Xiyu Liu

Shandong Normal University, Chi-nan-shih, Shandong Sheng, China

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Publications (34)5.53 Total impact

  • Xiyu Liu, Jie Xue
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    ABSTRACT: Spatial cluster analysis is an important data mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann's computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis based on sticker systems of DNA computing. We will adopt the Bin-Packing Problem idea and then design algorithms of sticker programming. The proposed technique has a better time complexity. In the case when only the intracluster dissimilarity is taken into account, this time complexity is polynomial in the amount of data points, which reduces the NP-completeness nature of spatial cluster analysis. The new technique provides an alternative method for traditional cluster analysis.
    Discrete Dynamics in Nature and Society 04/2013; 2013. · 0.82 Impact Factor
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    ABSTRACT: Trust is an important mechanism to promote cooperation among persons in social network. As a security mechanism, it is widely implemented computer networks. In P2P applications, trust among cooperating peers is an essential precondition. It is becoming increasing vital in open, distributed, dynamic and anonymous networks to protect against malicious peers. This paper proposed a trust-aware propagation model based on the social network and with the basis of analyzing aware-computing to attempt to discover the propagation characteristics and regularity of trust being as network stability factor, and to reveal the functional mechanism of trust in the network security, which can improve the stability and robustness of the network. Firstly, we proposed a trust-aware propagation framework that contains three layers: propagation layer, aware layer, and computation layer. And then, the trust-aware propagation algorithm is presented to implement the formation of trust networks as fast as in P2P. A fitness function for peers computes their fitness degree based on contextual information to provide an initial entity identification mechanism, and the process of trust-aware propagation based on Markov process is defined to apperceive of trust among peers to ulteriorly form trust alliance. Thirdly, we built the dynamics model of trust propagation in order to deeply analyze the stability of trust networks. Next, three propagation strategies is proposed for implementing trust propagation. Finally, simulation experiments are carried in the bio-network platform. The results show that the trust-aware propagation model can effectively enhance the security and stability of P2P network, and improve the availability of the peer's resources.
    Knowledge-Based Systems. 03/2013; 41:8-15.
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    ABSTRACT: As a popular web innovation, Web service technology can provide a flexible solution to integrating diverse Web applications, taking advantage of existing Internet protocols and open standards. To provide on-request Web applications, Web services are evolving to be highly available, ubiquitous, self-managing, and adaptable to dynamic requests through distributed collaborations. However, the distributed collaborations unavoidably need security requirements, and traditional security mechanisms fail to address the challenge. On the other hand, trust is an important social concept and present in all human interactions. It has been proven as a promising way to resolving security problems raised by the distributed collaborations. This paper applies trust mechanisms into the development of a novel trust evaluation model of Web services. We first incorporate a trust management module into the standard Service Oriented Architecture (SOA). Then, regarding the trust relationships of service entities in Web service networks as a small-world network, we propose a trust evaluation model based on an amendatory subjective logic. The results of simulation experiments show the effectiveness of the proposed model, which outperforms other two models in terms of both detection capability and stability.
    Knowledge-Based Systems. 01/2013;
  • Xiyu Liu, Jie Xue, Xiaolin Yu
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    ABSTRACT: A novel multi-agent membrane computing technique is proposed. We provide a new membrane structure on graph to construct a multi-agent membrane system, which offers a new framework for collaboration and resources sharing among designers. The new design environment provides a tool to extend designer's ideas with the help of communication rules of membrane. Shapes were generated and changed in membrane systems by rules base on the idea of genetic computing with operators crossover, mutation and selection. A multi-agent membrane system with rules is constructed in detail. Finally, a pipe design example is adopted to illustrate the entire design process, which also shows the great parallelism, less time-consuming and synchronization of MAMC.
    Computer Supported Cooperative Work in Design (CSCWD), 2013 IEEE 17th International Conference on; 01/2013
  • Laisheng Xiang, Feng Qi, Xiyu Liu
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    ABSTRACT: A neural tree network model has been successfully applied to solving a variety of complex nonlinear problems. The optimization of the neural tree model is divided into two steps in general: first, structure optimization, and then parameter optimization. One major problem in the evolution of structure without parameter information is noisy fitness evaluation, so an improved breeder genetic programming algorithm is proposed to the synthesis of the optimization in neural tree network model. Simulation results on two time series prediction problems show that the proposed optimization strategy is a potential method with better performance and effectiveness.
    Kongzhi yu Juece/Control and Decision 01/2013; 28(1).
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    ABSTRACT: A class of new cloud computing model DCaaS is proposed. This model combines traditional DNA computing with SaaS model. The main advantage of DCaaS model is to separate biological experiments with DNA computing, and obtain biological operations as a service via DNA programs. As application frame, approximate solution of a class of nonlinear problems is presented.
