Risk identification and safety assessment of human-computer interaction in integrated avionics based on STAMP

To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction.This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling.The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework.We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions.By summarizing rescheduling rules,we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model.A series of numerical experiments are presented,demonstrating strong performance across the entire system.Furthermore,theflexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of humancomputer interactions in the previous step.This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions.It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.

Reform of Human-Computer Interaction Course based on Mobile Application Interaction Design

With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional Human-Computer Interaction(HCI)course and teaching material is out of date,it cannot meet the needs of mobile application interaction design and enterprises for students.Therefore,we need a new generation HCI course based on intelligent mobile devices to study the relationship between users and systems.The HCI course not only teaches students HCI theory and model,but also needs to cultivate students’interaction-oriented design practical ability.This paper proposes a set of HCI teaching material design and teaching methods for improving HCI class quality on mobile application interaction design,so as to make students more suitable for the employment requirements of enterprises.

Design and Implementation of the Image Interactive System Based on Human-Computer Interaction

Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.

Woven fabric triboelectric nanogenerators for human-computer interaction and physical health monitoring

Triboelectric nanogenerator(TENG)converts mechanical energy into valuable electrical energy,offering a solution for future energy needs.As an indispensable part of TENG,textile TENG(T-TENG)has incredible advantages in harvesting biomechanical energy and physiological signal monitoring.However,the application of T-TENG is restricted,partly because the fabric structure parameter and structure on T-TENG performance have not been fully exploited.This study comprehensively investigates the effect of weaving structure on fabric TENGs(F-TENGs)for direct-weaving yarn TENGs and post-coating fabric TENGs.For direct-weaving F-TENGs,a single-yarn TENG(Y-TENG)with a core-sheath structure is fabricated using conductive yarn as the core layer yarn and polytetrafluoroethylene(PTFE)filaments as the sheath yarn.Twelve fabrics with five different sets of parameters were designed and investigated.For post-coating F-TENGs,fabrics with weaving structures of plain,twill,satin,and reinforced twill were fabricated and coated with conductive silver paint.Overall,the twill F-TENGs have the best electrical outputs,followed by the satin F-TENGs and plain weave F-TENGs.Besides,the increase of the Y-TENG gap spacing was demonstrated to improve the electrical output performance.Moreover,T-TENGs are demonstrated for human-computer interaction and self-powered real-time monitoring.This systematic work provides guidance for the future T-TENG’s design.

An Interactive Fuzzy Satisficing Method for Multiobjective Stochastic Integer Programming with Simple Recourse

This paper considers multiobjective integer programming problems involving random variables in constraints. Using the concept of simple recourse, the formulated multiobjective stochastic simple recourse problems are transformed into deterministic ones. For solving transformed deterministic problems efficiently, we also introduce genetic algorithms with double strings for nonlinear integer programming problems. Taking into account vagueness of judgments of the decision maker, an interactive fuzzy satisficing method is presented. In the proposed interactive method, after determineing the fuzzy goals of the decision maker, a satisficing solution for the decision maker is derived efficiently by updating the reference membership levels of the decision maker. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method.

Interactive Fuzzy Programming for Random Fuzzy Two-Level Integer Programming Problems through Fractile Criteria with Possibility

This paper considers two-level integer programming problems involving random fuzzy variables with cooperative behavior of the decision makers. Considering the probabilities that the decision makers’ objective function values are smaller than or equal to target variables, fuzzy goals of the decision makers are introduced. Using the fractile criteria to optimize the target variables under the condition that the degrees of possibility with respect to the attained probabilities are greater than or equal to certain permissible levels, the original random fuzzy two-level integer programming problems are reduced to deterministic ones. Through the introduction of genetic algorithms with double strings for nonlinear integer programming problems, interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented. An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method.

RGxE: An R Program for Genotype x Environment Interaction Analysis

Genotype x environmental interaction (GxE) can lead to differences in performance of genotypes over environments. GxE analysis can be used to analyze the stability of genotypes and the value of test locations. We developed an Rlanguage program (RGxE) that computes univariate stability statistics, descriptive statistics, pooled ANOVA, genotype F ratio across location and environment, cluster analysis for location, and location correlation with average location performance. Univariate stability statistics calculated are regression slope (bi), deviation from regression (S2d), Shukla’s variance (σi2), S square Wricke’s ecovalence (Wi), and Kang’s yield stability (YSi). RGxE is free and intended for use by scientists studying performance of polygenic or quantitative traits over multiple environments. In the present paper we provide the RGxE program and its components along with an example input data and outputs. Additionally, the RGxE program along with associated files is also available on GitHub at https://github.com/mahendra1/RGxE, http://cucurbitbreeding.com/todd-wehner/publications/software-sas-r-project/? and http://cuke.hort.ncsu.edu/cucurbit/wehner/software.html.

A New Interactive Method to Solve Multiobjective Linear Programming Problems

Multiobjective Programming (MOP) has become famous among many researchers due to more practical and realistic applications. A lot of methods have been proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP by starting from a utopian point, which is usually infeasible, and moving towards the feasible region via stepwise movements and a simple continuous interaction with decision maker. We consider the case where all objective functions and constraints are linear. The implementation of the pro-posed algorithm is demonstrated by two numerical examples.

Efficient Graph-based Genetic Programming Representation with Multiple Outputs

In this work, we explore and study the implication of having more than one output on a genetic programming （GP） graph-representation. This approach, called multiple interactive outputs in a single tree （MIOST）, is based on two ideas. First, we defined an approach, called interactivity within an individual （IWI）, which is based on a graph-GP representation. Second, we add to the individuals created with the IWI approach multiple outputs in their structures and as a result of this, we have MIOST. As a first step, we analyze the effects of IWI by using only mutations and analyze its implications （i.e., presence of neutrality）. Then, we continue testing the effectiveness of IWI by allowing mutations and the standard GP crossover in the evolutionary process. Finally, we tested the effectiveness of MIOST by using mutations and crossover and conducted extensive empirical results on different evolvable problems of different complexity taken from the literature. The results reported in this paper indicate that the proposed approach has a better overall performance in terms of consistency reaching feasible solutions.

Multi-View Multi-Modal Head-Gaze Estimation for Advanced Indoor User Interaction

Gaze estimation is one of the most promising technologies for supporting indoor monitoring and interaction systems.However,previous gaze estimation techniques generally work only in a controlled laboratory environment because they require a number of high-resolution eye images.This makes them unsuitable for welfare and healthcare facilities with the following challenging characteristics:1)users’continuous movements,2)various lighting conditions,and 3)a limited amount of available data.To address these issues,we introduce a multi-view multi-modal head-gaze estimation system that translates the user’s head orientation into the gaze direction.The proposed system captures the user using multiple cameras with depth and infrared modalities to train more robust gaze estimators under the aforementioned conditions.To this end,we implemented a deep learning pipeline that can handle different types and combinations of data.The proposed system was evaluated using the data collected from 10 volunteer participants to analyze how the use of single/multiple cameras and modalities affect the performance of head-gaze estimators.Through various experiments,we found that 1)an infrared-modality provides more useful features than a depth-modality,2)multi-view multi-modal approaches provide better accuracy than singleview single-modal approaches,and 3)the proposed estimators achieve a high inference efficiency that can be used in real-time applications.

Empathic Responses of Behavioral-Synchronization in Human-Agent Interaction

Artificial entities,such as virtual agents,have become more pervasive.Their long-term presence among humans requires the virtual agent’s ability to express appropriate emotions to elicit the necessary empathy from the users.Affective empathy involves behavioral mimicry,a synchronized co-movement between dyadic pairs.However,the characteristics of such synchrony between humans and virtual agents remain unclear in empathic interactions.Our study evaluates the participant’s behavioral synchronization when a virtual agent exhibits an emotional expression congruent with the emotional context through facial expressions,behavioral gestures,and voice.Participants viewed an emotion-eliciting video stimulus(negative or positive)with a virtual agent.The participants then conversed with the virtual agent about the video,such as how the participant felt about the content.The virtual agent expressed emotions congruent with the video or neutral emotion during the dialog.The participants’facial expressions,such as the facial expressive intensity and facial muscle movement,were measured during the dialog using a camera.The results showed the participants’significant behavioral synchronization(i.e.,cosine similarity≥.05)in both the negative and positive emotion conditions,evident in the participant’s facial mimicry with the virtual agent.Additionally,the participants’facial expressions,both movement and intensity,were significantly stronger in the emotional virtual agent than in the neutral virtual agent.In particular,we found that the facial muscle intensity of AU45(Blink)is an effective index to assess the participant’s synchronization that differs by the individual’s empathic capability(low,mid,high).Based on the results,we suggest an appraisal criterion to provide empirical conditions to validate empathic interaction based on the facial expression measures.

Design of space-centered interaction using invisible and intangible spatial inputs

In this paper,we investigate methodologies to improve direct-touch interaction on invisible and intangible spatial input.We firstly discuss about the motive of looking for a new input method for whole body interaction and how it can be meaningful.We also describe the role that can play spatial interaction to improve the freedom of interaction for a user.We propose a method of spatial centered interaction using invisible and intangible spatial inputs.However,given their lack of tactile feedback and visual representation,direct touch interaction on such input can be confused.In order to make a step toward understanding causes and solutions for such phenomena,we made 2 user experiments.In the first one,we test 5 setups of helper that provide information of the location of the input by constraining the dimension it is located at.The results show that using marker on the ground and a relationship with the height of the user’s body improve significantly the locative task.In the second experiment,we create a dancing game using invisible and intangible spatial inputs and we stress the results obtained in the first experiment within this cognitively demanding context.Results show that the same setup of helper is still providing very good results in that context.

