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International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)

  • Author(s)/Editor(s):
  • Published:
    2009
  • DOI:
    10.1115/1.802977
Description | Details

The ICACTE 2009 was organized to gather members of the international community of Computer Theory and Engineering scientists so that researchers from around the world could present their leading-edge work, expanding our community's knowledge and insight into the significant challenges currently being addressed in that research.

  • Copyright:
    All rights reserved. Printed in the United States of America. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. ©  2009  ASME
  • ISBN:
    9780791802977
  • No. of Pages:
    2012
  • Order No.:
    802977
Front Matter PUBLIC ACCESS
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  • Session 1

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      This research aimed to design an intelligent S/W agent to represent the sign languages to educate the deaf student as special needs individuals according to the international criteria of tutoring computer software as an intelligent tutoring system. Semi-experimental method and a comparative study between two types of representing sign language (digital video or 3d animation) are shown to determine the most appropriate methods for raising the learning rate of the deaf students. The designed application limited to the unit taught is “The nutrition systems” from the Science curriculum, Second year, Al Amal Schools, at Egypt. The research results revealed that there are significant statistical differences between the averages of the degrees of the two experimental groups in achievement, attributed to the difference type of displaying the sign language (Digital Video or 3d animations) for behalf of the group used the digital video and the Intelligent S/W agent.
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      Reconfigurable computing is the next generation approach to compute the algorithms with as much high speed as that of application specific integrated circuits along with the as much flexibility as that of programmable processors. The reconfigurable instruction set processors being most prominent execution platforms for reconfigurable computing have been evolved through many design alternatives. The evolution has explored that the execution performance of a typical reconfigurable processor is greatly dependant on the basic design of its configuration unit. Configuration updation of reconfigurable processor is the dynamically controlled by this unit and hence this unit plays a vital role in the performance enhancement of reconfigurable processor. In this research paper an efficient configuration unit design has been presented which has the capability of loading the most optimal configurations by making the maximum reusability of the existing configuration streams. The simulated results have shown that proposed configuration unit always demonstrates most optimal configuration overhead for reconfigurable processors and hence can be used in high speed reconfigurable instruction set processors.
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      Biomedical signal recordings are affected by different kinds of noise that make their interpretation difficult. In this paper, we present a comparative study of some wavelet functions in the denoising of phonocardiogram (PCG) signals. In particular, we consider the Daubechies of order 4, 6, 8, 10 and 15, Coiflets of order 3, 4, 5 and finally Symlets 10 (sym 10). The performance of these wavelets is based on the measurement of the signal-to-noise Ratio (SNR) of the denoised signal as well as the Mean Square Error (MSE) between the original noisy signal and its denoised counterpart. The results indicate that Daubechies of order 10 (db10) outperform other wavelet functions and, consequently, are potential candidates in the characterization of abnormal PCG signal.
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      Image reconstruction is the art of obtaining a three dimensional scene from 2D images.. Approaches for image reconstruction are, Shape from shading, Shape from texture, Shape from motion, and Shape from stereo. In Shape from stereo or the Stereo Image Reconstruction only two images are used to reconstruct the scene. The most difficult problem in Stereo image reconstruction is the correspondence problem. Matching each pixel is a complex process results in many mismatches and inaccurate three dimensional scene. We have done matching in two levels, the first level is Feature based matching, the second level is Area-based matching. We have joined the two levels to obtain a more accurate pixel by pixel correspondence. We also obtained an adaptive search range and window size for each pixel to reduce the mismatches. Our procedure introduced high accuracy results and more dense 3D scene.
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      Traditional data collection protocols suffer “hot spot” problem heavily in area around the sink node. Recently proposed schemes using mobile sinks try to balance the load with the cost of sink mobility. However, most approaches are based on unit disk graph (UDG) model, which is inaccurate in physical world. We propose an UDG-free solution for data collection with mobile sinks using dominating set and traveling salesman problem (TSP) techniques. A distributed algorithm for dominating set construction is presented, and the result set is used in approximate TSP algorithm to generate a moving path. Our solution not only reduces communication overhead, but also balances the load distribution.
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      This paper presents investigations into the development of feed-forward control schemes for anti-swaying control of a rotary crane system. A nonlinear rotary crane system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. An unshaped square-pulse torque input is used to determine the characteristic parameters of the system for design and evaluation of the feed-forward control techniques. Feed-forward control schemes based on input shaping and filtering techniques are to be examined. The proposed techniques are designed based on the properties of the system for anti-sway control. The responses of the rotary crane system to the shaped inputs are analyzed in time and frequency domains. Performances of the control schemes are examined in terms of sway angle reduction and time response specifications. Finally, a comparative assessment of the proposed control techniques is presented and discussed.
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      Learning systems are very effective tools for discovering knowledge from databases. Most symbolic learning systems face difficulties when discovering knowledge from large databases. Adapting the learning systems to cope with large databases is the traditional solution to overcome these limitations. This paper evaluates a new methodology for partitioning the representation space. The method selects an irrelevant attribute, determined by a utility function, to partition the representation space. Since irrelevant attributes are not needed to describe concepts learned from the original data, the knowledge discovered from all subspaces should be independent of such an attribute. If the representation space is partitioned by a relevant attribute, the knowledge discovered from all subspaces are combined simply using information about that attribute. The method is analyzed using C5 learning system, or See5.
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      One of the major drawbacks of multi-carrier systems is the high peak-to-average power ratio (PAPR) of the transmitted signals. In this paper, the proposed novel low-complexity selective mapping (SLM) and partial transmit sequences (PTS) schemes are applicable to interleaved orthogonal frequency division multiple access (OFDMA) uplink systems for PAPR reduction. The basic idea is to explore the special structure of interleaved OFDMA, so as to reduce the complexity of PAPR reduction. Current PAPR reduction techniques can be combined with the proposed structure, SLM and PTS are combined for instance. Simulation results show that compared with traditional techniques, the proposed technique can gain the same PAPR reduction but with considerable complexity reduction. The new SLM interleaved OFDMA scheme reduces the computational complexity, while it shows almost the same performance of PAPR reduction as that of the conventional SLM interleaved OFDMA scheme, the new PTS proposed can reduce the complexity too. This method needs side information in the receptor.
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      In this paper, based on the concept of domain decomposition, we construct a class of new alternating group explicit iterative method for fifth order dispersive equations. The method has the intrinsic property of parallelism. Results of numerical experiments show the method is more effective than the known SOR iterative method.
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      In Content-Based Image Retrieval (CBIR), indexing techniques based on global features that relate color and texture are commonly used to represent a description of images. However this approach is unable to capture local information of parts of the image that contain different characteristics. Therefore, some necessary local features of image may be might do not taking in account. This research introduces the new methods in which using the force histograms and radial density to capture some invariant local features. The results show that the force histograms and radial density use to solve the problem caused by variations in scaling, rotation, and translation. Furthermore this technique provides that efficient features to retrieve the sought image where difference pattern of objects may affect the retrieval accuracy.
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      This paper proposes a comparative study of different noise removel techniques and wavelet analysis for image denoising. The performance of these techniques was investigated using an image test Lena and real-life images obtained by the Scanning Electron Microscope (SEM) with a set of predefined noise levels. The performance of these techniques was carried out with respect to two quantitative measures: Peak signal-to-noise ration (PSNR), and mean Square Error (MSE). Experimental results on Lena image and image of SEM are compared with various denoising techniques such as mean filtering; median filtering, Wiener filtering and discrete wavelet transform (DWT) analysis in conjunction with neighbour threshold. The results of the comparative study show that this method presents the best performance among all denoising techniques.
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      The atomic force microscope (AFM) is considered a powerful tool used for imaging at nanometer scale. The microscope tip has to go back and forth in a raster scanning motion over a substrate carrying the sample at slow rate to get enough accurate image of the sample. Many algorithms are designed to solve such problem by steering the tip along the surface of the sample. In the present work, a control algorithm is designed to steer the tip along the desired sample surface only. The scanning process is carried out simply, rabidly, and acquiring high resolution. The proposed algorithm depends only on the data coming from the vertical sensing device. The algorithm is tested for different samples and it is found to be ideal in imaging string-like objects, such as carbon nanotubes, nanowires, and DNA strands. The algorithm performance is accurate, reliable, and resolution is now a controlled parameter.
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      With the widely applied of P2P technology recent year, its illegitimate use on unauthorized sharing of copyrighted files is increasingly rampant. In order to track down these illegal activities, monitoring P2P tasks precisely is needed. To address this issue, we present a method for monitoring the specific content of BtiTorrent file sharing. The method is able to monitor BitTorrent stream according to specific content, no mater the torrent file of the content is possessed or not.
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      Asynchronous transfer mode (ATM) has been adopted as the switching and transport infrastructure for the future broadband integrated services digital network (B-ISDN). The extension of broadband services to the wireless environment is being driven mainly by the proliferation of multimedia portable computers, personal digital assistants, and personal information assistants. Although there are various competing technologies that may provide these services, such as 3G cellular networks and WLAN, wireless ATM has the advantage of offering end-to-end multimedia capabilities with guaranteed quality of service (QoS). The wireless medium has several unique properties which make the design of WATM networks more challenging than the wired one. The most important challenge is the MAC protocol and the Scheduling algorithms that is used to traffic regulation based on traffic characteristics.
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      Student project allocations models (SPA) in which lecturers have preferences over students or projects have been studied in [8, 9]. This paper presents a visualization of a new general student project allocation model in which the lecturers have preference over pairs. The purpose is to provide the user with visual illustrations of student-project allocation algorithm with Preference over Pairs. The visualization is implemented in Java for the fact that it is a web-oriented language.
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      A mobile platform is a huge opportunity for future commercial transactions. This platform should be equipped with a proper middleware, and then traditional commercial applications could be redefined for this new platform. We proposed an architecture style to fill the gap, and excess the development of commercial applications on mobile phones.
  • Session 2

