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Data fusion algorithm based on Bayes sequential estimation for wireless sensor network

Dianzi Yu Xinxi Xuebao/Journal of Electronics and information technology 2009年第3期31卷 716-721页

作者： Zhang, Shu-Kui Cui, Zhi-Ming Gong, Sheng-Rong Sun, Yong Fang, Wei School of Computer Science and Technology Soochow University Suzhou 215006 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China

Mobile Agent (MA) is more suitable for wireless sensor networks than the C/S model in data fusion. In MA based data fusion, the order of nodes visited along the route by MA has a significant impact on the algorithm efficiency and life time of wireless sensor networks. This paper proposes a Mobile Agent Data Fusion (MADF) algorithm based on bayes sequential estimation for wireless sensor networks. By designing data packet and data table with specific structure, and considers MA in multihop environments and adopts gradient of Bayes sequential estimation to dispatch MA. MA accounts for performing data processing and making data aggregation decisions at nodes rather than bring data back to a central processor (sink), redundant sensory data will be eliminated. Theoretical analysis and experimental results show that the proposed scheme is able to provide less energy consumption and network delay compared to directed diffusion schemes.

关键词： Mobile agents

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Multiple phase transitions in networks of directed networks

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Physical Review E 2019年第1期99卷 012312-012312页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Department of Physics Center for Polymer Studies Boston University Boston Massachusetts 02215 USA Department of Computer Science Rensselaer Polytechnic Institute Troy New York 12180 USA

The robustness in real-world complex systems with dependency connectivities differs from that in isolated networks. Although most complex network research has focused on interdependent undirected systems, many real-world networks—such as gene regulatory networks and traffic networks—are directed. We thus develop an analytical framework for examining the robustness of networks made up of directed networks of differing topologies. We use it to predict the phase transitions that occur during node failures and to generate the phase diagrams of a number of different systems, including treelike and random regular (RR) networks of directed Erdős-Rényi (ER) networks and scale-free networks. We find that the the phase transition and phase diagram of networks of directed networks differ from those of networks of undirected networks. For example, the RR networks of directed ER networks show a hybrid phase transition that does not occur in networks of undirected ER networks. In addition, system robustness is affected by network topology in networks of directed networks. As coupling strength q increases, treelike networks of directed ER networks change from a second-order phase transition to a first-order phase transition, and RR networks of directed ER networks change from a second-order phase transition to a hybrid phase transition, then to a first-order phase transition, and finally to a region of collapse. We also find that heterogenous network systems are more robust than homogeneous network systems. We note that there are multiple phase transitions and triple points in the phase diagram of RR networks of directed networks and this helps us understand how to increase network robustness when designing interdependent infrastructure systems.

关键词： Attacks on networks Cascades Continuous phase transition Discontinuous phase transition Network phase transitions Percolation phase transition Random attacks Robustness Topological phase transition

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CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution

arXiv

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arXiv 2022年

作者： Gao, Guangwei Xu, Zixiang Li, Juncheng Yang, Jian Zeng, Tieyong Qi, Guo-Jun The Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China The School of Communication & Information Engineering Shanghai University Shanghai China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing China The Center for Mathematical Artificial Intelligence Department of Mathematics The Chinese University of Hong Kong Hong Kong Research Center for Industries of the Future School of Engineering Westlake University OPPO Research Seattle United States

Recently, deep convolution neural networks (CNNs) steered face super-resolution methods have achieved great progress in restoring degraded facial details by joint training with facial priors. However, these methods have some obvious limitations. On the one hand, multi-task joint learning requires additional marking on the dataset, and the introduced prior network will significantly increase the computational cost of the model. On the other hand, the limited receptive field of CNN will reduce the fidelity and naturalness of the reconstructed facial images, resulting in suboptimal reconstructed images. In this work, we propose an efficient CNN-Transformer Cooperation Network (CTCNet) for face super-resolution tasks, which uses the multi-scale connected encoder-decoder architecture as the backbone. Specifically, we first devise a novel Local-Global Feature Cooperation Module (LGCM), which is composed of a Facial Structure Attention Unit (FSAU) and a Transformer block, to promote the consistency of local facial detail and global facial structure restoration simultaneously. Then, we design an efficient Feature Refinement Module (FRM) to enhance the encoded features. Finally, to further improve the restoration of fine facial details, we present a Multi-scale Feature Fusion Unit (MFFU) to adaptively fuse the features from different stages in the encoder procedure. Extensive evaluations on various datasets have assessed that the proposed CTCNet can outperform other state-of-the-art methods significantly. Source code will be available at https://***/IVIPLab/CTCNet. Copyright © 2022, The Authors. All rights reserved.

