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IEEE Transactions on Artificial Intelligence 2024年第2期5卷 882-894页

作者： Qin, Shujin Zhang, Shancheng Wang, Jiacun Liu, Shixin Guo, Xiwang Qi, Liang School of Economics and Management Shangqiu Normal University Shangqiu476000 China School of Information and Control Engineering Liaoning Petrochemical University Fushun113001 China Monmouth University West Long Branch NJ07764 United States College of Information Science and Engineering Northeastern University Shenyang110819 China Department of Computer Science and Technology Shandong University of Science and Technology Qingdao266590 China

The development of technology accelerates the upgrade of products, which results in a significant number of obsolete products. This research aims to solve the multirobotic multiproduct U-shaped disassembly line balancing problem (M2UDP), in which different products are disassembled on a U-shaped model in a preset cycle time and assigned tasks to robots in each workstation reasonably. A linear mixed-integer model is established to maximize disassembly profit and minimize carbon emissions. An improved multiobjective multiverse optimizer (IMMO) that utilizes the sigmoid activation function in neural networks is proposed to find the optimal plan for the model. The improved algorithm is verified via a set of real-life instances and compared with three classical multiobjective optimization algorithms. The experimental results show that the proposed IMMO performs better than those peers in solving the M2UDP problems. © 2023 IEEE.

关键词： Profitability

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Exploring the Potential of Serious Games: Integrating Technological Innovations in Healthcare and Beyond

Exploring the Potential of Serious Games: Integrating Techno...

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Computing in Natural Sciences, Biomedicine and engineering (COMCONF), International Conference on

作者： Victor Triohin Ionela Samuil Andreea Ionica Monica Leba Department of System Control and Computer Engineering University of Petrosani Petrosani Romania Department of Management and Industrial Engineering University of Petrosani Petrosani Romania

ISBN: (数字)9798350353358

ISBN: (纸本)9798350353365

This paper explores the expansive field of digital games with the objective of identifying a niche for a novel game concept, “Everyday Fantasy,” designed to promote well-being through interactive and immersive gameplay. The game seeks to integrate physical activity, cognitive stimulation, and social engagement by encouraging users to explore their environment, solve puzzles, and interact with others, thereby harnessing the benefits of walking, brain training, and socialization within a singular platform. Employing User Experience design principles within the Software Development Life Cycle framework, this study outlines the development process and assesses the game's market viability through dynamic simulation. By analyzing four distinct market scenarios based on adoption rates, the research identifies key technical components essential for the game's functionality, including a step counter, map generator, database management system, network mirroring technologies, and Unity game mechanics. The findings from this study not only affirm the potential market space for “Everyday Fantasy” but also set a foundational base for future development efforts, highlighting the game's capacity to make a meaningful impact on users' wellbeing.

关键词： Training Legged locomotion Technological innovation Medical services User experience Generators Database systems Serious games Object recognition Software development management

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X-OAR: Orchestration of Access Resources for eXtended Reality Educational Applications

X-OAR: Orchestration of Access Resources for eXtended Realit...

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IFIP Networking Conference

作者： Alessandro Priviero Luca Mastrandrea Ioannis Chatzigiannakis Stefania Colonnese Department of Information Engineering Electronics and Telecommunications Sapienza University of Rome Department of Computer Control and Management Engineering Sapienza University of Rome Italy

ISBN: (数字)9783903176638

ISBN: (纸本)9798350390605

Extended reality offers unprecedented learning and training occasions, and unique challenges related not only to throughput and delay, but also to the characteristic spatial concentration of trainees. We have developed an algorithm for eXtended reality oriented Orchestration of Access Resources (X-OAR) grounding on next generation network technologies. X-OAR is designed to efficiently allocate edge computing facilities and cooperatively scheduled radio access network resources for extended reality applications. Building on the 3GPP guidelines on quality of experience in XR services, X-OAR meets the stringent XR delay requirements by leveraging edge and radio resources and employing cooperative scheduling within the radio access network. We introduce a graph model of the X-OAR optimization problem, and we present the X-OAR greedy algorithm, that reduces the orchestration complexity and the dependency on user subscription information. Experimental results show that X-OAR, with its cooperative scheduling technique, outperforms state-of-the-art competitors in terms of XR quality of experience. X-OAR paves the way for further studies extending the system orchestration to the application layer and the related resource charging policy.