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      There are more than 1000 languages and 14 scripts used by 112 million people in India. All of these scripts divide the document in three parts: Text block, Image block, and Table block. In 21st century, there is a need, obvious reasons, to convert these old printed documents in digital form. Converting them manually is a huge and difficult task. Further it is prone to human errors. Another automated technique is to use Optical character recognition (OCR) system to convert the entire printed document image into editable document. In this paper, an effort has been made to develop OCR technique which converts the printed document into editable document. Firstly a scanned document is preprocessed for noise and skew correction. It is then followed by text-non text classification. Then text line detection has to be performed in the text area. There is no method available which can detect the text line if the image contains the multicolumn text area. In this paper the main contribution is to detect the blocks and detect the text lines in these detected blocks. The technique which can extract the text lines in image document is presented here. After extraction of text lines, word segmentation, character segmentation, and template matching can be performed.
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      EC_ERP is proposed in this paper for integration of E-Business and ERP. The necessity and feasibility analysis of E-Business and ERP integration in terms of market competition, problems in ERP implementation, software development etc. are provided; Strategy is given for implementing ERP in Chinese enterprises; 4-stage EC_ERP implementation process is presented based on the 4-stage ERP implementation theory proposed by Markus and Tanis.
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      In this paper, based on the nine point implicit difference scheme we present a class of alternating group explicit (AGE) iterative method of order four accurate for poisson equations. Also convergence analysis is given. The method has the property of intrinsic parallelism and group explicit computation. In order to verify the AGE method we give several numerical examples. Comparison of the AGE iterative method with nine point implicit scheme show that the method is of nearly the same accuracy with the nine point implicit scheme, and the AGE method can shorten the running time clearly.
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      The Inadequacies of classical design process in developing load compatible-lightweight components have compelled the designers to exploit CAE (computer aided engineering) structural optimization tools effectively early at design stage. Currently, the contemporary design process has entered to a realm where CAE based optimization; simulations and analysis are indispensable for designing the optimal configurations of novel products. In this research, nonparametric three-dimensional structural topology optimization is investigated to find the novel load-compatible configuration design of an operating structure of civil aircraft by exploiting TOSCA and ANSYS software. Analytical load calculations pertinent to the operating and ground conditions are estimated and applied by considering the orientation of structural assembly members and build-in supports offered in the main structure. A smoothened topological optimized model is then imported in CATIA software to extract the CAD viable design. A methodology is also devised to modify the layout of topological optimized voids with splines and fillets, to construct manufacturalbe features and avoid stress concentrations. The resulting novel design is then analyzed and validated against stipulated loads, constraints and other requirements.
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      Aerial image classification is a method to classify and identify the objects on digital maps. Color, edge, shape, and texture have been extracted in order to classify objects on the aerial images. These feature attributes can be obtained directly from aerial images. However the complexity of data and number of rule based may be over information, which it can be reduced by the data mining techniques. In this research, we focus on the use of Fuzzy Logic for pattern classification. The attribute classifications have followed by the design and the implementation of its corresponding tool (Fuzzy Miner). Finally, the context of Fuzzy Miner is identified and to classify for its improvement are formulated. Extensive tests are performed to demonstrate the performance of Fuzzy Miner and compared with a performance Fuzzy C-Mean classifier. The results showed that, Fuzzy Miner has the best outcomes while Fuzzy C-Mean has the second rank outcomes.
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      One of the most important challenges of Bayesian networks is training an optimal network based on existing training samples. We propose two Learning Automata-based methods for training parameters and structure of the network. Parameter training method is an incremental method which performs training and testing simultaneously and has lower computational cost than enumerative or search based parameter training methods. The structure training method uses a guided search scheme and avoids getting stuck in local maxima. This outputs a network that improves classification accuracy. We could also use both these methods together to train the network. Results indicated that this combinational method further improved classification accuracy while still kept computational cost rational.
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      The exploration of lunar satellite, “No.l Chang e” is simulated with the orbit design by using Matlab GUI and virtual reality design tool. The scene can be chosen by selecting different observation angles. In the mean time, image capturing, processing and transmitting are also simulated. It is the long distance that signal has to pass thus suffers a tremendous attenuation during the deep space transmission. The image will get serious noise which makes the picture blurry. Therefore, we should take the link budget very carefully, including the influence of the atmosphere, to make sure that the image quality is acceptable. On the other hand, some image processing algorithms are also considered.
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      On account of the interferential problem of milling the helicoid, the helical groove's profile are different from the milling cutter's cutting edge that result in difficulty in tool edge design; and the chip flutes of cutting tools have crucial effect in cutting capability and the machining quality, It need improve design precision of milling cutter so that meet the machining precision demand of spiral flute, especially under the different cutting parameters circumstances. Using BP neural network's nonlinear mapped characteristic to simulate discrete coordinates of cutting edge so that obtain the purpose of high precision designing cutting tools' profile. Therefore, a nonlinear model, which is established between the reamer's spiral finite and the milling cutter's profile by BP neural network. According to spiral flute profile, BP neural network simulate the cutting edge of under different helicoid parameter with the Levenberg-Marquardt back-propagation algorithm, the simulating experimental result has proved that using neural network to design milling cutter's profile can satisfy the actual need and can simulate the tool edge under different machining parameter.
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      Following the direction of higher vocational education reform, based on the reform practice at Baoding Vocational College of Technology, we proposed “3-tower diagram” reverse educing method to develop highly skilled personnel training plan. The method characters and procedure are briefly described and detailed implementation is given by an example of developing computer application major vocation personnel training plan.
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      This paper describes an adaptive middleware platform, consisting of the interface model, framework model and perception model, which respectively build on components-based, reflection and event-driven technologies. The interface model encapsulates reusable implementation code, and makes it interact with its environment through well-defined interfaces. The framework model classifies component, and makes component statically or its corresponding object dynamically evolvable. The perception model based on event-driven asynchronous push model opens component object's inner states to outer world. Finally, this paper presents an application example of the implementation of GUI system on our platform.
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      In the paper, the computer control system of self-learning expert for industrial powder injection production is introduced which has been successfully applied. And the working principle and design method of computer hardware and software is discussed. Moreover, the whole process of continuous real-time measurement and closed-loop control for powder injection amount and feed rate of fed-batch part is introduced.
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      In this paper, we present a four order unconditionally stable implicit scheme for 2D hyperbolic equations. Based on the scheme and the concept of decomposition a class of parallel alternating group explicit (AGE) iterative method is derived, and convergence analysis is given. In order to verify the AGE iterative method, we give an example at the end of the paper.
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      A corporate network consists of many individual network security components. Firewall, active directory, and IDS are some examples of these components. Each network security component has its own high level security policy which is translated into low level security mechanisms. There is a wide gap between high level and low level representation of security policy making enforcement of high level security policy faces some essential difficulties. Consistency, verification, and maintenance are the major ones of these difficulties. One approach to overcome these difficulties is to present security policy in an intermediate level and then automate the translation of the intermediate level security policy into low level security mechanisms. Extended Organization Based Access control (EOrBAC) model is valuable step towards introducing this intermediate level. One of the major advantages of EOrBAC is its ability to model most network security components. This paper extends the work of EOrBAC by applying its concept on active directory network security component. Also, an EOrBAC based network security management toolkit is developed to realize this approach.
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      Urban water supply quantity forecasting belongs to non-linear system problem. To forecast urban water supply quantity exactly, support vector machine optimized by genetic algorithm (GA-SVM) is proposed. Genetic algorithm (GA) is used to determine training parameters of support vector machine in GA-SVM. The experimental results indicate that the proposed GA-SVM model can achieve great accuracy in urban water supply quantity forecasting.
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      Spatial exploration projects become more and more complex, involving several different communication nodes posing various communication challenges. To deal with communication challenges in Mars, an interplanetary overlay Network is proposed to establish a communication infrastructure among planets, natural and artificial satellites, and various mission elements such as spacecrafts and rovers. Mars surface nodes in such network have limited resources in terms of storage, energy, processing power. To this end, the paper proposes a resource-aware routing in Interplanetary Surface Network (IPRAR). Performance results are promising.
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      This paper introduces the multicast communication model based on TCP/IP protocol, explicates the support for IP multicast by Winsock 2, designs and realizes the activity image IP multicast system in the local area network environment.
  • Session 3

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      In this paper, we present a new time-frequency voice modification concept of speech signal for listeners with hearing impairment. The proposed method, named FBSOLA, for Filter Bank Synchronous Overlap and Addition, explore the SOLA algorithm used for Time-Scale-Modification of speech signal in order to establish a new time-frequency modification method using the M subbands obtained by a Filter Bank analysis-synthesis. We have used the Cosine Modulated Pseudo-QMF Banks. This combined technique allows the modification of both temporal rhythm and spectral envelope of speech signal. A practical solution for perfect reconstruction using the Cosine Modulated Pseudo-QMF Bank is proposed in this paper. The result is a fairly inexpensive (small amount of computation), flexible algorithm that performs a large variety of modifications in order to improve the speech intelligibility for hearing impaired listeners. A software system of the proposed technique is implemented in order to perform complex high quality modifications of speech signal. Experimental results show that the speech signal can be successfully modified to different time-scale/ frequency-magnitudes with high quality.
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      An enterprise would get into a disaster state if they take the liberty to develop software without a good risk measurement. Therefore, the measure is very significant no matter for theoretic or practice. However, the measurement is quite difficult because there are many risk factors in process of software development. And, how much is the holistic risk of a project? Balanced the profit gained from the project and the risk, whether is worth to develop it or not? The questions are always scabrous for the corporations and scholars researched in software engineering field. In this paper, we made creatively a definition of risk fusion, and demonstrated the rationality of risk fusion measurement by using information entropy, and developed a model of risk fusion measurement of software development based on information entropy, and answered the former problems, and also provided a model case. The model can be used to measure the risk fusion, which have been proved in practice, and can be used as basis for risk decision-making.
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      Project-oriented teaching methods were proposed in developing an Engineering Hydrology in a learning content management system, in which a digital learning environment was used to manage, organize and implement course materials, teaching, and evaluation. The system will be applied in training water information technology professionals. The system adopted information technology and curriculum integration, which enable student to complete the training, learn necessary knowledge, and to build up the ability to achieve the designated goals.
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      Accurate forecasting of reservoir's water flow dispatching is very significant to reservoir's optimum dispatching. In order to realize accurate forecasting results of reservoir's water flow dispatching, RBF neural network optimized by genetic algorithm (GA-RBFNN) is proposed in the paper. Genetic algorithm is well suited for searching global optimal values in complex search space. Thus, genetic algorithm is used to dynamically optimize the training parameters of RBFNN. Based on the comparison with the forecast result from BP neural network, the proposed GA-RBFNN model has higher forecasting accuracy.
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      The process and characteristics of the instructional design of adult mobile learning resources are studied in this paper. We first analyzed the characteristics of adult mobile learning resources, and studied each step in the designing process, considering the characteristics of adult mobility. Then we referred to international digital learning resources standards and criteria, considering the characteristics of mobile equipment and adult learners, and we built a resources designing model suitable for adult mobile learning. In the end, we gave some advices to the resource- designers.
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      The target of this contribution is presentation of non standard ways of backup database creation in Oracle. First way is the creation of physical standby database by PL/SQL script, which consists of creation standby initialization files, hot backup copy of primary database data files to standby location and startup of new standby database in Data Guard configuration. Alternative way uses cold backup of primary database and offline copy of backup data files to standby locality. A concept of database backup creations for specific problem, where using of implemented tools in Oracle is unnecessary, is also presented. At that manner are used PL/SQL tools only, without using supplementary services.
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      A set of time- and frequency-domain mixed indexes considering both guidance loop overall performance and hardware constraint was presented. However, the autopilot response using the index exhibited slowly. A general autopilot design procedure synthesized optimal control and frequency-domain constraint was thus proposed. Wherein, the weights selection was transformed into an optimization problem. A four-loop topology was examined to deal with the special case of low-frequency actuator. The analysis and simulation results show that relaxing the static stability of a missile is only benefit to improve missile steady performance. Though a static unstable missile can be stabilized, the finite resource of actuator is the crucial limited factor dominating autopilot function.
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      Sensing coverage and expanding lifetime are important issues for wireless sensor networks. The nodes scheduling for energy-efficiency coverage problem is NP-complete. We considered the problem for the wireless sensor networks with heterogeneous sensing ranges. It typically belongs to a multi-objective optimal model. We present an energy-efficient coverage optimization algorithmbased on Micro-GA multi-objective optimization algorithm (MGAMOO) to solve it. The novel strategy aims to search a Pareto non-dominated front to give a strong support to the selection of optimal active nodes set. To be practical, we have obtained a protocol, HEECO. Numerical simulation experiments were carried out to demonstrate the performance of the proposed algorithm and protocol. Compared with other former protocols, our method shows better qualities in the effects of deployed nodes and amount of active nodes.
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      In view of the early prediction of mine fires, a new method had been studied. The parameters, the coal's spontaneous combustion tendency, the concentration of some gases, were comprehensively analyzed according to different mine condition, which could be used to predict mine fires. The fire prediction model was set up based on neural network optimized by Levenberg-Marquardt algorithm. This was benefit to speed up the convergence rate and improve forecasting rate of identification. Simulation results show that the rate of correct prediction was further improved. This algorithm propound a new way on fire information identification which achieves the most early prediction and the accurate identification of non-fire information before the fire happens.
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      In order to strengthen the data consistency of asynchronous replication protocol, this paper presents an asynchronous replication protocol under fixed space-consistency (ARPFS). ARPFS can achieve fixed data consistency between the primary and backup systems by adjusting the response time of completing write requests dynamically. It is proved by experiments that ARPFS affords a performance between synchronous protocol and asynchronous protocol. It is useful to construct a practical replication system base on fixed data consistency.
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      In the typical implementation of the SHA-1 algorithm, resource constrain makes it meet the limit in the low cost FPGA. The huge need of Slice challenges the use of it. In this paper, we present a spectrum of approaches to implement SHA-1. They are not only taking full advantage of the embedded block RAM and distribute RAM in the FPGA, but also the algorithm optimization to balance the logic block consumption and the speed. We aim to provide different implementation to satisfy the FPGA of different classes in various embedded applications.
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      The paper presents an algorithm for path planning and cooperating two mobile robots, for doing all possible tasks by one mobile robot by using two mobile robots, with cooperation mobile robots in a dynamic environment with obstacles and without any collision between them. Path planning for two mobile robots by using artificial potential field (APF) for reach the same target. Two mobile robots in an environment have neighboring area for collision avoidance. Using two mobile robots for doing tasks will cause increasing speed and decreasing time. The algorithm can be extended for three or more robots.
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      Aiming at the simulation problem of 3D flexible cable in equipment operation simulation training platform, the cable model is classified as two types which are named as constant length model and changeable length model. Then two different simulation methods are put forward according to their respective 3D shape characteristics. Firstly, the catenary method is adopted to describe the constant length model considering the gravity it deserved and the curve equation is deduced to be the final math model. Secondly, the changeable length model is equal to draw a 3D line according two given 3D coordinate points and cylinder with certain radius around the line can be drawn with calling OpenGL API. The rendering effect of each model is presented to prove the simulation feasibility. Finally, the realization mechanism called OpenGL call-back function combining with Vega is brought forward. It shows greatest traits on cable simulation in similar virtual reality system.
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      A coupling model which is based on the Chaos phase space reconstruct and the radial basis function neural network and its utility for rainfall prediction is developed. In general, the precipitation time series, while the time of precipitation processes from beginning to end, has a non-linear feature, which usually can be expressed through a monthly rainfall. Therefore, a new coupling model based on the Chaos theory is produced in this study. In according with the new model monthly rainfall time delay and embedding dimension was computed by autocorrelation function, saturated related dimension and CAO methods, respectively. Furthermore, phase space reconstruction is achieved after the time delay and embedding dimension are counted. Afterwards, the RBF neural networks based on chaotic time series were proposed. In this study, monthly average precipitation of Jianyang city of Sichuan Province, in southeast China, was carried out from 1951 to 2008 to investigate the Chaos phenomenon and simulation. The calculating results show that, the time delay for this time series is 3, the embedding dimension is 9 and the saturated correlation dimension exists. The RBF neural networks coupling with chaotic simulation results show that the proposed model has effective prediction outcome and high prediction precision for the simulated chaotic time sequence, as well as the final absolute error comes to 1.09e-l 1 and the relative errors are lower than 5% except several minimum data. In addition, this coupling model would be used to estimate an annual precipitation and adjust the pattern of planting and guarantee the harvest in agriculture, etc.
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      A hybrid algorithm for global optimization of multivariate polynomial with bound constraints was proposed. The algorithm combines numerical, interval and symbolic methods. Interval methods can obtain small intervals and are guaranteed to contain the global optimum in the presence of rounding errors. Almost all interval-based global optimization methods use interval Newton method to verify existence and uniqueness of a solution to the problem. However, existence and uniqueness verification of a solution to a problem will not succeed when the Jacobi matrix is singular at some point in the region. To overcome the interval methods' shortcomings, we propose to use the symbolic method proposed by Pedersen et al. to improve the system's efficiency and to guarantee the interval methods' integrity. The hybrid method can solve problems that separately none of traditional methods is unable to solve. Furthermore, all the methods in our algorithm have nice properties for parallelization. So the performance of the system can be improved further.
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      Nowadays, frozen foods are well-known among Malaysia society. This is due to the modern lifestyles which require short food preparing times without neglecting the food nutritious. In supporting this requirement, the manipulation of vending machine is identified as a tool to promote modern and healthy living style, besides to simplify the cooking process. This paper describes the effort on designing conceptual model for a proposed steaming food vending machine simulator. Conceptual modelling is the most crucial part in developing simulation model; since in this part, the developer need to identify the variables; recognize the desired simulation flows and transform the deliverables into visualized form which can be understood by all parties related to the project. In this study, the process of three main states (user selection state, freezer state and steaming state) has been modelled using process approach, which emphasized on the process flow or control logic to construct the model for steamed buns vending machine application.
  • Session 4

