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A mixed Nash equilibrium solution for visibility-based pursuit-evasion game with multiple obstacles

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science China(information sciences) 2024年第9期67卷 330-332页

作者： Shaoming BU Li LIANG Youqing WANG college of information science and Technology Beijing University of Chemical Technology

This study primarily investigates a visibility-based pursuitevasion game with multiple obstacles. The pursuer aims to maintain surveillance over the evader as long as possible, while the evader's objective is to escape the pursuer's surveillance as quickly as possible. We use the explicit strategy method to analyze the winning conditions and optimal strategy of the player in the case of corner obstacles and propose a 'Present-Future-Past'(PFP) loop structure to extend the strategy to the case of multiple obstacles.

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Quantum circuit-based proxy blind signatures:A novel approach and experimental evaluation on the IBM quantum cloud platform

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Chinese Physics B 2024年第5期33卷 247-253页

作者：娄小平昝慧茹徐雪娇 college of information science and Engineering Hunan Normal UniversityChangsha 410081China

This paper presents a novel approach to proxy blind signatures in the realm of quantum circuits,aiming to enhance security while safeguarding sensitive *** main objective of this research is to introduce a quantum proxy blind signature(QPBS)protocol that utilizes quantum logical gates and quantum measurement *** QPBS protocol is constructed by the initial phase,proximal blinding message phase,remote authorization and signature phase,remote validation,and de-blinding *** innovative design ensures a secure mechanism for signing documents without revealing the content to the proxy signer,providing practical security authentication in a quantum environment under the assumption that the CNOT gates are securely *** existing approaches,our proposed QPBS protocol eliminates the need for quantum entanglement preparation,thus simplifying the implementation *** assess the effectiveness and robustness of the QPBS protocol,we conduct comprehensive simulation studies in both ideal and noisy quantum environments on the IBM quantum cloud *** results demonstrate the superior performance of the QPBS algorithm,highlighting its resilience against repudiation and forgeability,which are key security concerns in the realm of proxy blind ***,we have established authentic security thresholds(82.102%)in the presence of real noise,thereby emphasizing the practicality of our proposed solution.

关键词： proxy blind signature quantum circuits quantum computation IBM quantum cloud platform

Expression Complementary Disentanglement Network for Facial Expression Recognition

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Chinese Journal of Electronics 2024年第3期33卷 742-752页

作者： Shanmin WANG Hui SHUAI Lei ZHU Qingshan LIU college of Computer science and Technology Nanjing University of Aeronautics and Astronautics college of Computer and Software Nanjing University of Information Science and Technology School of information and Control Nanjing University of Information Science and Technology

Disentangling facial expressions from other disturbing facial attributes in face images is an essential topic for facial expression *** methods only care about facial expression disentanglement(FED)itself,ignoring the negative effects of other facial *** to the annotations on limited facial attributes,it is difficult for existing FED solutions to disentangle all disturbance from the input *** solve this issue,we propose an expression complementary disentanglement network(ECDNet).ECDNet proposes to finish the FED task during a face reconstruction process,so as to address all facial attributes during *** from traditional reconstruction models,ECDNet reconstructs face images by progressively generating and combining facial appearance and matching *** designs the expression incentive(EIE) and expression inhibition(EIN) mechanisms,inducing the model to characterize the disentangled expression and complementary parts *** geometry and appearance,generated in the reconstructed process,are dealt with to represent facial expressions and complementary parts,*** combination of distinctive reconstruction model,EIE,and EIN mechanisms ensures the completeness and exactness of the FED *** results on RAF-DB,AffectNet,and CAER-S datasets have proven the effectiveness and superiority of ECDNet.

关键词： Geometry Image recognition Annotations Face recognition Task analysis Image reconstruction Facial features

Adaptive Dead-Time Modulation Scheme for Bidirectional LLC Resonant Converter in Energy Router

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1710-1721页

作者： Chenghao Sun Qiuye Sun Rui Wang Yuyang Li Dazhong Ma college of information science and Engineering Northeastern UniversityShenyang 110819China

Although the dead-time optimization design of resonant converters has been widely researched,classical design methods focus more on achieving zero-voltage switching(ZVS)*** body diode loss is always ignored,which results in low-efficiency of the converter,especially,in energy router(ER).To deal with this problem,this paper proposes an adaptive deadtime modulation scheme for bidirectional LLC resonant converters in ***,the power loss of the MOSFET is analyzed based on the ***,a novel dead-time optimization modulation principle is *** can eliminate the body diode loss of MOSFET compared with existing *** on the optimization modulation principle,this paper proposes an adaptive dead-time modulation *** this end,the converter adopting the scheme no longer needs to calculate dead-time,which simplifies the parameter design ***,this scheme enables dead-time to dynamically change with working conditions according to the dead-time optimization modulation *** these effects,the ZVS operation is achieved,and the body diode loss of MOSFET is also ***,a digital implementation method is designed to make the proposed modulation scheme have fast-transient ***,experimental results show that the proposed dead-time modulation scheme enables converters to achieve ZVS operation in all working conditions,and has higher efficiency than classical dead-time design methods.