关键词： Training Extended reality Processor scheduling Throughput Delays Quality of experience Optimization

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Human arm motion capture system

Human arm motion capture system

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International Conference on Mathematics and computers in Sciences and in Industry (MCSI)

作者： Marius Leonard Olar Monica Leba Andreea Ionica Department of System Control and Computer Engineering University of Petrosani Petrosani Romania Department of Management and Industrial Engineering University of Petrosani Petrosani Romania

ISBN: (数字)9798350377224

ISBN: (纸本)9798350377231

The implementation of robotics and human support technologies has opened up new possibilities for recovering the mobility impaired and increasing human productivity in the last few decades. Exoskeletons have been developed as a major component of this progress in order to capture any form of arm motion be it passive or active. Motion capture systems, employing different sensors like IMU sensors, EMG sensors, motion sensors, fiber optic sensors are used to capture arm movements. These sensors provide information on position, movement, muscle contraction, and movement intent of the arm. The use of multiple sensor types allows for redundancy and accurate outcomes. Potentiometer position sensor can be combined with other types of sensors to measure acceleration, orientation, force exerted and arm bendability. The combinations improve accuracy and adaptability for arm motion capture during rehabilitation. Various combinations of adapted sensors can be used for each joint of the hand depending on the peculiarities of application. Sensors enable precise and natural control over recovery devices or exoskeletons which is especially important in terms of rehabilitation process improvement.

关键词： Hands Optical fiber sensors Accuracy Service robots Exoskeletons Potentiometers Manipulators Motion capture Sensor systems Sensors

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The Emergence of Artificial Intelligence in Education and its Impact on Individual Literacy in Higher Education 7

The Emergence of Artificial Intelligence in Education and it...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2024

作者： Farkas, Imre Kovari, Attila Rajcsanyi-Molnar, Monika Institute of Computer Engineering University of Dunaujvaros Department of Computer Systems and Control Technology Dunaujvaros Hungary Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary Institute of Electronics and Communication Systems Kandó Kalmán Faculty of Electrical Engineering Obuda University Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Social Sciences University of Dunaujvaros Department of Economics and Management Dunaujvaros Hungary

ISBN: (纸本)9798331531119

In the last three years, a new partner has emerged for teachers and educators in the field of education. The mushrooming of applications based on large language models has greatly shaped the educational development fields of the present era. The use of various AI applications has become commonplace among students and teachers alike. Many questions are being raised by researchers in this field. What does the rapid development of AI applications bring to the field of pedagogy? Should the products of such applications be compared with human performance? The form presented in this thesis seeks to answer similar questions. What is the impact of frequent use of these applications on the literacy level of individuals? In which areas do students tend to use these applications? The results indicate that half of the students believe their literacy levels will decrease with the mass emergence of AI applications, while 36% feel it will not change. However, 88 % of students have already dealt with AI-based applications, with 64 % using them several times or more, suggesting a high level of integration into their educational processes. © 2024 IEEE.

关键词： Students

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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The Impact of the Digital Transformation of Education on Literacy 7

The Impact of the Digital Transformation of Education on Lit...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2024

作者： Farkas, Imre Kovari, Attila Rajcsanyi-Molnar, Monika Institute of Computer Engineering University of Dunaujvaros Department of Computer Systems and Control Technology Dunaujvaros Hungary Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary Obuda University Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Social Sciences University of Dunaujvaros Department of Economics and Management Dunaujvaros Hungary

ISBN: (纸本)9798331531119

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills. © 2024 IEEE.

关键词： digital education digital literacy digital-informatics literacy

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Adaptive Fractional-Order Sliding Mode control for Mobile Robots: A PSO-Based Optimization Framework 22

Adaptive Fractional-Order Sliding Mode Control for Mobile Ro...

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22nd IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2025

作者： Nasir, M. Fareh, R. Ghommam, J. Gad, Om Khadraoui, S. Bettayeb, M. University of Sharjah Department of Electrical Engineering Sharjah United Arab Emirates Sultan Qaboos University Department of Electrical and Computer Engineering Oman Ecole National d'Ingenieur de Sfax Control and Energy Management Laboratory (CEM Lab) Tunisia

ISBN: (纸本)9798331542726

This study presents an adaptive fractional sliding mode control (AFSMC) strategy for finite-time trajectory tracking of differential drive mobile robots (DDMR) in the presence of system uncertainties and external disturbances. The proposed control strategy employs a fractional-order sliding surface and an optimized reaching law to ensure finite-time convergence of tracking errors while retaining robustness against external disturbances. Particle Swarm Optimization (PSO) is employed for offline parameter tuning, where its capability to efficiently handle a large parameter space makes it an ideal choice for optimizing the control system, ensuring both enhanced performance and computational feasibility. Simulation tests comparing the AFSMC with a conventional SMC show that the AFSMC exhibits higher tracking accuracy, robustness, and precise linear and angular velocity tracking. The results demonstrate the AFSMC's resilience to disturbances and minimal steady-state error, even under challenging conditions. © 2025 IEEE.

