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.

Investigation on behavior of crack penetration/deflection at interfaces in intelligent coating system

Based on the three-phase model, the propagation behavior of a matrix crack in an intelligent coating system is investigated by an energy criterion. The effect of the elastic mismatch parameters and the thickness of the interface layer on the ratio of the energy release rate for infinitesimal deflected and penetrated crack is evaluated with the finite element method. The results show that the ratio of the energy release rates strongly depends on the elastic mismatch al between the substrate and the driving layer. It also strongly depends on the elastic mismatch a2 between the driving layer and the sensing layer for a thinner driving layer when a primary crack reaches an interface between the substrate and the driving layer. Moreover, with the increase in the thickness of the driving layer, the dependence on a2 gradually decreases. The experimental observation on aluminum alloys monitored with intelligent coating shows that the established model can better explain the behavior of matrix crack penetration and can be used in optimization design of intelligent coating.

Web GIS Human-Machine Interactive Interface Design with VISI

The fusion of VlSI （visual identity system Internet）, digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, elements and contents for the Web GIS. The design of the Wuhan Bus Search System is fulfilled to confirm the validity and practicability of the fusion.

Intelligent Interfaces: Pedagogical Agents and Virtual Humans

Little by little, we are entering the new era, intelligent interfaces are absorbing us more and more every day, and artificial intelligence makes its presence in a stealthy way. Virtual humans that represent an evolution of autonomous virtual agents;they are computer programs and in the future capable of carrying out different activities in certain environments. They will give the illusion of being human;they will have a body, and they will be immersed in an environment. They will have a set of senses that will allow them: 1) Sensations and therefore associated expressions;2) Communication;3) Learning;4) Remembering events, among others. By integrating the above, they will have a personality and autonomy, so they will be able to plan with respect to objectives;allowing them to decide and take actions with their body, in other words, they will count on awareness. The applications will be focused on environments that they will inhabit, or as interfaces that will interact with other systems. The application domains will be multiple;one of them being education. This article shows the design of OANNA like an avatar with the role of pedagogical agent. It was modeled as an affective-cognitive structure related to the teaching-learning process linked to a pedagogical agent that represents the interface of an artilect. OANNA, has the necessary animations for intervention within the teaching-learning process.

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.

Human-Machine Shared Lateral Control Strategy for Intelligent Vehicles Based on Human Driver Risk Perception Reliability

Intelligent vehicle(Ⅳ)technology has developed rapidly in recent years.However,achieving fully unmanned driving still presents numerous challenges,which means that human drivers will continue to play a vital role in vehicle operation for the foreseeable future.Human-machine shared driving,involving cooperation between a human driver and an automated driving system(AVS),has been widely regarded as a necessary stage for the development of IVs.Focusing onⅣdriving safety,this study proposed a human-machine shared lateral control strategy(HSLCS)based on the reliability of driver risk perception.The HSLCS starts by identifying the effective areas of driver risk perception based on eye movements.It establishes an anisotropic driving risk field,which serves as the foundation for the AVS to assess risk levels.Building upon the cumulative and diminishing effects of risk perception,the proposed approach leverages the driver's risk perception effective area and converts the risk field into a representation aligned with the driver's perspective.Subsequently,it quantifies the reliability of the driver's risk perception by using area-matching rules.Finally,based on the driver’s risk perception reliability and dif-ferences in lateral driving operation between the human driver and the AVS,the dynamic distribution of driving authority is achieved through a fuzzy rule-based system,and the human-machine shared lateral control is completed by using model predictive control.The HSLCS was tested across various scenarios on a driver-in-the-loop test platform.The results show that the HSLCS can realize the synergy and complementarity of human and machine intelligence,effectively ensuring the safety ofⅣoperation.

Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control

With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.

Artificial intelligence for the understanding of electrolyte chemistry and electrode interface in lithium battery

Recognizing the critical role of electrolyte chemistry and electrode interfaces in the performance and safety of lithium batteries,along with the urgent need for more sophisticated methods of analysis,this comprehensive review underscores the promise of machine learning(ML)models in this research field.It explores the application of these innovative methods to studying battery interfaces,particularly focusing on lithium metal anodes.Amid the limitations of traditional experimental techniques,the review supports a hybrid approach that couples experimental and simulation methods,enabling granular insights into the formation process and characteristics of battery interfaces at the molecular level and harnessing AI to extract patterns from voluminous data sets.It showcases the utility of such techniques in electrolyte design and battery life prediction and introduces a novel perspective on battery interface mechanisms.The review concludes by asserting the potential of artificial intelligence(AI)or ML models as invaluable tools in the future of battery research and highlights the importance of fostering confidence in these technologies within the scientific community.

Fully Fabric-Based Triboelectric Nanogenerators as Self-Powered Human-Machine Interactive Keyboards

Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator(F-TENG)with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication.The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves.A self-powered wearable keyboard(SPWK)is also fabricated by integrating large-area F-TENG sensor arrays,which not only can trace and record electrophysiological signals,but also can identify individuals’typing characteristics by means of the Haar wavelet.Based on these merits,the SPWK has promising applications in the realm of wearable electronics,self-powered sensors,cyber security,and artificial intelligences.

