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2nd International Conference on Industrial Artificial Intelligence, IAI 2020

作者： Zhang, Lei Liu, Qing Xia, Jiajun Yang, Haipeng Zhang, Xingyi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University China

ISBN: (纸本)9781728182162

The critical node detection for sequential attacks based on cascading failure model is an important way for analyzing network vulnerability, which has attracted the attention of many researchers in the field of complex network recently. However, most of the existing cascading critical node detection algorithms focus on designing effective attack strategies leading to the maximal damage to the network (i.e. attack effect), while ignoring the cost of attacks. To this end, we transform the cascading critical node detection for sequential attacks as a bi-objective optimization problem (named BCVNDSeq), where the attack cost and the attack effect are simultaneously optimized. In order to solve the transformed problem, we propose a multiobjective cascading critical node detection algorithm (named MO-BCVNDSeq), which can provide decision makers with a holistic view for analyzing the network vulnerability. In MO-BCVNDSeq, a local search strategy based on sequential matrix is proposed to accelerate the population convergence and an individual repairing strategy is also suggested to further improve the search efficiency. Finally, the experimental results on 6 real-world complex networks demonstrate the effectiveness of the proposed algorithm compared with several representative baselines. © 2020 IEEE.

关键词： Multiobjective optimization

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Broadband external rejection miniaturized SIW filter based on C-shaped symmetric structure

Broadband external rejection miniaturized SIW filter based o...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Xiao, Shuang Li, Minquan Qu, Xin Li, Chen Zhang, Zufeng Anhui University Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Liaoyang Province Hefei230601 China

ISBN: (纸本)9781665452366

To effectively improve the frequency selectivity of the filter, a substrate integrated waveguide (SIW) filter with miniaturization and out-of-band rejection was designed. To achieve the desired filter response, symmetrical C-shaped resonators are etched on the top and bottom layers of the SIW filter. The C-shaped resonator etched on the top layer of SIW achieves miniaturization and filtering characteristics. In order to improve the frequency response, a two-stage SIW filter and a SIW filter with coupled gap-ring defected ground structure (CGRDGS) are proposed, and an equivalent circuit is given to verify the transmission response. The simulation results show that the filter achieves miniaturization, out-of-band rejection and low insertion loss, which can be used in 5G wireless communication The simulation results show that the filter achieves miniaturization, out-of-band rejection and low insertion loss, which can be used in 5G wireless communication. © 2022 IEEE.

关键词： Resonators

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Uplink Supportive Number of Users in Massive MIMO Systems 9

Uplink Supportive Number of Users in Massive MIMO Systems

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jun Zhu Chao Wang Peng Ma Chaochao Jia Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Technology and Innovation Department Shanghai Research Center for Wireless Communication

ISBN: (纸本)9781509038237;9781509038220

The supportive number of users achieving the maximum sum rate is studied in uplink massive MIMO systems for zero-forcing(ZF) and maximum-ratio combining(MRC). We obtain the lower bound of the achievable rate of each user for ZF and MRC receivers with any finite number of base station(BS) antennas, respectively. By this theoretical result, this paper will focus on the supportive number of users which was constrained with the minimum achievable rate. Through analyzing the optimal problem of maximizing the overall sum rate, we obtain the expression of optimal number of users and present the user scheduling algorithm for achieving the maximized sum rate. The numerical results show that the massive MIMO systems can improve the supportive number of users, and ZF receivers can support more number of users than MRC under the same condition.

关键词： large number of antennas achievable uplink rate supportive number of users massive MIMO

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A Novel Transformed Nested Array with Enhanced DOFs Based on Sum-Difference Coarray 6

A Novel Transformed Nested Array with Enhanced DOFs Based on...

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

作者： Xin, Wei Li, Yingsong Harbin Engineering University China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350399059

Sum-difference driven coarray (SDCA) was paid great attention in array-signal-processing (ASP). By considering SDCA, the degrees of freedom (DOFs) for sparse arrays can be further improved. Here, a new transformed nested-array (TNA) is constructed, which reduces the element redundancy via rearranging the density of sub-arrays of the constructed new TNA. Compared to former TNAs, the constructed TNA gets higher DOFs and maximization signals, numerical simulation are given for getting its superior behaviors. © 2023 IEEE.

