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5th International Conference on Control and Automation, ICCA'05

作者： Zhang, Jian Sun, Jigui Li, Niya Hu, Chengquan Li, Zehai College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Ministry of Education China

ISBN: (纸本)0780391381

The workflow model is the abstract expression of the workflow or the business process. Following the WfMC reference model, a PKI-based lightweight workflow model named as PBLW is put forward in this paper. The framework of PBLW is proposed. Based on the time constraint directed graph, the workflow theory model in formalization is described in detail, and the time constraint problems are discussed in order to enhance the time management ability of the workflow model. Furthermore, in order to express the complicated secure access control constraint of the workflow, a conditioned RBAC model based on PKI technology is presented, according to the traditional RBAC security access control model. Finally, the workflow engine driven algorithms for the workflow instance are given. By the actual inspection and users' feedback, it proves that this model can express the basic requirements of a majority of the process applications. © 2005 IEEE.

关键词： Electronic document identification systems

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Detecting epistasis by LASSO-penalized-model search algorithm in human Genome-Wide Association Studies

Detecting epistasis by LASSO-penalized-model search algorith...

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4th International Conference on Materials Science and Information Technology, MSIT 2014

作者： Zhou, Zhi Hui Liu, Gui Xia Su, Ling Tao Han, Liang Yan, Lun College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9783038351733

Extensive studies have shown that many complex diseases are influenced by interaction of certain genes, while due to the limitations and drawbacks of adopting logistic regression (LR) to detect epistasis in human Genome-Wide Association Studies (GWAS), we propose a new method named LASSO-penalized-model search algorithm (LPMA) by restricting it to a tuning constant and combining it with a penalization of the L1-norm of the complexity parameter, and it is implemented utilizing the idea of multi-step strategy. LASSO penalized regression particularly shows advantageous properties when the number of factors far exceeds the number of samples. We compare the performance of LPMA with its competitors. Through simulated data experiments, LPMA performs better regarding to the identification of epistasis and prediction accuracy. © (2014) Trans Tech Publications, Switzerland.

关键词： Genes

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A BRS-based approach for modeling RFID untraceability

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International Journal of Advancements in computing Technology 2011年第11期3卷 96-103页

作者： Jialiang, He Dantong, Ouyang Youjun, Xu College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China College of Computer Science and Information Technology Daqing Normal University China

Untraceability is an important aspect of RFID security. A BRS-based approach for modeling RFID untraceability is provided in this paper. Elements in a RFID protocol can be represented as bigraphs, communications between elements can be represented as reaction rules. RFID untraceability can be represented as behavioral congruences. We take a RFID air interface protocol as a case study and show the usability of this approach.

关键词： Radio frequency identification (RFID)

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Multiple Auxiliary Information Based Deep Model for Collaborative Filtering

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Journal of Computer Science & Technology 2018年第4期33卷 668-681页

作者： Lin Yue Xiao-Xin Sun Wen-Zhu Gao Guo-Zhong Feng Bang-Zuo Zhang School of Information Science and Technology Northeast Normal University Changchun 130117 China Key Laboratory of Applied Statistics of Ministry of Education Northeast Normal University Changchun 130024 China School of Environment Northeast Normal University Changchun 130117 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

With the ever-growing dynamicity, complexity, technique is proposed and becomes one of the most effective and volume of information resources, the recommendation techniques for solving the so-called problem of information overload. Traditional recommendation algorithms, such as collaborative filtering based on the user or item, only measure the degree of similarity between users or items with single criterion, i.e., ratings. According to the experience of previous studies, single criterion cannot accurately measure the similarity between user preferences or items. In recent years, the application of deep learning techniques has gained significant momentum in recommender systems for better understanding of user preferences, item characteristics, and historical interactions. In this work, we integrate plot information as auxiliary information into the denoising autoencoder （DAE）, called SemRe-DCF, which aims at learning semantic representations of item descriptions and succeeds in capturing fine-grained semantic regularities by using vector arithmetic to get better rating prediction. The results manifest that the proposed method can effectively improve the accuracy of prediction and solve the cold start problem.

关键词： semantic representation plot information denoising autoencoder collaborative filtering auxiliary information

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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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A design of product configuration manager based on weight constraint parameter value in manufacture

A design of product configuration manager based on weight co...

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5th International Conference on Control and Automation, ICCA'05

作者： Li, Niya Liu, Dayou Zhang, Jian College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China

ISBN: (纸本)0780391381

The configuration problem in manufacture is more complicated than most other fields. Therefore, the design of modeling and reasoning module for product configuration manager in manufacture is very important and complex. It is just what is mainly discussed in this paper. A framework of PCM in manufacture is put forward according to the Expert System theories, and a series of formalized knowledge representations and a data-driven graph control strategy for the PCM are provided. In the knowledge representations, the weight constraint is defined to distinguish the origins of the parameter value. It can be used to simplify the consistency check and effectivity check of the parameter. Furthermore, the search space of the configuration problem can be also easily compressed. The control strategy strengthens the real-time interaction between the user and the PCM so as to decompose the reasoning process. The reasoning process of the control strategy is described in detail by the configuration reasoning graph which is defined in this paper. © 2005 IEEE.

关键词： Flexible manufacturing systems

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A Spatial Correlation-Based Hybrid Method for Intrusion Detection 9

A Spatial Correlation-Based Hybrid Method for Intrusion Dete...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jianqi Zhu Jian Mu Da Wei Bao Feng Youjin Wang Kexin Yin College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Communication and Knowledge Engineering of Ministry of Education Jilin University School of Computer Science and Engineering Changchun University of Technology

ISBN: (纸本)9781509038237;9781509038220

In order to solve the problem of low intrusion detection rate and weak generalization ability of Intrusion Detection System（IDS）, it proposes a new hybrid method based on the relationship of feature and spatial correlation for IDS. The proposed IDS reduces the dimension of network data flow by spatial correlation-based dimension reduction method（SCDR）. It improves the effectiveness of intrusion detection, and the negative feedback learning method can also improve the generalization ability of IDS. Experiments show that the method in this paper can improve the detection rate notably and also enhance the detection ability of unknown attacks.

关键词： network security intrusion detection systems data dimension reduction negative feedback learning method

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Operational semantics of ambient calculus

Operational semantics of ambient calculus

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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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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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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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