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Information Engineering, 2009. ICIE '09. WASE International Conference on

Date 10-11 July 2009

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Displaying Results 1 - 25 of 126
  • [Front cover - Vol 2]

    Page(s): C1
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  • [Title page i - Volume 2]

    Page(s): i
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  • [Title page iii - Volume 2]

    Page(s): iii
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  • [Copyright notice - Volume 2]

    Page(s): iv
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  • Table of contents - Volume 2

    Page(s): v - xii
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  • Preface - Volume 2

    Page(s): xiii
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  • Organizing Committee - Volume 2

    Page(s): xiv
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  • Technical Program Committee - Volume 2

    Page(s): xv
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  • Reviewers - Volume 2

    Page(s): xvi
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  • Case Study on Dynamic Evolution of Software Based on AOP

    Page(s): 3 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (414 KB) |  | HTML iconHTML  

    Many software must be upgraded continuously and dynamically for the bugs and the needs of new function as well as the change of environment. Dynamic evolution to software contains the adding, modifying, deleting of software modules and the transferring of states from the old version to the new one. In this paper, we propose an AOP based method that (1) views the evolution of modules as aspects, (2) uses analysis to ensure the correctness of evolution, and (3) provides 3 sub-methods to handle addition, deletion and modification of classes. An example is impleented using JBOSS AOP, demonstrating correctness of the proposed method. View full abstract»

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  • Genetic Algorithm for Hybrid Flow-Shop Scheduling with Parrel Batch Processors

    Page(s): 9 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (172 KB) |  | HTML iconHTML  

    In classical flow-shop scheduling problem, each processor can process one job at a time. However, in practice, there may be many processors that can process jobs batch by batch. We call these processors batch processors. If the processing time of a batch is equal to the largest processing time among its members, we call such a batch processor parallel batch processor. In this paper, we study the hybrid flow-shop problem in which the processors are parrel batch processors. This problem is obviously NP-hard. Therefore, we propose a genetic algorithm in this work. View full abstract»

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  • An Identity-Based Proxy Signature from Bilinear Pairings

    Page(s): 14 - 17
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    Currently, ID-based PKC has attracted much attention and got many achievements. Proxy signature allows an original signer to delegate his private key to a proxy signer to sign some message on behalf of the original signer. We present a ID-based proxy signature in this paper. The scheme is relatively efficient as there is no pairing computation during the Delegation and PSign phases. It is secure against existential forgery under adaptive chosen message and identity attack under the random oracle model. Its security can be reduced to the hardness of CDHP. View full abstract»

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  • Improved Energy-Aware AODV Routing Protocol

    Page(s): 18 - 21
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (291 KB) |  | HTML iconHTML  

    Ad hoc mobile network is a highly dynamic wireless network, routing is the key issues in application. The most of current routing protocols perform not well on energy-saving, for which a improved energy-saving AODV is proposed. The protocol proposes a strategy for energy levels and improved Hello mechanisms. Simulations and related analyses show that in large-scale ad hoc network, the routing protocols can significantly improve the efficiency of the route extend the network's lifetime. View full abstract»

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  • Design of Cognitive Radio Node Engine Based on Genetic Algorithm

    Page(s): 22 - 25
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (199 KB) |  | HTML iconHTML  

    The radio frequency spectrum is a scarce natural resource, so it is very important to use the spectrum efficiently. Cognitive radio, which can greatly improve the spectrum utilization, is able to adjust the transmit parameters according to the environment. In this paper, an adaptive multi-objective genetic algorithm is proposed to design the cognitive radio engine. In order to improve the performance of the algorithm, adaptive mutation mechanism and the elite strategy is introduced into the proposed algorithm. Moreover, the proposed algorithm is used to design a cognitive radio engine in a multi-carrier system with ten sub-carriers. The simulation results show that the proposed algorithm is feasible and effective. View full abstract»

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  • An Algorithm of Static Load Balance Based on Topology for MPLS Traffic Engineering

    Page(s): 26 - 28
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (227 KB) |  | HTML iconHTML  

