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A Multi-Objective Particle Swarm Optimization Algorithm Based on Decomposition and Multi-Selection Strategy

Computers, Materials & Continua 2025年第1期82卷 997-1026页

作者： Li Ma Cai Dai Xingsi Xue Cheng Peng School of Computer Science Shaanxi Normal UniversityXi’an710119China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China information Construction and Management Center and institute of Artificial Intelligence and Educational New Productivity Ningxia Normal UniversityGuyuan756099China

The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization *** the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search ***,two update strategies based on decomposition are used to update the evolving population and external archive,***,a multiselection strategy is *** first strategy is for the subspace without a non-dominated *** the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global *** second strategy is for the subspace with a non-dominated *** the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local *** third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated *** the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to ***,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search ***,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test *** results show that the proposed algorithm has better performance.

关键词： Multi-objective optimization multi-objective particle swarm optimization decomposition multi-selection strategy

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High resolution radar target adaptive detector and performance assessment

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Journal of Systems Engineering and Electronics 2011年第2期22卷 212-218页

作者： Tao Jian You He Feng Su Changwen Qu Dianfa Ping Research institute of information fusion Naval Aeronautical and Astronautical University Yantai 264001 P. R. China

The high resolution radar target detection is addressed in the non-Gaussian clutter. An adaptive detector is derived for range-spread target based on a novel covariance matrix estimator. It is proved that the new detector is constant false alarm rate （CFAR） to both of the clutter covariance matrix structure and power level theoretically for match cases. The simulation results show that the new detector is almost CFAR for mismatch cases, and it outperforms the existing adaptive detector based on the sample covariance matrix. It also shows that the detection performance improves, as the number of pulses, the number of secondary data or the clutter spike increases. In addition, the derived detector is robust to different subsets, estimated clutter group sizes and correlations of clutter. Importantly, the number of iterations for practical application is just one.

关键词： non-Gaussian clutter adaptive detection range-spread target performance assessment.

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Highly maneuvering target tracking using multi-parameter fusion Singer model

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Journal of Systems Engineering and Electronics 2017年第5期28卷 841-850页

作者： Shuyi Jia Yun Zhang Guohong Wang Research institute of information fusion Naval Aeronautical and Astronautical University Department of Aircraft Engineering Naval Aeronautical and Astronautical University

An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.

关键词： maneuvering target multi-parameter fusion Singer (MF-Singer) fuzzy reasoning Singer model

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Joint range ambiguity resolving and multiple maneuvering targets tracking in clutter via MMPHDF-DA

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Science China(information Sciences) 2014年第8期57卷 117-128页

作者： TAN ShunCheng WANG GuoHong WANG Na YU HongBo institute of information fusion Technology Naval Aeronautical and Astronautical University Unit 92941 93 Element

It is difficult to track multiple maneuvering targets of which the number is unknown and timevarying,especially when there is range *** random finite sets(RFS)based probability hypothesis density filter(PHDF)is an effective solution to the problem of multiple targets ***,when tracking multiple targets via the range ambiguous radar,the problem of range ambiguity has to be *** this paper,a multiple model PHDF and data association(MMPHDF-DA)based method is proposed to address multiple maneuvering targets tracking with range ambiguous radar in ***,by introducing the turn rate of target and the discrete pulse interval number(PIN)as components of target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the problem of multiple maneuvering targets tracking with range ambiguity is converted into a hybrid state filtering ***,by implementing a novel"track-estimate"oriented association with the filtering results of the hybrid filter,target tracks are provided at each time *** results demonstrate that the MMPHDF-DA can estimate target state as well as the PIN simultaneously,and succeeds in multiple maneuvering target tracking with range ambiguity in *** results also demonstrate that the MMPHDF-DA can overcome the limitation of the Chinese Remainder Theorem for range ambiguity resolving.

关键词： probability hypothesis density particle filter range ambiguity maneuvering target tracking data association

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Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

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Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University institute of information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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Orbitronics for energy-efficient magnetization switching

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Science China(information Sciences) 2025年第1期68卷 398-399页

作者： Yuxuan YAO Daoqian ZHU Qingtao XIA Jianing LIANG Yuhao JIANG Zhiyang PENG Jiaxu LI Chen XIAO Renyou XU Wenwen WANG Xiantao SHANG Shiyang LU Dapeng ZHU Hong-Xi LIU Kaihua CAO Weisheng ZHAO Fert Beijing institute School of Integrated Circuit Science and Engineering Beihang University National Key Lab of Spintronics Institute of International Innovation Beihang University Qingdao Research institute Beihang University Truth Memory Corporation

Spin-orbit torque （SOT）,as a promising writing method for magnetic random-access memory （MRAM）,has garnered widespread interest for over a decade [1].Heavy metals,such as β-W,have been broadly adopted as spin current sources,but suffer from phase change at a limited thickness,resulting in a dramatic reduction of the charge-tospin conversion efficiency θSH[2].The thickness limitation leads to stringent etching conditions and large distribution among devices,posing challenges for simultaneously satisfying SOT efficiency,etching-stop margins,and back-end-ofline （BEOL） compatibility.

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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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镉合金化对溶液法制备CZTSSe太阳电池的影响:形貌、能带排列和效率提高（英文）

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Science China Materials 2025年

作者：郑媛元相春旭龚元才李沂泽肖仕梁郭浩宇马乘风王少荧闫伟博黄维辛颢 State Key Laboratory for Organic Electronics and information Displays Institute of Advanced Materials Nanjing University of Posts & Telecommunications

锌黄锡矿结构的Cu2ZnSn（S,Se）4（CZTSSe）薄膜太阳能电池因其理论效率高、地球丰富且低毒性的元素组成而被认为是可持续光伏应用的有前景的候选者.然而,其性能受到CuZn反位缺陷及相关缺陷簇的制约,因为这些缺陷会造成有害的能带拖尾...

锌黄锡矿结构的Cu2ZnSn（S,Se）4（CZTSSe）薄膜太阳能电池因其理论效率高、地球丰富且低毒性的元素组成而被认为是可持续光伏应用的有前景的候选者.然而,其性能受到CuZn反位缺陷及相关缺陷簇的制约,因为这些缺陷会造成有害的能带拖尾和非辐射复合.用具有较大离子半径的Cd替代Zn已被证明能有效抑制非辐射复合,最高可实现11.73%的效率.然而,Cd合金化对CZTSSe电池吸收层形貌、电学性能和器件性能的影响尚未得到充分研究.在本工作中,采用Cu+-Sn4+-DMSO溶液体系,我们成功地在全浓度范围内将Cd2+引入到CZTSSe晶格中,系统地研究了Cd合金化的作用.结果表明,Cd合金化促进了晶粒生长,在低浓度时能得到平整紧密的吸收层薄膜,但在高浓度时则出现过度晶粒生长.此外,低Cd含量能够抑制晶格无序,从而减少能带拖尾Cd的掺入可以通过提高价带顶和降低导带底来线性降低带隙,从而增加异质结的导带偏移（CBO）,但在低Cd含量（<50%）时仍保持相对理想的值（<0.3 eV）.特别是在Cd合金化浓度为5%时,CZTSSe太阳能电池实现了13.31%的最佳效率（无减反层）,相较于未合金化的原始器件性能提高了超过7.0%,这归功于改善的薄膜性能、理想的CBO （<0.24 eV）和界面复合的有效抑制.然而,高浓度Cd合金化可能会导致吸收层薄膜质量变差,出现大量空洞,而且在50%Cd合金化时,晶体结构从锌黄锡矿结构转变为黄锡矿结构,导致器件性能显著恶化.

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Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

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Computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and information Security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

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