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2024 International Conference on Machine Learning, Pattern Recognition and automation engineering, MLPRAE 2024

作者： Rao, Jinjun Wang, Cong Liu, Mei Lei, Jingtao Giernacki, Wojciech Department of Precision Mechanical Engineering School of Mechatronic Engineering and Automation Shanghai University China Institute of Robotics and Machine Intelligence Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Poland

ISBN: (纸本)9798400709876

Aiming at the problem that the combination of self-play (SP) and deep reinforcement learning (DRL) only involves two-party games and the policy learning of each party is limited, a multi-party asymmetric self-play algorithm (MASP) is proposed. Firstly, by improving the ELO scoring system, the ELO scoring takes into account each party of the unmanned surface vehicle (USV) clusters, and the imbalance of the number of USV clusters, so that the frequency of exchanging strategies of all USV clusters in the confrontation process is equal. Secondly, it ensures that USV clusters have a balanced combat ability, and at the same time ensures that the combat ability of all parties is strong and weak and the gap is not too wide. In addition, the parameters are dynamically set to reduce the update frequency of the policy of the stronger party. The experimental results show that the MASP can make the USV clusters learn more effective policies, have a shorter game time, and obtain higher rewards and ELO scores in the simple 2v2 adversarial game scenario and the three-party game scenario of a warship escort mission. © 2024 ACM.

关键词： Deep reinforcement learning

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An Advanced Rivest Cipher 4 Algorithm to Transfer Fast and Secure Data Using Li-Fi Technology 13

An Advanced Rivest Cipher 4 Algorithm to Transfer Fast and S...

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13th IEEE International Conference on System engineering and Technology, ICSET 2023

作者： Msallam, Mohammed Majid Samet, Refik Ankara University Computer Engineering Department Ankara Turkey University of Technology Control and Systems Engineering Department Baghdad Iraq

ISBN: (纸本)9798350340891

The Light-Fidelity (Li-Fi) is a wireless communication technology that is light-based and can complete wireless fidelity (Wi-Fi) technologies for many applications. Li-Fi technology which uses light spectrum is a technology for solving the lack of radio spectrum at Wi-Fi. One of the main benefits of Li-Fi technology is the ability to communicate by light with a high level of safety. However, the signal of Li-Fi technology is the same as other signals that are susceptible to eavesdropping because no security system is infallible. The objective of this paper is to decrease the computational cost of encryption and decryption and keep the security of transformed data when transmitted via Li-Fi technology. This study proposes the advanced Rivest Cipher 4 (ARC4) algorithm that will be used in the physical layer of Li-Fi applications. The novelty will be in the pseudo-random generation algorithm (PRGA) which is part of Rivest Cipher 4 (RC4). The data will become an index of the s-array and get the value of that index in the s-array instead of using the XOR operation. The proposed ARC4 was evaluated by the National Institute of Science and Technology (NIST) test. The obtained results illustrate that ARC4 is more robust and effective than RC4 when the data is transformed by Li-Fi communication. © 2023 IEEE.

关键词： Wi-Fi

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Large Language Models for topic analysis: Insights from robotic accident narratives 6

Large Language Models for topic analysis: Insights from robo...

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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Costantino, Francesco Sabetta, Nicolò Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

The integration of robotics in manufacturing has significantly enhanced productivity and safety by performing hazardous tasks. However, it also introduces new risks and accident profiles that require thorough analysis. This study explores the application of Large Language Models (LLMs) for topic modeling on accident narratives from the Occupational Safety and Health Administration (OSHA) database, focusing on incidents involving robots. Advanced Natural Language Processing (NLP) techniques, specifically LLMs, were employed to uncover prevalent themes, common risk factors, and patterns in these narratives. The methodology includes data collection, text processing, statistical analysis, and various topic modeling techniques. The analysis identifies six topics, and key themes including maintenance-related accidents, types of machinery involved, and specific body parts frequently affected. The findings highlight critical areas for improving safety measures, such as rigorous lockout/tagout procedures and enhanced training for maintenance personnel. This study provides a novel approach to analyze accident narratives. © 2025 The Author(s).

关键词： Collaborative robots

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Feedback Optimization of Nonlinear Strict-Feedback Systems

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Journal of Systems Science & Complexity 2025年第2期38卷 717-738页

作者： LIU Tong LIU Tengfei JIANG Zhong-Ping Department of Electrical and Computer Engineering New York University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

Feedback optimization aims at regulating the output of a dynamical system to a value that minimizes a cost function. This problem is beyond the reach of the traditional output regulation theory, because the desired value is generally unknown and the reference signal evolves according to a gradient flow using the system's real-time output. This paper complements the output regulation theory with the nonlinear small-gain theory to address this challenge. Specifically, the authors assume that the cost function is strongly convex and the nonlinear dynamical system is in lower triangular form and is subject to parametric uncertainties and a class of external disturbances. An internal model is used to compensate for the effects of the disturbances while the cyclic small-gain theorem is invoked to address the coupling between the reference signal, the compensators, and the physical system. The proposed solution can guarantee the boundedness of the closed-loop signals and regulate the output of the system towards the desired minimizer in a global sense. Two numerical examples illustrate the effectiveness of the proposed method.

