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IEEE Transactions on Computational Biology and Bioinformatics 2025年第2期22卷 842-854页

作者： Jin Liu Junbin Mao Hanhe Lin Hulin Kuang Shirui Pan Xusheng Wu Shan Xie Fei Liu Yi Pan Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of software Xinjiang University Wulumuqi China Hunan Province Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha China School of Science and Engineering University of Dundee Dundee U.K. School of Information and Communication Technology Griffith University Gold Coast QLD Australia Shenzhen Health Development Research and Data Management Center Shenzhen China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Graph learning-based multi-modal integration and classification is one of the most challenging tasks for disease prediction. To effectively offset the negative impact among modalities in the process of multi-modal integration and heterogeneous information extractions from graphs, we propose a novel method called Multi-modal Multi-Kernel Graph Learning (MMKGL). To solve the problem of negative impact among modalities, we propose a multi-modal graph embedding module to construct a multi-modal graph. Different from conventional methods that manually construct static graphs for all modalities, each modality generates a separate graph by adaptive learning, where a function graph and a supervision graph are introduced for optimization during the multi-graph fusion embedding process. We then propose a multi-kernel graph learning module to extract heterogeneous information from the multi-modal graph. The information in the multi-modal graph at different levels is aggregated by convolutional kernels with different receptive field sizes, followed by generating a cross-kernel discovery tensor for disease prediction. Our method is evaluated on the benchmark Autism Brain Imaging Data Exchange (ABIDE) dataset and outperforms the state-of-the-art methods. In addition, discriminative brain regions associated with autism are identified by our model, providing guidance for the study of autism pathology.

关键词： Diseases Autism Random access memory Data mining Kernel Electronic mail Training Neuroimaging Graph convolutional networks Bioinformatics

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A Power Control Scheme for Target Localization in WSN

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电子学报(英文版) 2008年第3期17卷 443-448页

作者： GU Yu ZHAO Baohua Department of Computer Science University of Science and Technology of China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230027 China

In this paper, we focus on the target tracking problem in sensor networks and propose an Powersaving target localization scheme (PSTL) based on a conjecture model that reflects the moving pattern of a target, and also a corresponding two-step communication protocol between Base station (BS) and sensors. BS executes a query mechanism to determine which sensors should be used for detailed information according to a limited amount of data received from sensors. This scheme reduces both energy consumption and communication bandwidth requirement, prolongs the lifetime of the wireless sensor networks. Simulation results indicate that it can achieve a high accuracy while saving a large amount of energy.

关键词：无线传感器网络功率控制目标定位推测模型

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Minimum-Energy Broadcast Trees in All-Wireless Networks

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电子学报(英文版) 2008年第2期17卷 227-230页

作者： HU Tian ZHAO Baohua Department of Computer Science University of Science and Technology of China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230027 China

This paper focuses on the problem of constructing the minimum-energy broadcast trees in all-wireless networks. We proposed a greedy algorithm called Greedy maximum-branch replacement algorithm (GMBR) to decrease the total power of the broadcast tree further. This algorithm can be developed to a distributed one easily. Compared with the previous algorithms, GMBR was proved to have better performance, especially when the propagation loss exponent and the network size become larger.

关键词：最小能量广播天线网络技术性能

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A qualitative and quantitative study of color emotion using valence-arousal

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Frontiers of computer Science 2012年第4期6卷 469-476页

作者： Shangfei WANG Rui DING Key Lab of Computing and Communicating Software of Anhui Province School of Computer Science and TechnologyUniversity of Science and Technology of ChinaHefei 230027China

This paper describes qualitative and quantita- tive analysis of color emotion dimension expression using a standard device-independent colorimetric system. To collect color emotion data, 20 subjects are required to report their emotion responses, using a valence-arousal emotion model, to 52 color samples that are chosen from CIElab Lch color spaces. Qualitative analysis, including analysis of variance （ANOVA）, Pearson＇s correlation and Spearman＇s rank cor- relation, shows that significant differences exist between re- sponses to achromatic and chromatic stimuli, but there are no significant differences between chromatic samples. There is a positive linear relationship between lightness/chroma and valence-arousal dimensions. Subsequently, several clas- sic predictors are used to quantitatively predict emotion in- duced by color attributes. Furthermore, several explicit color emotion models are developed by using multiple linear re- gression with stepwise and pace regression. Experimental results show that chroma and lightness have stronger effects on emotions than hue, which is consistent with our qualitative results and other psychological studies. Arousal has greater predictive value than valence.

关键词： color emotion valence and arousal qualitative quantitative

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Secure Two-Party Point-Circle Inclusion Problem

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Journal of computer Science & Technology 2007年第1期22卷 88-91页

作者：罗永龙黄刘生仲红 Department of Computer Science University of Science and Technology of China Hefei 230027 China Department of Computer Science Anhui Normal University Wuhu 241000 China Anhui Province Key laboratory of Software in Computing and Communication Hefei 230027 China

Privacy-preserving computational geometry is a special secure multi-party computation and has many applications. Previous protocols for determining whether a point is inside a circle are not secure enough. We present a two-round protocol for computing the distance between two private points and develop a more efficient protocol for the point-circle inclusion problem based on the distance protocol. In comparison with previous solutions, our protocol not only is more secure but also reduces the number of communication rounds and the number of modular multiplications significantly.