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      Replication system belongs to highly reliable software; therefore, the reliability of itself is particularly important. This paper discusses the error brought about by the breakdown of primary-backup replication system. Then, an error handling method for primary-backup replication protocol (LVR) is presented in this paper aiming at handling this error and improving the reliability. LVR can maintain the data consistency by reconstructing write requests and updating them to backup. Analysis and experiment have revealed that LVR performs highly efficiently and it can be widely used in primary-backup replication protocols.
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      The increasing product diversity and sophistication have demanded an integrated system which can integrate subsystems of an enterprise. The purpose of this research work is to efficiently use all resources available in a manufacturing enterprise by developing a fully integrated system. The proposed system uses the electronic data processing methods together with new database techniques. A framework based on single source of product data (SSPD) system is established to completely integrate the different subsystem of production line. The SSPD framework describe the product data generation, transmission and processing of a production line. The SSPD system validation is carried out by implementing the system in an aerospace enterprise. Before implementing the system the step wise integration and function test was performed and documented.
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      To overcome the disadvantages of the electrostatic target characteristic signal predictors based on Adaline and Elman neural network, such as big error and slow speed, a prediction model based on a four-layer fuzzy neural network (FNN) was proposed for electrostatic target detection. In this model, the membership functions were Gauss functions and the back propagation (BP) algorithm was applied to train the network parameters. The simulation results show that the performance of FNN prediction model is superior to that of Adaline and Elman neural network. It is characterized by smaller error, smaller calculation amount and faster speed which are crucial in real-time system. The proposed prediction method can provide an effective way to compensate the delay of circuits and improve the real-time of the electrostatic detection system.
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      In this paper we present an extension to the Honey Bee Foraging PSO (HBF-PSO) algorithm. This algorithm is modeled after the food foraging behavior of the honey bees and performs a collective foraging for fitness in promising neighborhoods in combination with individual scouting searches in other areas. The strength of the algorithm lies in its continuous monitoring of the whole scouting and foraging process with dynamic relocation of the bees if more promising regions are found. The algorithm has the potential to be useful for optimization problems of multi-modal nature. The extension we propose allows HBF-PSO to automatically adjust the neighborhood size during execution which results in improved performance. The details of the algorithm are presented followed by experimental results on some commonly used multi-modal benchmark test functions. We present a comparison of both versions of HBF-PSO with NichePSO and SPSO.
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      According to ballistic characteristics, bomb-parachute system was simplified and calculation model of trajectory stability was established. Based on the model, effect of related factors and sensitive degree of these factors on trajectory stability was analyzed and compared. The results indicate that equatorial damping coefficient, equatorial rotational inertia and drag coefficient of parachute are key influence factors of trajectory stability. In addition, extending flight distance before parachute opening can speed up convergence rate of attack angle and the trajectory stability will be better correspondingly. The results could provide references not only for the research of optimal design of bomb-parachute system, but also the further analysis of trajectory stability.
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      This paper presents an energy-efficient scheduling algorithm with accrual utility in battery-powered embedded systems. We propose our Two-Step Energy-Efficient Algorithm (TSEEA), which comprises two parts: a static algorithm, which runs offline and achieves the static execution frequencies of all tasks under conservative conditions; and a dynamic one, which strives to reclaim slack time and effectively tunes execution frequency of candidate task in a timely manner. Compared with other algorithms, our algorithm can fully exploit a supply of limited energy to yield more utility. The experiments validate our analytical results and demonstrate that the proposed algorithm outperforms other existing algorithms with respect to utility.
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      Now the existing wave directional spectrum estimation methods have their respective advantages on calculation accuracy and computing time. The paper presents a hybrid algorithm, which gets initial solution by using MLM, and then does second optimization by using a new designed parametrical algorithm based on a wave direction spreading model. The new parametrical algorithm presented here sets up nonlinear equations by using the equal relationship between measured cross spectrum and theoretical cross spectrum, and then gets solution by using nonlinear least squares algorithm. Simulation shows that the hybrid algorithm above has very high computation accuracy, short computing time, and strong anti-noise ability.
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      Process migration which can improve the efficiency in the implementation of task is the key technology in grid. In the current grid environment, a large-scale application program is often broken down into a number of tasks that contain much relation. In order to improve the efficiency, the task needs to be migrated after submitting to the grid. This paper proposes a task selection strategy about migration which is based on fuzzy migration cost, and according to the relation among the tasks, it realizes the selection algorithm about the destination nodes. The experimental results show that the strategy improves the implementation efficiency of associated tasks obviously.
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      In order to supply a reliable and low-cost method for testing excavator's controllers and evaluating the performance of strategies, an excavator real-time simulation system has been developed. The hardware-in-the-loop system, including dynamic model of the arms, dynamic model of the main hydraulic system and an 3D real-time display subsystem, is presented in this paper. The simulation results are also described at the end of the paper.
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      To resolve the problem of the quality detection of cold-rolled strips online,, an approach for defects detection using the method of digital filter with the theory of artificial immune is put forward. The structure of the cold-rolled strips system and the principle of this method are stated detailed. The experiment results in one steelworks show this method can meet the demands of the quality detection of cold-rolled strips and can be used to implement the online quality detection of cold-rolled strips.
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      Taking Chinese Shandong Province for example, Grey Incidence Analysis was utilized to do an empirical research on the relationships between industrial structure and economic development. The results showed that: (i) because of the influence from the original situations of indicator sequences, the absolute degrees of grey incidence about three industries were basically equivalent, which was in line with hypothesis 1 and hypothesis 2; (ii) from the relative degrees of grey incidence and synthetic degrees of grey incidence about three industries, there were such relationships as follows: relative (synthetic) degree of grey incidence about secondary industry > relative (synthetic) degree of grey incidence about primary industry > relative (synthetic) degree of grey incidence about secondary industry > relative (synthetic) degree of grey incidence about tertiary industry; and (iii) from the perspective of the application of grey incidence analysis, it is necessary to pay more attention to the original situation influence of time sequences to computing results.
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      Prefetching is a common technique of tolerating the memory latency. However, it rapidly increases the communications traffic between the upper-level storage and the lower-level. Based on the analysis of access patterns of the SPEC benchmarks, we propose a novel push structure, in which the L2 cache can actively push instructions and data to the L1 cache at a proper time without the request from the L1 cache. By using a cycle-accurate simulator running SPEC benchmarks, the experimenting results showed that our push structure can significantly reduce the access to the L2 cache by 34.6%. Therefore, our push structure can effectively reduce the communications traffic between the L1 and the L2 cache. Our push structure also averagely increases the IPC by 6.6%.
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      A target tracking algorithm based on particle swarm optimization (PSO) is proposed. Due to a premature convergence with PSO in multimodal problems, an improved PSO, i.e. hierarchic particle swarm optimization (HPSO), is proposed and utilized to track target. To maintain high diversity of particle swarm, dynamic propagation is utilized to generate new particles in tracking process. In addition, parameters in PSO are adaptively adjustment in iteration process, leading to a favorable performance in tracking applications. Experiment results demonstrate the proposed algorithm is accurate and effective.
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      Animating virtual crowds with a large number of autonomous agents are effective to enhance realism in virtual reality applications. In this paper we present some preliminary results concerning a real-time visualization methods for large crowds reside in virtual environments. Making good use of LOD, we adopt three resolution models as detailed, less detailed geometry and imposter to represent virtual agent. At the same time we divide virtual crowd into crowd, group, and agent. Then we continue to divide agent into leader- agent and general-agent. We only have to certain which model should be adopted for leader-agent in one group not for every agent for less time complexity. We demonstrate our methods through the manifest the large number of human crowd in the virtual environment.
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      We do to curb noise and improve image quality, you must first pre-processing of images, that is, smooth images. The purpose of image smoothing is to improve the image of the visual effects and improve image clarity in order to become more conducive to the computer image processing and analysis of various characteristics. We use a classic cellular automata “Game of Life,” conducted a study about image smoothing based on game of life to image that a cell for each pixel, using a radius of 1 neighbors of Moore type. We transform the image of the different rules, the use of two-dimensional cellular automaton model area of the smoothed image. We experimentally demonstrate that the smoothing method with the median filter to the normalized mean square error and peak signal to noise ratio comparison method revealed that the more obvious advantages.
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      The aim of this study is to develop a prototype of web based machinery maintenance scheduling system. Maintenance is an important task in remaining the system functionality and to extend the life time of an asset. However, a weak maintenance management and practice may leads to the major system failure which involved high maintenance cost. This paper describes an initial attempt of developing e-maintenance application - Web Based Machinery Maintenance Scheduler System (MMS). MMS is developed to manage the maintenance scheduling of all machines operated in Mechanical Engineering Laboratory. Based on the study, the prototype is able to generate maintenance scheduling for each machines based on the machine maintenance specification, record the data for the emergency maintenance case and generate the monthly maintenance report. The detail outcomes and the results from the study are discussed in this paper.
  • Session 5