关键词： Restoration

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Learning robust and discriminative low-rank representations for face recognition with occlusion

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Pattern Recognition 2017年 66卷 129-143页

作者： Guangwei Gao Jian Yang Xiao-Yuan Jing Fumin Shen Wankou Yang Dong Yue Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Engineering Laboratory of Big Data Analysis and Control for active distribution network Nanjing University of Posts and Telecommunications Nanjing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University) Fuzhou China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Automation Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Automation Southeast University Nanjing China

For robust face recognition tasks, we particularly focus on the ubiquitous scenarios where both training and testing images are corrupted due to occlusions. Previous low-rank based methods stacked each error image into a vector and then used L 1 or L 2 norm to measure the error matrix. However, in the stacking step, the structure information of the error image can be lost. Depart from the previous methods, in this paper, we propose a novel method by exploiting the low-rankness of both the data representation and each occlusion-induced error image simultaneously, by which the global structure of data together with the error images can be well captured. In order to learn more discriminative low-rank representations, we formulate our objective such that the learned representations are optimal for classification with the available supervised information and close to an ideal-code regularization term. With strong structure information preserving and discrimination capabilities, the learned robust and discriminative low-rank representation (RDLRR) works very well on face recognition problems, especially with face images corrupted by continuous occlusions. Together with a simple linear classifier, the proposed approach is shown to outperform several other state-of-the-art face recognition methods on databases with a variety of face variations.

关键词： Face recognition Low-rank matrix recovery Nuclear norm

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Video Captioning With Temporal And Region Graph Convolution Network

Video Captioning With Temporal And Region Graph Convolution ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xinlong Xiao Yuejie Zhang Rui Feng Tao Zhang Shang Gao Weiguo Fan School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China School of Information Managerment and Engineering Shanghai University of Finance and Econnomics Shanghai China School of Information Technology Deakin University Victoria Australia Department of Business Analytics University of Iowa Iowa USA

ISBN: (数字)9781728113319

ISBN: (纸本)9781728113326

Video captioning aims to generate a natural language description for a given video clip that includes not only spatial information but also temporal information. To better exploit such spatial-temporal information attached to videos, we propose a novel video captioning framework with Temporal Graph Network (TGN) and Region Graph Network (RGN). TGN mainly focuses on utilizing the sequential information of frames that most of existing methods ignore. RGN is designed to explore the relationships among salient objects. Different from previous work, we introduce Graph Convolution Network (GCN) to encode frames with their sequential information and build a region graph for utilizing object information. We also particularly adopt a stack GRU decoder with a coarse-to-fine structure for caption generation. Very promising experimental results on two benchmark datasets (MSVD and MSR-VTT) show the effectiveness of our model.

关键词： Decoding Feature extraction Convolution Task analysis Vocabulary Electron tubes Computational modeling

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Level attraction and PT symmetry in indirectly coupled microresonators

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Physical Review A 2020年第4期102卷 043527-043527页

作者： Zhao-Hui Peng Chun-Xia Jia Yu-Qing Zhang Ji-Bing Yuan Le-Man Kuang Institute of Modern Physics and Department of Physics College of Physics and Electronic Science Hunan University of Science and Technology Xiangtan 411201 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 China College of Physics and Electronic Engineering and Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal University Hengyang 421008 China

Benefiting from the tunability of their phase delay and gain, we show the possibility of realizing level attraction, parity-time (PT)-, and anti-PT-symmetric photonic structures with indirectly coupled active and passive microresonators mediated by drop-filter waveguides. We find that level attraction originates from two mechanisms, i.e., exceptional point and resonance, and it may emerge not only for dissipative coupling but also coherent coupling and hybrid coupling after considering the gain and loss of microresonators, which confirms the universality of level attraction in the coupled photonic system. On the other hand, the transition from PT to anti-PT symmetry or vice versa may be realizable by tuning their phase delay and gain; thus the indirectly coupled microresonators may provide an excellent platform for exhibiting the unique features of PT and anti-PT symmetry. Furthermore, we also reveal the intrinsic relationship of the line shape and phase behavior of the reflection spectrum with PT symmetry, anti-PT symmetry, and level attraction.

关键词： Nanophotonics Optics & lasers Quantum optics Optical microcavities Waveguides Quantum theory

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Byzantine-resilient Federated Learning With Adaptivity to Data Heterogeneity

arXiv

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arXiv 2024年

作者： Zuo, Shiyuan Yan, Xingrun Fan, Rongfei Hu, Han Shan, Hangguan Quek, Tony Q.S. The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Hangzhou China The Singapore University of Technology and Design Singapore487372 Singapore The Yonsei Frontier Lab Yonsei University Korea Republic of

This paper deals with federated learning (FL) in the presence of malicious Byzantine attacks and data heterogeneity. A novel Robust Average Gradient Algorithm (RAGA) is proposed, which leverages the geometric median for aggregation and can freely select the round number for local updating. Different from most existing resilient approaches, which perform convergence analysis based on strongly-convex loss function or homogeneously distributed dataset, we conduct convergence analysis for not only strongly-convex but also non-convex loss function over heterogeneous dataset. According to our theoretical analysis, as long as the fraction of dataset from malicious users is less than half, RAGA can achieve convergence at rate O(1/T2/3−δ) where T is the iteration number and δ ∈ (0, 2/3) for non-convex loss function, and at linear rate for strongly-convex loss function. Moreover, stationary point or global optimal solution is proved to obtainable as data heterogeneity vanishes. Experimental results corroborate the robustness of RAGA to Byzantine attacks and verifies the advantage of RAGA over baselines on convergence performance under various intensity of Byzantine attacks, for heterogeneous dataset. Copyright © 2024, The Authors. All rights reserved.

