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作者： Zhu, Yungang Liu, Dayou Li, Yong Wang, Xinhua College of Computer Science and Technology Jilin University No. 2699 Qianjin Street Changchun China State Key Laboratory of Applied Optics Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Mathematics Jilin University Changchun China

Active and dynamic fusion for fuzzy and uncertain data have key challenges such as high complexity and difficult to guarantee accuracy, etc. In order to resolve the challenging issues, in this article a selective and incremental data fusion approach based on probabilistic graphical model is proposed. General Bayesian networks are adopted to represent the relationship among the data and fusion result. It purposively selects the most informative and decision-relevant data for fusion based on Markov Blanket in probabilistic graphical model. Meanwhile we present a special incremental learning method for updating the fusion model to reflect the temporal changes of environment. Theoretical analysis and experimental results all demonstrate the proposed method has higher accuracy and lower time complexity than existing state-of-the-art methods. © 2015 - IOS Press and the authors. All rights reserved.

关键词： Data fusion

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A fast rigid registration algorithm for medical images

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Journal of Fiber Bioengineering and Informatics 2014年第3期7卷 409-418页

作者： Feng, Yuncong Li, Xiongfei Zhang, Xiaoli Ding, Tienan Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China Department of Computer Science and Technology Changchun China

Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high e±ciency. In the registration algorithm, we firstly segmented the reference image and °oat image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.

关键词： Image registration

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Integration of scanning and image processing algorithms for lane detection based on fuzzy method

Integration of scanning and image processing algorithms for ...

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作者： Zhang, Jindong Jia, Xiaoyan Li, Jinfeng College of Computer Science and Technology Jilin University Changchun China Department of Hand Surgery First Hospital of Jilin University Changchun130021 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

In order to detect lane rapidly and accurately, the integration of scanning and image processing algorithms (SIP) based on the fuzzy method is proposed. Further, combination of the proposed algorithm with an adaptive threshold value for image binarization, the least-square method and Bessel curve algorithm are proposed for detection and to fit the lane. The proposed SIP algorithm was evaluated by various tests. The experimental results indicate that the average time consumed for the detection of lane in each frame is 16.7639ms, and the accuracy of lane detection is 95. The proposed algorithm demonstrates good robustness, and can be used as the core algorithm for further application in lane departure warning systems. © 2015 - IOS Press and the authors. All rights reserved.

关键词： Computer vision

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Using a random forest method for epistasis detection in genome-wide association studies

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Journal of computational Information Systems 2014年第18期10卷 8043-8050页

作者： Zhou, Zhihui Liu, Guixia Su, Lingtao Han, Liang Yan, Lun College of Computer Science and Technology and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

Detecting susceptibility genes and gene-gene interactions (epistasis) is an important issue in genetic association analysis and genetic epidemiology. Due to the huge number of single nucleotide polymorphisms (SNPs) and inappropriate statistical tests, epistasis detection is a computational and statistical challenge and becomes a "needle-in-a-haystack" problem. Also some epistasis detection algorithms proposed in lots of literature have demonstrated their successes for small scale data, while most of them cannot be directly applied into genome-wide association studies (GWAS) and the pathogenesis of many common complex human diseases is mysterious. Here we adopted a random forest method incorporating information theory and a powerful statistical test, B-stat to detect epistasis. We conducted sufficient artificial experiments on a wide range of simulated datasets and compared performance of our random forest method with its two competitors, COE and BEAM. Experimental results demonstrated that this method is quite available and time efficiency for the haystack problem. We also presented the results of the application of the method to the WTCCC type 1 diabetes dataset. We reported some previously well known genes as well as some significant SNP interactions.

关键词： Statistical tests

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A survey on virtual network embedding in cloud computing centers

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Open Automation and Control Systems Journal 2014年第1期6卷 414-425页

作者： Wei, Xiaohui Hu, Shoufeng Li, Hongliang Yang, Fan Jin, Yue College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China

Bridging virtualized environments with physical environments, virtual network plays an important role in Cloud Computing infrastructures. How to allocate physical resources for virtual nodes/links to construct virtual network is known as Virtual Network Embedding (VNE) problem. It is a crucial issue that draws wide attention. This paper surveys existing VNE methods and algorithms and how they work under different application scenarios. First, a survey of different VNE objective metrics is presented;then several VNE algorithms are presented and categorized;finally, the performance of different VNE solutions are compared and discussed. © 2010, Bentham Science Publishers B.V. All rights reserved.

关键词： Cloud computing

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Simplifying Calculation of Graph Similarity Through Matrices

Simplifying Calculation of Graph Similarity Through Matrices

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The 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA 2015)

作者： Xu Wang Jihong Ouyang Guifen Chen College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University College of Information Technology Jilin Agricultural University

ISBN: (纸本)9783319483535

A method to simplify the calculation in the process of measuring graph similarity is proposed, where lots of redundant operations are avoided in order to quickly obtain the initial tickets matrixIn this proposal, the element value of the initial tickets matrix is assigned to 1 when it is positive in corresponding position of the paths matrix at the first timeThe proposed method calculates the initial tickets matrix value based on the positive value in the paths matrix in a forward and backward wayAn example is provided to illustrate that the method is feasible and effective.

