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.

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.

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.

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.

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.

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.

Research on the Interactive Interpreting Teaching Mode under the Multimedia and Traditional Microteaching Environment

In this paper, we conduct research on the interactive interpreting teaching mode under the multimedia and primary traditional microteaching environment. English interpretation course system construction request from the student reality, on the basis of the actual situation, improving students＇ comprehensive ability in English interpretation as communicative teaching method in the very great degree to overall effective guide students to practice real interpreting scene comprehensively improve students＇ intercultural business negotiation, reception and comprehensive ability of the exhibition, and is advantageous to the interpretation of curriculum system construction and the improvement of the students＇ comprehensive quality. Our research integrates the general principles of the multimedia and primary traditional microteaching environment to form the better paradigm for the education that will enhance the contemporary teaching condition.

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.

Mixed Reality-based Interactive Technology for Aircraft Cabin Assembly

Due to the narrowness of space and the complexity of structure, the assembly of aircraft cabin has become one of the major bottlenecks in the whole manufacturing process. To solve the problem, at the beginning of aircraft design, the different stages of the lifecycle of aircraft must be thought about, which include the trial manufacture, assembly, maintenance, recycling and destruction of the product. Recently, thanks to the development of the virtual reality and augmented reality, some low-cost and fast solutions are found for the product assembly. This paper presents a mixed reality-based interactive technology for the aircraft cabin assembly, which can enhance the efficiency of the assemblage in a virtual environment in terms of vision, information and operation. In the mixed reality-based assembly environment, the physical scene can be obtained by a camera and then generated by a computer. The virtual parts, the features of visual assembly, the navigation information, the physical parts and the physical assembly environment will be mixed and presented in the same assembly scene. The mixed or the augmented information will provide some assembling information as a detailed assembly instruction in the mixed reality-based assembly environment. Constraint proxy and its match rules help to reconstruct and visualize the restriction relationship among different parts, and to avoid the complex calculation of constraint＇s match. Finally, a desktop prototype system of virtual assembly has been built to assist the assembly verification and training with the virtual hand.

Three-dimensional visualization interactive system for digital twin workshop

To improve the human-physical-virtual coordination and integration of the digital twin workshop,3D visual monitoring and human-computer interaction of the digital twin workshop was studied.First,a novel 6D model of the 3D visualization interactive system for digital twin workshops is proposed.As the traditional 5D digital twin model ignores the importance of human-computer interaction,a new dimension of the user terminal was added.A hierarchical real-time data-driven mapping model for the workshop production process is then proposed.Moreover,a real-time data acquisition method for the industrial Internet of things is proposed based on OPC UA(object linking and embedding for process control unified architecture).Based on the 6D model of the system,the process of creating a 3D visualization virtual environment based on virtual reality is introduced,in addition to a data-driven process based on the data management cloud platform.Finally,the 6D model of the system was confirmed using the blade rotor test workshop as the object,and a 3D visualization interactive system is developed.The results show that the system is more transparent,real-time,data-driven and more efficient,as well as promotes the coordination and integration of human-physical-virtual,which has practical significance for developing digital twin workshops.

强化学习的可解释方法分类研究

强化学习能够在动态复杂环境中实现自主学习,这使其在法律、医学、金融等领域有着广泛应用。但强化学习仍面临着全局状态空间不可观测、对奖励函数强依赖和因果关系不确定等诸多问题,导致其可解释性弱,严重影响其在相关领域的推广,会遭遇诸如难以判断决策是否违反社会法律道德的要求,是否准确及值得信任等的限制。为了进一步了解强化学习可解释性研究现状,从可解释模型、可解释策略、环境交互、可视化等方面展开讨论。基于此,对强化学习可解释性研究现状进行系统论述,对其可解释方法进行归类阐述,最后提出强化学习可解释性的未来发展方向。