    Aimed to the limitations of traditional routing algorithms and to perfect MPLS application in the domain of load balance, an algorithm of static load balance based on topology is designed in this dissertation. When the shortest path is congested in the network, the algorithm is used to find a low load sub-shortest path for the congestion path based on the bandwidth occupied situation and the topology. By using MATLAB to simulate the algorithms and compared with traditional algorithm, this algorithm can better ease the network congestion problems because of unbalanced allocation of network resource. View full abstract»

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  • Novel Routing Algorithms for Hierarchical Architecture in ASON

    Page(s): 29 - 32
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (402 KB) |  | HTML iconHTML  

    The hierarchical routing infrastructure in automatic switched optical network (ASON) is researched. Three operational algorithms MLLR (multi-layer least loaded routing algorithm), MLCR (multi-layer least congestion routing algorithm) and MROB (multi-layer routing algorithm based on backtracking) are proposed. In these algorithms, the resource coordination and balancing of multi-domain and multilayer are considered based on the fixed alternate hierarchical routing. A platform named AHORSP (ASON based hierarchical optimal routing & signaling platform) supporting our routing optimization scheme is proposed and demonstrated. Based on the platform the average block probability can be reduced effectively with acceptable time performance by these algorithms. View full abstract»

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  • Research of Grid-Similarity-Based Clustering Algorithm

    Page(s): 33 - 36
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (307 KB) |  | HTML iconHTML  

    Aim at the limitations of traditional measurement method on similitude between objects, we put forward grid-similarity-based clustering algorithm (GSCA), it brings in a new criterion to measure the similitude between objects. It applies on the grid clustering and disposes the density threshold of grid by the method of density threshold that improves the precision of clustering. Besides, the GSCA algorithm disposes the very high dimension datasets by the technique of entropy. The algorithm appears its advantages in the comparative experiments with some traditional clustering algorithm. View full abstract»

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  • Combining Classifier Based on Decision Tree

    Page(s): 37 - 40
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (256 KB) |  | HTML iconHTML  

    A new classifier ensemble learning algorithm based on decision tree is proposed. Ensemble learning algorithm is one of the algorithms which have best classification results in many classification algorithms. A decision tree algorithm is a kind of greedy algorithm, it use top-down recursive way to determine the tree structure. The proposed algorithm improved the accuracy of classification by combining the advantage of Boosting algorithm with decision tree. The main idea is to make full use of the advantages of ensemble learning algorithm and decision tree. We introduce the algorithm procession in detail. The proposed algorithm proved that the property which has the smallest classification error rate as of decision tree is equivalent to the branching method of traditional decision tree. The algorithm uses the rapid classification capabilities of decision tree. In the meantime, we take into account the classification accuracy of joint classification. Finally, Experiments with UCI machine learning data sets show the effectiveness of the proposed algorithm. View full abstract»

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  • An Improved Entropy-Based Ant Clustering Algorithm

    Page(s): 41 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (234 KB) |  | HTML iconHTML  

    Sorting and clustering methods inspired by the behavior of real ants are among the earliest methods in ant-based meta-heuristics. We revisit these methods in the context of a concrete application and introduce some modifications that yield significant improvements in terms of both quality and efficiency. In this paper, we propose an Improved entropy-based ant clustering (IEAC) algorithm. Firstly, we apply information entropy to model behaviors of agents, such as picking up and dropping objects. The entropy function led to better quality clusters than non-entropy functions. Secondly, we introduce a number of modifications that improve the quality of the clustering solutions generated by the algorithm. We have made some experiments on real data sets and synthetic data sets. The results demonstrate that our algorithm has superiority in misclassification error rate and runtime over the classical algorithm. View full abstract»

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  • A Depth-Dependent Fusion Algorithm for Enhanced Reality Based on Binocular Vision

    Page(s): 45 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5957 KB) |  | HTML iconHTML  