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      This paper proposed an image steganalysis scheme based on the statistic moments of 2-D histogram in frequency domain. The difference is calculated in three directions, horizontal, vertical and diagonal towards adjacent pixels to obtain three-directional differential images for a natural image. Then the features for steganalysis are extracted from the 2-D DFT of the 2-D histogram of image itself and its differential images. Support vector machine (SVM) with RBF kernel is applied as classifier to distinguish between stego images and cover images. We test the performance of our proposed steganalysis method over spread spectrum (SS) data hiding method, LSB method and QIM data hiding method. The experiment results have proved that the proposed method is effective in attacking these steganograhic schemes applied in spatial domain.
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      To analyze agitation characteristic of screw shaft in Bituminous Mixture Transfer Vehicle (BMTV), a Neural Network (NN) model was established, based on helical blade radius, pitch and rotational speed of screw shaft used as input vector, while asphalt mixture segregation rate used as output vector. To solve the problems of the slow convergence rate and easily falling into local minimum in BP algorithm, PSO algorithm combined with Levenberg-Marquardt algorithm was employed as learning algorithm of the NN. Model of BMTV was designed and manufactured, and model experiment data was applied to simulation experiment of the screw shaft NN model. Simulation and experiment results indicate that the proposed approach not only can overcome the drawbacks of BP algorithm, but also has faster convergence and higher computational precision than original PSO. It also can be applied to building model for agitation characteristics of screw shaft in BMTV, and it is effective.
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      It is inevitable that barcode images captured by mobile phone camera have some extent of tilting and distortion. In traditional method, the Hough Transform method is adopted to detect the L-shape in the barcode image of Data Matrix. However, with huge complexity and large storage space, it is not suitable for application on the mobile phone. In this paper, under Symbian OS in Nokia, an improved convex hull algorithm is adopted to exclude some invalid convex hull vertices through angle, length calculation filters. Then a fake quadrilateral is created to fit Data Matrix image contour. This approach can both shorten calculation time and ensure accurate positioning. It is suitable for mobile phone application. At the end of this paper, both the traditional method and the improved approach are tested on Nokia N73 for the comparison of the efficiency and effectiveness.
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      The push technique is an effective method of tolerating the Load-to-use latency. However, not every memory level can gain a sound performance improvement when the push technique is adopted. In this paper, we devise a quantitative approach to analyze workload on the bus. For balancing workload, we propose a novel architecture, which compounds the push and prefetching technique to serve different storage levels. Between the L1 and the L2 cache, we use the push technique. Between the L2 cache and memory, we utilize the prefetching technique. Focusing on the L2 cache prefetching, we propose AAP and AAPM, both of which meet the requirement of timeliness and bandwidth adaptability and can increase the IPC by 2% compared with SRP.
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      Considering the visual features of eyes, À trous contrast pyramid transform combining nonsubsampled directional filter bank is proposed. The source image is decomposed into low-frequency image and high-frequency images by à trous contrast pyramid transform. Then apply directional filter bank to each high-frequency. The different fusion rule is adopted in low-frequency image and high-frequents subbands. Finally the fused image is obtained through inverse transform. Experimental results show that the proposed method is valid to fusion of infrared and visible images, and has better subjective visual effect.
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      Aim at the gateway node of the wireless sensor network, this paper designs and implements a kind of wireless gateway. Inside the wireless sensor network, the data transferring is based on the Zigbee module; between the gateway node and the host, the transferring is based on the Wi-Fi module. Both the hardware scheme and the programming method of software are introduced. At the end, the performance of the gateway is tested, and the result shows that it can be used for general purposes.
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      The challenge and control problem of static unstable missiles were presented. The steady-state benefits of static instability were illustrated, while the corresponding control challenge was described by the characteristic lag of airframe and the increment of necessary control usage. Control limitation led by unstable zero-pole pair was analyzed for preliminary design and evaluation. Linear control strategy was examined wherein the three loop acceleration autopilots was developed using an optimal control approach combined with frequency domain constraint. The weights selection and relation with system performance were detailed. Then the nonlinear backstepping recursive method was detailed. The results show that the actuator bandwidth is the crucial limiting factor for controlling a static unstable missile.
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      In the area of large-scale device collaborative system, represented by the central area of the Olympic landscape lighting control system, the number of device is large, collaborative process is complex, and the “time” properties become an important factor in collaborative processes. In view of the above characteristics, a large-scale device collaborative process design meta-model is proposed, which supports time properties, and Pi calculus is introduced to describe the key elements of the meta-model. Finally take the central area of the Olympic landscape lighting control system for the case, put forward a formal definition of lighting device operation and the conflict.
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      In this paper, a class of networked control system (NCS) with disturbance, time delay and packet dropout is converted into a discrete-time system which could be viewed as an asynchronous dynamical system with rate constraints. For the system, based on Lyapunov stability theory and LMI approach we present two new state feedback controllers which can make the closed-loop system exponentially stable and meet prescribed or optimal H∞ performance index. A numerical example is worked out in detail to illustrate our results.
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      Aiming at the shortcoming of manual recognition of spores, the paper proposes an auto-recognition method based on BP neural network. After pre-treatment of spore images and feature vector extraction, the BP neural network is set up for spore characteristics identification. The simulation results of MATLAB7.0 show that the auto-recognition method is able to identify the characteristics of spore images.
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      As the concept of Digital City becomes more and more important, people are inclined to building digital cities. In order to manage cities better, it is necessary to add remote monitoring to digital cities because it could solve the problem that something is not convenient for field survey though remote monitoring in digital cities. In addition, Google Earth(GE) is one of the most convenient platforms for building digital cities. Therefore, we propose a remote monitoring system based on GE. We employ the GIS searching & orientation module to search and locate places where users want to monitor on GE. Besides, the monitoring module is used to monitor places by updating image overlays on GE. And we utilize the voice guiding module to tell users the information about places in voice. Thus, it will be convenient for city management though remote monitoring based on GE.
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      Biometric recognition suggests a reliable solution to the problem of user authentication in our networked society. Among all biometrics, palmprint-based recognition is one of the most reliable personal identification methods. In this study, a new approach to the palmprint recognition phase is presented. 2D Gabor filters are used for feature extraction of palmprints. After Gabor filtering, standard deviations are computed in order to generate the palmprint feature vector. In addition, Genetic algorithm based feature selection is used to select the best feature subset from the palmprint feature set. Four different algorithms of Artificial Neural Networks are then applied to the feature vectors for recognition of the people. Recognition rate equal to 98 percent are obtained by using conjugate gradient algorithms.
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      Many virtual environment applications incorporate avatars as some of their inhabitants. Interactions between avatar and surrounding objects, as well as avatar and avatar, need to be done in real-time in order to retain the degree of realism and immersion of the virtual environment application. In this study, we consider an avatar as a human-like, 3D hierarchical representation. The aim is to improve the collision detection process involving a human-like avatar and its interaction. Previous work on avatar collision detection is presented. A proposed improvement is summarized from methods that have been implemented in other fields like ray-tracing and deformable objects simulation that can also be beneficial for this purpose.
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      Dynamic cloth simulation becomes the most important issue in certain applications such as games, animation, virtual reality and medical which is the dynamic effect with fast self collision between cloth-to-cloth becomes the main problem to resolve. To achieve the reality cloth simulation, we use a mass-spring system, which is the universal model in cloth simulation. For the animation of the particles, we considered internal and external forces to create cloth to look more realistic. As cloth simulators, to handle the cloth self collision is more complicated. So, several methods have been suggested by numerous researchers. Furthermore, we discuss numerous methods for an efficient avoidance of self collision detection. So that the efficiency animation of cloth can be improves much.
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      Mechanisms based on frequency hopping have been widely used in many applications such as the personal communications services and the wireless networks. In this paper, we describe, simulate and implement a frequency hopping spread spectrum transceiver. A baseband model for Bluetooth Frequency Hopping Transceiver is presented. Several modulation techniques, such as QPSK, 8-FSK and 16-QAM, are exploited to achieve a bit rate of 2Mbps, 3Mbps and 4Mbps respectively. We clacutate the bit error rate of the described transceiver model with the aid of Monte Carlo analysis technique. The proposed model is then implemented using the C6713 floating-point DSP. The functionality of the implemented system is tested via Real Time Data Exchange (RTDX).
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      Learning process is very important in academic industry. Students are the person that will give their service to the country after they graduated. As an academician, lecturer responsible in making sure their students are having skills that needed by industry. The industry in Malaysia always complaint that Malaysian student are having no skill. So, with this problem, we applied problem-based learning method to make our students can solve whatever problem given by superior, critical thinking in solving the problem, can work independence and minimized supervision and others. The PBL method was introduced to the Faculty of Computer Systems and Software Engineering (FSKKP) second year students in the Bachelor of Software Engineering. The subject is Formal Methods 3 credit hours. The number of students is 88. We analyzed 88 students' assignment to see their performance of construction of formal specification. Using this method help student in gain skill that required by the industry at the same time to construct formal specifications. This approach can train our student more critical thinking, independent, confidence, developed team working and others.
  • Session 6

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      Along with the rapid growth of the Web Service(WS), how to choose a suitable WS for consumers becomes a hotspot. Nowadays, researchers focus on the selection method based on quality of service (QoS). It does work but need a good model and methods for the selection based on QoS. The work in this paper is based on an extended service model. It puts forward a new model for WS. Based on this service model, service provider can define the attributes for a WS to describe the QoS of the WS. And in the similar matter, service consumer can use these attributes to give an evaluation for the WS. This service model and related methods we designed and implemented are already benefited in a IBM Global SUR (Shared University Resources) project and is running in the real world to collect and catalog the public WS from Internet.
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      A rectangular hybrid automata model of a four-phase intersection is given, in which the queue lengths are considered as continuous variables to represent the vehicle flow behavior of the intersection and the discrete event part represent the traffic light behavior. Based on the rectangular hybrid automata model, all directional vehicle flows are analyzed. A method for reachability analysis of rectangular hybrid automata is applied to analyze the maximum and minimum of each queue length of the single intersection. Simulation completed with the help of the toolbox CheckMate shows that the rectangular hybrid automata model and the method can not only perfectly represent the hybrid character of the dynamic traffic flow of the single intersection, but also can verify the efficiency of the timed scheme of the traffic light.
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      This paper discusses about new way for motioning planning of robots in dynamic environments that they depend on wave expansion approach that avoids wave re-expansion in sudden obstacles case. Wave that is re-expansion in big measure environments takes an important amount of time and process. A new wave expansion algorithm about path finding, either abrupt obstacles are met or local minima, has been suggested as so-called virtual wave hill algorithm, which prevents re-expansion of wave. In addition the reflects of the simulation and its results reflects that how the performance has developed the current methods. By using the algorithm it's been tried to prevent the re-expansion of the wave.
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      As color devices may lose accuracy during a period of time, characterization should be made to calibrate them. A 4th order polynomials regression method is proposed for color characterization. In the experiment, different forms of polynomials are used to represent the relationship of RGB and L*a*b*, and the result shows the new proposed 4th order polynomials have smaller errors than other forms of polynomials. What's more, the 3D LUT and neural network method are also compared with our method, and the result suggested that all these three method have the error about 2 color difference units, which is far lower than the replicate threshold of 6. While our method takes up the least time in experiment, which is significant and may broaden its application in image processing.
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      Nowadays, Augmented Reality (AR) has become well-accepted technology with realism as one of the major contribution in computer graphics. AR is a technology that superimposed virtual and real scene in the same space. This technology requires accurate registration between virtual and real world augmentation, be it geometric registration or illumination registration. Hence, a lot of efforts have been done to explore the elements in AR technology including features and challenging issues in AR that need to be highlighted in order to reconstruct AR system. In cultural heritage system, the accurate registration is important to produce realistic environment and to improve the user's experience. The culture heritage reconstruction is significance to preserve, protect and interpret our culture and history. This paper will present an overview on the potentials of AR approach in cultural heritage system that will improve the quality of the system.
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      Speech is becoming the privileged mean of communication. With the advent of computers, researchers and industrials are using it like a mean of communication in the Human Machine Interface domain.All the current systems, based on the natural language, are far from assimilating all the characteristics of the language. Nowadays The Automatic Treatment of speech is progressing, in particular in the fields of Automatic Speech Recognition “ASR” and Speech Synthesis.The automatic speaker recognition is represented like a particular pattern recognition task. It associates the problems relating to the speaker identification or verification using information found in the acoustic signal: we have to recognize a person by using his voice. ASR is used in many fields, like domestic, military or jurisprudence applications.In this work we explore the automatic speaker recognition and present an Automatic Speaker Recognition System. We will use speaker recognition in text independent mode since we dispose of very few training data. We have to estimate with few data a robust speaker model to allow the recognition of the speaker.
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      At present, the research of M-learning is mainly about school education and lifelong education but rarely about family education. At the same time, as the deepening of the academic study in family education, family education has been expanded to all members of the family. In the family, The elderly are important components. With the advent of an aging society, the increasing proportion of the elderly, more and more problems among the elderly can not be ignored. So how to apply mobile technology in the life of the elderly to solve the prevailing problems has become the focus of this study. In this study, we have carried on the comprehensive social investigation and the full literature investigation to the problems of the elderly to mine the currently prevailing problems of the elderly. Finally, explore the solutions to the problems by mobile technology.
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      In this paper, design, simulation and implementation of Asymmetric Digital Subscriber Line (ADSL) modem is presented which can be applied to different telephone networks. Lhe ADSL modem is modeled and simulated under the MATLAB version 7.3 (R2006b) environments by which the simulation is achieved for both the downstream and upstream directions of the modem. The ADSL modem with a transmission throughput between 640 kbps and 6 Mbps operating over most of existing telephone subscriber loops has been implemented on TI TMS320C6713 DSP for consumer multimedia applications. Except the Analog Front End, all the basic building blocks of the ADSL modem functionalities are implemented with DSP platform. We use Real-Time Data Exchange (RTDX) as a way to debug and test our DSP designs.
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      Cognitive radar can be aware of its environment, utilize intelligent signal processing, provide feedback from the receiver to the transmitter for adaptive illumination and preserve the information contents of radar returns. In this paper, based on the analysis of the parameters of radar mesurements, range-Doppler resolution cell is built up. Then stochastic dynamic programming model of waveform selection in cognitive radar is proposed, which is viewed as an important part of cognitive radar. In simulation, the importance of adaptive waveform selection in cognitive radar is shown.
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      Since currently in China the power supply distribution system adopts low current grounding system with indirect grounding of neutral, so the fault of single phase grounding in the system takes place frequently. With reference of actual conditions for single phase grounding fault, The paper designs a new realtime monitoring and fault diagnosis device, On the one hand, the device can measure some elementary power parameters, such as the three-phase voltages, current, power, frequency etc. on the other hand, it can really monitor system status. Results of operation show that this device computing speed quickly, strong anti-jamming capability, stable operation, has the good performance-to-price ratio, is very practical in the small current grounding and the grid.
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      This paper introduces an intelligent and interactive control system (IICS) based on Personal Digital Assistant (PDA) with Windows Embedded Compact System (Windows CE). IICS can configure, monitor and control the wireless digital terminals of digital home. The system consists of a software platform, a controller on PDA and the wireless communication network. Also, Field Programming Gate Array (FPGA) is designed as microcontroller in hardware part to connect PDA and home appliances. In addition, a digital home server is proposed for remote control that PDA can link to the server by GPRS network outside. User interface of IICS provides an efficient way of operating all the appliances in the home. Finally, the experimental results demonstrate that IICS is of high performance for coordinating the home appliances.
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      The decision and constitution of the Sheffer function is one of the important problems in multi-valued logic theory. This problem can be reduced to the decision of the minimal covering of precomplete sets in the multi-valued logic function sets. According to the completeness theory in partial k-valued logic and the similar relationship theory among precomplete sets, the methods of determination on the minimal covering precomplete sets are found out, and the minimal covering members of function sets preserving full symmetric, simply separable and regularly separable relations in partial four-valued logic are decided.
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      In this paper, two algorithms, Differential Evolution Algorithm (DEA) and Genetic Algorithms (GAs), are applied to the offline identification of induction motor parameters. DEA is compared with the prediction errors and the genetic algorithm via determination parameters using nameplate data like starting torque, breakdown torque, and full-load torque in two different cases. Consequently, it is seen that DEA can be find more precise parameter values than the genetic algorithm and especially convergences to global optimum not to be stuck local optimum.
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      Due to the information explosion, web IE (information extraction) comes into being. Though people get used to inquiring information by 2-D text reading in traditional way, browsing words is not enough for users' acquiring knowledge today. Actually, people find that most information is geo-referenced especially after Digital Earth (DE) is proposed, which makes people can get information in a 3-D environment. Google Earth (GE) is such kind of one important product of DE. In order to make people get more information from GE's limited information recourses, we utilize IE to extract needed information from semi-structured web page biographies and map the information to corresponding places on GE. Also, how people read traditional 2-D text in a 3-D environment is studied. How the previous text biography is vividly presented on ‘our planet’ like a man's life trace is introduced in our work.
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      A robust face tracking algorithm is proposed to color video sequence of complex background, in which uses a fusion of gradient model and color histogram model as clues. First, the method constructs histogram model according to color characteristics of high clustering about H-channel of HSV, Cb-channel and Cr-channel of YCbCr, and a gradient model according to gradient characteristics in the elliptic border is also constructed. Second, an improved CONDENSATION filtering algorithm is applied to face tracking, in which the problem of occlusion is solved better in video sequence. Experiment result shows the robustness of the method against the complex background of face rotation, partial occlusion and skin color distraction.
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      Developing a weapon that can be utilized to intercept and destroy a ballistic missile during the boost phase of its flight is the first step in eliminating the threat of the attacking ballistic missile. Boost phase interception is considered successful, when a complete destruction of the missile and its on board munitions is achieved. Various weapon systems have been developed for boost phase interception of ballistic missiles. This work is applied to one of these systems which is the ground-based intercept missile. The requirements for the interceptor effectiveness will be discussed. The work is based on simulated engagements between the attacking ballistic missile and the interceptor employing proportional navigation for the guidance law. The distance between the target missile warhead and the interceptor at the end of engagement, which is called the miss distance, is calculated as a measure of the interceptor performance. The effect of changing the navigation ratio on the acceleration requirement and the total flight time for the interceptor to attain minimum miss distance is illustrated. The Matlab programming environment is used to carry out the mathematical analysis and plotting the output results.
  • Session 7