关键词： Degrees of freedom (mechanics)

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A Spectrum Based Algorithm for Image Classification

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电子学报(英文版) 2009年第3期18卷 427-430页

作者： WANG Nian ZHANG Jiang TANG Jun FAN Yizheng LIANG Dong Key Laboratory of Intelligent Computing and Signal Processing Anhui University Education Ministry Hefei 230039 China Hefei Teachers College Hefei 230601 China Department of Mathematics Anhui University Hefei 230039 China

In this paper, a novel algorithm for image classification is presented which uses the projective value of adjacency spectrum as classified samples. Firstly, the eigenvalues of adjacency matrices constructed on the feature point-sets of images are obtained by singular value decomposition. Secondly, the eigenvalues are projected onto the eigenspace by means of the covariance matrix. Finally, image classification is performed by adopting RBF and PNN neural networks as classifiers respectively. Meanwhile, some theoretical analyses are given to support the proposed method.

关键词：图像分类分类算法神经网络分类器矩阵特征值奇异值分解协方差矩阵射影分类特征空间

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Challenge-aware U-net for breast lesion segmentation in ultrasound images

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Pattern Recognition 2025年 168卷

作者： Dengdi Sun Changxu Dong Yuchen Yan Bo Jiang Yayang Duan Zhengzheng Tu Chaoxue Zhang Key Laboratory of Intelligent Computing & Signal Processing (ICSP) Ministry of Education School of Artificial Intelligence Anhui University China Institute of Artificial Intelligence Hefei Comprehensive National Science Center China Anhui Provincial Key Laboratory of Multimodal Cognitive Computing School of Computer Science and Technology Anhui University China Department of Ultrasound the First Affiliated Hospital of Anhui Medical University China

Deep learning methods can enhance the efficiency of tumor segmentation in breast ultrasound (BUS) images. However, noise interference, small tumors, and blurred boundaries can reduce segmentation accuracy. We design a three-branch challenge-aware U-net (CAU-net) to address these main challenges in BUS images. Our CAU-net extracts the features from three challenge-aware encoders in parallel first. Secondly, we propose an adaptive aggregation layer (AAL) to merge the multi-scale features of three challenging branches, enabling the network to adaptively handle different breast lesion samples with these main challenges. To further enhance the accuracy of segmentation, we introduce the graph reasoning module (GRM) to the network to model the correlation between the channels of the features and acquire the global information in the features. The result of our experiment on two datasets demonstrates the superiority of CAU-net over the advanced medical image segmentation methods. Our code can be downloaded from https://***/tzz-ahu .

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Enhanced Discriminant Analysis Based Fault Diagnosis Scheme for Marine Diesel Engines 11

Enhanced Discriminant Analysis Based Fault Diagnosis Scheme ...

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11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022

作者： Zhong, Kai Wang, Jiayi Pan, Donghui Institutes of Physical Science and Information Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Anhui Hefei230601 China School of Mathematical Science Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Hefei230601 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Since the marine diesel engine is one of the most popular power equipments for modern shipping, accurate and timely diagnose the faults occurred in diesel engine is extraordinary important for long service life and high reliability. Note that Fisher discriminant analysis (FDA) has been widely applied in fault diagnosis field. However, it is quite susceptible to the small sample size (SSS) problem, which is very common in the running process of diesel engine. In response to the problem, this study pro-poses a new fault classification criterion based exponential discriminant analysis (EDA) scheme for diesel engine fault diagnosis, in which the exponential transformation is carried out first to enlarge the margin between different classes, thus the different fault classes are further separated and the diagnosis capability is enhanced. In addition, the theorems of matrix exponential guarantee that the matrix exp (Sw) is always full-rank, even though the Sw is singular. That means, the novel methodology is still appli-cable when confronts with the SSS problem. Finally, based on the more reasonable fault classification criterion, the simulation results on a real-world two-stroke six-cylinder low-speed marine diesel engine indicate that the EDA based diagnosis scheme achieves higher fault diagnosis accuracy with good robustness and practicability in real-world engineering applications. © 2022 IEEE.