    As one of the pivot techniques in enhanced reality the fusion of virtual and real scene image often happens in two ways, either to incorporate a real object into a virtual environment, or to incorporate a virtual object into a real scene. Most of the conventional methods for the fusion are conducted at the image level, which fails to handle three-dimensional objects. In this paper, a novel depth-dependent algorithm for the fusion of virtual and real scene image in enhanced reality based on binocular vision will be proposed. The algorithm simulates the human observation process, and computes the spatial position of an image pixel by means of binocular parallax. With the assistance of object recognition techniques, the depth computation results will then be utilized to determine the spatial position of the object in the observation coordinate frame. The fusion is consequently implemented by positioning the object of interest at the right position and establishing the depth relationship with other objects in the scene. Experiment results demonstrate that the proposed algorithm is both valid and effective to achieve a high quality fusion for an enhanced reality application. View full abstract»

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  • Hybrid Ant Colony Algorithm Based on Vehicle Routing Problem with Time Windows

    Page(s): 50 - 53
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (290 KB) |  | HTML iconHTML  

    Vehicle routing problem with time windows (VRPTW) is an NP-complete optimization problem. The objective of VRPTW is to use a fleet of vehicles with specific capacity to serve a number of customers with fixed demand and time window constraints. A hybrid ant colony system (DSACA-VRPTW) is proposed to solve this problem. Firstly, each antpsilas solution might be improved by dynamic sweep algorithm which makes improvement to the solutions by grouping the customers. Then a new improved ant colonies technique is proposed, after all colonies are in the state of stagnation, communication among them is carried out in order to do favor to leave the local peaks. Finally, Solomonpsilas benchmark instances (VRPTW 100-customer) are tested for the algorithm and shows that the DSACA is able to find solutions for VRPTW. View full abstract»

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  • Quantum Algorithms of the Subset-Sum Problem on a Quantum Computer

    Page(s): 54 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    In this paper, quantum algorithms for solving an instance of the subset-sum problem is proposed and a NMR experiment for the simplest subset-sum problem to test our theory is also performed. View full abstract»

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  • A New Ultralightweight RFID Protocol with Mutual Authentication

    Page(s): 58 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (231 KB) |  | HTML iconHTML  

    Due to the well-developed technology and its variety of applications, the radio frequency identifications (RFIDs) become more and more popular. In many applications such as authentication, the RFID systems need security mechanism to resist all possible attacks and threats. However, most of the security mechanisms always too complex on computation or need large memory space such that they are not suit for low-cost RFIDs. In this paper, we propose a new ultralightweight RFID authentication protocol with mutual authentication. The protocol requires only simple bit-wise operations and can resist various attacks. View full abstract»

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  • Bionic Learning Algorithm Based on Skinner's Operant Conditioning and Control of Robot

    Page(s): 62 - 65
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (251 KB) |  | HTML iconHTML  

    Aiming at the problem about the movement balance control of two-wheeled self-balancing mobile robot, a learning algorithm that it is made up of BP neural network and eligibility traces based on the operant conditioning theory is put forward as a learning mechanism of the two-wheeled robot. The algorithm utilizes the characters of eligibility traces about quicker learning speed, higher reliability and ability in resolving effect about delay, so that the two-wheeled robot can obtain the movement balance skills of controlling like a human or animal by interacting, studying and training with unknown environmental, and realize the movement balance control of the two-wheeled robot by using the complex learning algorithm. Finally, a simulation experiment is done and the simulation results show that a learning mechanism of the complex learning algorithm can embodies the stronger skills of self-learning and abilities of balance control of the robot, and it also has the higher research significance in theory and the application value in project. View full abstract»

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  • An Adaptable Anycast Routing Algorithm Based on Density and Proximity

    Page(s): 66 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB) |  | HTML iconHTML  

    Most existing anycast routing algorithms are based on shortest path algorithm. In this paper, an adaptable anycast routing algorithm based on density and proximity is proposed. While determining anycast member, both the proximity factor and nearby anycast members number of the target (density factor) should be considered. Density is calculated on the base of field theory. In comparison with proximity-based algorithm, density-based algorithm is strong in routing robustness, but weak in routing efficiency, so the best performance lies in a tradeoff between proximity and density. In this algorithm, parameter k adjusts the weight of proximity factor and density factor hence influences anycast member selection, therefore the algorithm is characteristic of adaptable. Simulation experiments performed in networks of different dynamic degrees show that by adjusting parameter k, routing robustness and routing efficiency can be well balanced. View full abstract»

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