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arXiv 2025年

作者： Hu, Guyue Song, Siyuan Kang, Yukun Yin, Zhu Zhao, Gangming Li, Chenglong Tang, Jin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Security Artificial Intelligence School of Artificial Intelligence Anhui University Hefei230601 China School of Internet Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China Department of Computer Science The University of Hong Kong Hong Kong

Medical image segmentation in X-ray images is beneficial for computer-aided diagnosis and lesion localization. Existing methods mainly fall into a centralized learning paradigm, which is inapplicable in the practical medical scenario that only has access to distributed data islands. Federated Learning has the potential to offer a distributed solution but struggles with heavy training instability due to client-wise domain heterogeneity (including distribution diversity and class imbalance). In this paper, we propose a novel Federated Client-tailored Adapter (FCA) framework for medical image segmentation, which achieves stable and client-tailored adaptive segmentation without sharing sensitive local data. Specifically, the federated adapter stirs universal knowledge in off-the-shelf medical foundation models to stabilize the federated training process. In addition, we develop two client-tailored federated updating strategies that adaptively decompose the adapter into common and individual components, then globally and independently update the parameter groups associated with common client-invariant and individual client-specific units, respectively. They further stabilize the heterogeneous federated learning process and realize optimal client-tailored instead of sub-optimal global-compromised segmentation models. Extensive experiments on three large-scale datasets demonstrate the effectiveness and superiority of the proposed FCA framework for federated medical segmentation. © 2025, CC BY.

关键词： Federated learning

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Joint relay selection and power allocation protocol for two-way relaying system

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International Journal of Wireless and Mobile computing 2019年第4期17卷 349-360页

作者： Zhi, Hui Zhu, Jun Hu, Yanjun Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui230601 China

The Joint Relay Selection and Power Allocation (JRSPA) for Amplify-and-Forward (AF) relaying (JRSPA-AF) combines Power Allocation (PA) and Relay Selection (RS) very well in Two- Way Relaying (TWR) system. In order to explore the system performance of JRSPA-AF protocol, the outage probability and Diversity-Multiplexing Trade-off (DMT) of JRSPA-AF protocol are analysed. One upper bound, two lower bounds and approximate expressions of outage probability along with the DMT are derived. Based on this, the idea of JRSPA is introduced into Decode-and- Forward (DF) relaying TWR system, and the JRSPA-DF protocol is proposed. Moreover, the exact expressions of outage probability and DMT for JRSPA-DF are derived. Simulations are developed to validate the analytical results, the results show that the approximation outage probability of JRSPA-AF can be used well to evaluate system outage probability over the entire transmission SNR region, and the analysis results of outage probability of JRSPA-DF are consistent with its simulation results. In addition, the simulation results indicate that JRSPA-DF can achieve lower outage probability than JRSPA-AF and other protocols. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Probability

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Informative gene selection using the Algebraic Connectivity Strength of Point and Scoring Criteria

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Chinese Science Bulletin 2013年第6期58卷 657-661页

作者： WANG Nian SU LiangLiang TANG Jun YE AiXia Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University School of Electronics and Information Engineering Anhui University

This paper presents a novel method that integrates the Algebraic Connectivity Strength of Point(ACSP) and Scoring Criteria to identify genes associated with tumor ***,for each gene,the ACSP is used to identify reliable expression levels of the gene in all the *** informative genes are then selected using Scoring Criteria based on these reliable expression ***,the Support Vector Machine(SVM) classifier is used to classify the two datasets of gene expression *** results show that the informative genes selected by the proposed method have higher credibility than those selected by Scoring Criteria alone.

关键词：基因选择评分标准信息化强度连通代数基因表达谱支持向量机

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DMFVAE:miRNA-disease associations prediction based on deep matrix factorization method with variational autoencoder

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Frontiers of Computer Science 2024年第6期18卷 259-270页

作者： Pijing WEI Qianqian WANG Zhen GAO Ruifen CAO Chunhou ZHENG Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230601China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial IntelligenceAnhui UniversityHefei 230601China

MicroRNAs(miRNAs)are closely related to numerous complex human diseases,therefore,exploring miRNA-disease associations(MDAs)can help people gain a better understanding of complex disease *** increasing number of computational methods have been developed to predict ***,the sparsity of the MDAs may hinder the performance of many *** addition,many methods fail to capture the nonlinear relationships of miRNA-disease network and inadequately leverage the features of network and neighbor *** this study,we propose a deep matrix factorization model with variational autoencoder(DMFVAE)to predict potential *** first decomposes the original association matrix and the enhanced association matrix,in which the enhanced association matrix is enhanced by self-adjusting the nearest neighbor method,to obtain sparse vectors and dense vectors,***,the variational encoder is employed to obtain the nonlinear latent vectors of miRNA and disease for the sparse vectors,and meanwhile,node2vec is used to obtain the network structure embedding vectors of miRNA and disease for the dense ***,sample features are acquired by combining the latent vectors and network structure embedding vectors,and the final prediction is implemented by convolutional neural network with channel *** evaluate the performance of DMFVAE,we conduct five-fold cross validation on the HMDD v2.0 and HMDD v3.2 datasets and the results show that DMFVAE performs ***,case studies on lung neoplasms,colon neoplasms,and esophageal neoplasms confirm the ability of DMFVAE in identifying potential miRNAs for human diseases.

