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Efficient Hybrid Multi-Population Genetic Algorithm for Multi-UAV Task Assignment in Consumer Electronics Applications

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IEEE Transactions on Consumer Electronics 2025年

作者： Bai, Xiaoshan Jiang, Haoyu Li, Chao Ullah, Inam Dabel, Maryam M. Al Bashir, Ali Kashif Wu, Zongze Sam, Shuzhi Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen University Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan University of Hafr Al Batin Department of Computer Science and Engineering College of Computer Science and Engineering Saudi Arabia Manchester Metropolitan University Manchester United Kingdom Shenzhen518060 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp

关键词： Genetic algorithms

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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

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One Solution for Deterministic Scheduling on GPU for Automotive Algorithms

One Solution for Deterministic Scheduling on GPU for Automot...

引用

2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Kenjic, Dusan Milosevic, Milena Antic, Marija Teslic, Nikola University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Novi Sad Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9781665404174

In order for higher levels of autonomous driving to be achieved, the demanding environmental perception and decision-making algorithms are developed. Meeting real-time system requirements is a mandatory task for all of these algorithms to be properly utilized. In order to meet these requirements, GPUs are widely used, and one of the biggest challenges is providing the deterministic scheduling of different tasks on GPU based on their priority classes. The complete determinism which ensures the absolute control of processes on GPU has still not been achieved. In this paper, we propose and evaluate one method that allows scheduling of tasks with different types of time constraints. © 2021 IEEE.

关键词： Scheduling

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State-Feedback control Design for Polynomial Discrete-Time Systems obtained via Second-Order Runge-Kutta Discretization

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IFAC-PapersOnLine 2024年第5期58卷 13-19页

作者： Priscila F.S. Guedes Márcio J. Lacerda Erivelton Nepomuceno Control and Modelling Group (GCOM) Department of Electrical Engineering Federal University of São João del-Rei - UFSJ São João del-Rei MG Brazil Centre for Communications Technology School of Computing and Digital Media London Metropolitan University UK Centre for Ocean Energy Research Department of Electronic Engineering Maynooth University Ireland

This paper addresses the state-feedback control problem for the class of state-polynomial discrete-time systems. The continuous-time polynomial nonlinear model is discretized by the second-order Runge-Kutta method. The Lyapunov theory and the exponential stability were employed to derive the conditions. The sum of squares formulation was used to check the constraints. Two approaches are presented, the first makes use of the Lyapunov function to recover the gain matrices. While the second formulation allows the design of rational state feedback control gains. We evaluated the impact of the step size used in the discretization process in the results. Numerical experiments were used to illustrate the potential of the proposed technique.

关键词： State-feedback control State polynomial systems Second-order Runge-Kutta method Computer arithmetic

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Protecting Personalized Trajectory with Differential Privacy under Temporal Correlations

Protecting Personalized Trajectory with Differential Privacy...

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IEEE Conference on Wireless Communications and Networking

作者： Mingge Cao Haopeng Zhu Minghui Min Yulu Li Shiyin Li Hongliang Zhang Zhu Han School of Information and Control Engineering China University of Mining and Technology Xuzhou China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of CyberScience and Engineering Wuhan University Wuhan China School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering University of Houston Houston TX USA

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Location-based services (LBSs) in vehicular ad hoc networks (VANETs) offer users numerous conveniences. However, the extensive use of LBSs raises concerns about the privacy of users' trajectories, as adversaries can exploit temporal correlations between different locations to extract personal information. Additionally, users have varying privacy requirements depending on the time and location. To address these issues, this paper proposes a personalized trajectory privacy protection mechanism (PTPPM). This mechanism first uses the temporal correlation between trajectory locations to determine the possible location set for each time instant. We identify a protection location set (PLS) for each location by employing the Hilbert curve-based minimum distance search algorithm. This approach incor-porates the complementary features of geo-indistinguishability and distortion privacy. We put forth a novel Permute-and-Flip mechanism for location perturbation, which maps its initial application in data publishing privacy protection to a location perturbation mechanism. This mechanism generates fake locations with smaller perturbation distances while improving the balance between privacy and quality of service (QoS). Simulation results show that our mechanism outperforms the benchmark by providing enhanced privacy protection while meeting user's QoS requirements.

关键词： Privacy Correlation Publishing Perturbation methods Simulation Vehicular ad hoc networks Quality of service

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Mitigating the Negative Impact of Over-association for Conversational Query Production

arXiv

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arXiv 2024年

作者： Wang, Ante Song, Linfeng Min, Zijun Xu, Ge Wang, Xiaoli Yao, Junfeng Su, Jinsong School of Information Xiamen University Xiamen China Xiamen Key Laboratory of Intelligent Storage and Computing Xiamen China Tencent AI Lab BellevueWA United States College of Computer and Control Engineering Minjiang University Fuzhou China

Conversational query generation aims at producing search queries from dialogue histories, which are then used to retrieve relevant knowledge from a search engine to help knowledge-based dialogue systems. Trained to maximize the likelihood of gold queries, previous models suffer from the data hunger issue, and they tend to both drop important concepts from dialogue histories and generate irrelevant concepts at inference time. We attribute these issues to the over-association phenomenon where a large number of gold queries are indirectly related to the dialogue topics, because annotators may unconsciously perform reasoning with their background knowledge when generating these gold *** carefully analyze the negative effects of this phenomenon on pretrained Seq2seq query producers and then propose effective instance-level weighting strategies for training to mitigate these issues from multiple perspectives. Experiments on two benchmarks, Wizard-of-Internet and DuSinc, show that our strategies effectively alleviate the negative effects and lead to significant performance gains (2% ∼ 5% across automatic metrics and human evaluation). Further analysis shows that our model selects better concepts from dialogue histories and is 10 times more data efficient than the baseline. The code is available at https://***/DeepLearnXMU/QG-OverAsso. © 2024, CC BY.

