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.

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.

The cost of collusion:economic thinking on the uniform accommodation price of the hotel industry in Kunming,Yunnan

This paper studies the case of the collusive price of the hotel industry in Kunming by economically analyzingthe unsustainability of the collusive price and instability of collusive organizations, doubts about the collusive behavior,and thinks that the collusive price is not helpful to the development of tourism industry, the pillar industry in YunnanProvince.

Collusion detector based on G-N algorithm for trust model

In the open network environment, malicious attacks to the trust model have become increasingly serious. Compared with single node attacks, collusion attacks do more harm to the trust model. To solve this problem, a collusion detector based on the GN algorithm for the trust evaluation model is proposed in the open Internet environment. By analyzing the behavioral characteristics of collusion groups, the concept of flatting is defined and the G-N community mining algorithm is used to divide suspicious communities. On this basis, a collusion community detector method is proposed based on the breaking strength of suspicious communities. Simulation results show that the model has high recognition accuracy in identifying collusion nodes, so as to effectively defend against malicious attacks of collusion nodes.

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.

Strategic interaction between institutional investors and supervision department:a theoretical analysis of low‑price collusion in SBIC

We introduce evolutionary game method to analyze low-price collusion in inquiry market of Sci-Tech Innovation Board of China(SIBC)from the perspective of strategic interaction between large institutional investors(LIIs),small and medium-sized institutional investors(SMIIs),and supervision department(SD).The results show that supervision behaviors of SD,and quotation behaviors of institutional investors,are subject to supervision conditions.Under the condition that benefits of tough supervision are lower a lot than minimum benefits of light supervision(light supervision condition),SD will choose light supervision and institutional investors will turn to illegal quotation in response.Finally,a steady-state equilibrium with low-price collusion will form in SIBC’s inquiry market even with a large supervision penalty for illegal quotation.On the contrary,under the condition that benefits of tough supervision are higher a lot than maximum benefits of light supervision(tough supervision condition)and with a large penalty for illegal quotation,SD and institutional investors will choose tough supervision and legal quotation.Further numerical simulations under light supervision condition show that:(1)High-price culling rule will become a booster for low-price collusion and accelerate SMIIs’evolutionary process to imitative quotation.(2)Blindly increasing penalties for illegal quotation or reducing the culling rate is not an appropriate approach to solve the problem of low-price collusion since it cannot shift supervision condition from light into tough and make SD supervise toughly.(3)Institutional investors’choices of quotation strategies are more volatile and highly susceptible to supervision behaviors of SD when facing exogenous uncertainty.Therefore,the keys to solving the problem of low-price collusion are shifting supervision condition from light into tough through increasing incremental benefits of tough supervision,and providing institutional investors with a stable and predictable supervision policy.In conclusion,the creation of a fair inquiry market doesn’t only depend on restraint and punishment to institutional investors,but also requires the establishment of supervision mechanism those are compatible with market-based inquiry.

DEFENSE AGAINST COLLUSION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSNs) are being deployed for a wide variety of applications and the security problems of them have received considerable attention. Considering the limitations of power, computation capability and storage resources, this paper proposed an efficient defense against collusion scheme based on elliptic curve cryptography for wireless sensor networks in order to solve the problems that sensor node-key leaking and adversaries make compromised nodes as their collusions to launch new attack. In the proposed scheme, the group-key distribution strategy is employed to compute the private key of each sensor node, and the encryption and decryption algorithms are constructed based on Elliptic Curve Cryptography (ECC). The command center (node) only needs to broadcast a controlling header with three group elements, and the authorized sensor node can correctly recover the session key and use it to decrypt the broadcasting message. Analysis and proof of the proposed scheme's efficiency and security show that the proposed scheme can resist the k-collusion attack efficiently.

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.

Collusion between Aggregated Industries in General Equilibrium

We analyze an infinite horizon difference game between four aggregated industries-production of producer goods, production of consumption goods, federation of labor unions, and commercial banking sector. Consumers do not behave strategically. They make their decisions on the basis of maximization of average discounted utility. Therefore, we do not include them in the set of players in the game. The payoffof each production industry and the commercial banking sector is equal to the average discounted sum of real dividends of its owners. The payoff of the federation of labor unions is equal to the average discounted sum of real wages and real unemployment benefits. A strict strong perfect general equilibrium is the applied solution concept for the game. It requires that there does not exist a coalition of players that can weakly Pareto improve the vector of continuation payoffs of its members in some subgame by a coordinated deviation. It is a refinement of Rubinstein＇s concept of a strong perfect equilibrium. We formulate and prove the sufficient condition for its existence. It is based on the assumption that no one of the aggregated industries can have a positive output without using some minimal amount of output of each other aggregated industry as an input. By definition, in each subgame, the equilibrium payoff vector in a strict strong perfect general equilibrium is strictly Pareto efficient. Thus, if each consumer either has only income from wage and unemployment benefit or receives dividend from only one aggregated industry, and his nominal income in each period along the equilibrium path exceeds social minimum, it is not possible to weakly Pareto improve the vector of consumers＇ average discounted real incomes. This holds not only for the whole game but also for each subgame starting in the first phase of some period.

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.

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.

