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9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Kumar, A. Kishore Rajesh Kumar, T. Balamanigandan, R. Kumar, A. Sasi Mahaveerakannan, R. Department of Robotics and Automation Sri Ramakrishna Engineering College Tamilnadu Coimbatore641022 India SIMATS Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Srinivas University Institute of Engineering & Technology Department of Cloud Technology & Data Science Surathkal India

ISBN: (纸本)9798350397376

Industrial Internet of Things (IIoT) may allow for the state of equipment to be monitored and defects to be detected before they become serious, helping smart factories keep up with the rising demands for safety and efficiency brought on by worldwide competition. In the case of Cloud Computing, data-driven approaches implemented in the cloud are used to first train the model using a vast quantity of raw data, and then end-machines send their real-time readings for processing at the cloud data centre. It is possible, however, that this will impose a significant delay and a high computational cost. In this study, we take into account a hierarchical structure in which edge-PLCs are used to collect sensed data locally and lessen the burden on long-distance connections. Due to the fact that a single responsibility may be associated with multiple swaying topographies, we aim to first reduce the sum of features required to identify a fault, and then identify the smallest possible set of edge-PLCs that still accounts for all of the most important ones, all while keeping deployment costs to a minimum. To address this, we present an Enhanced Harris Hawkins Optimization (EHHO) approach to tackling the features selection issue, followed by the assortment of edge-PLCs through the set coverage problematic. The model named Residual Attention Neural Network (RANN) is proposed the in this study to forecast the fault detection procedure. Residual Neural Network (ResNet) is used by RANN to help diagnose problems, alongside the knowledge of experts. We evaluate the performance of our technique in comparison to existing AI-based approaches, such as the lregression model and its expansions, by simulating on a real data trail. The findings confirm competence and presentation of the suggested approach, which meets or even surpasses the correctness of approaches employing the entire collection of data. © 2023 IEEE.

关键词： Internet of things

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Head Pose Feature for Prediction Pedestrian Intention to Crossing the Road Using LSTM 38

Head Pose Feature for Prediction Pedestrian Intention to Cro...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Sidharta, Hanugra Aulia Ilham Perdana, Muhammad Mulyanto Yuniarno, Eko Al Kindhi, Berlian Hery Purnomo, Mauridhi Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia Universitas Muhammadiyah Malang Department of Informatics Malang Indonesia Institut Teknologi Sepuluh Nopember Department of Electrical Automation Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Department of Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350302196

Understanding pedestrian behaviour when crossing the road is an important key to the development of autonomous vehicles. Because pedestrians are considered Vul-nerable Road Users (VRUs), they are likely to be killed if they are involved in an accident. To ensure their safety, it is then necessary to predict the pedestrian's intention based on their behaviour. In this experiment, we propose head pose observation for predicting their intention, by observing pedestrians' head pose data, we can then predict their intention to cross the road. To achieve this purpose, we use human head detector and head pose extraction feature, and the resulting yaw, pitch and roll as three head pose features. To select the most optimal feature is important for predicting pedestrian intention, then we make 7 combination scenarios based on these three features and compare it with the same model. Based on this scenario, it is proved that all these three data are optimal to observe pedestrian intention. There are three behavioural annotation that have been used, there are crossing, not crossing and will crossing. We derive will crossing from the annotation looking and not crossing while waiting at the roadside. Prediction of pedestrian behaviour is done by using LSTM model, and the resulting precision on crossing and not crossing with 0.98, while will crossing is 0.94. © 2023 IEEE.

关键词： Forecasting

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Memô the Game: Serious Game for Development of Memorization in Children with Autistic Spectrum Disorder 9th

Memô the Game: Serious Game for Development of Memorizat...

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9th Latin American Congress on Biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on Biomedical engineering, CBEB 2022

作者： Freitas, Éberte Panceri, João Schreider, Sheila Caldeira, Eliete Bastos-Filho, Teodiano Postgraduate Program in Electrical Engineering Federal University of Espirito Santo Vitoria Brazil Automation and Control Engineering Department Federal Institute of Espirito Santo Linhares Brazil Electrical Engineering Department Federal University of Espirito Santo Vitoria Brazil Postgraduate Program in Biotechnology Federal University of Espirito Santo Vitoria Brazil

ISBN: (纸本)9783031494062

This work presents the architecture and development of the Serious Game (SG) Memô which is aimed at exercising the Short-Term Memory (STM) of children with Autism Spectrum Disorder (ASD). This serious game proposes an individualized functional approach through Dynamic Difficulty Adjustment (DDA), which considers the performance, the expressed facial emotions, and the level of eye attention during child performance. In addition, it is used to recording the presence of hand and eye stereotypies. The SG is developed in Unity 3D, uses MediaPipe to determine the points of the hands, and is executed by our Socially Assistive Robot (SAR), termed Mobile Autonomous Robot for Interaction with Autistics and Trisomy 21 (MARIA T21). We believe that the creation of SGs to assist in the cognitive development of children with ASD and explore the detection of other stereotyped movements, associating them with a communicative and emotional proposal, is feasible. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Serious games