关键词： Graph similarity measure Paths and tickets Adjacency matrix Forward and backward Simplifying calculation

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A Dynamic Multi-path Routing for VANET

A Dynamic Multi-path Routing for VANET

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2015 International Conference on Automation,Mechanical and Electrical engineering(AMEE 2015)

作者： Z.Y.Yuan D.Wei J.Q.Zhu Y.J.Hou M.Li T.Sun College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Regional Road Transportation Administrative Bureau

Compared with traditional VANET(Vehicular Ad-Hoc Networks) routing techniques, geographic routing has been proven to be more fittable for highly mobile scenes. Traditional routings use greedy modes or fixed forwarding paths to sent packets. But, the dynamic features of VANET such as fast changed topology, vehicles density and radio obstacles, could cause local maximum and sparse connectivity. Due to the characteristics of wireless channel, while there are too many packets transmit through a path, the delay and the number of packets loss will both increase clearly. We propose DMPR, a Dynamic Multipath Routing, combined with node location and digital map. The proposed DMPR detects transmission delay of different paths every once in a period of time, and dynamically determine the transmission ratio of each path. We execute NS2 simulation to exhibit that DMPR routing protocol significantly outperform three well known VANET ones in terms of the average packet delivery ratio and end-to-end delay.

关键词： VANET dynamic multi-path routing digital map transmission delay detection

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TDRec: Enhancing Social Recommendation Using Both Trust and Distrust Information

TDRec: Enhancing Social Recommendation Using Both Trust and ...

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European Network Intelligence Conference (ENIC)

作者： Tiansheng Bai Bo Yang Fei Li School of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China Computer Science Department George Mason University Fairfax VA USA

ISBN: (纸本)9781467375931

Traditional Collaborative Filtering has been one of the most widely used recommender systems, unfortunately it suffers from cold-start and data sparsity problems. With the development of social networks, more recommendation systems are trying to generate more eligible recommendation through excavating users' potential preferences using their social relationships. Almost all social recommender systems employ only positive inter-user relations such as friendship or trust information. However, incorporating negative relations in recommendation has not been investigated thoroughly in literature. In this paper, we propose a novel model-based method which takes advantage of both positive and negative inter-user relations. We apply matrix factorization techniques and utilize both rating and trust information to learn users' reasonable latent preference. We also incorporate two regularization terms to take distrust information into consideration. Our experiments on real-world and open datasets demonstrate the superiority of our model over the other state-of-the-art methods.

关键词： Europe

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An ensemble feature selection method based on mRMR for paired microarray data

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Journal of computational Information Systems 2014年第11期10卷 4875-4882页

作者： He, Lihua Cao, Zhongbo Wang, Yan Du, Wei Liang, Yanchun Key Laboratory for Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 China

With the development of high-throughput microarray chip technology, there are a large number of microarray expression data, which have few samples compared to the genes of high dimensions. And in recent years, more and more expression datasets contain samples of cancer tissues with their corresponding control tissues as paired. In the last decade, a variety of filter feature selection methods have been proposed. However, most of these methods rarely consider the effect of outlier and paired samples. In this article, we propose an ensemble feature selection method based on minimum redundancy maximum relevance (mRMR) method for paired microarray data. In order to increase the stability of the method, the improved method uses an ensemble strategy to generate diverse subsets from the original dataset. Then, the mRMR method is used to obtain multiple feature lists on the subsets. Finally, a rank aggregation strategy is adopted to decide the final list of selected features. We apply the method on six paired microarray datasets across different cancer types. Through comparison on the performance with other widely used filter methods, the proposed method obtains an excellent performance on the results. It indicates that the improved method is effective and has good applicability of feature selection for paired microarray expression data analysis. © 2014 Binary Information Press.

关键词： Feature Selection

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Dynamic lip identification algorithm based on automatic calibration of feature points

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Journal of Information and computational Science 2015年第15期12卷 5659-5665页

作者： Shen, Xuanjing Wang, Ziyu Wang, Yu Chen, Haipeng College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Applied Technology College Jilin University Changchun China

In order to avoid the defect of lip identification about one single picture and enhance the accuracy of the recognition, this paper applies the dynamic lip identification and puts forward the method to calibrate the feature points inner and outer of lips at the same time. Meanwhile, this paper introduces the algorithm of calibration of feature points and improves it on the basis of the algorithms. The improved algorithm not only reduces the computational complexity of the calibration, but also increase the accuracy of the calibration. In matching and recognition stage, the classifier of this paper is HMM. Experiments show that the algorithm reduces the computational complexity. Meanwhile, it enhances the accuracy of the recognition. © 2015 by Binary Information Press

关键词： Calibration

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