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A concurrent model for temporal hierarchical task network

Journal of computational and Theoretical Nanoscience 2016年第5期13卷 3135-3138页

作者： Feng, Yuxuan Ouyang, Dantong Feng, Shasha Liu, Jie College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun130012 China

When several actions preformed at the same time, or performed concurrently, the possibility of multiple concurrent and mutually interacting make the planning solving process difficult. In this paper, we reform the framework of hierarchical task network planning paradigm to present the concurrent action planning, to make good use of domain knowledge to improve the performance of planner. There are several remarkable works deal with temporal planning problem by hierarchical task network planning paradigm, our work focus on the concurrent performing actions. The experimental results is positive. Copyright © 2016 American Scientific Publishers All rights reserved.

关键词： Nanoscience

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Pancreatic cancer biomarker detection using recursive feature elimination based on Support Vector Machine and large margin distribution machine

Pancreatic cancer biomarker detection using recursive featur...

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International Conference on Systems and Informatics (ICSAI)

作者： Yidan Lv Yan Wang Yongfei Tan Wei Du Keke Liu Hao Wang Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Basic Medicine School Jilin University Changchun China Department of Hepatopancreatobiliary Surgery and Second Affiliated Hospital Harbin Medical University Harbin China

Pancreatic cancer acts as one of the leading causes of cancer-connective deaths. Its five-year overall survival rate being reported is about 7.7% from 2006 to 2012 by the National Cancer Institute. One of the main causes for its poor prognosis is because its non-typical symptoms make early diagnosis very challenging. Therefore, a predominant strategy for early accurate detection and prognostication on pancreatic cancer is vital to the whole course of comprehensive therapy. In this research, we proposed a method which combined Recursive Feature Elimination (RFE) method based on Support Vector Machine (SVM) and Large Margin Distribution Machine (LDM) to identify potential biomarkers for pancreatic cancer. In our experiments, we have strengthened the process of RFE to achieve better performance. The dataset GSE15471 we adopted are from GEO database with 39 pairs of pancreatic ductal carcinoma and adjacent control pancreatic tissues. Through experiments, a panel of twelve genes was identified as biomarkers in pancreatic cancer with 91.28% classification accuracy. The universality of the candidate genes was examined on another dataset GSE28735 and the classification accuracy was higher than 80%. In addition, by using the SVM, LDM and BP classifiers, we compared the ordered feature sets generated by our proposed method with T-test, SVM-RFE and LDM-RFE, and the results indicated our proposed method obtained higher average classification accuracy.

关键词： Cancer Support vector machines Feature extraction Tumors Training data Testing

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Optimizing simple tabular reduction with a bitwise representation 25

Optimizing simple tabular reduction with a bitwise represent...

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25th International Joint Conference on Artificial Intelligence, IJCAI 2016

作者： Wang, Ruiwei Xia, Wei Yap, Roland H.C. Li, Zhanshan School of Software Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Education Ministry China School of Computing National University of Singapore Singapore

Maintaining Generalized Arc Consistency (GAC) during search is considered an efficient way to solve non-binary constraint satisfaction problems. Bit-based representations have been used effectively in Arc Consistency algorithms. We propose STRbit, a GAC algorithm, based on simple tabular reduction (STR) using an efficient bit vector support data structure. STRbit is extended to deal with compression of the underlying constraint with c-tuples. Experimental evaluation show our algorithms are faster than many algorithms (STR2, STR2-C, STR3, STR3-C and MDDc) across a variety of benchmarks except for problems with small tables where complex data structures do not payoff.

关键词： Data structures

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The BBC news hunter: A novel crawler for BBC news 2nd

The BBC news hunter: A novel crawler for BBC news

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2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

作者： Wang, Mingxin Wang, Ning Wang, Boran Tian, Can Liang, Yanchun Zhao, Guozhong Han, Xiaosong College of Software Jilin University Changchun130012 China Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun130012 China Zhuhai Laboratory of Key Laboratory for Symbol Computation Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Zhuhai519041 China Daqing Oilfield Personnel Development Institute CNPC Daqing163000 China

ISBN: (纸本)9789811020971

In order to distinguish and extract the topic information from other interferential information on the BBC news website for the study in social computing, the BBC News Hunter was proposed in this paper. The whole system consists of 6 subsystems, respectively named: UI, Control, Download, Analysis, Storage and Log. Numerical experiments show that satisfactory results can be obtained from the BBC news website, whose average accuracy as well as efficiency are acceptable. © Springer Science+Business Media Singapore 2016.

关键词： Data mining

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A Group key Management Scheme Based on Random Transmission for VANET

A Group Key Management Scheme Based on Random Transmission f...

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2016 6th International Conference on Machinery,Materials,Environment,Biotechnology and Computer(MMEBC 2016)

作者： Liang PANG Da WEI Qi ZHAO Jianqi ZHU College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Jilin University

ISBN: (纸本)9781510828087

Group key management plays an important role in ensuring the safety and reliability of the VANET(vehicular ad-hoc network) over the channelThrough considering the characteristics of VANET communication and topology, a VANET group key management scheme is proposed based on random transmission which is combined with the construction of polynomial and key updating by Hash chainThe scheme achieves the random transmission function of group key and the node revocation capabilityMoreover, it can ensure the forward and backward and other security attributes of the group keyThe results show that the proposed scheme has less communication complexity and better communication performance, also it can suitable for large scale VANET group.

