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Multilevel Characteristic Basis Function Method with ACA for Accelerated Solution of Electrically Large Scattering Problems

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第3期35卷 449-454页

作者： Li Chenlu Sun Yufa Wang Zhonggen Wang Guohua Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University College of Electrical and Information Engineering Anhui University of Science and Technology

The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is *** reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated ***,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this *** results are given to demonstrate the accuracy and efficiency of the method.

关键词： multilevel characteristic basis function method(MLCBFM) adaptive cross approximation(ACA) characteristic basis functions(CBFs) electromagnetic scattering

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An Anti-Eavesdrop Transmission Scheduling Scheme Based on Maximizing Secrecy Outage Probability in Ad Hoc networks

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China Communications 2016年第1期13卷 176-184页

作者： WANG Yajun LIAO Tongqing WANG Chuanan School of Mathematical and Information Engineering Anhui Science and Technology University Ministry of Educational Key Laboratory of Intelligent Computing and Signal Processing Anhui University

In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their *** propose an optimal transmission scheduling scheme to defend against the eavesdropper,where a source node having the highest secrecy rate is scheduled to access the wireless medium for transmitting to its destination in an opportunistic *** be specific,the secrecy rate between a pair of the source and destination in the presence of an eavesdropper varies temporally due to the wireless fading *** proposed optimal transmission scheduling scheme opportunistically selects a source node with the highest secrecy rate to transmit its data for the sake of maximizing the security of the ad hoc network against eavesdropping *** comparison purposes,we also consider the conventional round-robin scheduling as a benchmark,where multiple source nodes take turns in accessing their shared wireless medium for transmitting to their respective *** derive closed-form secrecy outage probability expressions of both the round-robin scheduling and the proposed optimal scheduling schemes over Rayleigh fading *** results show that the proposed transmission scheduling scheme outperforms the conventional round-robin method in terms of its secrecy outage ***,upon increasing the number of source-destination pairs,the secrecy outage probability of the round-robin scheme keeps unchanged,whereas the secrecy outage performance of the proposed transmission scheduling significantly improves,showing the security benefits of exploiting transmission scheduling for protecting wireless ad hoc networks against eavesdropping.

关键词： transmission scheduling eavesdropping secrecy outage probability secrecy rate rayleigh fading

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Staggered Grid Scheme for the FFT-Based Methods

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Chinese Journal of Electronics 2019年第5期28卷 1066-1072页

作者： XIE Jiaye KONG Weibin PANG Lili SONG Weiju HUANG Zhixiang WU Xianliang Industrial Center Nanjing Institute of Technology State Key Laboratory of Millimeter Waves College of Information Engineering Yancheng Institute of Technology Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

A staggered grid scheme is proposed to reduce both the total memory requirement and the CPU time of generating the corrected near matrix in the FFTbased methods. Two sets of Cartesian grids are used to project the source points and the field points, *** proposed method does not lower the efficiency of computing far matrix-vector products, compared with the traditional uniform Cartesian grid scheme. Some numerical experiments are provided to demonstrate both the correctness and the efficiency of the proposed method.

关键词： Green’s function Singularity RFG-FFT Staggered grid scheme Corrected near matrix

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Mechanical properties of individual core-shell-structured Sn O2@C nanofibers investigated by atomic force microscopy and finite element method

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Science China(Technological Sciences) 2018年第8期61卷 1144-1149页

作者： LIU Xing LI KeFeng DUAN XiaoLu HUANG YuTing LI Shuai LIU YiLin XU Fu LI Zheng ZHANG Ping DING YanHuai Institute of Rheological Mechanics Xiangtan University School of Science Harbin Institute of Technology at Shenzhen Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University

Although SnO_2-based nanomaterials used to be considered as being extraordinarily versatile for application to nanosensors,microelectronic devices, lithium-ion batteries, supercapacitors and other devices, the functionalities of SnO_2-based nanomaterials are severely limited by their intrinsic vulnerabilities. Facile electrospinning was used to prepare SnO_2 nanofibers coated with a protective carbon layer. The mechanical properties of individual core-shell-structured SnO_2@C nanofibers were investigated by atomic force microscopy and the finite element method. The elastic moduli of the carbon-coated SnO_2 nanofibers remarkably increased, suggesting that coating SnO_2 nanofibers with carbon could be an effective method of improving their mechanical properties.

关键词： SnO2 nanofiber core-shell structure elastic modulus atomic force microscopy finite element method

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Progress in the Development of National Knowledge Infrastructure

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Journal of Computer Science & Technology 2002年第5期17卷 523-534页

作者：曹存根丰强泽高颖顾芳司晋新眭跃飞田雯王海涛王丽丽曾庆田张春霞郑宇飞周肖彬 Knowledge Acquisition and Sharing Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology The Chinese Academy of Sciences Beijing 100080 P.R. China

This paper presents the recent process in a long-term research project, calledNational Knowledge Infrastructure (or NKI). Initiated in the early 2000, the project aims todevelop a multi-domain shareable knowledge base for knowledge-intensive applications. Todevelop NKI, we have used domain-specific ontologies as a solid basis, and have built morethan 600 ontologies. Using these ontologies and our knowledge acquisition methods, we haveextracted about 1.1 millions of domain assertions. For users to access our NKI knowledge,we have developed a uniform multi-modal human-knowledge interface. We have also imple-mented a knowledge application programming interface for various applications to share theNKI knowledge.