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EFFICIENT MULTI-AGENT REINFORCEMENT LEARNING BY PLANNING 12

EFFICIENT MULTI-AGENT REINFORCEMENT LEARNING BY PLANNING

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12th International Conference on Learning Representations, ICLR 2024

作者： Liu, Qihan Ye, Jianing Ma, Xiaoteng Yang, Jun Liang, Bin Zhang, Chongjie Department of Automation Tsinghua University China Institute for Interdisciplinary Information Sciences Tsinghua University China Department of Computer Science & Engineering Washington University St. Louis United States

Multi-agent reinforcement learning (MARL) algorithms have accomplished remarkable breakthroughs in solving large-scale decision-making tasks. Nonetheless, most existing MARL algorithms are model-free, limiting sample efficiency and hindering their applicability in more challenging scenarios. In contrast, model-based reinforcement learning (MBRL), particularly algorithms integrating planning, such as MuZero, has demonstrated superhuman performance with limited data in many tasks. Hence, we aim to boost the sample efficiency of MARL by adopting model-based approaches. However, incorporating planning and search methods into multi-agent systems poses significant challenges. The expansive action space of multi-agent systems often necessitates leveraging the nearly-independent property of agents to accelerate learning. To tackle this issue, we propose the MAZero algorithm, which combines a centralized model with Monte Carlo Tree Search (MCTS) for policy search. We design a novel network structure to facilitate distributed execution and parameter sharing. To enhance search efficiency in deterministic environments with sizable action spaces, we introduce two novel techniques: Optimistic Search Lambda (OS(λ)) and Advantage-Weighted Policy Optimization (AWPO). Extensive experiments on the SMAC benchmark demonstrate that MAZero outperforms model-free approaches in terms of sample efficiency and provides comparable or better performance than existing model-based methods in terms of both sample and computational efficiency. Our code is available at https://***/liuqh16/MAZero. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Multi agent systems

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A novel 3D-Space Vector Modulation for Three single-phase combined 400Hz Ground Power Unit 12

A novel 3D-Space Vector Modulation for Three single-phase co...

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12th IEEE International Conference on control, automation and Information Sciences, ICCAIS 2023

作者： Que, Son Tran Van Diep, Huynh Dich, Nguyen Quang Trung, Nguyen Kien Hanoi University of Science and Technology Institute for Control Engineering and Automation Ha Noi Viet Nam Hanoi University of Science and Technology Department of Industrial Automation Ha Noi Viet Nam

ISBN: (纸本)9798350328783

The three single-phase combined (TSC) topology has been ruling the power converter industries for many years. In this research, TSC topology with Lithium Battery DC source is proposed for 400Hz Ground Power Unit (GPU) due to its advantages particularly in increasing the system flexibility and reliability. Sinusoidal Pulse Width Modulation (SPWM) is one of the most viable PWM techniques for inverter, however, it is shown that SPWM has no good contribution on three phase control system, hence, Space Vector Modulation (SVM) technique is now more widely used. This paper proposes a novel effectual three-dimensional Space Vector Modulation (3D-SVM) technique for three single-phase combined inverter, which can provide up to 27 switching states, expanding the possible range to find the best decision boundary to compare with traditional SPWM. The effectiveness of the proposed method is verified through MATLAB simulations. © 2023 IEEE.

关键词： Topology

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Resilient control of Networked control Systems With Hidden DoS Attacks and Unknown Observation Probability

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IEEE Transactions on control of Network Systems 2025年第2期12卷 1313-1323页

作者： Wang, Yuan Yan, Huaicheng Park, Ju H. Zhang, Hao Shen, Hao East China University of Science and Technology School of Information Science and Engineering Shanghai200237 China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education Shanghai200237 China Weifang University College of Machinery and Automation Weifang261061 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of Tongji University Department of Control Science and Engineering Shanghai200092 China Anhui University of Technology School of Electrical and Information Engineering Ma'anshan243002 China

This paper systematically studies the problem of resilient controller design for networked control systems under imperfect communication environments. The denial of service (DoS) attacks in the case of an imperfect network are remodeled. The semi-Markov chain is introduced in this paper to provide a suitable description of random attacks. On this basis, the double-layer stochastic process is constructed, which consists of an attack sequence and an observation one. Second, since the attack modes are inaccessible, a controller is constructed based on the observation sequence by virtue of the emission probability to stabilize the system under random attacks. Due to the complexity of the network, the probability that an observer can accurately detect an attack when it occurs is considered unknown. Based on the introduced double-layer stochastic process, a mode-associated Lyapunov function is constructed to facilitate the stability analysis. Building on this foundation, sufficient conditions that can ensure the δ-error mean square stability of the closed-loop system are derived. In the end, a simulation of the unmanned ground vehicle is presented, showcasing the feasibility and validity of the proposed control scheme. © 2025 IEEE.