Human Machine Interface with Wearable Electronics Using Biodegradable Triboelectric Films for Calligraphy Practice and Correction

Letter handwriting,especially stroke correction,is of great importance for recording languages and expressing and exchanging ideas for individual behavior and the public.In this study,a biodegradable and conductive carboxymethyl chitosan-silk fibroin(CSF)film is prepared to design wearable triboelectric nanogenerator(denoted as CSF-TENG),which outputs of V_(oc)≈165 V,I_(sc)≈1.4μA,and Q_(sc)≈72 mW cm^(−2).Further,in vitro biodegradation of CSF film is performed through trypsin and lysozyme.The results show that trypsin and lysozyme have stable and favorable biodegradation properties,removing 63.1%of CSF film after degrading for 11 days.Further,the CSF-TENG-based human-machine interface(HMI)is designed to promptly track writing steps and access the accuracy of letters,resulting in a straightforward communication media of human and machine.The CSF-TENG-based HMI can automatically recognize and correct three representative letters(F,H,and K),which is benefited by HMI system for data processing and analysis.The CSF-TENG-based HMI can make decisions for the next stroke,highlighting the stroke in advance by replacing it with red,which can be a candidate for calligraphy practice and correction.Finally,various demonstrations are done in real-time to achieve virtual and real-world controls including writing,vehicle movements,and healthcare.

Haptic Interface with Magnetic Field Sensitive Elastomer

Sense of touch is one of the important information from environment for human to live in daily life. Haptic interface is a hot topic in virtual reality but almost all of the devices focus on fingers and hands as targets. In this paper, we focus on the foot haptic device with magnetic flied sensitive elastomer （MSE）. We developed a haptic unit used as a magnetic field generator for MSE and contact point of foot haptic device. MSE samples mixed with 80 wt% carbonyl iron particles were prepared and evaluated with the developed magnet. Experimental results show that the mechanical property of the haptic unit can be modeled with the adjustable friction element. This property has a good advantage for the haptic unit.

Implementation of Strangely Behaving Intelligent Agents to Determine Human Intervention During Reinforcement Learning

Intrinsic motivation helps autonomous exploring agents traverse a larger portion of their environments.However,simulations of different learning environments in previous research show that after millions of timesteps of successful training,an intrinsically motivated agent may learn to act in ways unintended by the designer.This potential for unintended actions of autonomous exploring agents poses threats to the environment and humans if operated in the real world.We investigated this topic by using Unity’s MachineLearningAgent Toolkit(ML-Agents)implementation of the Proximal Policy Optimization(PPO)algorithm with the Intrinsic Curiosity Module(ICM)to train autonomous exploring agents in three learning environments.We demonstrate that ICM,although designed to assist agent navigation in environments with sparse reward generation,increasing gradually as a tool for purposely training misbehaving agent in significantly less than 1 million timesteps.We present the following achievements:1)experiments designed to cause agents to act undesirably,2)a metric for gauging how well an agent achieves its goal without collisions,and 3)validation of PPO best practices.Then,we used optimized methods to improve the agent’s performance and reduce collisions within the same environments.These achievements help further our understanding of the significance of monitoring training statistics during reinforcement learning for determining how humans can intervene to improve agent safety and performance.

Intelligent Agent Technologies: The Work Horse of ERP E-Commerce

Agents are the new defacto standard for inclusion in modules of today’s software systems such as ERP systems, mobile applications and operating systems. Agents are an integral part of today’s software design. The question is how do intelligent agents work in the specific area of ERP credit card processing e-commerce models? To answer this question, a specific area of ERP systems will be analyzed: credit card processing for merchants. One specific merchant credit card processor will be specifically investigated: EVO Merchants. This paper will research how exactly does ERP systems interact using Application Programing Interface or “API” specified by a credit card clearing house. Secure Socket Layers or SSL, and XML are discussed and elaborated on specifically how intelligent agents play such a pivotal role in ERP e-commerce systems for credit card processing.

Design and Evaluation of a User Interface for an Autonomous Agricultural Sprayer

This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer to commence operation, monitor the status of the sprayer and its operation in the field, and intervene when needed (i.e., to stop or shut down). Design principles and guidelines were carefully selected to help develop a human-centered automation interface. Evaluation of the interface using a combination of heuristic, cognitive walkthrough, and user testing techniques revealed several strengths of the design as well as areas that needed further improvement. Overall, this paper provides guidelines that will assist other researchers to develop an ergonomic user interface for a fully autonomous agricultural machine.

Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum/Soft Computing Approach

The article consists of two parts.Part I shows the possibility of quantum/soft computing optimizers of knowledge bases(QSCOptKB™)as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface.In particular case,the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™and QCOptKB™sophisticated toolkit.Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described.The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown.Developed information technology examined with special(difficult in diagnostic practice)examples emotion state estimation of autism children(ASD)and dementia and background of the knowledge bases design for intelligent robot of service use is it.Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated.