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      Mat-Core is a research processor aiming at exploiting the increasingly number of transistors per IC to improve the performance of a wide range of applications. It extends a general-purpose scalar processor with a matrix unit for processing vector/matrix data, where scalar and vector/matrix instructions are executed out-of-order. To hid memory latency, the extended matrix unit is decoupled into two components: address generation and data computation, which communicate through data queues and executed also out-of-order. Like vector architectures, the data computation unit is organized in parallel lanes. However, on parallel lanes, Mat-Core can execute scalar-matrix, vector-matrix, and matrix-matrix instructions in addition to scalar-vector and vector-vector instructions. By extending the well known scoreboard algorithm, these instructions are executed out-of-order on parallel pipelines. This paper describes the SystemC (system level modeling language) implementation of Mat-Core and evaluates its performance on vector and matrix kernels. On four parallel lanes and matrix registers of size 4×8 or 32 elements each, the performance of Mat-Core with queues size of 10, start up time of 6 clock cycles, and memory latency of 10 clock cycles, is about 1.4, 2.1, 4.2, 2.6, 4.2, and 6.4 FLOPs per clock cycle; achieved on scalar-vector multiplication, SAXPY, Givens, rank-1 update, vector-matrix multiplication, and matrix-matrix multiplication, respectively.
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      The increasing airplane diversification, complication, serialization, and customization needs an excellent configuration management and control system to guarantee the consistency, integrity, orderly and traceability of information data. In this paper, few key methods are proposed and analyzed to improve the airplane configuration management and control. Airplane configuration definition is optimized by classifying options and module. Management mode has been change from drawing-central to part-central management, and every part has been assigned a unique identification number. Airplane product structure is established by modules whereas Link-Module and Independent-Module are classified by relationship of modules and options. Effectivity is replaced on the module not on every part to simplified effectivity management. Improved hierarchical version control by two-level version tracking model has been introduced which provides the rules of changes about part number or version identification.
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      In practical applications, adaptive beamformers can suffer significant performance degradation in the presence of the even slight mismatch between the actual and assumed signal steering vectors. In this paper, a novel robust constrained LSCMA is proposed based on explicit modeling of uncertainties in the desired signal array response. The proposed algorithm provides excellent robustness against the signal steering vector mismatches, improves the array system performance and makes the mean output array SINR consistently close to the optimal one. Computer simulations demonstrate substantial performance improvements of the proposed algorithm compared as linear constrained LSCMA algorithm.
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      According to the analysis of existent evaluation methods for cylindricity errors, an intelligent evaluation method is provided. The evolutional optimum model and the calculation process are introduced in detail. Based on the characteristics of cylindricity error evaluation, Particle Swarm Optimization (PSO) is proposed to evaluate the minimum zone error. Compared with conventional optimum methods, it can find the global optimal solution, and the precision of calculating result is very good. Then, the objective function calculation approaches for using the PSO to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by using different methods indicate that the proposed method does provide better accuracy on cylindricity error evaluation and it has fast convergent speed. The evaluation method can also be extended to other form errors.
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      GPS provides consistently accurate positioning solutions if four or more GPS satellites can be observed. Unfortunately, this condition is usually not satisfied. ABS (Antilock Brake System) Navigation System consists of self-contained optical encoders mounted on a vehicle wheels that can continuously provide accurate short-term positioning solutions. In this paper, a new concept regarding GPS/ABS integration, based on intelligent method is presented. A fuzzy system is used to identify GPS position accuracy based on environment and vehicle dynamic knowledge. The GPS is used as reference during the time it is in a good condition and replaced by ABS positioning system when GPS information is unreliable. The MATLAB simulations manifested that the proposed algorithm improves the location precision and the tracking capability.
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      In this work a model is developed for the gate-cathode junction of a power thyristor containing an amplifying gate and emitter shorts. The geometry of this junction and the model parameters are defined and extracted according to a new methodology. The simulation results are compared with the measured results. It has been found that the developed model satisfactorily describes the performance of the gate-cathode junction of practical thyristors.
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      In this study cutting forces prediction was modeled using back propagation (BP) neural network algorithm. Experimental turning dataset is used in this study to train and evaluate the model. The Input dataset includes speed, feed rate, depth of cut, vibration levels along the three axes on tool holder (ax,ay,az). The Output dataset includes feed force, vertical force, and radial force. Marginally acceptable results were given by early experiments of this study and when data was examined, high non-linearity can be seen from the prepared graphic. In the previous work, a fine development of reliability of predicting the cutting forces can be observed by the help of results. To compare the estimated results of cutting force from this method with the cutting force signal can be measured directly by dynamometer; it is found that the difference between measured and estimated cutting forces is less than 0.2% in all case.
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      Along with the great flourish in world trade, patent is becoming increasingly important for protecting intellectual property. Although there are many patent retrieval systems for patent information searching, most of them, especially Chinese patent retrieval systems, are based on database that cannot support the huge amount of accesses. Thus, it is necessary to develop more efficient patent retrieval system to satisfy the growing requirements. A Distributed Patent Retrieval Service Platform (DPRSP) based on Nutch is proposed in this paper, which enables users get more related patent information. The concept retrieval is introduced in DPRSP to make DPRSP can understand the users' query more precisely. The architecture of DPRSP is described in this study and the detailed implementation of DPRSP is also explained. Finally, we demonstrate how the DPRSP improves the efficiency of the Chinese patent retrieval significantly by an application.
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      Object reconstruction is one of the most important topics in computer vision due to its wide field of application. Reverse engineering has an increasing need for reconstruction of stereo parts. A system for reconstruction three dimensional (3-D) object's surface from its 2-D views using a coded structured light combining with the epipolar geometry that exists between the stereo image pair is presented. A set of multiple gray code patterns and a sequence of sine wave patterns are projected onto the target object through a projector and the distorted strips patterns produced by its surface are captured by two cameras. Stereo camera calibration is carried out before capturing the views. By demodulating the distorted patterns and adding epipolar constraints the match points between the image pair are found out and then the target object's 3-D point's coordinates on surface are obtained. This system has the advantage of speeding up the reconstruction process.
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      How to establish composite service in a just-in-time manner and allow users to configure their applications conveniently becomes a hot issue in the research area of web services composition. This paper proposes an approach of user-oriented service composition. The approach is centered on the proposed 3-level web service mapping mechanism. Based on such mechanism, a hierarchical composing structure is proposed which includes user-defined composition, system-supported composition and instance-oriented composition. By a prototype and experiments, the feasibility of the proposed approach is verified.
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      A new modelling method of the prop control system of hydraulic support is presented in this paper, and a certain prop control system is modeled based on the software MSC.EASY5. Then the dynamic characteristic of prop control system is gotten, and the effects of prop's different working parameters are analyzed. A test about yielding characteristics of prop in overflow load stage is done to verify the simulation model. Finally, some suggestions for improvements are presented which are helpful to the designer of hydraulic support.
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      Computer generated force (CGF) has become an important topic in modern combat simulation. Through expatiating the function of CGF and the common characteristic of its behavior models, the hierarchical structure of CGF and the general infrastructure of CGF behavior model were proposed. Then the theory of finite state machine (FSM) and production rules (PR) were combined organically to provide a kind of CGF behavior modeling method. And an application example of the behavior modeling method was also give in the paper.
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      Low voltage low power 4-bits 90Ms/s, 40uw, with DNL (+0.19/−0.4)LSB and INL (+0.47/−0.46)LSB is designed using 0.13um UMC CMOS technology operated with 1.2V voltage supply. The converter is composed of three stages the first, second stages produce 1.5bit/stage and last stage produce 2 bit/stage. Using Bottom-Plate Switching and fully digital error correction which corrects errors due to capacitor mismatch, charge injection, and comparator offsets. The calibration is performed without any additional analog circuitry, and the conversion does not need extra clock cycles.
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      This study is related to multi-agents modeling of complex systems. This interest deals more particularly with situation where the spatial and temporal components make a great part of the system to model (for example systems of production). Within the framework of this article, we will be interested in the production systems where the multi-agent systems are well suited to model phenomena in which the interactions between diverse entities are so complicated to be expressed by classic mathematical tools. This paper proposes an approach based on the producer consumer computing problem and Petri net tool to present an oriented Petri net meta-model to model a production multi-agent system.
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      Based on the analysis of existent evaluation methods for form and position errors, a novel evaluation method is provided for parallelism error evaluation of planar lines. The evolutional optimum model and the calculation process are introduced in detail. According to characteristics of parallelism error evaluation, genetic algorithm (GA) based on real-code is proposed to evaluate the minimum zone error. Compared with conventional optimum evaluation methods, it can find the global optimal solution, and the precision of calculating result is very high. Then, the objective function calculation approaches for using the GA to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by different methods indicate that the proposed method does provide better accuracy on parallelism error evaluation. The evaluation method can also be extended to other position errors.
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      WS-Security provided a total framework for web services, but it is only abstract standard. On the basis of WS-Security, experts in IBM Tokyo laboratory bought forward Session Authentication Protocol which would be new solution for session entity authentication. In the paper, we give security defects of the original protocol, then make some improvements by selecting Diffie-Hellman algorithm improved with PKI certificate as new key-exchanging mechanism.
  • Session 8

