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13th International Conference on Intelligent control and Information Processing, ICICIP 2025

作者： Zhao, Jin Wang, Jun Han, Min Fan, Jianchao School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Department of Computer Science Department of Data Science City University of HongKong Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798331516147

Marine aquaculture image segmentation plays a crucial role in managing aquatic resources and environmental protection. Traditional deep learning models rely on manual parameter tuning for image segmentation, which limits their efficiency and accuracy. This paper proposes an adaptive Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the U-net model automatically. The algorithm dynamically adjusts the PSO parameters based on the population’s entropy and clustering metrics and employs a hill-climbing algorithm to address the issue of the PSO easily falling into local optima, enhancing the algorithm’s adaptability. The proposed algorithm updates and iterates particles to automatically find suitable model parameters. The remote sensing data used in this experiment were from the Yellow Sea aquaculture area near Dalian, China, with a segmentation accuracy of 91.8%. This method improves segmentation accuracy, reduces the burden of manual parameter tuning, and provides an effective solution for optimizing deep learning models. © 2025 IEEE.

关键词： Aquaculture

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Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

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computers, Materials & Continua 2024年第9期80卷 4475-4496页

作者： Xiwang Guo Liangbo Zhou Zhiwei Zhang Liang Qi Jiacun Wang Shujin Qin Jinrui Cao College of Information and Control Engineering Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Research Center of the Economic and Social Development of Henan East Provincial Joint Shangqiu Normal UniversityShangqiu476000China Department of Computer Science New Jersey City UniversityJersey CityNJ 07305USA

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle *** on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is *** enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular *** established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,*** a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

关键词： Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm

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PVWA: Privacy-preserving and Verifiable Weighted Aggregation for Federated Learning

PVWA: Privacy-preserving and Verifiable Weighted Aggregation...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Li, Zihan Wang, Xiaodong Yuan, Shuai Guan, Zhitao Du, Xiaojiang Guizani, Mohsen North China Electric Power University School of Control and Computer Engineering China Canada Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States Machine Learning Department United Arab Emirates

ISBN: (纸本)9798350351255

Federated learning provides clients with a means of collaboratively training a global model without sharing their local data, managed by a central server. However, this server cannot always be trusted, as it may act dishonestly and compromise the privacy of clients' local data. Consequently, mechanisms for privacy preservation and aggregation verification become crucial components of a secure federated learning system. In addition, support for weighted aggregation is also essential to address the challenges posed by non-IID training data. In this article, we present the Privacy-Preserving and Verifiable Weighted Aggregation (PVWA) scheme. Our approach introduces a new privacy-preserving solution by leveraging masking and homomorphic encryption techniques to protect local and global models, respectively. The masking protocol facilitates secure weighted aggregation, whereas a verification mechanism based upon homomorphic hashing and bilinear aggregated signatures ensures the correctness of aggregated results. Experimental evaluations of the performance, compared against alternative methods on two datasets, demonstrate its effectiveness and efficiency. © 2024 IEEE.

关键词： Federated learning

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Sliding Mode control in Power Converters and Drives: A Review

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 392-406页

作者： Ligang Wu Jianxing Liu Sergio Vazquez Sudip K.Mazumder IEEE Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China Electronic Engineering Department Universidad de Sevilla41092 SevillaSpain Electrical and Computer Engineering Department University of Illinois ChicagoChicagoIL 60607 USA

Sliding mode control(SMC)has been studied since the 1950s and widely used in practical applications due to its insensitivity to matched *** aim of this paper is to present a review of SMC describing the key developments and examining the new trends and challenges for its application to power electronic *** fundamental theory of SMC is briefly reviewed and the key technical problems associated with the implementation of SMC to power converters and drives,such chattering phenomenon and variable switching frequency,are discussed and *** recent developments in SMC systems,future challenges and perspectives of SMC for power converters are discussed.

关键词： Motor drive power electronics systems sliding mode control

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baptti at GeoLingIt: Beyond Boundaries, Enhancing Geolocation Prediction and Dialect Classification on Social Media in Italy 8

baptti at GeoLingIt: Beyond Boundaries, Enhancing Geolocatio...

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8th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop, EVALITA 2023

作者： Koudounas, Alkis Giobergia, Flavio Benedetto, Irene Monaco, Simone Cagliero, Luca Apiletti, Daniele Baralis, Elena Department of Control and Computer Engineering Politecnico di Torino Turin Italy MAIZE Turin Italy

The proliferation of social media platforms has presented researchers with valuable avenues to examine language usage within diverse sociolinguistic frameworks. Italy, renowned for its rich linguistic diversity, provides a distinctive context for exploring diatopic variation, encompassing regional languages, dialects, and variations of Standard Italian. This paper presents our contributions to the GeoLingIt shared task, focusing on predicting the locations of social media posts in Italy based on linguistic content. For Task A, we propose a novel approach, combining data augmentation and contrastive learning, that outperforms the baseline in region prediction. For Task B, we introduce a joint multi-task learning approach leveraging the synergies with Task A and incorporate a post-processing rectification module for improved geolocation accuracy, surpassing the baseline and achieving first place in the competition. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Linguistics

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EverydayFantasy - A Mobile Computing Application in Mental Healthcare 18

EverydayFantasy - A Mobile Computing Application in Mental H...