    Proceedings of the 2012 international conference on Pervasive Computing and the Networked World; 11/2012
  • Jie Xue, Xiyu Liu
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    ABSTRACT: The directed Hamiltonian path (DHP) problem is one of the hard computational problems for which there is no practical algorithm on conventional computer available. Many problems, including the traveling sales person problem and the longest path problem, can be translated into DHP problems. Inspired by the biological neurons, priority of rules in membrane computing, we introduce spiking neural P systems with priority and multiple output neurons into the application of DHP problems. In this paper, a new SN P System based algorithm is presented. We use neurons to stand for all the possible path and filter out the DHP we want automatically, all the processes will implement in the new SN P system. Instances indicate that the proposed SN P system based algorithm reduces the time complexity efficiently by huge parallelism.
    Proceedings of the 2012 international conference on Pervasive Computing and the Networked World; 11/2012
  • Yuzhen Zhao, Xiyu Liu, Jianhua Qu
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    ABSTRACT: In this paper a clustering algorithm based on a P System with active membranes is proposed which provides new ideas and methods for cluster analysis. The membrane system has great parallelism. It could reduce the computational time complexity. Firstly a clustering problem is transformed into a graph theory problem by transforming the objects into graph nodes and dissimilarities into edges with weights of complete undirected graph, and then a P system with all the rules to solve the problem is constructed. The specific P system with external output is designed for the dissimilarity matrix associated with n objects. First all combinations of all nodes are listed to show all possibilities of the paths (the solution space) by using division rules of P system. Then a shortest path with the minimum sum of weights is selected. At last the path is divided into k parts from the edges with the k-1 biggest weights according to the preset number of clusters k. That is to say, all nodes are divided into k clusters. The calculation of the P system can get all the clustering results. Through example test, the proposed algorithm is appropriate for cluster analysis. This is a new attempt in applications of membrane system.
    Proceedings of the 2012 international conference on Pervasive Computing and the Networked World; 11/2012
  • Jie Xue, Xiyu Liu
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    ABSTRACT: Using membrane computing to do some creative design is a new approach in this field. We use multi-sets of P system to assign customers' requirements and experienced models, constructing P system with rewriting rules which is suit for our design, getting the results that we want. All of the above steps are carried out in membranes. Because of the high parallelism of membrane computing, we can get the results rapidly.
    01/2012;
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    ABSTRACT: Spatial cluster analysis is an important data-mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann’s computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis based on DNA computing and a grid technique. We will adopt the Adleman-Lipton model and then design a flexible grid algorithm. Examples are given to show the effect of the algorithm. The new clustering technique provides an alternative for traditional cluster analysis.
    Discrete Dynamics in Nature and Society 01/2012; 2012. · 0.82 Impact Factor
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    ABSTRACT: Logistics company alliance building problem studies that how to build alliance with a method of great rate and low cost. It presents an improved algorithm about graph clustering base on PSO to solve the problem. Optimize the clustering result through PSO, and expand the solution space through disturbance strategies in order to obtain the optimal solution. Experimental result shows that the algorithm can solve the problem in a high rate and low cost.
    Information Technology in Medicine and Education (ITME), 2012 International Symposium on; 01/2012
  • Feng Qi, Xiyu Liu, Yinghong Ma
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    ABSTRACT: Neural tree model has been successfully applied to solving a variety of interesting problems. In most previous studies, optimization of the neural tree model was divided into two steps: first structure optimization, then parameter optimization. One major problem in the evolution of structure without parameter information was noisy fitness evaluation. In this paper, an improved breeder genetic programming algorithm is proposed to the synthesis of neural tree model. The effectiveness and performance of the method are evaluated on time series prediction problems and compared with those of related methods. Simulation results show that the proposed algorithm is a potential method with better performance and effectiveness.
    Neural Computing and Applications 01/2012; · 1.76 Impact Factor
  • Xiyu Liu, Alice Xue
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    ABSTRACT: The purpose of this paper is to propose a new kind of P systems on simplicial complexes. We present the basic discrete Morse structure, membrane structures on complexes, and communication rules. A new grid-based clustering technique is described based on this kind of new P systems. Examples are given to show the effect of the algorithm. The new P systems provide an alternative for traditional membrane computing.