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      In cryptography, the advanced encryption standard (AES) is an encryption standard issued as FIPS by NIST as a successor to data encryption standard (DES) algorithm. The applications of the AES are wide including any sensitive data that requires cryptographic protection before communication or storage. This paper proposes extending general-purpose processors with crypto coprocessor based on decoupled architectures. The extended coprocessor splits an encryption/decryption instruction into memory (load/store) and computation (encryption/decryption) portions (pseudo instructions). Loading/storing and encrypting/decrypting data are performed in parallel and communicated through architectural queues. The computational unit includes parallel AES pipelines for fast encrypting/decrypting data. On four parallel AES pipelines, our results show a performance of 222 Gigabits per second.
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      In this paper, a new cryptosystem based on hybrid approaches is proposed. This scheme provides multi-security services. The proposed scheme takes the advantage of neural networks computation power to build an encryption algorithm to serve data confidentiality, where the encrypting process is done by used shard key as input to the ANN model, and the data need to be secured will be the output of it, the generated set of weights will act as the cipher. Also, made combination between MAC technique and RSA encryption algorithm produced digital signature of the scheme which provided the integrity and authentication services. The experimental results indicate that the proposed cryptosystem has a high confusion and diffusion properties, therefore it has a high security and it is suitable for secure communications.
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      The Web has dramatically changed the way that customers express their opinions about some products. Everyone can post reviews/feedbacks of products at merchant sites. The huge amount of the information is a challenge to the customer's patience to read all these feedbacks. Classical sentimental classification does not find what the reviewer liked or disliked. Feature Based Summarization (FBS) techniques are being developed to exploit these sources to help companies and individuals to gain market intelligence info. In this paper, we build a new system called Fast Feature Based Summarization (FFBS) that employs the Quick-Apriori algorithm (proposed in [10]) for speeding the process of extracting the frequent product features. Moreover, in this system, we present a fast technique for finding nouns (product features) and adjectives (opinions) at the same time. These modifications speed the process of the summarizing system.
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      This paper presents a new method for motion planning of mobile robots in dynamic environments based on wave expansion approach which avoids full wave expansion in sudden and moving obstacles case. Full Wave expansion in large scale environments takes considerable amount of time and process. A new wave expansion algorithm for path finding, local minima, sudden obstacles and moving obstacle are met, has been suggested, as so-called wave expansion from obstacle (WEFO) algorithm that prevents re-expansion of wave. In moving obstacle case, the wave expanse in each step of the obstacle movement. Moreover, the simulation results reflects that how the work has enhanced the already-existing methods for path finding. By the use of WEFO algorithm it's been tried to prevent the re-expansion of the wave.
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      In this paper, we present a physically based model of power diodes. The model is based on the numerical solution of the ambipolar diffusion equation using a modified finite difference method. The model is implemented using Matlab. Optimization routines are executed within Matlab to extract the design parameters of the power diode under investigation. Comparisons between the results of the Matlab model with Silvaco mixed-mode simulations are presented. The model is used to extract design parameters of selected power diodes whose experimental waveforms are given.
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      Today, and more than ever, communication is a key element in any project undertaken. The Internet is now part of our everyday life to instantly connecting people all around the world. Telecommunication and Internet services will not stay at only e-commerce but be evolved into other domains such as electronic services for communities, colleges, companies and further, which allow many different partners to communicate and get forward. The innovating project called PERSEUS is no different from other projects, which need to interconnect and ease the cooperation and coordination of the different participants originating from a wide variety of technical and non-technical domains.A web portal called “Portail PERSEUS” was developed as a common interface between all those involved via the Internet. To provide the components of this comprehensive platform, a centralized server architecture is proposes. In order to achieve the best performances for all connected users, it is necessary to parameterize and tune the environment in which it will be hosted. Thus in this paper we presented the modeling of user behavior in the platform and their connectivity and also shown its performance analysis.
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      Membrane protein interactions play an important role in the compartmental organization of eukaryotic cells. Some membrane proteins are specifically targeted to some other ones and fuse with the target membrane to effect content mixing. Traditionally, biochemical methods have been used to identify the composition of interacting membrane proteins. However, these methods are generally restricted by the experimental conditions in practice. AdaBoost is a strong learning algorithm and it finds an accurate classification ruler. In this paper, we construct a classifier by combining with several FSVM classifiers. Jackknife tests on the working datasets indicate that the precision, sensitivity and accuracy are improved greatly. The results show that the proposed method may provide a novel approach to genetically identify membrane protein interactions.
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      Agile software development has gained popularity due to its adaptability, simple design and working software practices. Agilists prefer to keep design simple by refactoring. Re-factoring is one of popular practice adopted by agile methods. Re-factoring in software development may be achieved in code as well as in database. Re-factoring is breaking the code or data without changing the behavioral aspects. Re-factoring improves the readability and understandability of code and database. This paper illustrates a case study to demonstrate quality improvement in design through re-factoring.
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      In this paper, we propose a new model to analyze the reputation stability based on the property of cluster framework in mobile hierarchical Ad Hoc networks with considering security requirements. According to the symbiotic theory in biology, we design the reputation mechanism that considers both the isolated reputation information of each individual node and the interdependent relationship of neighborhood. We present the Logistic model that is commonly used in ecosystem for analyzing and comparing the different reputation values in stable state. Through studying the symbiotic conditions and reasons in hierarchical Ad Hoc network, we can not only effectively improve the maintenance of cluster framework but also harmoniously and consistently promote the development of networks.
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      The effective measures to predict scouring of river bed and water lever lowing downstream of the reservoir are needed in channel engineering. In this paper, the SMS version 8.1 model was evaluated to predict the process of the riverbed longitudinal erosion and water level lowing downstream of Changzhou Reservoir. According to the model calculation results, the consequence is that the water level descends about 59cm in the near-dam reach downstream and the maximum erosion depth of cross section is about 2.08m.
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      It is significant to detect and prohibit the abnormal actions by studying the intrusion detection method and constructing the intrusion detection system. RBF neural network (RBFNN) is a pattern classification tool that has been widely used in a variety of engineering applications. However, the problem by using the RBF neural network is about how to choose the optimum initial values of the following three parameters: the output weights, the centers and widths of the hidden unit. Therefore, the novel method based on the combination of RBF neural network and genetic algorithm (GA-RBFNN) are adopted to network intrusion detection, the genetic algorithm (GA) is applied to optimize the RBF neural network parameters. Compared with the BP neural networks approach the experimental results show that the GA-RBF neural network approach is superior to the conventional BP neural networks in network intrusion detection.
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      In this paper we propose a Gabor filter-based feature points matching approach. Gabor filters of different orientation are adopted to perform multi-orientational filtering on feature points that are to be matched, and vector elements of N-dimensional normed linear space are constructed by sub-image standard deviation of N-dimensional orientations. The similarity between feature points is described by ‘distance’ of two feature point vectors, thus it achieves matching between homogeneous feature points. The experiment results show the method is not sensitive to noise added in image and can be adapted to match images with great different gray scale levels. Moreover, the method has no special requirements on feature points.
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      The construction of massive multiplayer online role-playing games is an intuitive challenge. After years of typical research into Markov models, we argue the exploration of wide-area networks, which embodies the compelling principles of steganography. In this paper we use trainable information to demonstrate that robots can be made client-server, stable, and replicated.
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      The term “packaging” has its role as: 1) Provide I/O connections to the semiconductor devices so the IC is tested and ready for board assembly. This is called IC packaging. 2) Integrate components into systems to form end product systems such as cell phones, PDAs, Laptops. This is called system packaging. Both the above IC and systems packaging are accomplished by interconnections or wiring at the package or board level. In future, the role of packaging is more than interconnections. The IC devices themselves began to integrate more and more transistors and functions, leading to what have been calling SOC or System- on-Chip with multiple systems functions in a single chip. This can be called horizontal or 2D integration of IC blocks toward system-level functionality. Such an approach presents design complexity and fundamental limits for computing, and integration limits for wireless systems. This led to 3-D packaging, often referred to as SIP or System-in-Package. In this review, starting from the introduction of SIP, an alternative approach of product design using SIP is discussed. After that SIP Integration which includes different technology, benefits are considered. Thereafter key issues in SIP integration and its future applications is discussed. Finally this work is compiled in conclusion.
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      Most existing work on sensor network target tracking concentrates on sensor selection solely based upon one characteristics such as the sensor position or sensing modality, and not much work has been done on collecting compositive information. In wireless sensor network target tracking, there are many influencing factors and the dimensions of these factors are different. This article combines the AHP(analytical hierarchy process) and the fuzzy mathematics method fundamental theory and presents a node selection algorithm. The algorithm estimates the possible trajectory of the target and wakes the appropriate node to participate in tracking. The results of the simulation indicate that the algorithm can turn off a mass of nodes and ensure the quality of the tracking simultaneously.
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      Process industry requires good man-machine interface in order to enhance the stability of system operation, in which the sense of tension and mental load of operators is an important indicator measuring human-machine optimization. To solve the problems of lots of events and too much work load for operators in process industry, in the paper, the industrial field data is utilized to classify the alarm messages of solid dosage machining line based on Rough Sets Theory (RST), which can improve the configuration monitoring interface. It is shown in practice that the method can effectively improve the display mode of alarm events of man-machine monitoring interface of solid dosage machine line, reduce mental load of operator, and enhance work efficiency.
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      Pole-axis system (PAS) is one of main modes of regional development in China. A fractal model of PAS, which considered poles and axes synthetically, was built to discriminate the phase PAS stating, and then a GIS computing model was developed for the fractal model of PAS. Urban-traffic system in Jinan, eastern China, which is the PAS's carrier in geo-space, was taken as an example. The results showed that: (1) PAS presented a fractal character when developing to a certain phase. The fractal model of PAS can effectively reflect its spatial structure state; (2) fractal, scale-free and space complexity were the different states of geo-space. We could deduce that spatial structure of PAS had experienced an iterative process of disorder, fractal, scale-free, spatial complexity and order with its development; and (3) the urban-traffic system in Jinan had shaped the rudimental structure of PAS, which was in the developing phase.
  • Session 9

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      Image matching is a fundamental task in image matching and other computer vision applications. The Scale Invariant Feature Transform (SIFT) algorithm is generally considered as the most appealing application for practical uses, the SIFT descriptors remain invariant under rotation, scaling, changing viewpoint, affine distortion and variations in lighting conditions. A efficient Image matching based on SIFT is proposed by using the rotation and scale invariant property of SIFT. We generate the keypoint descriptor with the steps of scale-space extreme detection, accurate keypoint localization and orientation assignment, and then match the feature point by comparing the feature vector. The experimental results demonstrate that the SIFT algorithm is robust to scaling, rotation and noise.
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      As an efficient way to describe functional requirements, use case is accepted by more and more developers. Despite their popularity, there are many problems in the usage of use cases. We discuss the required use case structure on different use case stakeholder's view, and then we propound an activity based use case structure meta-model.
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      The implications of classical models have been far-reaching and pervasive. In fact, few steganographers would disagree with the analysis of lambda calculus [16]. Our focus in this position paper is not on whether suffix trees and web browsers are always incompatible, but rather on describing a classical tool for synthesizing compilers (WAYANI).
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      This paper presents a simple yet efficient method for signal detection in the case of low SNR. Under the circumstance of low SNR, noise will bring more negative effects to the signal detection which we must avoid as far as possible. To satisfy this request, we propose a novel topology of signal detection. By analysis and experiment, such new topology is proved to have the ability to work under the circumstance of low SNR efficiently.
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      In the recent years, digital image and video have emerged as the new techniques for the creation, distribution and storage of information. Latest developments in multimedia technologies facilitate the capture and storage of video data with comparatively low-cost computers. Moreover, the novel possibilities provided by the information highways have resulted in the widespread availability of large amount of video data. Nevertheless these data are highly futile unless appropriate search methodologies are employed. Contemporary users are dissatisfied with the video retrieval systems that offer analogue VCR functionality. Content-based search and retrieval of video data has turned out to be a demanding and significant issue. Video encompasses multiple types of audio and visual information those are hard to extract, combine or trade-off in common video information retrieval. In this paper, we address the specific aspect of inferring our approach for content-based video retrieval from a collection of videos. In particular, we introduce a new video data model that supports the integrated use of different approaches. Initially the system splits a video into a sequence of elementary shots, extracts a few representative frames from each shot and computes frame descriptors based on color, Edge and motion features. The extracted features of all the elementary video shots are stored in feature library. In our system, the videos are retrieved based on a query clip. For a query video clip, the color, edge and motion features are extracted and compared against the features in the feature library. The comparison is performed with the aid of Kullback- Leibler distance similarity measure. Afterwards, similar videos are retrieved from the collection of videos based on the calculated Kullback- Leibler distance.
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      The process of discovering the least pattern is more challenging as compared to frequent pattern. Thus, only few attentions have been paid in the past decades in this area. Discovery of least pattern mining is very important especially in detecting the abnormal events or errors such as in networking system, tsunami disaster system, etc. Here, we propose a scalable Causality Least Pattern Algorithm (CALPA) that can discover the least pattern sets with the degree of causality. The study shows that this algorithm can easily reveals the desired pattern sets and can be applied in any standard datasets.
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      In this paper, we use multinomial logistic regression (MLR) to categorize breast cancer based on survival or death. We discuss the need for survival analysis. We develop a multinomial MLR to evaluate the probability of breast cancer. The methods for MLR can often be applied in a modified way to solve classification or survival problems of breast cancer. Finally, the diagnostic performance of models was compared to that of the radiologist in term of sensitivity, specificity and accuracy, using receiver operating characteristics (ROC).
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      This paper contains a new series and parallel single-phase active power filter based on high input power factor and low input harmonics; it is for power quality purposes. The filters are designed to meet the requirements of voltage-current sourced harmonic loads it is based on a load current estimation using a DC capacitor voltage of active power filter sensing the load current. The proposed filters can improve the problems of a non-linear loads like as washing machines, faxes, photocopier machines printers, computers…etc and it also can suppress the harmonic current and compensate for the reactive power at the float charge mode. The simulation results and experimental results verify that the proposed filters have the expected performance.
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      The image deformation technology based on the control points has been widely applied in image deformation. This paper proposes an image deformation method which is based on the gravitation field of control points. This method establishes the transformation function using the interaction between pixels and the control points, and take shape deformation as the carrier, making that the deformed image can be automatically matched with the target shape. We can obtain the target image conveniently and efficiently when the original image is constantly updated, taking the dress deformation as an example to verify this method.
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      Pattern recognition of finite automata in RS image have been studied in the paper. There are three Finite automata(A FA,B FA and C FA) was chosed in the paper. The value of R(red color),G(green color) and B(blue color) which was gotten from every pels of RS image was used in the function of finite automata.Some curves were set up by the results of finite automata. These curves will be compared for the pattern recognition of RS image. A FA was proved to be most effective way in the Pattern recognition of RS image.(the paper is supported by the research fund for the doctoral program of southwest university,No:SWUB2008055,104220-20710913)
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      Searching a misplaced or lost object efficiently has been an important issue of research for many years. Some small but important objects which we use in our everyday life sometimes get misplaced or lost and we need to find them out. Searching such small objects is not always an easy task even if we are not much away from where those objects are. There are a number of known techniques for solving this problem. However, in those known techniques the receiver needs to be powerful enough to detect the strength of the signal and guide the searching agent according to it. As a result the costs of those systems become high and remain out of reach for the general people. In this paper, a simple, cost-efficient and reliable system has been proposed which is based on geometric models and uses binary detection sensor as the signal detector.
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      VANETs have been envisioned to be useful in road safety and many commercial applications. The vehicle node in VANET has many moving status, such as normal driving, waiting for traffic lights, which has great impact on many applications in VANETs. In the paper, the Data fusion method based on Rough Sets Theory is presented, which can integrate data from different sources such as GPS data and digital map data, and provides a more accurate Classification for vehicle moving status. The model architecture and an example are also presented.
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      Buffer management is very crucial to the Cellular IP networks as its proper use not only increases the throughput of the network but also results in the reduction of call drops. A model for buffer management in Cellular IP network using GA is being proposed in this work. It deals with two kinds of buffers; Gateway buffer and Base Station buffer. This is a two-tier model, where in the first tier a prioritization algorithm is applied for prioritizing real-time packets and to serve them in the buffer of the Gateway within a specified threshold. Remaining packets which couldn't be served after the threshold will be given to the nearest cells of the network to be dealt with in the second part. A GA based procedure is applied here in order to store these packets in the buffer of the base stations. Experiments have been conducted with different numbers of returned packets in order to study the effect of available buffer space on the number of dropped packets and to check the efficiency of the proposed model in reducing dropped packets.
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      Three-dimensional (3D) integration using through Silicon-Vias (TSVs) allows the formation of high signal bandwidth, fine pitch, and short-distance interconnections in stacked dies. There are several approaches for 3D chip stacking which includes chip to chip, chip to wafer, and wafer to wafer. Chip-to-chip integration and chip-to-wafer integration provides the ability to stack known good dies (KGD), which can lead to higher yields without integrated redundancy. In near future, with structure and process optimization, wafer-to-wafer integration may provide an ultimate solution for the highest manufacturing throughput assuming a high yield and minimal loss of good dies and wafers. In future, chip-to-chip and chip-to-wafer integration may offer high yield, high flexibility, and high performance with added time to market advantages. In this paper, 3D integration using chip to chip, chip-to-wafer & wafer to wafer approaches has been described. 3D chip integration technology and 3D stack technology with TSVs are discussed.
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      There is an increasing need for having Arabic text parsing tools as an important prerequisite for high-quality natural language processing applications targeting this language. In this paper an attempt to parse Arabic sentences with a link grammar supported with a statistical tokenization phase is presented. This step of the presented work can be considered as a complement to the state-of-the-art tools presented in literature. The problems of such approach are described, followed by a description of untokenized parsing as a solution to the problems of the tokenized approach. The two systems presented, take as input untokenized Arabic sentences and produce the possible linking graphs.
  • Session 10