关键词： Structured Query Language

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Drives and Impulses: Shaping Motivation and Procedural Learning for Humanoid Robots

Drives and Impulses: Shaping Motivation and Procedural Learn...

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IEEE International Conference on Development and Learning, ICDL

作者： Leonardo L. Rossi Letícia Berto Paula D. P. Costa Ricardo Gudwin Esther Colombini Alexandre Simões School of Electrical and Computer Engineering University of Campinas Campinas Brazil Hub for Artificial Intelligence and Cognitive Architectures (H.IAAC) Campinas Brazil Institute of Computing University of Campinas Campinas Brazil Department of Control and Automation Engineering São Paulo State University Sorocaba Brazil

ISBN: (数字)9798350348552

ISBN: (纸本)9798350348569

In the emerging field of robotics, the initial development of robots handling basic tasks represented a revolutionary breakthrough. With ongoing advancements in science and technology, we anticipate the integration of artificial entities into diverse environments, performing a range of tasks autonomously. This necessitates the cultivation of intelligence and adaptability in these agents. To achieve this, agents must make informed decisions, considering environmental consequences. Motivation becomes pivotal, guiding decision-making and behavior toward fulfilling the agent's needs, drawing inspiration from human adeptness driven by motivation. This research endeavors to adapt two distinct motivation theories from human literature for the learning process of artificial agents. Employing a cognitive architecture, our investigation involves the learning process of a simulated humanoid robot, incorporating two distinct motivation systems: (i) behaviors driven by enduring needs and (ii) behaviors arising from impulses linked to temporary needs. The primary aim is to enhance comprehension of behaviors under diverse motivational frameworks within artificial cognitive agents and give insights into the direction of autonomous robots.

关键词： Affordances Scalability Decision making Humanoid robots External stimuli Learning (artificial intelligence) Drives

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Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

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Computers, Materials & Continua 2023年第2期74卷 2379-2395页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences 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 General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Electrocardiogram(ECG)signal is a measure of the heart’s electrical ***,ECG detection and classification have benefited from the use of computer-aided systems by *** goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization(DTO)and Differential Evolution Algorithm(DEA)into a unified algorithm to optimize the hyperparameters of neural network(NN)for boosting the ECG classification *** addition,we proposed a new feature selection method for selecting the significant feature that can improve the overall *** prove the superiority of the proposed approach,several experimentswere conducted to compare the results achieved by the proposed approach and other competing ***,statistical analysis is performed to study the significance and stability of the proposed approach using Wilcoxon and ANOVA *** results confirmed the superiority and effectiveness of the proposed *** classification accuracy achieved by the proposed approach is(99.98%).

关键词： Electrocardiogram differential evolution algorithm dipper throated optimization neural networks

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FRNet: A Full-Resolution Convolutional Neural Network for OCTA Vascular Segmentation

FRNet: A Full-Resolution Convolutional Neural Network for OC...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Liang Wang Dongxu Gao Hongwei Gao Guozhang Jiang Zhaojie Ju School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China School of Computing England University of Portsmouth Britain Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

Optical coherence tomography angiography (OCTA) is an advanced, non-invasive imaging technique. Automatic segmentation of vascular networks in retinal OCTA images is essential for the early diagnosis and progression assessment of various vision-related diseases. However, most existing methods for OCTA image vessel segmentation rely on encoder-decoder architectures, which typically involve a high number of parameters and result in slower inference speeds. In this paper, we introduce FRNet V2, an accurate and efficient neural network specifically designed for retinal vessel segmentation in OCTA images. This is achieved by integrating a modified recursive ConvNeXt V2 block and a recursive HAAM attention mechanism into a full-resolution convolutional network framework. We evaluate our proposed method on two large public datasets: ROSSA and OCTA-500. Experimental results demonstrate that our network achieves performance on par with other methods, while boasting significantly fewer parameters and faster inference speeds. This makes it highly suitable for practical industrial applications.

关键词： Image segmentation Accuracy Three-dimensional displays Computational modeling Angiography Optical coherence tomography Neural networks Object segmentation Retinal vessels Convolutional neural networks

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Intelligent 3D Visual defect Detection for Industrial Applications 3

Intelligent 3D Visual defect Detection for Industrial Applic...

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2022 3rd International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022

作者： Yang, Rui Ke, Hualin Gan, Lin Li, Yuhong Hu, Ruihan Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Guangdong Key Laboratory of Modern Control Technology Guangdong Institute of Intelligent Manufacturing Guangzhou China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery Shihezi University Shihezi China

Currently, new energy industries such as electric vehicles and energy storage batteries are experiencing rapid growth throughout the world. As a recognized ideal energy storage element, lithium batteries have also attracted considerable interest. To improve image contrast, the industry employs image preprocessing algorithms. Due to the high requirement of image consistency in the template matching method, which is difficult to meet in practice, and the large apparent difference between defects, it is challenging to design features. Therefore, the framework for defect detection is based on a method of deep learning with strong feature expression capability. In light of the severe imbalance in the number of samples in defect detection, data augmentation and generation methods are used to simulate real samples in order to improve the training effect of deep neural networks and alleviate the burden of data annotation to some extent. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Lithium batteries

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