关键词： miRNA-disease association deep matrix factorization self-adjusted nearest neighbor variational encoder network structure

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A Direct-Path Interference Cancellation Approach to Passive Radar Based on Adaptive Fractional Delay Estimation

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电子学报(英文版) 2007年第2期16卷 359-362页

作者： ZHU Jiabing WU Xianliang TAO Liang HONG Yi Education Ministry Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China Institute of Signal Processing East China Research Institute of Electronic Engineering Hefei 230031 China

Target detection by non-cooperative illuminator is a study hotspot in electronic warfare field, with'four countering' potential advantages for passive radar. One of the major problems in continuous wave bistatic radar is Direct path interference (DPI). Conventional solutions to this problem is the use of an adaptive antenna, steering null towards the interference. Unfortunately the null depth obtained by this technology is not enough for surveillance radar. First of all, DPI appeared in passive radar based on non-cooperative FM broadcast transmitter is analyzed in this paper. Secondly, a DPI cancellation based on Adaptive fractional delay estimation (AFDE) is in detail introduced how to deal with this problem. Finally, a passive radar experimental system based on non-cooperative FM broadcast transmitter is provided, simulation results by real collected data show applying the method proposed in this paper is effective in suppression DPI.

关键词：无源雷达直达波干扰对消自适应分数延迟估计 FM广播

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A Full-Rate and Low-Detection Complexity Cooperative Transmission Scheme Based on Distributed Space-Time-Frequency Code Design

A Full-Rate and Low-Detection Complexity Cooperative Transmi...

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2013 IEEE 4th International Conference on Software Engineering and Service Science

作者： Hongyu Fang Ruzi Li Li Wang Xiaohui Li Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University

ISBN: (纸本)9781467349994

The cooperative transmission schemes based on the amplify and forward（AF） mode have the defect of low transmission rate and the exiting full-rate cooperative transmission schemes based on space-time code design have the defect of high detection ***,this paper makes the best of linear constellation precoding（LCP） technique and cyclic delay diversity（CDD） technique,and adopts the nonorthogonal amplify and forward（NAF） mode,finally proposes a new full-rate wireless cooperative transmission scheme based on space-time-frequency code *** with the cooperative transmission schemes that only pursue the transmission rate or the BER performance,this new scheme can apply to multi-relay scenario,and has the advantages of simple structure,low signal detection complexity that does not increases with the number of relay *** of above makes the real-time data transmission service of high quality come to be possible.

关键词： cooperative space-time-frequency full-rate lowdetection complexity

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Classification of Cervical Images Based On Deep Neural Network With Attention Mechanism 6

Classification of Cervical Images Based On Deep Neural Netwo...

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6th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Feng, Yun Chen, Lan Zhang, Xia Li, Yingsong Li, Liping Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350399059

In this paper, we propose a DenseNet-CBAM model that utilizes DenseNet121 as the backbone network for feature extraction. The features are then weighted using the Convolutional Block Attention Module (CBAM), which incorporates both channel and spatial attention mechanisms. The features are further processed with ReLU activation and adaptive average pooling operations. Finally, a linear classifier is applied to output the final category predictions. Experiment results show that the proposed model performs the best in terms of the ability in detecting patients with high-grade squamous intraepithelial lesions (HSIL). © 2023 IEEE.

关键词： Image classification

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Design of two-turns loop antenna with magnetic core for efficient wireless powering of medical telemetry

Design of two-turns loop antenna with magnetic core for effi...

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2017 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2017

作者： Song, Yong Song, Kaihong Wu, Xianliang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

ISBN: (纸本)9780996007856

We present an inductive powering system of a two-turns loop antenna which includes external and implanted antennas each with a cylinder magnetic core. It can wirelessly transfer power to loop antenna of a compact plane structure in cortex. Compared to single antenna without magnetic core, it can achieve highly-efficient (24.8%) wireless power transferring to implanted loop antenna and reduce the SAR to 83.2%. By improving the link power transfer efficiency and decreasing the SAR, we optimize the antenna's structural parameter. Then, we propose different liquid of concentrations to simulate human skin, which is used for power transmission experiment at 100MHz. © 2017 Applied Computational Electromagnetics Society.

关键词： Loop antennas

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Two-Weight Codes and Second Order Recurrences

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Chinese Journal of Electronics 2019年第6期28卷 1127-1130页

作者： SHI Minjia ZHANG Zhongyi SOLé Patrick Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Sciences Anhui University School of Wendian Anhui University Aix Marseille Univ CNRS Centrale Marseile

Cyclic codes of dimension 2 over a finite field are shown to have at most two nonzero weights. We compute their weight distribution, and give a condition on the roots of their check polynomials for them to be maximum ... 详细信息

关键词： Two-weight codes Irreducible Cyclic codes MDS codes Linear recurrences

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A Band-pass FSS with Wide Angular Stability and High Polarization Stability 6

A Band-pass FSS with Wide Angular Stability and High Polariz...

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6th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Gao, Yunshuai Ding, Shuying Huang, Zhixiang Li, Yingsong Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350399059

A mimic multi-layer polarization-independent FSS with accessible angular-stability is reported using a three-layer structure, where the top layer and the bottom layer are realized based the metal rings that are same, and the middle is constructed by a slotted metal structure. The mentioned three layers are aimed to separate the used two dielectric substrates. For a well illustration, the constructed dimensions of the installed FSS are 5× 5 mm2. As a case of the FSS cell design, here the dimension is limited as 0.15λ× 0.15λ. Since two different structure is used, the FSS has double resonace, making a wide operation. From the numerical evaluations, the FSS can reject the signal from C-and X-band. © 2023 IEEE.

关键词： Polarization

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