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SOSE 2005: IEEE International Workshop on Service-Oriented System engineering

作者： Zhang, Jing Jin, Ying Guo, De-Gui Liu, Lei Jin, Cheng-Zhi Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education of P.R.China Juin University Changchun 130012 China

ISBN: (纸本)0769524389

Mobile ambients is a process calculus for modeling mobile agents in wide-area networks. It has important theoretical and practical values in studying concurrent and mobile computation as well as the security of interactive systems. In this paper a frame structure is given for Mobile Ambients. First we introduce the concept of ambient calculus frame. Then we propose a construction method for translating an ambient definition into the frame definition, a transformation function is given based on the method. Next the movement and interaction of the code are discussed based on the frame structure. Finally an operating semantics is developed basing on the frame structure, an example of a frame and its execution are given. Introducing frame structure for ambient calculus is an attempt to provide languages support for asynchronous, distributed, and mobile programming. The ideas and methods in this paper can also be applied to other calculi with concurrency and mobility. © 2005 IEEE.

关键词： Mobile computing

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Learning essential graph with immune co-evolutionary algorithm

Learning essential graph with immune co-evolutionary algorit...

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International Conference on Information Science, Signal Processing and Their Applications

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

ISBN: (纸本)9780769541327

Essential graph is a graphical representation for Markov equivalence classes of Bayesian networks. Learning essential graph can avoid some problems in traditional Bayesian networks learning algorithms: (1) the number of illegal structures is exponential, which infect the efficiency of structure learning;(2) comparing the structures in same equivalent class slow down the speed of convergence;(3) if the prior distribution for each structure is equal, the more structures contain in the equivalent class the higher prior probability of the class has. This paper employs two competitive bio-inspired algorithms, immune algorithm and co-evolutionary algorithm, for learning Essential graph. The algorithm combines dependency analysis and search-scoring approach together. Experiments show that the searching space was decreased, compare with prior works, the convergence speed and the efficiency was improved. © 2010 IEEE.

关键词： Bayesian networks

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Grid Partition and Agglomeration for Bidirectional Hierarchical Clustering 2nd

Grid Partition and Agglomeration for Bidirectional Hierarchi...

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2nd EAI International Conference on Security and Privacy in New Computing Environments, SPNCE 2019

作者： Wu, Lei Chen, Hechang Yu, Xiangchun Chao, Sun Yu, Zhezhou Dou, RuiTing College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)9783030213725

Clustering is an important data processing tool, which can be used to reveal the distribution structure of unfamiliar domain data, or as preprocess methods to magnify data object to accelerate subsequent processing or simplify models. However, the distribution of many real-world data in feature space is very complex or uneven. Besides, the similarity/distance is not easy to be properly defined in feature space with different dimensional quantity. Therefore, many existing clustering algorithms are not stable in real datasets, and better performance of different datasets relies on artificial special design, such as scale normalization. In this paper, we propose a bidirectional hierarchical clustering (BHC) algorithm with two phases. In the first phase (Top-down), based on the probability density function of data in different dimensions, the feature space is divided into over-segmented grids to adapt to the complex distribution of data. In the second phase (Bottom-up), based on statistical information, a robust distance instead of geometrical distance is defined to agglomerate the grids into a dendrogram. Compared with the individual data points, grids created in the first phase can carry more statistical information, and the magnified processing objects can accelerate the clustering process. The second phase enhances the algorithm’s ability by the ability of recognize arbitrary shape data clusters. The effectiveness of BHC is compared with 20 popular or recent clustering algorithms on 8 artificial datasets and 6 real-world datasets. And the results show that our algorithm can achieve good results on most datasets. In particular, BHC surpasses all the comparison algorithms involved in the experiment on all real-world datasets. In addition, in order to test the efficiency of the algorithm, we design an experiment which can test the influence of dimension and data size on the operation time. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommuni

关键词： Clustering algorithms

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A Survey on Performance Optimization of High-Level Synthesis Tools

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Journal of Computer Science & Technology 2020年第3期35卷 697-720页

作者： Lan Huang Da-Lin Li Kang-Ping Wang Teng Gao Adriano Tavares College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012China Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Zhuhai 519041China Algorithm Center University of MinhoGuimaraes 4800058Portugal