关键词： Iterative methods

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Modal Analysis of a Tooth-PDL-Bone Complex

Modal Analysis of a Tooth-PDL-Bone Complex

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2014 4th IEEE International Conference on information Science and technology

作者： Zaijin Li Yangzhou Gan Jing Xiong Jiali Tan Zeyang Xia Qunfei Zhao Harbin Institute of Technology Shenzhen Graduate School Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences and The Chinese University of Hong Kong Guanghua School of Stomatology Hospital of Stomatology Sun Yat-Sen University and Guangdong Provincial Key Laboratory of Stomatology

Introduction: Previous studies have shown that applying external vibrational load of a certain frequency and intensity can accelerate the tooth movement, thus shorten orthodontic treatment time. It is believed that the optimal frequency is correlative to the modal mode of the target toothperiodontal ligament(PDL)-bone complex(TPBC). This study aims to investigate modal mode, natural frequencies included,of the TPBC using finite element(FE) method. Methods: A three dimensional TPBC model of a maxillary central incisor were reconstructed from cone beam CT images. A FE model was then created in Ansys 14.5. The tooth, PDL, and bone were meshed with 10-node hexahedral elements(SOLID 187)with the numbers of the elements equaled to 17,803, 4,137,and 32,577, respectively. All parts were considered homogeneous and isotropic. The material properties(Young's Module(Pa),Poisson's ratio and Density(kg/m3) as: 2e10, 0.31 and 1.36e3 for tooth, 4.7e5, 0.4 and 1.1e3 for PDL, and 3.5e9, 0.33 and 1.4e3 for bone, respectively. Fixed constraint was set for the alveolar bone. PCG Lanczos method was used in the modal *** order modes were included in the computation. Result:The first six order modal mode of the TPBC were *** corresponding natural frequencies were 702, 1049, 2713,2805, 3026, and 3530 Hz, respectively. Different tooth movement patterns, including translation, rotation, extrusion/intrusion,were observed in these modal modes. Conclusion: The proposed method is able to obtain the natural frequencies and modal modes of a TPBC. The results can be used as reference for developing vibrational device to accelerate orthodontic tooth movement.

关键词： Modal Analysis of a Tooth-PDL-Bone Complex PDL

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Improving Classroom Quality by Analyzing Student Behaviors Through computer Vision

Improving Classroom Quality by Analyzing Student Behaviors T...

引用

information Science and Education (ICISE-IE), International Conference on

作者： Xiaopan Chen Boyuan Li Xiaoke Zhu Tao Zhang School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology Henan University Kaifeng China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

This paper aims to enhance the efficiency of teaching and learning by leveraging computer vision technology for automated analysis of student behavior in the classroom. We propose a feature-enhanced method for recognizing student behavior, which integrates an Upsampling module (UPS) and a convolutional block layer (CBL) module into the YOLOv5 model. This innovative approach significantly improves the detection and feature extraction capabilities for student targets, effectively addressing challenges associated with small-sized targets and lowresolution images. Through algorithm optimization, it achieves a balance in sample diversity, enhancing the model's adaptability and generalizability in complex classroom environments. Building upon these technological advancements, we have developed a Classroom Student Posture Perception System (CSP2S). This system integrates functions for data collection, student behavior detection, and result visualization. The CSP2S operates in realtime by capturing and analyzing students’ behavioral dynamics while providing teachers with immediate feedback. Experimental results demonstrate that this system substantially reduces teachers’ workload in student assessment, offering significant potential to improve teaching effectiveness. These robust technical advancements provide strong support for future applications in real educational environments.

关键词：

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An Improved Differential Evolution Algorithm Integrating the Plant Evolutionary Strategy

SSRN

引用

SSRN 2024年

作者： Zhang, Xiaoming Cheng, Hongwei Li, Jun Li, Tingjuan Zhang, Panpan Tian, Ye Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China Qinghai Institute of Science and Technology Information Xining810008 China School of Computer Science and Technology Anhui University Hefei230601 China

Differential evolution algorithm (DE) and their variants often encounter a decrease in population diversity and convergence rate along with the evolution, resulting in local optima and premature convergence. To address this issue, this paper proposes an improved differential evolution integrating the plant evolutionary strategy, named DEPES, leveraging the exploitation capability of DE and the exploration capability of the plant population distribution evolutionary strategy. First, a tri-subpopulation optimization framework with a mutation strategy is introduced to cope with diversity maintenance, convergence enhancement, and local optima a Cauchy mutation operator based on plant population distribution evolutionary model is employed to enhance the exploration capability of the mutation strategy. Second, a parameter control strategy is performed on the superior and inferior solutions to balance the exploitation and exploration of the population. Third, a covariance matrix-based crossover strategy is designed to minimize interference from local population information, consequently generating high-quality solutions. The superior efficiency of DEPES is fully verified by comparing it with advanced DE-based variants and other algorithms on the IEEE CEC2020 test suite and engineering design problems. © 2024, The Authors. All rights reserved.

关键词： Covariance matrix

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