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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ke Chen Xiaosong Han Xiaoran Li Yanchun Liang Dong Xu Renchu Guan Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Software Jilin University Changchun China Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun China Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education School of Computer Science Zhuhai College of Science and Technology Zhuhai China Department of Electrical Engineering and Computer Science Christopher S. Bond Life Sciences Center University of Missouri Columbia USA

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Drug-Drug Interaction (DDI) task plays a crucial role in clinical treatment and drug development. Recently, deep learning methods have been successfully applied for DDI prediction. However, training deep learning models always need large amount of data, while known DDIs are scarce. To address this challenge, a graph neural network-based DDI prediction model named PNESR-DDI is proposed, which compensates for the lack of DDIs by enriching drug representations. First, to obtain initial node representations that incorporate rich semantic information from the biomedical knowledge graph (KG), a link prediction pre-training method on external KG is proposed in the node embedding pre-training module. Then, considering the large scale of the KG, subgraph extraction for the target drug pairs is introduced to reduce noise and decrease computational complexity in the subgraph anchoring module. After that, the subgraph is updated, and node similarities are propagated in the subgraph reconstruction module. Based on the node similarity scores, the subgraph is pruned and reconstructed, which adjusts node representations to be more conducive to DDI prediction. Finally, the drug embeddings, subgraph representations, and drug fingerprint features are concatenated to predict DDIs. PNESRDDI is evaluated on two benchmark DDI datasets: DrugBank and TWOSIDES. Experiment results show that PNESR-DDI achieves better performance than baselines. Ablation results validate the effectiveness of the pre-training method and the adaptive subgraph reconstruction strategy.

关键词： Drugs Deep learning Adaptation models Visualization Biological system modeling Noise knowledge graphs Predictive models Fingerprint recognition Transformers

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Mutual conversion of regression and classification based on least squares support vector machines

Mutual conversion of regression and classification based on ...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Jiang, Jing-Qing Song, Chu-Yi Wu, Chun-Guo Liang, Yang-Chun Yang, Xiao-Wei Hao, Zhi-Feng Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Mathematics and Computer Science Inner Mongolia University for Nationalities Tongliao 028043 China Key Laboratory of Information Science and Engineering Beijing Jiaotong University Railway Ministry Beijing 100044 China School of Mathematical Science South China University of Technology Guangzhou 510640 China

ISBN: (纸本)354034439X

Classification and regression are most interesting problems in the fields of pattern recognition. The regression problem can be changed into binary classification problem and least squares support vector machine can be used to solve the classification problem. The optimal hyperplane is the regression function. In this paper, a one-step method is presented to deal with the multi-category problem. The proposed method converts the problem of classification into the function regression problem and is applied to solve the converted problem by least squares support vector machines. The novel method classifies the samples in all categories simultaneously only by solving a set of linear equations. Demonstrations of numerical experiments are performed and good performances are obtained. Simulation results show that the regression and classification can be converted each other based on least squares support vector machines. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Learning systems

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Analysis the uncertainties of the Ant Colony Algorithm

Analysis the uncertainties of the Ant Colony Algorithm

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International Conference on computational Aspects of Social Networks, CASON

作者： Zhang, Yi Zhang, Meng Cao, Xin-Yan Department of Information Engineer Jilin Business and Technology College Changchun 130062 China College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China College of Electronic Information Engineering University of Changchun Changchun Jilin Province 130000 China

ISBN: (纸本)9780769542027

In this paper, the subject of discussion is the uncertainties of Ant Colony Algorithm(ACA). In order to find application and popularize the ACA, we try to find some disciplinarians which can eliminate the impact of uncertainties in our algorithm and find the best assembled of the parameters by a series of experiments. Results show that our works had great effects in practicality. © 2010 IEEE.