Field-programmable gate arrays(FPGAs)have recently evolved as a valuable component of the heterogeneous *** register transfer level(RTL)design flows demand the designers to be experienced in hardware,resulting in a possible failure of ***-level synthesis(HLS)permits designers to work at a higher level of abstraction through synthesizing high-level language programs to RTL *** provides a promising approach to solve these ***,the performance of HLS tools still has *** example,designers remain exposed to various aspects of hardware design,development cycles are still time consuming,and the quality of results(QoR)of HLS tools is far behind that of RTL *** this paper,we survey the literature published since 2014 focusing on the performance optimization of HLS *** with previous work,we extend the scope of the performance of HLS tools,and present a set of three-level evaluation criteria,covering from ease of use of the HLS tools to promotion on specific metrics of *** also propose performance evaluation equations for describing the relation between the performance optimization and the *** find that it needs more efforts on the ease of use for efficient HLS *** suggest that it is better to draw an analogy between the HLS development process and the embedded system design process,and to provide more elastic HLS methodology which integrates FPGAs virtual machines.

关键词： evaluation criterion field-programmable gate array(FPGA) high-level synthesis(HLS) performance optimization quality of results(QoR)

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Building a Private Cloud Based on Microservices for Computer Science laboratory in Universities 7

Building a Private Cloud Based on Microservices for Computer...

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7th International Conference on Information Science and Control engineering, ICISCE 2020

作者： Liu, Hao Wang, Zhe Huang, Lan Wang, Kangping Jilin University School of Computer Science and Technology Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun China

ISBN: (纸本)9781728164069

Computer science labs in universities have different demands in cloud computing compared with typical IT companies. They differ greatly in software requirements and resource utilization. As an instance, we propose building a private cloud based on microservices with Docker and Kubernetes in our laboratory to match our labs' typical *** private cloud proposed in this paper is composed of multiple components such as authentication, service gateway, distributed storage, knowledge management, code management, etc. Furthermore, some typical research software systems are deployed as microservices in the private cloud. To satisfy complex software environment requirements, a multi version microservice is implemented. In our microservices platform, users can submit their own microservices and manage these microservices' life cycle through a web interface. In addition, the platform will automatically start and stop low frequency services to improve resource utilization rate. We use laboratory resources to conduct experiments and build a platform. With deploying the platform in our laboratory, it shows that the platform meets most of typical demands in research work and improves research efficiency. © 2020 IEEE.

关键词： Laboratories

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CBR and micro-architecture antipatterns based software design improvement

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IFIP TC12 1st International Conference on Artificial Intelligence Applications and Innovations, AIAI 2004

作者： Feng, Tie Zhang, Jiachen Wang, Hongyuan Wang, Xian Institute of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China

ISBN: (纸本)1402081502

This paper presents a Case Based Reasoning (CBR) approach to identifying micro-architecture anti-patterns and replacing them with "good" patterns in order to improve the design of software system. The resulting system design benefits from better flexibility for adapting to future requirement change and expansion. In this approach, both problematic inflexible structures and their corresponding refactoring designs are formally defined and organized in a case base. The identification of anti-patterns is carried out through similarity measurement on class diagrams, sequence diagrams, OO quality metric and semantic constraints. A supporting system CBDIT was developed to aid this approach. © 2004 Springer Science + Business Media, Inc.

关键词： Case based reasoning

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Extracting a justification for OWL ontologies by critical axioms

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Frontiers of Computer Science 2020年第4期14卷 55-64页

作者： Yuxin YE Xianji CUI Dantong OUYANG College of Computer Science and Technology Jilin UniversityChangchun130012China Key Lab of Symbolic Computation and Knowledge Engineering(Jilin University) Ministry of EducationChangchun130012China College of Information and Communication Engineering Dalian Minzu UniversityDalian116600China

Extracting justifications for web ontology language(OWL)ontologies is an important mission in ontology *** this paper,we focus on black-box techniques which are based on ontology *** creating a recursive expansion procedure,all elements which are called critical axioms in the justification are explored one by *** this detection procedure,an axiom selection function is used to avoid testing irrelevant *** addition,an incremental reasoning procedure has been proposed in order to substitute series of standard reasoning tests *** is implemented by employing a pseudo model to detect“obvious”satisfiability *** experimental results show that our proposed strategy for extracting justifications for OWL ontologies by adopting incremental expansion is superior to traditional Black-box methods in terms of efficiency and performance.

