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2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008

作者： Xiang, Junping Hu, Maolin Key Laboratory of Intelligent Computing and Signal Processing School of Mathematics and Computational Science Anhui University Hefei Anhui China

ISBN: (纸本)9781424417483

We try to evaluate the sequential and non-sequential and flexible structural alignment methods on SCOP 1.71. Firstly, we compare the flexible method with rigid methods and compare the sequence order dependent methods with sequence order independent methods by two typical cases. Secondly, the performances of the above methods are evaluated using ten protein pairs which are considered as "hard to detect" similarities. Thirdly, we evaluate the methods by comparing the ROC curves based on their native score and geometric measure Qscore. Then we compare the methods directly using geometric match measure Qscore, which also allows the creation of a 'Best-of-All' method. The main conclusions are: (1) we find that the best alignments found by sequential methods are more consistent with the SCOP classification;(2) we show that ROC curves are of limited value and that their ranking of the methods is not consistent with the ranking implied by the quality of the alignments the methods find;(3) we also find that the alignments of flexible method and non-sequential methods are better than the corresponding alignments of rigid sequential method from the viewpoint of geometric superposition, and flexible method and non-sequential methods can find more cross-fold similarities. © 2008 IEEE.

关键词： Proteins

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Improving mutation pathogenicity prediction of metal-binding sites in proteins with a panoramic attention mechanism

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Pattern Recognition 2025年

作者： Yuan Zhang Jiafeng Wu Qiuye Zhao Mingyuan Dong Junsheng Deng Xieping Gao Kai Hu Dapeng Xiong Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China Department of Computational Biology Cornell University Ithaca NY 14853 USA Weill Institute for Cell and Molecular Biology Cornell University Ithaca NY 14853 USA Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha 410081 China

Accurately identifying the pathogenicity of mutations at protein-metal binding sites is crucial for uncovering the structural and functional complexity of metalloproteins, and the molecular mechanisms behind numerous diseases. In this study, we present a novel deep learning framework, CASTLE, for the accurate pathogenicity prediction of mutations at metal-binding sites through an effective depiction of the message-passing in local environment surrounding both the metals and metal-binding sites. Specifically, CASTLE weaves multiple attention-driven units to construct comprehensive panoramic message-passing paths, enabling the capture of intricate structural patterns associated with the metal-binding conformations. In addition, CASTLE seamlessly integrates structural information at both residue and atomic levels, and further deeply fuses structural and sequence representations to ensure the incorporation of more comprehensive information. We demonstrate that CASTLE significantly outperforms other state-of-the-art methods across all datasets we evaluated, showcasing its robustness and generalization abilities. Our interpretability analysis illustrates CASTLE's capability in capturing meaningful representations from the metal coordinate-dependent environments. Moreover, the model optimization reaffirms the advantages of our model building strategy, which can effectively capture distinct binding patterns for different metal types. Overall, CASTLE provides a powerful deep learning tool that may offer valuable insights into the study of metalloprotein-related disease mechanisms and drug design.

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Solving Electromagnetic Scattering from Microstrip Arrays with Multiple-Traces Surface Integral Equations

Solving Electromagnetic Scattering from Microstrip Arrays wi...

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2018 IEEE International Conference on Computational Electromagnetics, ICCEM 2018

作者： Zhao, Ran Feng, Jian Song, Kaihong Huang, Zhixiang Hu, Jun Anhui University Ministry of Education Key Laboratory of Intelligent Computing and Signal Processing China School of Electronic Engineering China

ISBN: (纸本)9781538612415

In this paper, a new multiple-traces Poggio-Miller-Chang-Harrington-Wu-Tsai (MT-PMCHWT) equation is proposed to simulate the electromagnetic scattering from microstrip structures. Different from traditional EFIE-PMCHWT method, in this new multiple-traces method, the original object can be decomposed into two independent domains i.e., the exterior region (free space) and interior region (microstrip), and Robin transmission conditions (TCs) is enforced on the interface between exterior and interior regions to ensure the continuity of fields. In comparison to the traditional EFIE-PMCHWT, this new MT-PMCHWT has a better convergence property. Because the continuity of fields is ensured by TCs, the exterior and interior regions can be discretized by non-conformal meshes, which improves the flexibility and efficiency of the proposed methods substantially. © 2018 IEEE.

关键词： Surface scattering

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Critical Node Detection for Sequential Attacks in Complex Networks via Multi-objective Optimization 2

Critical Node Detection for Sequential Attacks in Complex Ne...

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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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A graph and PNN-based approach to image classification

A graph and PNN-based approach to image classification

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Tang, Jin Zhang, Chun-Yan Luo, Bin Key Lab of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)078039092X

In this paper, a new image classification method is developed. This approach applies graph decomposition and probabilistic neural networks(PNN) to the task of supervised image classification. We use relational graphs to represent image. These graphs are constructed from the feature points of images. Spectra of these graphs will be obtained as feature vectors for classification. PNN is adopted to classifies image according to the feature vectors. Experimental results show that this method can achieve best result of images classification. ©2005 IEEE.

关键词： Image segmentation

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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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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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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 novel algorithm of artificial immune system for high-dimensional function numerical optimization

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Progress in Natural Science:Materials International 2005年第5期15卷 463-471页

作者： DU Haifeng 1,2*, GONG Maoguo1, JIAO Licheng1 and LIU Ruochen1(1. Institute of intelligent Information processing and key laboratory of Radar signal processing, Xidian University, Xi'an 710071, China 2. School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China) Institute of Intelligent Information Processing and Key Laboratory of Radar Signal Processing Xidian University Xi''an 710071 China School of Mechanical Engineering Xi''an Jiaotong University Xi''an 710049 China

Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.

关键词： clonal selection immune memory artificial immune system evolutionary algorithms Markov chain.

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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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