关键词： Traveling salesman problem

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Inversing cardinal direction relations

Inversing cardinal direction relations

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International Conference on Frontier of Computer Science and Technology

作者： Chen, Juan Jia, Haiyang Liu, Dayou Zhang, Changhai College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9780769541396

Focusing on the inversing operation of cardinal directions, the current generative method does not always work correctly. According to the given definitions of smallest rectangular direction and original directions, the correlations between cardinal directions and interval algebra are built. Basing on the above analysis, the algorithm to compute the inverse direction and its proof are given. The results show that out of 511*511 possible pairs of basic cardinal directions, there are 757 pairs of inverse relations over simple regions and 1621 pairs over compound regions. Finally the discussion points out the reason why existing generative method works incorrectly and indicates that our method has a quite good dimensional expansibility. © 2010 IEEE.

关键词： Inverse problems

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A Method of Gene-Function Annotation Based on Variable Precision Rough Sets

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Journal of Bionic engineering 2007年第3期4卷 177-184页

作者： Zhi-li Pei Xiao-hu Shi Meng Niu Xu-ning Tang Li-sha Liu Ying Kong Yan-chun Liang College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 P. R. China College of Mathematics and Computer Science Inner Mongolia University for NationalitiesTongliao 028043 P. R. China College of Software Jilin University Changchun 130012 P. R. China Department of Biochemistry and Molecular Biology Institution of Glycobiology Dalian Medical University Dalian 116027 P. R. China

It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.

关键词： gene function annotation variable precision rough set GO BLAST

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Static knowledge representation of multi-agent system's specification by description logics

Static knowledge representation of multi-agent system's spec...

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2006 International Workshop on Description Logics, DL 2006

作者： Che, Haiyan Sun, Jigui Yu, Haibo College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

Modularity and rigor are two key elements for multi-agent technology. Hong Zhu's multi-agent system (MAS) development method provides proper language facilities supporting modularity. To enhance this method with rigor advocates a DL method to map the specification of MAS into a DL TBox. Thus, we can use the existing DL reasoners and systems to verify and validate some system's properties.

关键词： Multi agent systems

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A novel hybrid butterfly optimization algorithm for feature selection with sine cosine velocity in the high-dimensional classification data

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Journal of Intelligent and Fuzzy Systems 2024年第5-6期47卷 369-391页

作者： Zhang, Li Chen, Xiaobo Key Laboratory of Data Science and Intelligence Education Hainan Normal University Ministry of Education Haikou Hainan China School of Computer Engineering Jiangsu University of Technology Changzhou Jiangsu China Changzhou City Center Branch People's Bank of China Changzhou Jiangsu China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

Aiming at the shortcomings of the traditional butterfly optimization algorithm in solving the high-dimensional classification feature selection problem, which has low convergence and is prone to fall into local optimal solutions, a new hybrid butterfly optimization algorithm is proposed, i.e., HBOA-SCV (A novel hybrid butterfly optimization algorithm with sine cosine velocity). The algorithm is applied to solve a high-dimensional classification feature selection problem. Firstly, the algorithm's global exploration and local exploitation ability can be dynamically balanced by introducing inertia weight coefficients w based on multiple learning strategies. Secondly, using the updated speed position formula of the sine-cosine acceleration strategy, individual butterflies' autonomous search ability and convergence speed can be further improved. Finally, according to the fitness value of each butterfly individual, the moving step length and direction of the butterfly individual are automatically adjusted better to fit the actual search process of the butterfly individual, increase the search ability in the global range, and avoid the algorithm from falling into the local optimum. To verify the algorithm's effectiveness, 18 high-dimensional classification numbers are selected to carry out simulation and comparison experiments between HBOA-SCV and traditional BOA algorithm, five improved BOA algorithms and other comparative algorithms for high-dimensional classification data successively. The experimental results show that the average fitness value and classification accuracy of the HBOA-SCV algorithm are better than the comparison algorithm, thus verifying the superiority of the HBOA-SCV algorithm. © 2024 - IOS Press. All rights reserved.

