Digital Twin Technology of Human-Machine Integration in Cross-Belt Sorting System

The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most crucial.However,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express items.In the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems.Striking a balance between efficiency in handling express items and operator well-being is challenging.Digital twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating framework.Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time simulation.The feasibility of the proposed method was verified in an express distribution center.

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.

On the politeness Diction Phenomenon and Misusage in the Intercommunication

礼貌是人类文明的标志,是人类社会活动的一条重要准绳。文章阐述了言语交际中的礼貌现象,分析了误用问题发生的成因,从文化及教学方面提出几点建设性建议,以期更好的避免误用问题的发生。

Deep Learning for EMG-based Human-Machine Interaction:A Review

Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.

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 compatibility and dynamic analysis of a novel unpowered and self-adaptive shoulder rehabilitation exoskeleton

To reduce the complexity of the configuration and control strategy for shoulder rehabilitation exoskeleton,a 2R1R1P2R serial of shoulder exoskeleton based on gravity balance is proposed.Based on three basic rotatory shoulder joints,an exact kinematic constraint system can be formed between the exoskeleton and the upper arm by introducing a passive sliding pair and a center of glenohumeral(CGH)unpowered compensation mechanism,which realizes the human-machine kinematic compatibility.Gravity balance is used in the CGH compensation mechanism to provide shoulder joint support.Meanwhile,the motion of the compensation mechanism is pulled by doing reverse leading through the arm to realize the kinematic self-adaptive,which decreases control complexity.Besides,a simple and intuitive spring adjustment strategy is proposed to ensure the gravity balance of any prescribed quality.Furthermore,according to the influencing factors analysis of the scapulohumeral rhythm,the kinematic analysis of CGH mechanism is performed,which shows that the mechanism can fit the trajectory of CGH under various conditions.Finally,the dynamic simulation of the mechanism is carried out.Results indicate that the compensation torques are reduced to below 0.22 N·m,and the feasibility of the mechanism is also verified.

Quantum Secure Direct Intercommunication with Superdense Coding and Entanglement Swapping

A quantum secure direct intercommunication scheme is proposed to exchange directly the communicators＇ secret messages by making ase of swapping entanglement of Bell states. It has great capacity to distribute the secret messages since these messages have been imposed on high-dimensional Bell states via the local unitary operations with superdense coding. The security is ensured by the secure transmission of the travel sequences and the application of entanglement swapping.

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.

BLIND SPEECH SEPARATION FOR ROBOTS WITH INTELLIGENT HUMAN-MACHINE INTERACTION

Speech recognition rate will deteriorate greatly in human-machine interaction when the speaker's speech mixes with a bystander's voice. This paper proposes a time-frequency approach for Blind Source Seperation (BSS) for intelligent Human-Machine Interaction(HMI). Main idea of the algorithm is to simultaneously diagonalize the correlation matrix of the pre-whitened signals at different time delays for every frequency bins in time-frequency domain. The prososed method has two merits: (1) fast convergence speed; (2) high signal to interference ratio of the separated signals. Numerical evaluations are used to compare the performance of the proposed algorithm with two other deconvolution algorithms. An efficient algorithm to resolve permutation ambiguity is also proposed in this paper. The algorithm proposed saves more than 10% of computational time with properly selected parameters and achieves good performances for both simulated convolutive mixtures and real room recorded speeches.

A Robotic Teleoperation System for Precise Robotic Manipulation by Human-Machine Interaction

Teleoperation is of great importance in the area of robotics,especially when people are unavailable in the robot workshop.It provides a way for people to control robots remotely using human intelligence.In this paper,a robotic teleoperation system for precise robotic manipulation is established.The data glove and the 7-degrees of freedom(DOFs)force feedback controller are used for the remote control interaction.The control system and the monitor system are designed for the remote precise manipulation.The monitor system contains an image acquisition system and a human-machine interaction module,and aims to simulate and detect the robot running state.Besides,a visual object tracking algorithm is developed to estimate the states of the dynamic system from noisy observations.The established robotic teleoperation systemis applied to a series of experiments,and high-precision results are obtained,showing the effectiveness of the physical system.

A Discourse Analysis to Intercommunication Accommodation

The goal of the qualitative study is to investigate the cultural influences on professional context based on the discourse approach and communicative accommodation theory. A face-to-face interview is conducted to look into the content and logic of the sample discourse to verify the objective measures, the underlied motives and assumptions and validate the principles of the communicative accommodation theory. The result supports the principles of the discourse approach and the communication accommodation theory both from a foreigner's perception on his communicative adjustment to the target culture and from the communicative adjustment between the interviewer and the interviewee.

The Human-Machine Safety Design of Mechanical Toys for Children

In order to ensure the safety of children while using machineries and avoid harm caused by mechanical toys,this paper analyzes the types and detection standards of children’s toys,discusses the reasons for the harm caused by these toys,and proposes human-machine safety design strategies for children’s toys as reference.

Flexible and multifunctional triboelectric nanogenerator based on liquid metal/polyvinyl alcohol hydrogel for energy harvesting and self-powered wearable human-machine interaction

Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriously hinder its development.Herein,we report a robust route to a liquid metal(LM)/polyvinyl alcohol(PVA)hydrogel-based TENG(LP-TENG).Owing to the intrinsically liquid feature of conductive LM within the flexible PVA hydrogel,the as-prepared LP-TENG exhibited comprehensiye advantages of adaptability,biocompatibility,outstanding electrical performance,superior stability,recyclability and diverse applications,which were unattainable by traditional systems.Concretely,the LP-TENG delivered appealing open circuit voltage of 250 V,short circuit current of 4μA and transferred charge of 120 nC with high stability,outperforming most advanced TENG systems.The LP-TENG was successfully employed for versatile applications with multifunctionality,including human motion detection,handwriting recognition,energy collection,message transmission and human-machine interaction.This work presents significant prospects for crafting advanced materials and devices in the fields of wearable electronics,flexible skin and smart robots.