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      This paper analyzed the advantage and disadvantage of TERCOM, probabilistic data association filtering(PDAF) and iterative closest contour point (ICCP) at first. Then it introduced the correction factor of tide and self-adaptive correction factor to improve the performance of seabed terrain elevation matching algorithm based on PDAF (STEMPDAF). By using STEMPDAF to make initial matching for ICCP, a combinational seabed terrain elevation matching algorithm was proposed. Mobile navigation is allowed during the matching period in the combinational algorithm. Theoretical analysis and simulation results both show that the performance of combinational algorithm is satisfactory.
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      Internet is the biggest source of information which is easily accessible but unstructured. Web mining - is the application of data mining techniques to discover patterns from the Web. According to analysis targets, web mining can be divided into three different types, which are Web usage mining, Web content mining and Web structure mining. [3]Web usage mining reveals about user's navigation pattern at any website through analyzing web logs.In this study we have tried to analyze the users online job seeking tendency pattern through two available web-based tools viz. Google Trends and Google Zeitgeist.
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      Based on analyzing the traditional association rules algorithm, an improved association rules Data Mining Algorithm is presented in this paper. The advantages of presented algorithm are fast removing redundant rules and not by the frequent items, so it is suitable for the massive data mining based on association rules. In view of the current large number of college students admitted after the loss of the candidates, some college enrollment data was mined based on the proposed algorithm. The results show that the proposed algorithm can mine useful information and play an important role in college enrolling affairs.
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      During the process of zinc hydrometallurgy, the control of pH value during leaching not only decides the quantity and rate of leaching but also restricts the quantity and quality in follow-up working procedure. Moreover, to keep high nonlinearity during the neutralization of pH value has always been very difficult in controlling fields. Aiming at this problem, this paper raised the idea of using nonlinear PID control based on Neural-network adaptive-PID in controlling pH of zinc hydrometallurgy so as to raise the controlling precision during leaching. It also made experimental compare with traditional PID controlling.
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      The artificial intelligence method to DHCP is defined not only by the synthesis of IPv4, but also by the intuitive need for context-free grammar. Given the current status of modular symmetries, cryptographers predictably desire the simulation of architecture, which embodies the extensive principles of hardware and architecture. In this work we concentrate our efforts on validating that the much-touted wearable algorithm for the key unification of redundancy and red-black trees [1] is NP-complete.
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      The operating systems method to semaphores is defined not only by the improvement of fiber-optic cables, but also by the confirmed need for fiber-optic cables. Given the current status of optimal theory, statisticians urgently desire the improvement of cache coherence. We motivate a novel application for the simulation of cache coherence, which we call Mime.
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      After researching on how to keep the security of intranet in dealing with interacting and data sharing between internet and intranet, this paper presents a kind of authentication protocol- a three-point authentication protocol basing on the kerberos protocol. In this authentication protocol, author presents a prefix-authentication server innovatively and combines kerberos and diffie-hellman protocol to improve traditional authentication protocol. Finally, it analyses and indicates that the protocol can solve the problem of security, workload of server and controllability of access, and the problem of data sharing effectively in the environment of internet and intranet.
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      The main intention of this paper is to analyze the application of digital technology to accounting. Digital technology has shaped a new revolution in human being's activities and has greatly changed all aspects of business. Accounting as the language of business is a part of this changing scenario and is experiencing a deep alteration in all dimensions. Digital accounting system is no longer a simple data keeping tool, but is rather a strong managerial mean. Implementation of digital technology on organization's accounting system is therefore a very sensitive matter and has been studied from different perspectives. There are different approaches towards applying digital technology to organization's accounting system and choosing an effective, optimum, and accurate approach is now a very noteworthy technical and managerial issue. This paper has introduced a decision matrix to provide manages with a flexible framework in order to help them improve the excellence of their decision. Other considerations for enhancing the development of an appropriate digital accounting system for the organization are also briefly declared.
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      Network video monitoring system realized with ARM9 and embedded linux. Monitor terminal hardware takes ARM9 S3C2410 processor for centralization, in virtue of Flash, SDRAM, USB, network controller,etc. Software system adopts embedded linux, the main function realized by C programming to achieve real-time camera data acquisition, image compression and network transmission. Monitoring center connects to the terminal by network, receives image data and displays with VC++ software. It is easier to be used in windows system. The results showed that the monitoring system has the advantage of high reliability, high efficiency and low cost with ARM9 and a wired or wireless network, and it provides a feasible method for remote video monitoring.
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      The implications of highly-available modalities have been far-reaching and pervasive. In fact, few leading analysts would disagree with the investigation of IPv4. We show that although the acclaimed trainable algorithm for the synthesis of symmetric encryption by Williams [2] follows a Zipf-like distribution, e-business and Byzantine fault tolerance can synchronize to overcome this riddle.
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      Von Neumann machines and compilers, while important in theory, have not until recently been considered structured. In fact, few end-users would disagree with the improvement of SCSI disks, which embodies the intuitive principles of artificial intelligence. Settle, our new methodology for Bayesian epistemologies, is the solution to all of these obstacles [1].
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      Recent advances in wearable communication and knowledge-based models collude in order to accomplish massive multiplayer online role-playing games. Of course, this is not always the case. After years of robust research into neural networks, we show the refinement of evolutionary programming, which embodies the key principles of algorithms [1]. We construct a novel application for the refinement of redundancy, which we call DyadicFund.
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      16 bit architectures and robots, while appropriate in theory, have not until recently been considered essential, in fact, few mathematicians would disagree with the construction of massive multiplayer online role-playing games. In this position paper, we demonstrate that although the little-known stochastic algorithm for the study of rasterization by U. Martinez [1] is optimal, evolutionary programming can be made modular, event-driven, and wireless.
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      Genetic Algorithms seek to solve optimization problems by implementing bioinspired techniques that simulate the evolution of living beings. This work explores a particular aspect of these techniques and proposes an individual mate choice criteria for the mating phase, called IBC. The main idea is to delegate the choice of the mate to the individuals, seeking to obtain a positive incidence in the evolution of the individuals throughout the generations. The choice criteria is codified within the chromosome, so it participates of the evolutionary process, giving each individual its own criteria. Experimental comparison between IBC, Rank and Binary Tournament show a positive tendency for the proposed technique.
  • Session 11

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      The paper redefines differential evolution algorithm's mutation and crossover operations for dealing with discrete problems effectively, and it also introduces a variation mechanism to avoid individual stagnation. Then the improved differential evolution algorithm is applied to solving routing problem with time windows. Simulation results show that the improved differential evolution algorithm can not only effectively avoids the premature convergence, with strong global optimization ability, but also excellently solves routing problem with time windows in short service time and long service time, and it also can be applied to other discrete problems.
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      This article first analyses the reason that A* algorithm influences speed when searching for optimum route in game map, then it gives the optimization scheme from the aspects of node structure, the maintenance of open queue and so on. What is more, it carries out theoretical analysis for the improvable A* algorithm. At the same time, the scheme is tested and evaluated by a lot of different big and small maps. Experiment result shows the improvable A* has very actual value in seeking the solution of way problem for map. And it has certain reference meaning in instant strategic kinds of game.
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      2D gel electrophoresis (2DGE) plays an important role in proteomics. It can separate proteins effectively with their pI values and molecular weights. Proteomics researchers needed to identify interested protein spots by examining the gel. This is time -consuming and labor extensive. It is desired that the computer can analyze the proteins automatically by first detecting and quantifying the protein spots in the digitized 2DGE images. In our work, we will investigate the use of the watershed algorithm in segmenting the protein spots from the varying background. However, the watershed algorithm often produces an over-segmented result. So, we will introduce the notion of fuzzy relations to improve the segmentation result
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      Base on the traditional workflow technology, the paper unified tasks, resources, data and control in a workflow process model and made a formalized description. The uniform process model improved the ability of description. Furthermore, the paper transformed the process model into equivalent Petri-net structure and improved it's ability of analysis and verification. Finally, the method was applied to the modeling process of space targets detection which validated the feasibility and effectiveness of the method.
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      Cultural Algorithm(CA) is an evolutionary model inspired by the cultural evolution process which shows many excellent characteristics and succeeded in solving some complicated problems. In this paper, a new CA is proposed based adaptive fuzzy controller, The new Algorithm adjusting parameter β using adaptive fuzzy controller, changing the member of individuals in evolution process, making the CA optimized. The experiments results illustrate that the fuzzy CA is better than CA. in three terms.
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      Expression recognition is an important research direction of pattern recognition, and the facial feature extraction is a key step. This paper presented a simple and fast feature extraction method. In this paper, facial feature points were calculated using integral image and rectangle templates and its results were the feature value, finally these feature value were used for expression classification. The experimental results show that this method improves efficiency while extracting facial feature and does not affect the result heavily.
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      COSMOS works software is applied to finite element analysis for the frame of high pressure grinding roll, the stress and deformation distribution law of the frame under the static load are revealed, the position of dangerous point is obtained, this provides a reasonable basis to optimize frame structure and identify the main design parameters.
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      In fatigue design, the dates from material test are used to describe the components' behavior. As the limitation of theory and method, the strong subjectivity in choosing correction coefficients makes it hard to evaluate the design quantitatively. Based on the finite element and optimal theories, fatigue specimen lying between material and component is put forward. Finally the virtual design method of that specimen is primarily discussed.
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      Traditional PID controller has gotten much attention in application. But in modern production activities, it is hard for traditional PID controller to satisfy more and more strict control requirements. So, on the basis of grey system theory, this paper proposed a grey PID control strategy, which consists of grey compensation technology and grey prediction technology. We applied both grey compensation and grey prediction into the controlled system for the first time in the paper, and simulation results show that the novel control strategy can greatly improve system performances, reduce overshooting and weak the influence of system's uncertainty section.
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      The simulation of flower plant is a new area in virtual plant. The paper presents a rendering algorithm to flower plant base on L-system theory and Bezier surface mathematics model. The morphologic topology structure of flower plant was described by L-system; the plant stem was modeled by parameters equation of cylindrical spiral; plant leaf, petals were rendered by bicubic Bezier surface; buds and calyces were mosaic merged by four to six Bezier surface. The result show the render algorithm was simple to generate various and realistic flower plant, moreover, the control parameters is few.
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      This paper presents a new Data Encryption Standard (DES) based on variable time data permutation. Data is periodically permutated by using a permutation box. The permutation box contains several data permutations. The permutation choice will be due to a timer value which controls the permutation choice. for the same data and key, the ciphered data is varied periodically by using the variable time permutation. The results show that the proposed scheme gives a more secure algorithm without additional delay. Also, increasing the size of permutation box increases the security of the proposed scheme.
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      Designed and implemented an in-vehicle information system based on Linux with IPv6. There were three modules in this system included CDMA connection module based IPv6 applications, NAT/firewall based on IPtables/Netfilter, and display module based on miniGUI. We could use CDMA connection module to send the GPS and the CAN bus data to the remote servers, and the firewall based on IPtables/Netfilter could provide some rules to protect the system against attack. It was also designed to support the inter-vehicle users to visit internet through the system based on NAT module. The GPS module could get GPS information from GPS receiver. A touch-screen was used to display the information of GPS and CAN bus by the display module.
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      Bit Interleaved Coded Modulation (BICM) was first suggested to improve the performance of Trellis Coded Modulation (TCM) over Rayleigh fading channels. It was shown that BICM with Iterative Decoding (BICM-ID) can be used to provide excellent performance over both gaussian and Rayleigh fading channels. The transmitter of BICM-ID system consists of three serially concatenated blocks which are, a convolutional encoder, a bit interleaver and a binary mapping function which maps blocks of coded bits to signal constellation points. It has been shown that when signal constellation, bit interleaver and convolutional encoder are fixed, signal mapping has a critical influence to the system's error performance. This paper studies the effects of signal mappings to the performance of a BICM-ID system using 8PSK constellation operating over a Rayleigh fading channel. The Bit Error Rate (BER) curves are used to determine the most attractive mapping. Simulation results for different mappings are also provided and discussed.
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      Isotonic regression is usually used to analyze the problem for normal means. This paper then studies an information process method for the order of normal variances, assuming means known, variances restricted by a given simple order.
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      Based on the connotation of e-government information security, the paper discusses China's current e-government information security problems, which cover problems of information, network, equipment and management. Besides, this paper puts forward effective countermeasures to solve problems of e-government information security from the technical, managerial and cultural perspective.
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      The implications of distributed modalities have been far-reaching and pervasive. After years of technical research into public-private key pairs, we validate the construction of e-commerce, which embodies the private principles of partitioned cyberinformatics. In order to accomplish this intent, we investigate how B-trees can be applied to the simulation of access points.
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      Genomics and proteomics researches greatly depend on the database search the operation on them will spend a great deal of computing time. In this paper, based on the research of the existing bio-sequence alignment algorithms, a parallel design program for the Blast algorithm is proposed. The experimental results show that the parallel of the Blast algorithm has greatly improved the running time of the program without prejudice to the outcome of biological sequence alignment.
  • Session 12