Modeling and Simulation for High Energy Sub-Nuclear Interactions Using Evolutionary Computation Technique

High energy sub-nuclear interactions are a good tool to dive deeply in the core of the particles to recognize their structures and the forces governed. The current article focuses on using one of the evolutionary computation techniques, the so-called genetic programming (GP), to model the hadron nucleus (h-A) interactions through discovering functions. In this article, GP is used to simulate the rapidity distribution of total charged, positive and negative pions for p--Ar and p--Xe interactions at 200 GeV/c and charged particles for p-pb collision at 5.02 TeV. We have done so many runs to select the best runs of the GP program and finally obtained the rapidity distribution as a function of the lab momentum , mass number (A) and the number of particles per unit solid angle (Y). In all cases studied, we compared our seven discovered functions produced by GP technique with the corresponding experimental data and the excellent matching was so clear.

Towards Sensor-free Academic Emotion Prediction in Programming Environment

he transition from traditional learning to practice-oriented programming learning will bring learners discomfort.The discomfort quickly breeds negative emotions when encountering programming difficulties,which leads the learner to lose interest in programming or even give up.Emotion plays a crucial role in learning.Educational psychology research shows that positive emotion can promote learning performance,increase learning interest and cultivate creative thinking.Accurate recognition and interpretation of programming learners’emotions can give them feedback in time,and adjust teaching strategies accurately and individually,which is of considerable significance to improve effects of programming learning and education.The existing methods of sensor-free emotion prediction include emotion prediction based on keyboard dynamic,mouse interaction data and interaction logs,respectively.However,none of the three studies considered the temporal characteristics of emotion,resulting in low recognition accuracy.For the first time,this paper proposes an emotion prediction model based on time series and context information.Then,we establish a Bi-recurrent neural network,obtain the time sequence characteristics of data automatically,and explore the application of deep learning in the field of Academic Emotion prediction.The results show that the classification ability of this model is much better than that of the original LSTM(Long-Short Term Memory),GRU(Gate Recurrent Unit)and RNN(Re-current Neural Network),and this model has better generalization ability.

Designing interactive glazing through an engineering psychology approach:Six augmented reality scenarios that envision future car human-machine interface

Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Several studies have addressed car HMI but were less attentive to designing and implementing interactive glazing for every day(autonomous)driving contexts.Methods Reflecting on the literature,we describe an engineering psychology practice and the design of six novel future user scenarios,which envision the application of a specific set of augmented reality(AR)support user interactions.Additionally,we conduct evaluations on specific scenarios and experiential prototypes,which reveal that these AR scenarios aid the target user groups in experiencing a new type of interaction.The overall evaluation is positive with valuable assessment results and suggestions.Conclusions This study can interest applied psychology educators who aspire to teach how AR can be operationalized in a human-centered design process to students with minimal pre-existing expertise or minimal scientific knowledge in engineering psychology.

不同结对编程策略对小学生学习效果影响的比较研究

结对编程是一种以协作方式学习编程的教学策略,该研究将结对编程与单独编程相结合,构成混合结对编程策略,采用准实验研究法,从编程总评成绩、结对融洽度、结对互动话语等方面,探究混合结对编程和常规结对编程两种策略对小学生学习编程效果影响的差异。实验结果表明,混合结对编程策略能够增进结对伙伴之间的融洽度,促进学生之间的积极互动,提高小学生的编程能力。教师应正确认识结对编程与单独编程的价值,通过组合应用,提高编程教学实效。

大语言模型驱动的交互式建筑设计新范式——基于Rhino7的概念验证

随着社会对建筑设计质量要求越来越高,建筑设计软件也变得越来越专业和复杂。现在的设计软件不仅学习成本高,而且交互模式复杂。大语言模型(LLM)的最新突破使计算机清晰地理解人类自然语言指令,并准确生成代码语言具有可行性,有望为人与软件的交互范式提供新思路。因此,本文提出了LLM驱动的交互式建筑设计新范式--将设计师通过多次键鼠操作与设计软件交互转变为LLM根据设计师自然语言指令生成并执行API调用脚本的方式;提出了技术路线并验证了其在建筑设计场景落地的可能性。该技术路线包括:①LLM根据用户指令从API库中搜索与任务相关的API;②LLM基于指令和候选API摘要信息编写程序脚本并运行;③LLM根据来自软件环境、用户等反馈改进优化所编写的程序脚本。通过Rhino7设计软件、GPT-4和CodeLlaMa完成多个设计任务,测试当前LLM是否具备执行该技术路线各关键环节的能力。测试结果不仅证明了LLM驱动的交互式设计范式在建筑设计场景已初具落地前景,也为技术落地提供经验和建议。该设计范式的落地可以降低软件的使用门槛和学习成本,提高设计师工作效率;有望在未来的建筑设计软件中发挥重要作用。

临床实践前课程线上教学效果及影响因素分析

探究北京协和医学院八年制临床实践前课程线上与线下教学效果的差异及影响因素。妇产科学、皮肤性病学和口腔科学的线上教学成绩显著低于线下,儿科学、神经病学、眼科学、耳鼻咽喉学和中医学线上教学成绩显著高于线下。互动可显著提高线上教学效果。线上教学可以作为临床实践前部分课程的有效教学方式。