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.

Recent advances in stretchable triboelectric nanogenerators for use in wearable bioelectronic devices

Wearable bioelectronic devices have the capacity for real-time human health monitoring,the provision of tailored services,and natural interaction with smart devices.However,these wearable bioelectronic devices rely on conventional rigid batteries that are frequently charged or replaced and are incompatible with the skin,leading to a discontinuity in complex therapeutic tasks related to human health monitoring and human-machine interaction.Stretchable triboelectric nanogenerator(TENG)is a high-efficiency energy harvesting technology that converts mechanical into electrical energy,effectively powering wearable bioelectronic devices.This study comprehensively overviews recent advances in stretchable TENG for use in wearable bioelectronic devices.The working mechanism of stretchable TENG is initially explained.A comprehensive discussion presents the approaches for fabricating stretchable TENG,including the design of stretchable structures and the selection of stretchable materials.Furthermore,applications of wearable bioelectronic devices based on stretchable TENG in human health monitoring(body movements,pulse,and respiration)and human-machine interaction(touch panels,machine control,and virtual reality)are introduced.Ultimately,the challenges and developmental trends regarding wearable bioelectronic devices based on stretchable TENG are elaborated.

多重三角关系抑或阵营化:国际体系演化逻辑及其前景

纵观国际体系演化的历史进程可以发现,多重三角关系和阵营化构成了两种不同的演化逻辑和路径。阵营化造成了集团对抗,或者引发大战,或者陷入冷战;多重三角关系基于议题而形成灵活外交,保持了国际体系的动态平衡。互通-互动是推动国际体系演化的动力,交通、通信等功能型互通-互动扩大了国际体系的规模,最终形成了具有全球广度的国际体系。在功能型互通-互动的推动下,国际体系的广度延伸、密度增强,到19世纪中后期,多元区域性国际体系朝着“全球性”的单一国际体系迈进;而以价值型互通-互动为主导的国际体系朝着阵营化演变,阵营化国际体系的对抗强化了体系阵营内部的凝聚力和等级性。经济社会的发展冲击着阵营化国际体系,多元权力中心的历史性回归为多重三角关系的重构奠定了基础,是未来国际体系的前景之一。

A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily activities.Unlike existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple scenarios.It features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance output.Through wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist movements.Remarkably,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various tasks.The system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and letters.The proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific training.Its utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

A Review on Security and Privacy Issues Pertaining to Cyber-Physical Systems in the Industry 5.0 Era

The advent of Industry 5.0 marks a transformative era where Cyber-Physical Systems(CPSs)seamlessly integrate physical processes with advanced digital technologies.However,as industries become increasingly interconnected and reliant on smart digital technologies,the intersection of physical and cyber domains introduces novel security considerations,endangering the entire industrial ecosystem.The transition towards a more cooperative setting,including humans and machines in Industry 5.0,together with the growing intricacy and interconnection of CPSs,presents distinct and diverse security and privacy challenges.In this regard,this study provides a comprehensive review of security and privacy concerns pertaining to CPSs in the context of Industry 5.0.The review commences by providing an outline of the role of CPSs in Industry 5.0 and then proceeds to conduct a thorough review of the different security risks associated with CPSs in the context of Industry 5.0.Afterward,the study also presents the privacy implications inherent in these systems,particularly in light of the massive data collection and processing required.In addition,the paper delineates potential avenues for future research and provides countermeasures to surmount these challenges.Overall,the study underscores the imperative of adopting comprehensive security and privacy strategies within the context of Industry 5.0.

Assistive Robotics for Upper Limb Physical Rehabilitation:A Systematic Review and Future Prospects

Physical assistive robotics are oriented to support and improve functional capacities of people.In physical rehabilitation,robots are indeed useful for functional recovery of affected limb.However,there are still open questions related to technological aspects.This work presents a systematic review of upper limb rehabilitation robotics in order to analyze and establish technological challenges and future directions in this area.A bibliometric analysis was performed for the systematic literature review.Literature from the last six years,conducted between August 2020 and May 2021,was reviewed.The methodology for the literature search and a bibliometric analysis of the metadata are presented.After a preliminary search resulted in 820 articles,a total of 66 articles were included.A concurrency network and bibliographic analysis were provided.And an analysis of occurrences,taxonomy,and rehabilitation robotics reported in the literature is presented.This review aims to provide to the scientific community an overview of the state of the art in assistive robotics for upper limb physical rehabilitation.The literature analysis allows access to a gap of unexplored options to define the technological prospects applied to upper limb physical rehabilitation robotics.

Machine learning and human‐machine trust in healthcare:A systematic survey

As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have proper trust in medical machines.Intelligent machines that have applied machine learning(ML)technologies continue to penetrate deeper into the medical environment,which also places higher demands on intelligent healthcare.In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious,the authors need to build good humanmachine trust(HMT)in healthcare.This article provides a systematic overview of the prominent research on ML and HMT in healthcare.In addition,this study explores and analyses ML and three important factors that influence HMT in healthcare,and then proposes a HMT model in healthcare.Finally,general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified.