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Aggregation tree constructing algorithm based on energy consumption assessment

Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2008年第1期45卷 104-109页

作者： Sun, Dayang Liu, Yanheng Wang, Aimin College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China College of Computer Science and Technology Harbin Engineering University Harbin 150001 China

This paper first gives an analysis of data aggregation and data compression based on energy consumption of sensor nodes, after which an approach is proposed to construct an aggregation tree in the case of non-perfect aggregation, since GIT considers only the case of perfect aggregation and it does not work well if the aggregation is non-perfect. An assessment scheme that can get the information of hops from the aggregation point to the sink and the hops from the aggregation point to the source node is used to construct such an aggregation tree. Moreover, the energy consumption of the aggregation is also considered. This scheme can be used when perfect aggregation cannot be performed. In this paper, an approach to reduce the cost of reinforcement is also proposed, in which the reinforcement work is done by the source nodes themselves, not by the sink node. Simulation result shows that this approach can save more energy than GIT when the aggregation ratio is small. This result also provides a theoretical limit of aggregation to tell when GIT will lose its superiority and thus gives a direction to choose among the aggregation algorithms. Another result shows that the further the sources are away from the sink, the less reinforcement messages are needed. Finally a guidance to tell when to use the EGA (energy consumption assessment) scheme is given.

关键词： Wireless sensor networks

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Efficient collision detection algorithm based on separating bounding volumes

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Ruan Jian Xue Bao/Journal of Software 2008年第SUPPL.期19卷 143-150页

作者： Wang, Yi Li, Wen-Hui Zhang, Zhen-Hua Key Laboratory of Symbol Computation and Knowledge Engineering College of Computer Science and Technology Jilin University Changchun 130012 China

An efficient collision detection method based on separating bounding volume (SBV) is proposed. The positions and shapes of SBVs are determined by the optimal separating support hyper planes of two objects. SBVs not only can efficiently detect the separation of models, but have a high culling ratio when models are intersecting. In order to compute SBVs efficiently, an approximate method using SVM is also put forward and tested. At last in penetration region, a method combined with GPU and SBVs is designed to handle the proximity queries. Experimental results illustrate that SBVs based collision detection algorithm is applicable to exact collision detection for 3D models even without topologies and achieves more efficient and balanced performances in separating, colliding and especially puncturing cases. © 2008 by Journal of Software. All rights reserved.

关键词： Support vector machines

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Combining Immune with Ant Colony Algorithm for Geometric Constraint Solving

Combining Immune with Ant Colony Algorithm for Geometric Con...

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International Workshop on knowledge Discovery and Data Mining (WKDD)

作者： Hua Yuan Yi Li Wenhui Li Kong Zhao Duo Wang Rongqin Yi Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China School of Computer Science & Engineering Changchun University of Technology China Suzhou Top Institute of Information Technology Suzhou China

Geometric constraint problem can be transformed to an optimization problem which the objective function and constraints are non-convex functions. In this paper an evolutionary algorithm based on ant colony optimization algorithm and the immune system model is proposed to provide solution to the geometric constraints problem. In the new algorithm, affinity calculation process and pheromone trail lying is embedded to maintain diversity and carry out the global search and the local search in many directions rather than one direction around the same individual simultaneously. This new algorithm different with current optimization methods in that it gets the good solution by excluding bad solutions. The experimental results reported here will shed more light into how affects the hybrid algorithm's search power in solving geometric constraint problem.

关键词： Immune system Ant colony optimization Nonlinear equations knowledge engineering Computer science Educational technology Evolutionary computation Data mining Laboratories Computer science education

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Unsupervised key-phrases extraction from scientific papers using domain and linguistic knowledge

Unsupervised key-phrases extraction from scientific papers u...

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International Conference on Digital Information Management (ICDIM)

作者： Mikalai Krapivin Maurizio Marchese Andrei Yadrantsau Yanchun Liang Department of Information Engineering and Computer Science University of Trento Italy Department of Computer Science Belarusian State University Minsk Belarus College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University China

The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement of userspsila navigation in the digital content. In this paper, we propose a combined use of machine learning techniques (i.e. Support Vector Machines) and Natural Language Processing techniques (i.e. Stanford NLP parser) to tackle the problem of unsupervised key-phrases extraction from scientific papers. The proposed method strongly depends on the robust structural properties of a scientific paper as well as on the lexical knowledge that we are able to mine from its text. For the experimental assessment we have use a subset of ACM papers in the Computer Science domain containing 400 documents. Preliminary evaluation of the approach shows promising result that improves - on the same data-set - on state-of-the-art Bayesian learning system KEA from a minimum 27% to a maximum 77% depending on KEA parameters tuning and specific evaluation set. Our assessment is performed by comparison with key-phrases assigned by human experts in the specific domain and freely available through ACM portal.

关键词： Data mining Software libraries Navigation Machine learning Support vector machines Support vector machine classification Natural language processing Robustness Computer science Bayesian methods

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A Heuristic Clustering Algorithm for Mining Communities in Signed Networks

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Journal of Computer Science & Technology 2007年第2期22卷 320-328页

作者：杨博刘大有 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 Changchun 130012 China

Signed network is an important kind of complex network, which includes both positive relations and negative relations. Communities of a signed network are defined as the groups of vertices, within which positive relations are dense and between which negative relations are also dense. Being able to identify communities of signed networks is helpful for analysis of such networks. Hitherto many algorithms for detecting network communities have been developed. However, most of them are designed exclusively for the networks including only positive relations and are not suitable for signed networks. So the problem of mining communities of signed networks quickly and correctly has not been solved satisfactorily. In this paper, we propose a heuristic algorithm to address this issue. Compared with major existing methods, our approach has three distinct features. First, it is very fast with a roughly linear time with respect to network size. Second, it exhibits a good clustering capability and especially can work well with complex networks without well-defined community structures. Finally, it is insensitive to its built-in parameters and requires no prior knowledge.