关键词： Adaptive modulation bidirectional LLC body diode loss dead-time energy router ZVS

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

Automated Algorithms for Detecting and Classifying X-Ray Images of Spine Fractures

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Computers, Materials & Continua 2024年第4期79卷 1539-1560页

作者： Fayez Alfayez Department of Computer science and information College of ScienceMajmaah UniversityAL-Majmaah11952Saudi Arabia

This paper emphasizes a faster digital processing time while presenting an accurate method for identifying spinefractures in X-ray pictures. The study focuses on efficiency by utilizing many methods that include picturesegmentation, feature reduction, and image classification. Two important elements are investigated to reducethe classification time: Using feature reduction software and leveraging the capabilities of sophisticated digitalprocessing hardware. The researchers use different algorithms for picture enhancement, including theWiener andKalman filters, and they look into two background correction techniques. The article presents a technique forextracting textural features and evaluates three picture segmentation algorithms and three fractured spine detectionalgorithms using transformdomain, PowerDensity Spectrum(PDS), andHigher-Order Statistics (HOS) for *** an emphasis on reducing digital processing time, this all-encompassing method helps to create asimplified system for classifying fractured spine fractures. A feature reduction program code has been built toimprove the processing speed for picture classification. Overall, the proposed approach shows great potential forsignificantly reducing classification time in clinical settings where time is critical. In comparison to other transformdomains, the texture features’ discrete cosine transform (DCT) yielded an exceptional classification rate, and theprocess of extracting features from the transform domain took less time. More capable hardware can also result inquicker execution times for the feature extraction algorithms.

关键词： Feature reduction image classification X-ray images

A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

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Computers, Materials & Continua 2024年第8期80卷 2031-2048页

作者： Zhongshang Chen Ji Feng Fapeng Cai Degang Yang college of Computer and information science Chongqing Normal UniversityChongqing400030China

In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering *** various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple *** life,people’s first instinct for complex things is to divide them into multiple parts to *** the dataset into more sub-graphs is a good idea approach to identifying complex *** inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold *** on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes.

关键词： Cluster analysis shared natural neighbor hierarchical clustering

INVARIANTS-PRESERVING DU FORT-FRANKEL SCHEMES AND THEIR ANALYSES FOR NONLINEAR SCHRÖDINGER EQUATIONS WITH WAVE OPERATOR

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Journal of Computational mathematics 2024年第3期42卷 814-850页

作者： Dingwen Deng Zhijun Li college of mathematics and information science Nanchang Hangkong UniversityNanchang 330063China

Du Fort-Frankel finite difference method(FDM)was firstly proposed for linear diffusion equations with periodic boundary conditions by Du Fort and Frankel in *** is an explicit and unconditionally von Neumann stable ***,there has been no research work on numerical solutions of nonlinear Schrödinger equations with wave operator by using Du Fort-Frankel-type finite difference methods(FDMs).In this study,a class of invariants-preserving Du Fort-Frankel-type FDMs are firstly proposed for one-dimensional(1D)and two-dimensional(2D)nonlinear Schrödinger equations with wave *** using the discrete energy method,it is shown that their solutions possess the discrete energy and mass conservative laws,and conditionally converge to exact solutions with an order of for ofο(T^(2)+h_(x)^(2)+(T/h_(x))^(2))1D problem and an order ofο(T^(2)+h_(x)^(2)+h_(Y)^(2)+(T/h_(X))^(2)+(T/h_(y))^(2))for 2D problem in ***,τdenotes time-step size,while,hx and hy represent spatial meshsizes in x-and y-directions,***,by introducing a stabilized term,a type of stabilized invariants-preserving Du Fort-Frankel-type FDMs are *** not only preserve the discrete energies and masses,but also own much better stability than original ***,numerical results demonstrate the theoretical analyses.

关键词： Nonlinear Schrodinger equations with wave operator Du Fort-Frankel finite difference methods Discrete energy and mass conservative laws Numerical convergence

An Underwater Target Detection Algorithm Based on Attention Mechanism and Improved YOLOv7

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Computers, Materials & Continua 2024年第2期78卷 2829-2845页

作者： Liqiu Ren Zhanying Li Xueyu He Lingyan Kong Yinghao Zhang college of information science and Engineering Dalian Polytechnic UniversityDalian116034China

For underwater robots in the process of performing target detection tasks,the color distortion and the uneven quality of underwater images lead to great difficulties in the feature extraction process of the model,which is prone to issues like error detection,omission detection,and poor ***,this paper proposed the CER-YOLOv7(CBAM-EIOU-RepVGG-YOLOv7)underwater target detection *** improve the algorithm’s capability to retain valid features from both spatial and channel perspectives during the feature extraction phase,we have added a Convolutional Block Attention Module(CBAM)to the backbone *** Reparameterization Visual Geometry Group(RepVGG)module is inserted into the backbone to improve the training and inference *** Efficient Intersection over Union(EIoU)loss is also used as the localization loss function,which reduces the error detection rate and missed detection rate of the *** experimental results of the CER-YOLOv7 algorithm on the UPRC(Underwater Robot Prototype Competition)dataset show that the mAP(mean Average Precision)score of the algorithm is 86.1%,which is a 2.2%improvement compared to the *** feasibility and validity of the CER-YOLOv7 are proved through ablation and comparison experiments,and it is more suitable for underwater target detection.

关键词： Deep learning underwater object detection improved YOLOv7 attention mechanism