关键词： Adaptive Mobile robots PSO optimization Sliding mode control Trajectory tracking

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Improved Proximal Policy Optimization Algorithm for Multi-objective Disassembly Line Balancing Considering Hazardous Tasks 21

Improved Proximal Policy Optimization Algorithm for Multi-ob...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Guo, Zeyu Guo, Xiwang Wang, Jiacun Qin, Shujin Qi, Liang Kang, Qi Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Computer Science and Software Eng. Wes Long BranchNJ United States Shangqiu Normal University Economics and Management Shangqiu China Shandong Technology University Computer Science Department Qingdao China New Jersey Institute of Technology Electrical and Computer Engineering Newark United States

ISBN: (纸本)9798350365221

As disassembly lines evolve, keeping workers safe from all potential dangers has become paramount. This work proposes an improved approach, Proximal Policy Optimization for Disassembly Line(PPO-DL), to address Multi-objective Dis-assembly Line Balancing Problem(MDLBP) that integrates task switching time and hazardous tasks. The MDLBP model aims to optimize disassembly net profit, balance workstation utilization, and mitigate penalties from hazardous tasks. The proposed PPO-DL modifies the action space of PPO to accommodate MD LBP characteristics, ensuring efficient learning by restricting actions to valid ranges through action masking. Comparative experiments with PPO, Q-learning, and A2C demonstrate PPO-DL's superiority in finding near-optimal solutions across various scenarios. © 2024 IEEE.

关键词： Assembly machines

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Results From a Large-Scale IoT-Based Intervention for Energy Saving and Sustainability Awareness via Behavior Change in 25 K-12 Schools in Europe

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IEEE Internet of Things Journal 2025年第12期12卷 19308-19325页

作者： Mylonas, Georgios Amaxilatis, Dimitrios Paganelli, Federica Chatzigiannakis, Ioannis Koulouris, Pavlos Falkouskaya, Yelizaveta Markopoulos, Panos Industrial Systems Institute Athena Research Center Patras26504 Greece Computer Technology Institute and Press Diophantus Research Unit 1 Rion26504 Greece Spark Works Ltd. GalwayH91 AHR1 Ireland Research Unit University of Pisa Department of Computer Science CNIT Pisa56127 Italy Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy Ellinogermaniki Agogi Research and Development Department Athens153 51 Greece Eindhoven University of Technology Department of Industrial Design Eindhoven Artificial Intelligence Systems Institute Eindhoven5612 Netherlands

The unfolding climate crisis has resulted in a rising interest for increasing sustainability awareness and achieving energy savings worldwide. Several interventions within educational environments have been aimed at mobilizing younger audiences toward such goals. However, most of the interventions carried out so far are based on a subset of possible tools (e.g., IoT monitoring and gamification) and offer "all or nothing" approaches, which do not cope well with the uniqueness of schools and the need to adapt interventions to specific contexts (e.g. school size, building, curriculum, and teacher involvement). We present a large-scale intervention in 25 school buildings in Europe over the course of two school years. Our intervention was based on the installation of a relatively low-cost IoT infrastructure in schools, that produced real-time energy-related data from the school buildings involved, and the application of a strategy combining, in a flexible and customizable way, educational activities, monitoring tools, gamification, and competition to motivate behavior change and achieve energy savings. Overall, 2983 students and 204 educators were directly involved to a variable degree of participation. Our results indicate a positive overall result in terms of short-term energy savings in most schools involved, with an average reduction of 20%–25% in the energy that could be affected by end-users, as well as a 32.9% increase after the intervention in students self-reporting good or very good sustainability awareness. These findings suggest that such interventions can be a valuable step toward educating young students regarding sustainability and toward sustainable schools, if designed and implemented properly. © 2014 IEEE.

关键词： Sustainable development Buildings Energy conservation Europe Meteorology Internet of Things Energy consumption Real-time systems Energy efficiency Psychology

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