关键词： complex network signed network community clustering graph theory

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Self-organization based divide and conquer algorithm for distributed constraint optimization problems

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2008年第11期45卷 1831-1839页

作者： Huang, Jing Liu, Dayou Yang, Bo Jin, Di College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Changchun 130012 China

Distributed constraint optimization problem (DCOP) is a kind of optimization problem oriented to large-scale, open and dynamic network environments, which has been widely applied in many fields such as computational grid, multimedia networks, e-business, enterprise resource planning and so on. Besides the features such as non-linear and constraint-satisfaction which the traditional optimization problems have, DCOP has its distinct features including dynamic evolution, regional information, localized control and asynchronous updating of network states. It has become a challenge for computer scientists to find out a large-scale, parallel and intelligent solution for DCOP. So far, there have been a lot of methods for solving this problem. However, most of them are not completely decentralized and require prior knowledge such as the global structures of networks as their inputs. Unfortunately, for many applications the assumption that the global views of networks can not be obtained beforehand is not true due to their huge sizes, geographical distributions or decentralized controls. To solve this problem, a self-organizing behavior based divide and conquer algorithm is presented, in which multiple autonomous agents distributed in networks work together to solve the DCOP through a proposed self-organization mechanism. Compared with existing methods, this algorithm is completely decentralized and demonstrates good performance in both efficiency and effectiveness.

关键词： Geographical distribution

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Genetic algorithm with local search for advanced planning and scheduling

Genetic algorithm with local search for advanced planning an...

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3rd International Conference on Natural computation, ICNC 2007

作者： Pu, Yan Dayou, Liu Donghui, Yuan Ji, Yu Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)0769528759

In this paper, a genetic algorithm approach with a novel mutation operator based on perturbation and local search has been proposed to solve an advanced planning and scheduling (APS) model in manufacturing supply chain, in which each customer order has a due date, each operation could be performed on alternative machines. The objective is to minimize the makespan of each customer order while ensuring the due date constraints. Various sizes of numerical experiments were carried out to demonstrate the efficiency of the proposed GA and the results indicate that the presented algorithm performs much better than previous work especially in large size problems. © 2007 IEEE.

关键词： Genetic algorithms

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Complex knowledge system modeling based on Hierarchical Fuzzy Petri Net

Complex knowledge system modeling based on Hierarchical Fuzz...

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2007 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2007

作者： Hongjun, Pan Jigui, Sun Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)0769530281

The difficulties of modeling complex knowledge system lie in a large quantity of knowledge rules and the difficulty in organizing rules and grasping their mutual logical relationships. This article proposed a concept of hierarchical fuzzy Petri nets (HFPN), which is more suitable for modeling complex knowledge system than other fuzzy Petri Net models. In addition, the concepts of abstract place and abstract transition in HFPN are allowed to describe and analyze the knowledge system at diverse abstract levels. Therefore, using HFPN, the iterative and incremental methods can be applied to modeling complex knowledge system. In addition, structured approach can be naturally applied to the process of modeling knowledge system. © 2007 IEEE.

关键词： Petri nets

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Logical reinforcement learning method based on heuristic contour list

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2008年第11期45卷 1824-1830页

作者： Liu, Quan Gao, Yang Chen, Daoxu Sun, Jigui Yao, Wangshu State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Institute of Computer Science and Technology Soochow University Suzhou 215006 China Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Changchun 130012 China

Reinforcement learning gets optimal policy through trial-and-error and interaction with dynamic environment. Its properties of self-improving and online learning make reinforcement learning become one of most important machine learning methods. Against reinforcement learning has been 'curse of dimensionality' troubled by the problem the question, a method of heuristic contour list is proposed on the basis of relational reinforcement learning. The method can represent states, actions and Q-functions through using first-order predications with contour list. Thus advantages of Prolog list can be exerted adequately. The method is to combine logical predication rule with reinforcement learning. A new logical reinforcement learning-CCLORRL is formed and its convergence is proved. The method uses contour shape predicates to build shape state tables, drastically reducing the state space;Using heuristic rules to guide the choice of action can reduce choice blindness when the sample does not exist in the state space. The CCLORRL algorithm is used in the Tetris game. Experiments show that the method is more efficient.

关键词： Reinforcement learning

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Dynamic graph software watermark based on the Chinese Remainder Theorem

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Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (engineering and Technology Edition) 2008年第SUPPL. 2期38卷 198-201页

作者： Zhu, Jian-Qi Liu, Yan-Heng Yin, Ke-Xin Song, Shuang Key Laboratory of Symbol Computation and Knowledge Engineer College of Computer Science and Technology Jilin University Changchun 130012 China College of Computer Science and Engineering Changchun University of Technology Changchun 130012 China

The watermark is split into a set of shares and represented as a set of graphs, which are embedded into the program dynamically. Code obfuscating technique in the embedding phase was used. A novel scheme of dynamic data structure software watermarking is presented. This scheme can restore the watermark according to partial watermark shares and is very robust and stealthy.

关键词： Application programs

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