用者为本,技之大道--评《以口译员为中心的技术可用性研究:以SmarTerp为例》

在口译学科“技术转向”的时代背景下,口译技术人性化和可持续发展的重要性日益凸显。《以口译员为中心的技术可用性研究:以SmarTerp为例》一书立足时代需求,介绍了全球首项使用可用性工程方法开发计算机辅助口译工具的案例研究,旨在反映口译领域技术变革,确保口译技术的公平可持续发展。该书通过采用人机交互的理论框架和方法论框架评估计算机辅助口译工具SmarTerp界面的可用性,弥补了当前计算机辅助口译实证研究的不足,对口译技术的研发和应用具有重要的启发意义和借鉴价值。

面向心律失常疾病的临床决策支持系统交互性研究与实现

目的/意义针对当前临床决策支持系统使用过程中存在的问题,提出界面设计原则并将其应用于心律失常疾病临床决策支持系统建设中。方法/过程从交互设计角度,针对可解释性、时效性、可用性、相关性、尊重性和循证性6个维度,提出界面设计原则。选取心律失常疾病决策支持作为临床场景,设计临床决策支持系统交互界面原型,阐述界面功能、信息功能、交互功能设计与实现过程。结果/结论本研究提出的界面设计原则可有效缓解6类问题,经论证具有应用于心律失常疾病临床决策支持原型系统的可行性以及可泛化性,可用于指导多种疾病辅助诊疗工具的交互设计。

面向任务的载人深潜人机交互信息重要度评估

为更好地识别复杂任务环境下深海载人潜水器驾驶舱人机交互信息重要度差异,提出一种基于复杂网络的人机交互信息重要度评估方法。以悬停采样任务为研究对象,运用决策阶梯模型及任务-网络建模技术识别复杂任务相关人机交互信息元及逻辑关联,构建交互信息复杂网络模型。基于网络拓扑特征参数,从节点间逻辑影响关系的角度提出节点全局及局部影响效应评估指标,结合解释结构模型层级权重指标对交互信息节点重要度综合值进行计算,得出悬停采样任务人机交互信息重要度排序。将排序结果与其他4种算法进行对比,在证明计算有效的基础上,邀请潜航员结合实际任务流程对交互信息进行主观重要度评估。结果显示,研究所得重要度排序结果与潜航员主观排序结果呈强相关,且对重要交互信息元的识别结果与潜航员主观感知相符合,验证了所提方法识别复杂任务人机交互信息重要度差异的有效性。

社会主义核心价值观融入法学专业课程的价值、作用与路径

社会主义核心价值观融入法学专业课程,既是新时代培养德法兼修的卓越法治人才的内在要求,也是深入推进法治中国建设的外在需求。社会主义核心价值观继承了中华优秀传统文化,践行了习近平法治思想,为培养新时代德法兼修的卓越法治人才奠定了优良的价值基础。社会主义核心价值观与法学专业课程的教学目标高度契合,法学教师可以从理论、实践双层面实现社会主义核心价值观浸润式融入法学专业课程,并通过多维度评价机制实现对学生的考核反馈,形成社会主义核心价值观与法学专业课程的相互作用,培养出社会主义核心价值观的合格践行者。

人智交互情境下的知识转化模型:内涵深化及外延拓展

[目的/意义]交互式人工智能时代下,机器对信息的处理达到人类难以触及的新高度,暗知识的产生对知识管理提出了新的要求,知识转化模型(SECI Model)已经难以诠释交互式人工智能时代知识管理的内涵及外延,亟须拓展更新以适应技术发展的新要求。[方法/过程]首先回顾SECI模型以及场(Ba)理论的发展沿革,随后结合人智交互特征讨论了知识管理的内涵与外延以及知识转化过程的拓展与变革,对知识管理模型进行进一步的思考与总结,并针对暗知识与显性知识相互转化的过程提出发展进路。[结果/结论]在SECI模型的基础上提出了人智交互情境下新的知识转化模型(T-E-D Model)。提出显性知识是人智交互中暗知识与隐性知识链接的桥梁,暗知识与显性知识的转化是知识管理新情境下的关键,需要从基础设施、过程管理、个性化设计以及标准制定4个方面推进暗知识转化的质量与效率。[局限]所提出理论模型仅建立在交互式人工智能作为认知主体的语境下,而AI能否作为独立于人脑外的认知主体还需进一步的伦理探索。

Interpretability of Neural Networks Based on Game-theoretic Interactions

This paper introduces the system of game-theoretic interactions,which connects both the explanation of knowledge encoded in a deep neural networks(DNN)and the explanation of the representation power of a DNN.In this system,we define two gametheoretic interaction indexes,namely the multi-order interaction and the multivariate interaction.More crucially,we use these interaction indexes to explain feature representations encoded in a DNN from the following four aspects:(1)Quantifying knowledge concepts encoded by a DNN;(2)Exploring how a DNN encodes visual concepts,and extracting prototypical concepts encoded in the DNN;(3)Learning optimal baseline values for the Shapley value,and providing a unified perspective to compare fourteen different attribution methods;(4)Theoretically explaining the representation bottleneck of DNNs.Furthermore,we prove the relationship between the interaction encoded in a DNN and the representation power of a DNN(e.g.,generalization power,adversarial transferability,and adversarial robustness).In this way,game-theoretic interactions successfully bridge the gap between“the explanation of knowledge concepts encoded in a DNN”and"the explanation of the representation capacity of a DNN"as a unified explanation.

VisCI:A visualization framework for anomaly detection and interactive optimization of composite index

Composite index is always derived with the weighted aggregation of hierarchical components,which is widely utilized to distill intricate and multidimensional matters in economic and business statistics.However,the composite indices always present inevitable anomalies at different levels oriented from the calculation and expression processes of hierarchical components,thereby impairing the precise depiction of specific economic issues.In this paper,we propose VisCI,a visualization framework for anomaly detection and interactive optimization of composite index.First,LSTM-AE model is performed to detect anomalies from the lower level to the higher level of the composite index.Then,a comprehensive array of visual cues is designed to visualize anomalies,such as hierarchy and anomaly visualization.In addition,an interactive operation is provided to ensure accurate and efficient index optimization,mitigating the adverse impact of anomalies on index calculation and representation.Finally,we implement a visualization framework with interactive interfaces,facilitating both anomaly detection and intuitive composite index optimization.Case studies based on real-world datasets and expert interviews are conducted to demonstrate the effectiveness of our VisCI in commodity index anomaly exploration and anomaly optimization.

Optimization and Performance Enhancement of Gesture Recognition Algorithm Based on FMCW Millimeter-Wave Radar

Gesture recognition plays an increasingly important role as the requirements of intelligent systems for human-computer interaction methods increase.To improve the accuracy of the millimeter-wave radar gesture detection algorithm with limited computational resources,this study improves the detection performance in terms of optimized features and interference filtering.The accuracy of the algorithm is improved by refining the combination of gesture features using a self-constructed dataset,and biometric filtering is introduced to reduce the interference of inanimate object motion.Finally,experiments demonstrate the effectiveness of the proposed algorithm in both mitigating interference from inanimate objects and accurately recognizing gestures.Results show a notable 93.29%average reduction in false detections achieved through the integration of biometric filtering into the algorithm’s interpretation of target movements.Additionally,the algorithm adeptly identifies the six gestures with an average accuracy of 96.84%on embedded systems.

Multiscale Feature Fusion for Gesture Recognition Using Commodity Millimeter-Wave Radar

Gestures are one of the most natural and intuitive approach for human-computer interaction.Compared with traditional camera-based or wearable sensors-based solutions,gesture recognition using the millimeter wave radar has attracted growing attention for its characteristics of contact-free,privacy-preserving and less environmentdependence.Although there have been many recent studies on hand gesture recognition,the existing hand gesture recognition methods still have recognition accuracy and generalization ability shortcomings in shortrange applications.In this paper,we present a hand gesture recognition method named multiscale feature fusion(MSFF)to accurately identify micro hand gestures.In MSFF,not only the overall action recognition of the palm but also the subtle movements of the fingers are taken into account.Specifically,we adopt hand gesture multiangle Doppler-time and gesture trajectory range-angle map multi-feature fusion to comprehensively extract hand gesture features and fuse high-level deep neural networks to make it pay more attention to subtle finger movements.We evaluate the proposed method using data collected from 10 users and our proposed solution achieves an average recognition accuracy of 99.7%.Extensive experiments on a public mmWave gesture dataset demonstrate the superior effectiveness of the proposed system.