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18th Iberian Conference on Information Systems and Technologies, CISTI 2023

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

ISBN: (纸本)9789893347928

The paper proposes a game, EverydayFantasy, based on the principles of serious games, game mechanics and gamification and intended for young people with cognitive behavior issues. The game is a mobile computing application in mental healthcare, in the architecture of which is integrated the connection to a database through a server and the use of dedicated APIs such as the one for locating on the map. The game creates a fantasy environment superimposed on the real environment in which the player is motivated to move, socialize and solve different challenges, all to improve his estimated state. © 2023 ITMA.

关键词： Serious games

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State Observer Design for a Class of Rational Nonlinear Systems 32

State Observer Design for a Class of Rational Nonlinear Syst...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Saraiva, Eduardo Scheffer Salton, Aurelio Tergolina Cristofaro, Andrea Universidade Federal do Rio Grande do Sul Department of Electrical Engineering Porto Alegre Brazil Sapienza University of Rome Department of Computer Control and Management Engineering Italy

ISBN: (纸本)9798350395440

This paper presents a novel methodology for the synthesis of state observers for a class of systems subject to rational nonlinearities. The key idea is to represent both the system and the observer in the so-called differential-algebraic representation in order to obtain the error dynamics. Once achieved, design conditions can be formulated through optimization problems subject to constraints in the form of linear matrix inequalities. This approach enables the development of a systematic observer design framework with formal theoretical guarantees, including the asymptotic stabilization of the error within a specified exponential decay rate along with constraints on the observer gains. A post-synthesis analysis is presented to ensure the stability of the plant considering the feedback of the estimated states. An illustrative example is provided to showcase the proposed method. © 2024 IEEE.

关键词： Linear matrix inequalities

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HKB-YOLO: transmission line fire detection method based on hierarchical feature fusion

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International Journal of Security and Networks 2024年第4期19卷 188-198页

作者： Ying, Zhilei Meng, Yanan Chen, Ruoxi Lou, Jianlou School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin 132022 China Department of Automation Jilin Institute of Chemical Technology Jilin 132022 China School of Computer Engineering Northeast Electric Power University Jilin 132012 China

Timely transmission line fire inspections are vital for power system safety. Although deep learning models are widely used for flame detection, struggle with small target recognition due to background interference and are vulnerable to input data perturbations, posing security risks. This study introduces a hierarchical feature fusion method based on the you only look once Version 8 (YOLOV8) framework. It employs high-performance GPU network version 2 (HGNetV2) to enhance small-target feature extraction while reducing computational complexity. A spatial pyramid pooling-fast module with large separable kernel attention is designed to highlight key features and suppress background noise. The proposed bidirectional slim neck structure (BiSlimneck) reduces feature loss. Adversarial training enhances the model’s robustness. Experimental results show a 1.4% accuracy improvement, with a reduction in parameters and complexity by 18.3% and 21.6%, respectively. After adversarial training, the accuracy of the network in the face of attacks increased by 10% compared to the pre-training. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Premixed flames

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Two-Stage Incentive Mechanism Based on a Cooperative Mode: A Stackelberg Game Approach

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IEEE Internet of Things Journal 2025年第13期12卷 24722-24737页

作者： Wang, Long Wang, Yingjie Teng, Haojun Jiao, Xiuzhen Sun, Meimei Yang, Jishen Cai, Zhipeng Yantai University School of Computer and Control Engineering Yantai264005 China China Judicial Big Data Research Institute Co. Ltd China Naval Aviation University China Georgia State University Department of Computer Science AtlantaGA30303 United States

With the explosive growth of mobile data, Mobile Crowd Sensing (MCS) has become a popular paradigm for large-scale data collection. The difficulty of data collection and the gaps in workers’ sensing capabilities are key factors to consider in worker recruitment and task assignment. To address these issues, we designed a two-stage cooperative incentive mechanism. In the first stage, a shelving level is introduced to assess task difficulty. Tasks are divided into high-quality and low-quality groups based on quality scores, while workers are categorized into high-ability and low-ability groups based on their historical performance. The Improved Chaotic Particle Swarm Optimization (ICPSO) algorithm is then applied to generate optimal task combinations. In the second stage, we address benefit distribution among cooperating workers by introducing time-dependent rewards and employing Stackelberg game theory to analyze the optimal completion time for both high-ability and low-ability workers. This analysis determines the optimal reward distribution and ability value allocation, with proof of the existence and uniqueness of a Nash equilibrium. Comparative experiments conducted on real-world datasets demonstrate that our cooperative task mechanism outperforms existing task bundling methods, validating its rationality and effectiveness. © 2014 IEEE.

关键词： Nash equilibrium

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Transient Angle Stability of Inverters Equipped with Robust Droop control

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CSEE Journal of Power and Energy Systems 2023年第2期9卷 659-670页

作者： Chen Qi Keyou Wang Qing-Chang Zhong Jin Xu Guojie Li Key Laboratory of Control of Power Transmission and Conversion Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIllinois60616USA

Transient angle stability of inverters equipped with the robust droop controller is investigated in this *** first,the conditions on the control references to guarantee the existence of a feasible post-disturbance operating point are ***,the post-disturbance equilibrium points are found and their stability properties are ***,the attraction regions of the stable equilibrium points are accurately depicted by calculating the stable and unstable manifolds of the surrounding unstable equilibrium points,which presents an explanation to system transient ***,the transient control considerations are provided to help the inverter ridethrough the disturbance and maintain its stability *** is shown that the transient angle stability is not a serious problem for droop controlled inverters with proper control settings.

关键词： Droop controlled inverter equilibrium point transient angle stability (un)stable manifold

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