关键词： description logics automated reasoning ontology engineering justification

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Applying Kumaraswamy distribution on stick-breaking process: a Dirichlet neural topic model approach

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Neural Computing and Applications 2024年第22期36卷 13731-13744页

作者： Ouyang, Jihong Wang, Teng Cao, Jingyue Wang, Yiming College of Computer Science and Technology Jilin University Qianjin Street Jilin Changchun130015 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Qianjin Street Jilin Changchun130015 China

In recent years, neural topic modeling has increasingly raised extensive attention due to its capacity on generating coherent topics and flexible deep neural structures. However, the widely used Dirichlet distribution in shallow topic models is difficult to reparameterize. Therefore, most existing neural topic models assume the Gaussian as the prior of topic proportions for reparameterization. Gaussian distribution does not have the sparsity like Dirichlet distribution, which limits the model’s topic extraction ability. To address this issue, we propose a novel neural topic model approximating the Dirichlet prior with the reparameterizable Kumaraswamy distribution, namely Kumaraswamy Neural Topic Model (KNTM). Specifically, we adopted the stick-breaking process for posterior inference with the Kumaraswamy distribution as the base distribution. Besides, to capture the dependencies among topics, we propose a Kumaraswamy Recurrent Neural Topic Model (KRNTM) based on the recurrent stick-breaking construction to ensure that the model can still generate coherent topical words in high-dimensional topic space. We examined our method on five prevalent benchmark datasets over six Dirichlet-approximating neural topic models, among which KNTM has the lowest perplexity and KRNTM performance best on topic coherence and topic uniqueness. Qualitative analysis of the top topical words verifies that our proposed models can extract more semantically coherent topics compared with state-of-the-art models, further demonstrating our method’s effectiveness. This work contributes to the broader application of VAEs with Dirichlet priors. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Benchmarking

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The Improved Characteristics of Bionic Gabor Representations by Combining with SIFT key-points for Iris Recognition

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Journal of Bionic engineering 2015年第3期12卷 504-517页

作者： Yuanning Liu Fei He Xiaodong Zhu Zhen Liu Ying Chen Ye Han Lijiao Yu College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Chanschun 130012 China Graduate School of Engineering Nagasaki Institute of Applied Science Japan College of Software Nanchang Hangkong University Nanchang 330063 China

Gabor filters are generally regarded as the most bionic filters corresponding to the visual perception of human. Their filtered coefficients thus are widely utilized to represent the texture information of irises. However, these wavelet-based iris representations are inevitably being misaligned in iris matching stage. In this paper, we try to improve the characteristics of bionic Gabor representations of each iris via combining the local Gabor features and the key-point descriptors of Scale Invariant Feature Transformation （SIFT）, which respectively simulate the process of visual object class recognition in frequency and spatial domains. A localized approach of Gabor features is used to avoid the blocking effect in the process of image division, meanwhile a SIFT key point selection strategy is provided to remove the noises and probable misaligned key points. For the combination of these iris features, we propose a support vector regression based fusion rule, which may fuse their matching scores to a scalar score to make classification decision. The experiments on three public and self-developed iris datasets validate the discriminative ability of our multiple bionic iris features, and also demonstrate that the fusion system outperforms some state-of-the-art methods.

关键词： iris recognition bionic Gabor features scale invariant feature transformation support vector regression score level fusion

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A new SAT Encoding Scheme for Exactly-one Constraints 5

A new SAT Encoding Scheme for Exactly-one Constraints

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5th Annual International Conference on Network and Information Systems for Computers, ICNISC 2019

作者： Cai, Jiatong Su, Yating Yang, Xixi Min, Jionghao Lai, Yong College of Software Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

Exactly-one constraints have comprehensive applications for the fields of artificial intelligence and operations research. For many encoded SAT problems generated by the existing encoding schemes of exactly-one constraints, the state-of-the-art knowledge compilers cannot complete compilation. In this paper, we propose a new encoding scheme of exactly-one constraints. We introduce two-dimensional auxiliary variables (represented as a matrix) to denote the constraint that exactly one of some variables can be assigned as true. The clauses generated by our scheme is significantly less than those generated by three other existing encoding schemes. The experimental results on the exact cover problems show that the encoded CNF formulas generated by our scheme requires less compilation time, compared with the other three coding schemes. © Published under licence by IOP Publishing Ltd.

关键词： Operations research

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