A Collusion-Resistant Distributed Agent-Based Signature Delegation (CDASD) Protocol for E-Commerce Applications

Mobile agent technology is promising for e-commerce and distributed computing applications due to its properties of mobility and autonomy. One of the most security-sensitive tasks a mobile agent is expected to perform is signing digital signatures on a remote untrustworthy service host that is beyond the control of the agent host. This service host may treat the mobile agents unfairly, i.e. according to its’ own benefit rather than to their time of arrival. In this research, we present a novel protocol, called Collusion-Resistant Distributed Agent-based Signature Delegation (CDASD) protocol, to allow an agent host to delegate its signing power to an anonymous mobile agent in such a way that the mobile agent does not reveal any information about its host’s identity and, at the same time, can be authenticated by the service host, hence, ensuring fairness of service provision. The protocol introduces a verification server to verify the signature generated by the mobile agent in such a way that even if colluding with the service host, both parties will not get more information than what they already have. The protocol incorporates three methods: Agent Signature Key Generation method, Agent Signature Generation method, Agent Signature Verification method. The most notable feature of the protocol is that, in addition to allowing secure and anonymous signature delegation, it enables tracking of malicious mobile agents when a service host is attacked. The security properties of the proposed protocol are analyzed, and the protocol is compared with the most related work.

政府监管下直播带货平台合谋行为的奖惩机制研究

“直播+电商”的新型商品销售模式正飞速发展,但该过程中存在诸多问题。本文考虑了直播带货平台与平台商家合谋以获取超额利润的现象,建立并分析了不同的奖惩机制下直播带货平台与政府监管机构的演化博弈模型,最终得出以下结论:静态奖惩机制与动态奖励静态惩罚机制下,系统不存在稳定均衡点;静态奖励动态惩罚和动态奖励动态惩罚机制下,系统存在稳定均衡点,但动态奖惩机制下直播带货平台与平台商家合谋的概率更低。动态奖惩机制下,直播带货平台和直播电商合谋行为与奖惩力度有关,当惩罚力度增加时,直播带货平台与平台商家合谋的概率下降,政府监管成本降低;当奖励强度增加时,政府严格监管概率降低,直播带货平台与平台商家合谋概率降低但变化较小。因此,政府监管机构采用科学合理的动态奖惩机制有助于直播带货行业的稳健发展。

地缘关系与机构投资者合谋报价:来自科创板IPO的经验证据

本文以科创板IPO公司为样本,基于地缘关系考察了机构投资者合谋报价行为。研究发现,科创板IPO过程中,存在地缘关系的机构投资者一致报价概率显著更高;在考虑了信息相似性、锚点报价问题、羊群效应及其他关系类型的替代性解释后,该研究结果依然成立,这表明机构投资者涉嫌实施基于地缘关系的合谋报价行为。拓展性分析显示,监管加强后,机构投资者报价行为随之改变,存在地缘关系的机构投资者一致报价频率降低,微小差异报价频率提升,从而降低了合谋报价嫌疑与被监管机构关注的风险;IPO公司信息环境较好时,机构投资者基于地缘关系的合谋报价嫌疑较低。本文不仅丰富了IPO领域的理论研究,也为舆论关切的机构投资者合谋报价问题提供了经验证据和机理解释。

新形势下串通投标犯罪数据化侦查实践路径

招投标全流程电子化的日益普及给串通投标犯罪侦查工作带来了一定困难。如何不断提升串通投标犯罪的数据化侦查能力和水平,已经成为全国经济犯罪侦查理论与实务部门广泛关注并亟待解决的问题。本文通过文献研究、案例分析等方法探讨了新形势下我国串通投标犯罪产生的原因、手段及危害,较为系统地阐释了如何综合利用各种数据导侦工具、采用企业基因测序、社会网络分析等方法和技术研判风险企业、分析违法资金流向等问题,深入挖掘显性和隐性犯罪网络,锁定重点人物,构建完整的证据体系,实现对串通投标犯罪的全链条式打击。

抗理性敌手共谋的安全K-prototype聚类

针对云环境下数据隐私泄露及聚类过程中云服务器间共谋的问题,提出一种抗理性敌手共谋的安全协作K-prototype聚类方案,目的在不泄露各方隐私数据情况下根据距离度量将相似的数据进行聚类。首先,考虑到同态加密不直接支持非线性计算,基于同态加密和加性秘密共享技术设计安全比较协议和安全大于协议,并确保输入数据、中间结果及模型参数均为加性秘密份额形式,以防止单个服务器能够获得完整数据,且能实现非线性函数的精确计算,在已设计的安全计算协议基础上,实现安全距离计算、安全聚类标签更新、安全聚类中心更新、聚类标签及聚类中心重构;其次,根据博弈均衡理论设计多种高效激励机制,构造互制合约及举报合约以约束云服务器诚实非共谋地执行聚类任务;最后,对所提的安全计算协议及合约进行理论分析,并对该方案的性能进行实验验证。实验结果表明,与明文环境下的模型精度相比,该方案的模型精度损失控制在0.22%内,进而验证了所提方案的有效性。

基于随机演化博弈视角的绿色农产品生产与合谋监管研究

考虑政府绿色农产品安全生产监管下,农企与第三方检测机构合谋寻租导致市面上“伪绿色”产品频现等问题。该研究将高斯白噪声作为随机干扰项引入,构建了政府监管部门、农企和第三方检测机构在绿色生产与质量监管中的三方随机演化博弈模型。在此基础上,通过数值仿真分析,探讨了随机扰动因素、政府奖惩等因素对各主体策略选择及演化至稳定状态收敛速度的影响;最后,结合数值仿真结果提出了相关政策和建议,以期对当前绿色食品生产与监管提供参考依据。