Artificial Intelligence and the Sustainable Development Goals: An Exploratory Study in the Context of the Society Domain

Artificial Intelligence (AI) experienced significant advancements in recent years, and its potential power is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its impact on meeting the Sustainable Development Goals (SDGs). The aim of this paper was to evaluate contributions and the potential influence of AI to sustainable development in the society domain. Furthermore, the study analyzed GPT-3 responses, as one of the largest language models developed by OpenAI, descriptively. We conducted a set of queries on the SDGs to gather information on GPT-3’s perceptions of AI impact on sustainable development. Analysis of GPT-3’s contribution potential towards the SDGs showcased its broad range of capabilities for contributing to the SDGs in areas such as education, health, and communication. The study findings provide valuable insights into the contributions of AI to sustainable development in the society domain and highlight the importance of proper regulations to promote the responsible use of AI for sustainable development. We highlighted the potential for improvement in neural language processing skills of GPT-3 by avoiding imitating weak human writing styles with more mistakes in longer texts.

生成式人工智能嵌入敏捷政府建设:影响、风险与应对

随着科学技术的不断发展,人工智能持续突破以传统算力和算法为基础的专门化人工智能“本体”,向着解决综合性复杂问题的通用型方向发展。技术变革催生政府创新,在新智能时代的社会背景下,传统政府利用最新科技工具向敏捷政府转型。以ChatGPT为代表的生成式人工智能所具有的大数据、大算法以及“类人化”等特征与敏捷政府的灵活响应、以人为本等特性相匹配,为其嵌入敏捷政府建设提供了可行性。然而,技术是一把双刃剑,政府在享受生成式人工智能技术带来便捷的同时,也要应对其超越性发展所带来的现实难题。总体来看,对生成式人工智能的广泛应用应该持包容态度,并将其作为技术工具赋能敏捷政府建设,推动生成式人工智能更好地落地实践。

群智创新时代下社区居家养老服务交互设计研究

目的解决目前养老中因服务组织参与度不高及智能交互产品利用率低下而导致的养老服务质量欠佳的问题。方法通过对当前社区居家养老服务现状进行分析,结合群智创新的发展及特点,分析养老服务设计的群智创新过程,提出了群智创新时代下基于用户的养老服务新组织,借助KANO模型原理对养老服务需求项目进行群体用户分析,并对分析数据结果进行优先顺序排序,获得老年用户群体对养老服务设计的真实需求情况。结果构建了以用户为中心的社区居家养老服务设计框架,并结合服务设计工具进行智能交互界面设计。结论对交互设计界面的测评显示,老年人对其满意度极高,该养老服务新模式有别于传统养老模式,顺应当今群智创新时代下大数据、互联网、云平台等科技的发展需求,在提高养老服务满意度的同时,使养老服务质量达到最优的效果。

从新媒体、科幻创意到通用人工智能:脑机接口的艺术革命

作为一种前沿技术,脑机接口不仅为科学家探索人类意识和思维的奥秘提供了重要的工具和途径,而且为艺术家提供了全新的创作手段和表达方式。在新媒体艺术领域,脑机接口给开拓者带来了新思路、新机遇,脑控绘艺、脑波音乐、脑控游戏等由此诞生。在科幻艺术领域,脑机接口赋予主创人员电光石火的灵感。相关作品想象如何通过这种技术在生理层面增强大脑能力、修改记忆或治疗疾病,在信息层面破译思想活动、深入赛博世界、实现灵明转移,在意向层面发挥自家大脑的主动性、利用他人大脑的受动性、增强多个大脑的交融性。脑机接口与通用人工智能的结合则为探索艺术创作提供了全新的视角和无限可能性。人们有可能通过纯思维与AI系统交互、超越传统肢体限制开展艺术活动,在梦境、冥想等特殊意识状态下配合AI抒情写照,共同经历丰富而深刻的艺术体验,形成前所未有的集体创作模式。

人工智能驱动新型界面分离材料的创制

计算机技术与人工智能的发展给新材料的开发带来了新的研究范式(第四代),也为新型界面分离材料的创制带来新的发展契机。然而,受界面分离过程机理研究和材料、基团的理化数据的局限性,人工智能在新型界面分离材料的创制中的应用仍处于初期阶段。本文为解决特定体系数据缺失的问题,构建了百万级(10^(6))的样板数据库,为大预测模型与生成模型提供了可靠、规范的示范数据基础;通过从大数据中挖掘分子结构与性质的隐藏关联,并借助分子模拟计算剖析其分子间相互作用机理,解析分子间相互作用机制和重组过程规律,进而实现高性能界面分离材料的构筑。最后,本文浅析了介尺度样板大数据、机器学习势理论、国产软件开发、有机合成、智能算法等多学科交叉在界面分离材料创制中的重要影响与发展机遇,以期推动虚拟实验室前沿发展。