关键词： Feedback optimization internal model output regulation small-gain theorem

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Predefined performance-based model-free adaptive fractional-order fast terminal sliding-mode control of MIMO nonlinear systems

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ISA Transactions 2022年 131卷 108-123页

作者： Esmaeili, Babak Salim, Mina Baradarannia, Mahdi Department of Control Engineering Faculty of Electrical and Computer Engineering University of Tabriz 29 Bahman Blvd. Tabriz *** Iran

The purpose of this article is to tackle with the problem of data-driven robust control of multi-input multi-output discrete-time nonlinear plants under tracking error constraints and output perturbations. Thereby, based upon the concept of dynamic linearization, a novel predefined performance based model-free adaptive fractional-order fast terminal sliding-mode controller is proposed so that the tracking errors can converge and remain within a preassigned neighborhood. The presented approach does solely rely on the real-time input/output data of the process, and the transient response together with the steady-state manner of the errors can be arbitrarily predefined. In the meantime, the closed-loop behavior is investigated by mathematical analysis, and the efficiency of the method is validated through various simulation examples. © 2022 ISA

关键词： MIMO systems

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FRCD: Future Ready Career-Duck a Machine Learning-Driven Career Guidance for Students

FRCD: Future Ready Career-Duck a Machine Learning-Driven Car...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Paritosh, Priyanshu Yadav, Vedant Gupta, Dev Biswas, Ujjwal Indian Institute of Information Technology Bhagalpur Department of Mechatronics and Automation Engineering Bhagalpur India Indian Institute of Information Technology Bhagalpur Department of Computer Science and Engineering Bhagalpur India

ISBN: (纸本)9798331540821

In today's society, finding a suitable career is crucial. High school students frequently need to fully understand the notion of labor due to a lack of experience and practical knowledge in various disciplines. This renders students particularly vulnerable to external influences while deciding on a career path. As a result, students must carefully consider high-paying careers to ensure that they align with their interests and skills. Otherwise, students may end up in jobs they dislike or are not suited to. In response to this issue, we intend to develop a machine-learning framework capable of predicting career pathways. Students will receive career recommendation from our model based on their performance and potential. Students can confidently follow their chosen fields if they do well academically;if not, they can choose to change to other fields that better suit them. There are challenges in determining the metrics and improving prediction accuracy to quantify students' career paths and performance in teaching-learning. Best on the test results, the proposed model has a higher prediction accuracy. Also, this method is both reliable and portable, and it may be used to predict career paths in real time. © 2024 IEEE.

关键词： Students

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Doped low-density parity-check codes

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Digital Communications and Networks 2024年第1期10卷 217-226页

作者： Yong Li Rui Liu Xianlong Jiao Youqiang Hu Zhen Luo Francis C.M.Lau College of Computer Science Chongqing UniversityChongqing400044China School of Automation Chongqing UniversityChongqing400044China College of Electronic and Information Engineering Southwest UniversityChongqing400715China Future Wireless Networks and IoT Focusing Area Department of Electronic and Information EngineeringHong Kong Polytechnic UniversityHong KongChina

In this paper,we propose a doping approach to lower the error floor of Low-Density Parity-Check(LDPC)*** doping component is a short block code in which the information bits are selected from the coded bits of the dominant trapping sets of the LDPC ***,an algorithm for selecting the information bits of the short code is proposed,and a specific two-stage decoding algorithm is *** results demonstrate that the proposed doped LDPC code achieves up to 2.0 dB gain compared with the original LDPC code at a frame error rate of 10^(-6)Furthermore,the proposed design can lower the error floor of original LDPC Codes.

关键词： LDPC codes Doped LDPC codes Tanner graph Quadratic residue codes Trapping sets

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Segment differential aggregation representation and supervised compensation learning of ConvNets for human action recognition

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Science China(Technological Sciences) 2024年第1期67卷 197-208页

作者： REN ZiLiang ZHANG QieShi CHENG Qin XU ZhenYu YUAN Shuai LUO DeLin School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin 541004China Department of the mechanical engineering Erlangen-Nuremberg UniversityErlangen 91508Germany School of Aerospace Engineering Xiamen UniversityXiamen 361102China

With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive ***,one of the main challenges is to effectively extract complementary features from different modalities for action *** this work,a novel multimodal supervised learning framework based on convolution neural networks(Conv Nets)is proposed to facilitate extracting the compensation features from different modalities for human action *** on information aggregation mechanism and deep Conv Nets,our recognition framework represents spatial-temporal information from the base modalities by a designed frame difference aggregation spatial-temporal module(FDA-STM),that the networks bridges information from skeleton data through a multimodal supervised compensation block(SCB)to supervise the extraction of compensation *** evaluate the proposed recognition framework on three human action datasets,including NTU RGB+D 60,NTU RGB+D 120,and *** results demonstrate that our model with FDA-STM and SCB achieves the state-of-the-art recognition performance on three benchmark datasets.

关键词： action recognition segment frame difference aggregation supervised compensation learning ConvNets

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Improving Power Response of Single-controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

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Complex System Modeling and Simulation 2025年第1期5卷 46-67页

作者： Benxue Lu Kaizhou Gao Peiyong Duan Adam Slowik School of Computer Science Liaocheng UniversityLiaocheng 252000China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Information and Automation Engineering Qilu University of TechnologyJinan 250353China Department of Electronics and Computer Science Koszalin University of TechnologyKoszalin 75-453Poland

This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy ***,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical ***,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_***,fourteen local search operators are employed to search for better *** different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration ***,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different *** experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned *** study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.

关键词： hybrid flow shop scheduling Q-learning lot streaming local search

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