the local area was scattered and random. The systematic and standardized consideration of HFE in local area was lacking, which also caused difficulties in the operation and maintenance of the local area in the NPP. Based on the relevant standards and codes, combined with the engineering practice of NPP projects, forms the local area HFE design guidelines from the aspects of workplace, human system interface, equipment layout, etc. and develops the HFE design process of the local area, and a set of technical system that can be applied to local human factors engineering design has been established. After being applied in the NPP projects, the compliance between local area design and human factors engineer improves, also the operability and maintainability of the nuclear power plants, and promotes the application of human factors engineering in local area design of nuclear power plants.

Human factors should be systematically considered and integrated throughout the entire process of retrofit activities for nuclear power plants (NPPs). Considering characteristics of the retrofit project, this study at the China Ningde NPPs developed a human factors engineering (HFE) plan suitable for the retrofit project, established a HFE management framework for NPP retrofit activities, and developed supporting work plans and management procedures to manage and control the retrofit process. This ensures that the human-machine interface after retrofitting conforms to ergonomic principles, thereby minimizing the risk of human errors, optimizing personnel efficiency, and ensuring NPP safe and efficient operating.

Decision making is the primary task of enterprise management. Breakeven analysis can provide sufficient support for decision-making and provide a more comprehensive understanding of the problems in enterprise management, and then propose corresponding solutions to improve work efficiency and productivity. Based on enterprise management, breakeven analysis incorporates variables such as cost, sales, profit, and output into the analysis framework and applies them to decision-making and forecasting in enterprise management. This article empirically verifies the correctness and rationality of the application of breakeven analysis in enterprise management.

Ergonomics is a highly experimental interdisciplinary subject, and vehicle design is its significant application scene. This paper highlights an innovative teaching experiment system aimed at optimizing human well-being and performance in automotive design. Specifically, the system integrates various experiments, including human body measurements, sensory and perceptual characteristics, human-machine interaction, environment measurement and automotive ergonomics into the course curriculum to bolster learning. Additionally, the system incorporates the latest research findings, including the evaluation of intelligent cockpit, to enrich the content. Undoubtedly, the experimental system elevates the effectiveness of the course.

In order to improve the single service mode and cumbersome operation of mobile shared charging stations for new energy vehicles, a mobile shared charging station for new energy vehicles based on service design theory is proposed. Using semi-structured interviews to acquire users’ product and service requirements, users’ product requirements are recovered through the user journey, combined with the FBS model to map the product requirements step by step. A model for the functional requirements of a new, the service mode design of a new shared energy vehicle charging station is designed based on the service design. The design of the service mode at mobile charging stations for new energy vehicles has confirmed the feasibility of the service design and provides ideas and guidance for the design and improvement of such products.