关键词： national knowledge infrastructure knowledge acquisition domain-specificontology human-knowledge interface knowledge application programming interface

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FLSSM: A Federated Learning Storage Security Model with Homomorphic Encryption

arXiv

引用

arXiv 2025年

作者： Li, Yang Xia, Chunhe Li, Chang Li, Xiaojian Wang, Tianbo School of Computer Science and Engineering Beihang University Beijing100191 China Key Laboratory of Beijing Network Technology Beihang University Beijing100191 China Guangxi Collaborative Innovation Center Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin541004 China School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou450000 China College of Computer Science and Information Technology Guangxi Normal University Guilin541004 China School of Cyber Science and Technology Beihang University Beijing100191 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai201112 China

Federated learning based on homomorphic encryption has received widespread attention due to its high security and enhanced protection of user data privacy. However, the characteristics of encrypted computation lead to three challenging problems: "computation-efficiency", "attack-tracing" and "contribution-assessment". The first refers to the efficiency of encrypted computation during model aggregation, the second refers to tracing malicious attacks in an encrypted state, and the third refers to the fairness of contribution assessment for local models after encryption. This paper proposes a federated learning storage security model with homomorphic encryption (FLSSM) to protect federated learning model privacy and address the three issues mentioned above. First, we utilize different nodes to aggregate local models in parallel, thereby improving encrypted models’ aggregation efficiency. Second, we introduce trusted supervise nodes to examine local models when the global model is attacked, enabling the tracing of malicious attacks under homomorphic encryption. Finally, we fairly reward local training nodes with encrypted local models based on trusted training time. Experiments on multiple real-world datasets show that our model significantly outperforms baseline models in terms of both efficiency and security metrics. Copyright © 2025, The Authors. All rights reserved.

关键词： Federated learning

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Support vector machine with mixture of kernels for automatic image annotation

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High Technology Letters 2013年第3期19卷 295-300页

作者：田东平 Zhao Xiaofei Shi Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Automatic image annotation(AIA)has become an important and challenging problem in computer vision due to the existence of semantic *** this paper,a novel support vector machine with mixture of kernels(SVM-MK)for automatic image annotation is *** one hand,the combined global and local block-based image features are extracted in order to reflect the intrinsic content of images as complete as *** the other hand,SVM-MK is constructed to shoot for better annotating *** results on Corel dataset show that the proposed image feature representation method as well as automatic image annotation classifier,SVM-MK,can achieve higher annotating accuracy than SVM with any single kernel and mi-SVM for semantic image annotation.

关键词： automatic image annotation （ AIA） support vector machine （ SVM） kernel func-tion principal component analysis （PCA）

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Fusion of multi-spectral image and panchromatic image based on support vector regression

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Journal of Beijing Institute of Technology 2012年第2期21卷 269-277页

作者：胡根生梁栋 Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui University School of Electronics and Information Engineering Anhui University

In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi-direction and multi-resolution. After that, the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image. Finally, the super-resolved multi- spectral image and the panchromatic image are fused based on regions at different levels. Our experi- ments show that, the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image. The fused image preserves both high space resolution and spectrum information of multi-spectral image.

关键词： image processing image fusion support vector regression super-resolution

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Interblock-interference-free precoding using square-root decomposition for faster-than-Nyquist signaling

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Digital Communications and networks 2025年

作者： Yan Wang Qiang Li Liping Li Yingsong Li Xingwang Li Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230601 China School of Physics and Electronic Information Engineering Henan Polytechnic University Jiaozuo China

Precodings using square-root decomposition, including Cholesky and G-To-Minus-Half (GTMH) precodings, are promising for eliminating the Faster-Than-Nyquist (FTN)-induced Intersymbol-Interference (ISI). However, the existing precodings using square-root decomposition either ignore Interblock-Interference (IBI) or increase the signal power, deteriorating the Bit Error Rate (BER) performance for high-order modulations and severe ISI. To overcome these drawbacks, we adopt two approaches for constructing the circular ISI matrix. The first approach inserts a Cyclic Prefix/Suffix (CPS) after each precoded symbol block, while the second approach replaces the linear convolution of the FTN shaping and the matched filter by the circular convolution, resulting in the Circular FTN (CFTN). Using these two approaches, we propose three IBI-free precodings, i.e., CPS-Cholesky, CFTN-Cholesky and CFTN-GTMH precodings. Furthermore, employing QR decomposition shows that the GTMH and Cholesky precodings can be converted interchangeably. Thus, we demonstrate that the GTMH precoding is essentially equivalent to the Cholesky precoding. Simulation results indicate that the BER performance of three IBI-free precodings approaches Nyquist performance for moderate ISI. However, as ISI intensifies, the CPS-Cholesky scheme increases the transmit power, causing BER performance degradation. In contrast, the CFTN-Cholesky and CFTN-GTMH precodings maintain optimal BER performance even for severe ISI. Considering 128-amplitude phase shift keying with a code rate of 1/2, the BER loss of CFTN-Cholesky and CFTN-GTMH precodings for the ideal BER of 10-5 is approximately 0.002 dB and 0.005 dB when packing factor is 0.7 and roll-off factor is 0.3. To the best knowledge of the authors, this is the optimal performance achievable through precoding.

关键词： Faster-than-Nyquist Intersymbol-interference Interblock-interference Bit error rate Precoding

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The propositional normal default logic and the finite/infinite injury priority method

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Science China(information Sciences) 2017年第9期60卷 99-108页

作者： Wei LI Yuefei SUI Yuhui WANG State Key Laboratory of Software Development Environment Beihang University Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences

In propositional normal default logic, given a default theory(?, D) and a well-defined ordering of D, there is a method to construct an extension of(?, D) without any injury. To construct a strong extension of(?, D) given a well-defined ordering of D, there may be finite injuries for a default δ∈ D. With approximation deduction ?s in propositional logic, we will show that to construct an extension of(?, D) under a given welldefined ordering of D, there may be infinite injuries for some default δ∈ D.

关键词： default extension strong extension finite/infinite injury priority method recursively enumerable sets

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