关键词： Failure analysis

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Dual-notch Ultra-wideband Bandpass Filter Based On Folded Dual-mode Resonator

Dual-notch Ultra-wideband Bandpass Filter Based On Folded Du...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Li, Qingqing Wu, Xianliang Huang, Zhixiang Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China

ISBN: (纸本)9781665452366

Aiming at the problem that ultra-wideband systems are easily interfered by narrowband signals, In this paper, a novel ultra-wideband (UWB) bandpass filter with dual-notch characteristics. This filter is mainly composed of Composition of a multimode resonator (MMR)and a folded dual-mode step-impedance resonator. Paralleling T-shaped SIR stubs in the basic MMR structure realizes the introduction of transmission zeros within the passband. At the same time, a pair of high-impedance stubs are also loaded to extend the upper stopband of the filter, and a folded dual-mode stepped impedance resonator is coupled below the filter to generate dual-notch frequencies. Through the electromagnetic simulation software HFSS for simulation optimization, the simulation results show that the passband of the filter is 3.4211.21GHz and its notch frequencies are 8.8GHz and 9.5GHz respectively. Insertion loss below 0.5dB and stopband up to 20GHz (S21 © 2022 IEEE.

关键词： Electromagnetic simulation

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DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis 38

DisenGCD: A Meta Multigraph-assisted Disentangled Graph Lear...

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38th Conference on Neural Information processing Systems, NeurIPS 2024

作者： Yang, Shangshang Chen, Mingyang Wang, Ziwen Yu, Xiaoshan Zhang, Panpan Ma, Haiping Zhang, Xingyi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Anhui Hefei230601 China Anhui Province Key Laboratory of Intelligent Computing and Applications China Department of Information Materials and Intelligent Sensing Laboratory of Anhui Province China

Existing graph learning-based cognitive diagnosis (CD) methods have made relatively good results, but their student, exercise, and concept representations are learned and exchanged in an implicit unified graph, which makes the interaction-agnostic exercise and concept representations be learned poorly, failing to provide high robustness against noise in students' interactions. Besides, lower-order exercise latent representations obtained in shallow layers are not well explored when learning the student representation. To tackle the issues, this paper suggests a meta multigraph-assisted disentangled graph learning framework for CD (DisenGCD), which learns three types of representations on three disentangled graphs: student-exercise-concept interaction, exercise-concept relation, and concept dependency graphs, respectively. Specifically, the latter two graphs are first disentangled from the interaction graph. Then, the student representation is learned from the interaction graph by a devised meta multigraph learning module;multiple learnable propagation paths in this module enable current student latent representation to access lower-order exercise latent representations, which can lead to more effective nad robust student representations learned;the exercise and concept representations are learned on the relation and dependency graphs by graph attention modules. Finally, a novel diagnostic function is devised to handle three disentangled representations for prediction. Experiments show better performance and robustness of DisenGCD than state-of-the-art CD methods and demonstrate the effectiveness of the disentangled learning framework and meta multigraph module. The source code is available at https://***/BIMK/intelligent-Education/tree/main/DisenGCD. © 2024 Neural information processing systems foundation. All rights reserved.

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Identifying Disease Modules Based on Connectivity and Semantic Similarities 14th

Identifying Disease Modules Based on Connectivity and Semant...

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14th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 2019

作者： Su, Yansen Zhu, Huole Zhang, Lei Zhang, Xingyi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China

ISBN: (纸本)9789811534140

The identification of disease modules has attracted increasing attention due to the importance in comprehending pathogenesis of complex diseases. Most of the existing methods were based on the protein-protein interaction (PPI) networks with the incompleteness and incorrectness of the interactome, which results in many disease-related proteins and pathways not within their disease modules. In this paper, we propose a method named IDMCSS to effectively identify disease modules by adding some potential interactions and removing some incorrect interactions in the existing human PPI network. Firstly, the connective similarity and semantic similarity are calculated between the known disease proteins and each of their neighbors. Then, the network is adjusted by adding the interactions with large connective and semantic similarity, and removing those with small connective and semantic similarity. Further, the proteins are sorted in the descending order according to the similarity to the known disease proteins, and the sorted proteins are added into a candidate node set one by one until a certain biological information is not enriched in the candidate node set. Finally, the connected subnetwork with the largest number of nodes in the candidate node set is selected as the disease module. The disease modules identified by IDMCSS involve crucial biological processes of related diseases and can predict 12 targets for drug intervention. The experimental results on asthma demonstrate the effectiveness of the proposed method in comparison to existing algorithms for disease module identification. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Proteins

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