关键词： Optimization algorithms

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Multi-Target Track Initiation in Heavy Clutter

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Computers, Materials & Continua 2022年第9期72卷 4489-4507页

作者： Li Xu Ruzhen Lou Chuanbin Zhang Bo Lang Weiyue Ding College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun130012China Norinco Group Air Ammunition Research Institute Co.Ltd. Harbin150036China Harvard Medical School Boston02115USA

In the heavy clutter environment, the information capacity is large,the relationships among information are complicated, and track initiationoften has a high false alarm rate or missing alarm rate. Obviously, it is adifficult task to get a high-quality track initiation in the limited measurementcycles. This paper studies the multi-target track initiation in heavy *** first, a relaxed logic-based clutter filter algorithm is presented. In thealgorithm, the raw measurement is filtered by using the relaxed logic *** not only design a kind of incremental and adaptive filtering gate, but alsoadd the angle extrapolation based on polynomial extrapolation. The algorithm eliminates most of the clutter and obtains the environment with highdetection rate and less clutter. Then, we propose a fuzzy sequential Houghtransform-based track initiation algorithm. The algorithm establishes a newmeshing rule according to system noise to balance the relationship between thegrid granularity and the track initiation quality. And a flexible superpositionmatrix based on fuzzy clustering is constructed, which avoids the transformation error caused by 0–1 voting method in traditional Hough *** addition, the algorithm allows the superposition matrixes of nonadjacentcycles to be associated to overcome the shortcoming that the track can’t beinitiated in time when the measurements appear in an intermittent way. Anda slope verification method is introduced to detect formation-intensive serialtracks. Last, the sliding window method is employed to feedback the trackinitiation results timely and confirm the track. Simulation results verify thatthe proposed algorithms can initiate the tracks accurately in heavy clutter.

关键词： Track initiation heavy clutter multi-target Hough transform

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An Improved Pigeon-Inspired Optimization for Multi-focus Noisy Image Fusion

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Journal of Bionic engineering 2021年第6期18卷 1452-1462页

作者： Yingda Lyu Yunqi Zhang Haipeng Chen Public Computer Education and Research Center Jilin UniversityChangchun130012China College of Software Jilin UniversityChangchun 130012China College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012China

Image fusion technology is the basis of computer vision task,but information is easily affected by noise during *** this paper,an Improved Pigeon-Inspired Optimization(IPIO)is proposed,and used for multi-focus noisy image fusion by combining with the boundary handling of the convolutional sparse *** two-scale image decomposition,the input image is decomposed into base layer and detail *** the base layer,IPIO algorithm is used to obtain the optimized weights for fusion,whose value range is gained by fusing the edge ***,the global information entropy is used as the fitness index of the IPIO,which has high efficiency especially for discrete optimization *** the detail layer,the fusion of its coefficients is completed by performing boundary processing when solving the convolution sparse representation in the frequency *** sum of the above base and detail layers is as the final fused *** results show that the proposed algorithm has a better fusion effect compared with the recent algorithms.

关键词： Improved pigeon-inspired optimization Convolutional sparse representation Noisy image fusion Bionic algorithm

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Visual saliency and extended hidden markov model based approach for image splicing detection

Visual saliency and extended hidden markov model based appro...

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2013 International Conference on Mechanical and Electronics engineering, ICMEE 2013

作者： Li, Xiang Shen, Xuan Jing Lv, Ying Da Chen, Hai Peng College of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China

ISBN: (纸本)9783037858103

In order to improve the detection accuracy of spliced images, a new blind detection based on visual saliency was proposed in this paper. Firstly, create the edge conspicuous map by an improved OSF-based method, and extract fixations by visual attention model. Then locate those fixations on conspicuous edges by conspicuous edge positioning method. Accordingly, key feature fragments can be captured. Secondly, extract Extended Hidden Markov Model features, and reduce their dimension by SVM-RFE. Finally, support vector machine was exploited to classify the authentic and spliced images. The experimental results showed that, when testing on the Columbia image splicing detection dataset, the detection accuracy of the proposed method was 96.68%. © (2013) Trans Tech Publications, Switzerland.

关键词： Hidden Markov models

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