    Discrete Dynamics in Nature and Society 01/2012; 2012. · 0.82 Impact Factor
  • Jie Xue, Xiyu Liu
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    ABSTRACT: Using DNA computation to solve graph clustering problem is a new approach in this field. We use DNA strands to assign vertices and edges, constructing the minimum spanning tree and cutting branches whose length is longer than the threshold .All of the above steps are carried out in test tubes. Because of DNA computation's high parallelism, we can get the results rapidly. Key words-DNA computation; graph clustering; minimum spanning tree; test tubes ,� Introduction Clustering is the assignment of a set of data into subsets so that data in the same cluster are similar and data between clusters are different. Graph clustering can divide vertices and their connected edges into subgraph so that vertices in the same subgraph are closely connected and vertices'connection between different subgraph are not close. When the number of information in graphs becomes too large, we cannot perceive all elements at the same time. A clustered graph can greatly reduce visual complexity ,thus, graph clustering is commonly used in many areas, such as visual presentation of large-scale map, observation, analysis , navigation and so on�‰ �>�=�? This paper proposes a new approach to cluster graph .We use DNA computing technique to solve the graph clustering problem. DNA computation means that DNA molecules can act as parallel processors to solve computation hard problems . In 1994 Adleman computed the seven vertices of Hamiltonian path problem with DNA in test tubes. From (Guo et al. 2005), we know that DNA-based algorithms can solve many computational problems. especially some NP-complete or NP-hard problem, In 1995, Lipton solved the 3- satisfiability problem. Later, the maximal clique problem and the
    01/2011;
  • Xiyu Liu, Laisheng Xiang
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    ABSTRACT: Graph clustering is an important area of cluster analysis with wide applications in social networks, data transformation and bioinformatics. The purpose of this paper is to propose a new method in graph clustering, the discrete Morse technique. We propose a new optimization outline using Morse theory, describe graph clustering into simplicial complex, and present an algorithm to construct the discrete vector fields. An example show the work procedure of the proposed method.
    01/2011;
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    ABSTRACT: Spatial clustering is an important cluster problem. Typical algorithms include k-medoids, density and gravity based clustering, and the minimum spanning tree based clustering. Although there have appeared extensive studies with proposed algorithms and applications, one of the basic computing architecture is that they are all at the level of data objects. The purpose of this paper is to propose a new clustering technique based on grid architecture. Our new technique integrates minimum spanning tree and grid clustering together. A time complexity analysis shows that the new technique has O(NlogN) computing time which is better than many proposed algorithms. This new technique is simple and will apply for large scale clustering problems potentially.
    Dynamics of Continuous, Discrete and Impulsive Systems Series B: Applications and Algorithms 01/2011; 3(3).
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    ABSTRACT: Spanning subgraph is necessary for the communication in networks. For example, the malfunctioning of one or more nodes in a network in general affects both the global and the local properties of the remaining nodes, because it makes some edges unusable and destroys the connectivity of the system. In this study, we focus on the characters of a network to be fractional-r-factors, fractional (r, k)-extendable and fractional (r,n)-deleteble. An efficient algorithm, based on a result which indicate that G has a minimum fractional 1-factor whose indictor function defined on {1, 1/2} if G has a fractional 1-factor, were designed to find a minimum fractional 1-factor.
    E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on; 12/2010
  • Jianhua Qu, Yinghong Ma, Xiyu Liu
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    ABSTRACT: This paper proposed a new point symmetry-based ant clustering algorithm which can defect the number of clusters and the proper partitions from data sets when data sets possess the property of symmetry. In the proposed algorithm, a revised ant clustering algorithm is presented which can reduce the running time of standard ant clustering algorithm. Each ant represents a data object. It will decide its next moving position according to similarity function and probability converting function between it and its neighbors. At the same time it will update its cluster number according to clustering rules. Each ant only depends on a little local information to cluster. Assignment of points to different clusters is done based on point symmetry distance rather than the traditional Euclidean distance. Kd-tree-based nearest neighbor search is used to reduce the complexity of computing PS-based distance. The effectiveness of point symmetry-based ant clustering compared to standard ant clustering is demonstrated for one artificial and one real-life data sets.
    Seventh International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010, 10-12 August 2010, Yantai, Shandong, China; 01/2010
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    ABSTRACT: Service overlay network (SON) is a virtual service network built on an underlying network. It purchases resources from the underlying network and provides cross-domain and QoS sensitive value-added services to gain profits. Resource pricing is thus a key problem for the SON operator. This paper is devoted to the study of the problem of resource pricing with elastic demand based on game theory. After giving an SON architecture, the pricing problem is formulated in a bi-level programming model taking the effect of congestion and QoS on the objectives into consideration. The upper level model aims to maximize the difference between the revenues and the cost of the whole SON system, while the lower level model is a Wardrop user equilibrium model with elastic demand. A heuristic solution algorithm based on the trial-and-error procedure and difference sensitivity analysis method is designed for the proposed bi-level programming model when precise link congestion metric function and demand function are unknown. Numerical examples are also performed to illustrate the convergence and effectiveness of the bi-level programming model.
    Journal of University of Science and Technology of China. 01/2010; 4(4).
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    ABSTRACT: The purpose of this paper is to propose a new design optimization technique based on flow computing and Morse theory. The basic idea is based on previous works by the authors on evolutionary architecture paradigm of evolving architectural form. Models will evolve according to a descending flow. Mathematical models include analytical functions, parametric functions and other nonlinear functions will be used to describe the design models. We also present analysis of relationship between evolution and exploration.
    01/2010;