关键词： secure multi-party computation computational geometry homomorphic encryption scheme private comparison

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Classifying and clustering in negative databases

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Frontiers of computer Science 2013年第6期7卷 864-874页

作者： Ran LIU Wenjian LUO Lihua YUE School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei 230027 China

Recently, negative databases （NDBs） are proposed for privacy protection. Similar to the traditional databases, some basic operations could be conducted over the NDBs, such as select, intersection, update, delete and so on. However, both classifying and clustering in negative databases have not yet been studied. Therefore, two algorithms, i.e., a k nearest neighbor （kNN） classification algorithm and a k-means clustering algorithm in NDBs, are proposed in this paper, respectively. The core of these two algorithms is a novel method for estimating the Hamming distance between a binary string and an NDB. Experimental results demonstrate that classifying and clustering in NDBs are promising.

关键词： negative databases classification clustering k nearest neighbor k-means hamming distance

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Test case generation based on program invariant and adaptive random algorithm

Test case generation based on program invariant and adaptive...

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2011 International Conference on computer Science and Education, CSE 2011

作者： Yuan, Yuan Fanping, Zeng Guanmiao, Zhu Chaoqiang, Deng Neng, Xiong Department of Computer University of Science and Technology of China China Anhui Province Key Lab. of Software in Computing and Communication Hefei Anhui China

ISBN: (纸本)9783642224171

Testing is a critical activity to find software errors. And choosing an effective test suite is the key problem in software testing area. Program invariant, as an attribute of program, can record the implementation state of test case very well and reveal the coverage of program data. In this paper, we integrate adaptive random testing and invariant technology, and present a new method which makes full use of the feedback information of program invariant and invalid case suite to generate the next case. Experiment results show that, compared with other similar methods, running for the same time, our method can achieve higher coverage and faster convergence speed. © 2011 Springer-Verlag.

关键词： software testing

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Research on method of object-oriented test cases generation based on UML and LTS

Research on method of object-oriented test cases generation ...

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1st International Conference on Information Science and Engineering, ICISE2009

作者： Zeng, Fanping Chen, Zhide Cao, Qing Mao, Liangliang Department of Computer University of Science and Technology of China Hefei Anhui 230026 China Anhui Province Key Lab. of Software in Computer and Communication Hefei Anhui 230026 China

ISBN: (纸本)9780769538877

We present a novel method of Object-Oriented test case generation based on UML state diagrams and label Transition System (LTS). The procedure is based on model-based testing techniques with test cases generated from UML state diagrams translated into LTS. UML state diagram can be a model of modeling software system. LTS model is an internal model to precisely represent the state transition. The examples and analysis show that our method is effective. ©2009 IEEE.

关键词： Model checking

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A new boundary treatment method for SPH and application in fluid simulation

A new boundary treatment method for SPH and application in f...

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3rd International Conference on Information and Computing, ICIC 2010

作者： Song, Bo Dong, Lanfang School of Computer Science and Technology USTC Hefei China Anhui Province Key Lab. of Software in Computing and Communication China

ISBN: (纸本)9780769540474

Appropriate dealing with boundary conditions is very important for SPH. Current boundary treatment methods like boundary force method, ghost particle method and virtual boundary layer method, when dealing with complex boundaries, they will have to compute much on putting external particles. For resolving this problem, we propose a new method assuming part of boundary surface instead of external particles, called effective force surface, directly repels the internal particles which approach sufficiently close. We call this new method EFS method. It is implemented in the SPH model for simulating fluid in rabbit-type cup and dam-breaking. In the former case, liquid flows vividly and no internal particles penetrate boundaries. In the latter case, the result is similar to existing result. The experimental results show that EFS method can effectively and precisely deal with complex boundary conditions. © 2010 IEEE.

关键词： Boundary conditions

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Eye localization from infrared thermal images

Eye localization from infrared thermal images

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1st IAPR TC3 Workshop on Multimodal Pattern Recognition of Social Signals in Human-computer-Interaction, MPRSS 2012

作者： Wang, Shangfei Shen, Peijia Liu, Zhilei Key Lab. of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China HeFei AnHui 230027 China

ISBN: (纸本)9783642370809

By using the knowledge of facial structure and temperature distribution, this paper proposes an automatic eye localization method from infrared thermal images. A facial structure consisting of 15 sub-regions is proposed to extract Haar-like features. Eight classifiers are learned from the features selected by Adaboost algorithm for left and right eye, respectively. A vote strategy is used to find the most likely eyes. Experimental results on the NVIE and Equinox databases show the effectiveness of our approach. © 2013 Springer-Verlag.

关键词： Adaptive boosting

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