关键词： VANET Group Random Transmission Polynomial Hash Chain

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Minimum cover set coverage algorithm for achieving low energy in wireless sensor networks

Minimum cover set coverage algorithm for achieving low energ...

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2016 4th International Conference on Advanced Materials and Information Technology Processing(AMITP 2016)

作者： AIMIN WANG YINGNAN GAO WENJUAN JIA College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University College of software Jilin University

A minimum cover set coverage algorithm（MCSCA） for pursuing low energy is presented in this paper to prolong the lifetime of wireless sensor networks. The proposed algorithm improves energy efficiency in three aspects. First, when generating cover sets, the selection strategy of the algorithm considers the contributions of sensor nodes, energy variance, and other factors. The algorithm can cover all targets with a few sensor nodes. Second, useless coverage optimization reduces coverage areas without target nodes to save energy. Third, redundant coverage optimization further saves energy by reducing redundant coverage in wireless sensor networks. Compared with similar heuristic algorithms, the proposed MCSCA can extend network lifetime by 11% on average.

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Dynamics Analysis of Bionic Parallel Joint Mechanism for the Snake Robot

Dynamics Analysis of Bionic Parallel Joint Mechanism for the...

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第35届中国控制会议

作者： Chuncheng Wu Zhengcai Cao Qing Xiao Yili Fu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University State Key Laboratory of Robotics and Systems Harbin Institute of Technology College of Information Science and Technology Beijing University of Chemical Technology

ISBN: (纸本)9781509009107

Joint mechanism is a key factor for a snake robot adjusting its postures adapted to clutter environments in search and rescue *** joint mechanisms in prior research simply consist of serially connected revolute joints,which are lack of great load carrying *** nature snake structure,a modular bionic parallel joint mechanism(BPJM) is proposed for the rescue snake *** analysis of the BPJM is necessary for its optimal design and control,providing the force and constraint that must be resisted by joints,links and *** reduce the dynamics computation load,Newton equation and Euler equation are combined by synchronizing the inertial force and inertial moment with the aid of screw ***,the dynamics equations for moving platform and links are formulated in a simplified *** friction at the joints and external force acting on BPJM,which actually affect the motion,are both considered in the ***,the virtual prototype is provided in order to visualize the joint mechanism and the numerical results from the dynamics analysis are given.

关键词： Rescue snake robot Dynamics analysis Bionic parallel joint mechanism Screw theory Newton method

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Interactive Activity Learning from Trajectories with Qualitative Spatio-Temporal Relation

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Chinese Journal of Electronics 2015年第3期24卷 508-512页

作者： WANG Shengsheng WEN Changji LAI Yong LIU Yiting LIU Dayou College of Computer Science and Technology Key Laboratory of Symbolic Computing and Knowledge Engineering of Ministry of Education Jilin University

Automatically analyzing interactions from video has gained much attention in recent years. Here a novel method has been proposed for analyzing interactions between two agents based on the tra jectories. Previous works related to this topic are methods based on features, since they only extract features from objects. A method based on qualitative spatio-temporal relations is adopted which utilizes knowledge of the model(qualitative spatio-temporal relation calculi) instead of the original tra jectory information. Based on the previous qualitative spatio-temporal relation works, such as Qualitative tra jectory calculus(QTC), some new calculi are now proposed for long term and complex interactions. By the experiments, the results showed that our proposed calculi are very useful for representing interactions and improved the interaction learning more effectively.

关键词： Interactive activity learning Tra jectory pair Qualitative spatio-temporal relation

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Attribute selection for job shop scheduling problem based on concept lattice

Attribute selection for job shop scheduling problem based on...

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第27届中国过程控制会议（CPCC2016）

作者： Wang Zhenjiang Cao Zhengcai Liu MinJilin College of Information Science and Technology Beijing University of Chemical Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education University Department of Automation Tsinghua University

Attribute selection is an effective approach to improve the inference efficiency of data-based schedulingstrategies system and many researchers have studied the attribute selection based on computational intelligence *** computational intelligence methods,concept lattice,an important tool for knowledge extraction andanalysis,has nature advantages in attribute

关键词： Attribute selection for job shop scheduling problem based on concept lattice

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Research on Trust Prediction from a Sociological Perspective

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Journal of Computer Science & Technology 2015年第4期30卷 843-858页

作者：王英王鑫左万利 College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun 130012 China School of Computer Technology and Engineering Changehun Institute of Technology Changchun 130012 China

Trust, as a major part of human interactions, plays an important role in helping users collect reliable infor-mation and make decisions. However, in reality, user-specified trust relations are often very sparse and follow a power law distribution; hence inferring unknown trust relations attracts increasing attention in recent years. Social theories are frameworks of empirical evidence used to study and interpret social phenomena from a sociological perspective, while social networks reflect the correlations of users in real world; hence, making the principle, rules, ideas and methods of social theories into the analysis of social networks brings new opportunities for trust prediction. In this paper, we investigate how to exploit homophily and social status in trust prediction by modeling social theories. We first give several methods to compute homophily coe？cient and status coe？cient, then provide a principled way to model trust prediction mathe-matically, and propose a novel framework, hsTrust, which incorporates homophily theory and status theory. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of homophily theory and status theory in trust prediction.

关键词： trust prediction homophily coefficient status coefficient social theory matrix factorization

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