关键词： Stochastic systems

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Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic

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computers, Materials & Continua 2023年第4期75卷 427-442页

作者： Reem Alkanhel El-Sayed M.El-kenawy D.L.Elsheweikh Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia

Traffic prediction of wireless networks attracted many researchersand practitioners during the past decades. However, wireless traffic frequentlyexhibits strong nonlinearities and complicated patterns, which makes it challengingto be predicted accurately. Many of the existing approaches forpredicting wireless network traffic are unable to produce accurate predictionsbecause they lack the ability to describe the dynamic spatial-temporalcorrelations of wireless network traffic data. In this paper, we proposed anovel meta-heuristic optimization approach based on fitness grey wolf anddipper throated optimization algorithms for boosting the prediction accuracyof traffic volume. The proposed algorithm is employed to optimize the hyperparametersof long short-term memory (LSTM) network as an efficient timeseries modeling approach which is widely used in sequence prediction *** prove the superiority of the proposed algorithm, four other optimizationalgorithms were employed to optimize LSTM, and the results were *** evaluation results confirmed the effectiveness of the proposed approachin predicting the traffic of wireless networks accurately. On the other hand,a statistical analysis is performed to emphasize the stability of the proposedapproach.

关键词： Network traffic soft computing LSTM metaheuristic optimization

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Intermittent control for Fixed-Time Synchronization of Coupled Networks

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1488-1490页

作者： Yongbao Wu Ziyuan Sun Guangtao Ran Lei Xue the School of Automation Southeast UniversityNanjing 210096China the Department of Applied Mathematics University of WaterlooOntario N2J 4N3Canada the Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China

Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are ... 详细信息

关键词： synchronization Synchronization overcome

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Transforming the Future: An Innovative LiFi Framework to Elevate Sustainability and Security in UAE Smart Cities 10

Transforming the Future: An Innovative LiFi Framework to Ele...

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10th International Conference on engineering and Emerging Technologies, ICEET 2024

作者： Ati, Modafar Jamil, Yaqoob Qadir, Brzo Aziz Abu Dhabi University Department of Computer Science & Information Technology Abu Dhabi United Arab Emirates Erbil Polytechnic University Department of Automation Industrial Technology Engineering Erbil Iraq

ISBN: (纸本)9798331532895

The rapid advancement of smart cities calls for the implementation of cutting-edge communication solutions that are capable of effectively addressing the myriad challenges associated with sustainability and security. This comprehensive research presents the innovative concept of integrating Light-Fidelity (LiFi) technology as a pivotal element for significantly enhancing smart city infrastructures, with a strong emphasis on its application in the United Arab Emirates. By harnessing the exceptional capabilities of light-emitting diodes (LEDs), LiFi offers a significantly low-energy, high-speed alternative to traditional Wi- Fi systems by utilizing visible light as the medium for the transmission of data. This in-depth investigation delves into the various ways through which LiFi enhances security measures by restricting communication to designated areas that are illuminated while simultaneously minimizing overall energy consumption, thus strongly supporting the sustainable development goals aimed at fostering smart cities. The thorough framework assesses the practicality, economic viability, and comprehensive security measures associated with the potential implementation of LiFi in diverse urban settings. Additionally, it proposes a sustainable communication method that effectively combats escalating energy demands, strategically targets areas lacking adequate Wi-Fi coverage, and addresses the prevalent security concerns that are common in densely populated city environments. The detailed results emphasize LiFi's transformative potential to revolutionize urban communication networks, aligning seamlessly with the ambitious aspirations of the UAE towards innovative and sustainable smart city initiatives. © 2024 IEEE.

关键词： Sustainable city

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Quantized Average Consensus With a Plateau Escaping Strategy in Undirected Graphs

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IEEE control Systems Letters 2025年 9卷 709-714页

作者： Oliva, Gabriele Fioravanti, Camilla Makridis, Evagoras Charalambous, Themistoklis University Campus Bio-Medico of Rome Department of Engineering Roma Italy University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia Cyprus Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland

In this paper, the average consensus problem has been considered for undirected networks under finite bit-rate communication. While other algorithms reach approximate average consensus or require global information about the network for reaching the exact average consensus, we propose a fully distributed consensus algorithm that incorporates an adaptive quantization scheme and achieves convergence to the exact average while only requiring knowledge of an upper bound of the network diameter. Using Lyapunov stability analysis, we characterize the convergence properties of the resulting nonlinear quantized system. Moreover, we provide a fully distributed strategy to escape plateaux, i.e., situations where the Lyapunov function stops descending. Simulation results justify the performance of our proposed algorithm. © 2025 IEEE.

关键词： adaptive quantization multi-agent systems plateau escaping strategy Quantized average consensus undirected graphs

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