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      The tradeoff between molecular complexity and accuracy of results continues to be a tug of war in computational material science. One of the challenges in computational nano materials science is the ability to parallelize the tools used, so as to facilitate the solution of more computationally extensive and complex problems with better accuracy. Though using more computationally powerful computers would enable solving larger problems, however real scalability is inherent to the underlying code used to implement the algorithms, and sometimes the algorithms themselves. Ab initio calculations are essential in identifying the properties of new nano materials. We investigate the performance scalability of Abinit1,2 in Band Structure calculations on a massively parallel architecture. We introduce a typical tool flow used for the computations involved. We study the scalability of the underlying tools while performing band structure calculations for C60 and EDOT molecules. We gained initial understanding of the factors affecting scalability for the molecules under consideration and we give some recommendations on how to address the possible issues that affect them.
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      Requirements change has become a great challenge in software development, in order to control requirements change more effectively, it's necessary to extend or improve the traditional Quality Function Deployment (QFD) method. Thus, on the basis of SECI model a new methodology called Dynamic Quality Function Deployment (DQFD) is put forward in this study. Then, combining with the software structure design method of Quantification Method of Type 3, DQFD is applied to control requirements change. Synthesizing the theory and method of knowledge management and an approach called software requirements change management based on DQFD is proposed. The applicability and validity of the proposed approach are testified through its application to an actual software development project, and these results further consummate the theory framework of this paper.
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      Construct E-government system in rural areas based on bank of villages and towns can attract peasants to gain prompt access to a variety of executive orders and such as policies, laws and regulations information relating to the vital interests of the peasants of the community through E-government network maximize, understand development measures for agriculture, rural areas and peasant quickly, in line with local conditions to make suitable agricultural economic development, promote the continuous development of the rural economic and social development well and faster through the level development of E-government.
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      Business process model plays an important role in business process management. It can share knowledge among stakeholders. So the problem such as: is this business process model easy to understand needs to be solved. Volker Gruhn and Ralf Laue have proposed a cognitive complexity measure for business process model. They hope this metric can help to measure the understandability of business process model. But the validity of this metric needs to be valided by theorical research or experiments. Weyuker properties must be satisfied by any complexity measure to qualify as a good and comprehensive one. In this paper, an attempt has been made to evaluate the cognitive complexity measure in terms of Weyuker properties to check whether it is a good metric.
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      By aid of economic grows and industry evolution theory, this paper constructed a construction industry growth dynamic model of china. Selected years 1990–2007 growth in construction industry-related economic data for simulation and analysis of industry growth through the three types of dynamic behavior: equilibrium stability, cycle, fractal and chaos. Combination of non-linear theory and computer simulation techniques such acts and given its economic policy conditions.
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      This article mainly aims to handle this kind of information and design the model based on human olfaction passivation. Using this control model, the high frequency of false alarm will gradually decrease to the level at which IDS will do no alarming for the false information. And meanwhile, during the procedure of controlling, IDS will record the repeating alarming information, which will be used in statistic analyzing. By using this control model, the internet management staff can devote themselves to the internet security and not be disturbed by the alarming deluge. Also the model will reduce the rate of wrong alarm.
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      Sznajd model, as a developed type of Ising model, has been introduced to simulate and analyze the dynamics of opinion formation and development. This paper aims to analyzing Sznajd opinion formation model on Weighted Networks by updating synchronously. We simulate the public opinion formation processes based on improved Sznajd Weighted Network model with influencing rules. Due to the disappearing of the dictatorship fixed points in the finally results, decisions can be made in a democratic way in this model. All this modifications display interesting dynamics and explain some socio-economic aspects.
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      With the recent emergence of business being conducted over the Internet, companies is inevitably using information technology to cut costs, increase productivity, reduce the time required to develop new products harness the collective expertise of their employees, and create an extended enterprise by forging closer relationships with their customers, suppliers, distributors and partners in order to remain competitive. In most companies, knowledge management and e-commerce initiatives have been dealt with independently. This paper introduces a relationship between knowledge management and e-commerce. Looking at how e-commerce can be optimized in a company with knowledge management.
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      Customer demand clustering is a key technology to modern company; however, the traditional clustering methods have many disadvantages on accuracy and efficiency. In order to cope with this problem, the self-organizing maps (SOM) were employed to cluster the customer demand. The SOM Toolbox in Matlab was used to realize the demand data clustering for transportation equipment. Experimental results show that the proposed technique may improve the clustering accuracy, and provide a visual clustering result.
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      Based on the analysis of several kinds of methods generally used to intercept network packets in different layers, a NDIS intermediate driver-based defense mechanism for SQL injection attack is proposed, and the structure is designed. The system is composed of NDIS-based data package capture module, SQL injection attack detection module and rules base. Characteristics of every entity are discussed in detail. Finally, experiments results show that the system can detect SQL injection attacks and intercept malicious packets effectively.
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      A novel meta-heuristic algorithm that is based on the principles of particle swarm optimization (PSO) is proposed for course scheduling problem. In the original PSO algorithm, particles search solutions in a continuous solution space. Since the solution space of the course scheduling problem is discrete, this study incorporates a local search method into the proposed PSO in order to explore a better solution improvement. The simulation results demonstrate that the proposed PSO in this study can significantly reduce the amount of computation required for course scheduling, and yields an optimal satisfaction of course scheduling for instructors and class scheduling arrangements.
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      Process of change in any organization aims to improve the organization's abilities. This improvement might need some changes in systems that organization uses, which might require change in the role of people and structure of the organization. Unfortunately, this process of change usually faces resistance, particularly in case of implanting of ERP systems. Deal with resistance is not an easy task; it needs to understand the sources, type, and reasons of this resistance. Thus, this paper aimed to give an overview about ERP systems and resistance to change associated with implementing of ERP systems. Then, proposed a people-change purposes conceptual model that can help in producing effective change with limited resistance.
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      This study analyzes the mortgage loans of five Taiwanese commerce banks to identify the key factors that influence prepayments and defaults. Using data from a total of 16,213 data entries of mortgage loans of five Taiwanese commerce banks in 2002 through 2007, this study first conducts Discriminant Analysis to analyze the behavior of prepayments and default. As far the overall predictability is concerned, this paper finds that the Discriminant Analysis model is able to provide simplified results in the measurement of model variables concerning defaults and prepayments.
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      To solve the problems of current E-learning systems, Web mining technology is applied in the E-Learning system. The Web mining technology and the architecture of the E-Learning system is simply introduced in this paper. A personalized recommendation model based on Web mining is proposed, which can improve intelligent and personalization. The Web mining based methods for personalized recommendation are explained in details.
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      In this paper, a new adaptive algorithm using URV updating for blind multiuser detection in impulsive noise is proposed. It is shown that under this scheme, the linear minimum mean-square-error (MMSE) detector can be obtained blindly, i.e., they can be estimated from the received signal with the prior knowledge of only the signature waveform and timing of the user of interest. A blind adaptive implementation based on URV updating is also developed. The new algorithm need not estimate the subspace rank in order to reduce the computational complexity. Simulation results show that the new algorithm offers substantial performance gains over the traditional subspace methods.
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      IT organizations are facing a changing understanding of their responsibilities and their role in companies. They are no longer just seen as IT service providers but as business-oriented drivers for innovations which have an impact on the business concept. Oftentimes IT enables innovations and is a decisive factor for the business development and the competitiveness. In this context, the central task of IT management is to ensure an innovation and value increasing use of IT. By an efficient management of the IT project portfolio, IT organizations can help to establish a more innovative company. Therefore, this research paper reveals how this portfolio ideally should be designed in order to encourage IT-based innovations. For this purpose, a literature review and an expert survey have been conducted. Altogether 14 experts - IT department manager, IT business unit manager as well as IT consultants - have been interviewed. As result of our research, four factors for an innovation-conducive management of the IT project portfolio have been identified. These are (1) sufficient supply of IT project resources for the implementation of business strategy, (2) sufficient supply of resources for IT innovation projects, (3) creation of project teams with fundamental IT and business knowledge and (4) extensive involvement of business departments into the IT project portfolio management process.
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      Clustering can help analysts to find the preference for books and the love for different types of new books of readers with different titles at different stages. This paper enumerates the clustering algorithm based on objective function commonly used in data mining and uses fuzzy C-means (FCM) clustering algorithm to carry out fuzzy clustering mining for the data warehouse established based on library log information, thereby mining book types loved by most readers.
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      Based on the analysis of pattern matching algorithm and data compression algorithm, this paper develops a kind of common and fast real-time monitoring software model according to high cohesion and low coupling design principles of software engineering. This model carries out data compression in the process of pattern matching for monitoring data, which can effectively reduce system time consumption and ensure the real-time performance of monitoring system, and meanwhile it can be applied to different application environments after being configured by configuration module, improving the reusability of software..
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      Based on traditional orthogonal grid decomposition algorithms, this paper studies the decomposition algorithm of boundary cut grid and develops the corresponding calculation program by ray method. It carries out grid decomposition of actual castings, the results show that compared to zigzag grid, boundary cut grid has good adaptability to castings with curved surface and can reflect surface features of castings, thereby laying a foundation for accurately solving physical fields, such as flow field and temperature field, etc.
  • Session 13

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      Unfortunately as the scale of integration has increased so also has the occurrence of intermittent faults. The characteristics of these types of faults render them undetectable by standard test strategies. This is particularly problematic with the wide use of complex circuits in safety-critical applications. Ensuring the reliability of these systems is a major testing challenge. The detection of intermittent faults requires the use of Concurrent Error Detection (CED) techniques, which continually monitor the operation of the circuit. One method of implementing CED in VLSI circuits is through the use of information Redundancy or coding techniques. This paper investigates the use of Berger code as a means of incorporating CED into a self checking hardware register stack.
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      In the Intelligent Transport Control System, one method of achieving communication between the control center and the mobile terminal is to install GPRS module on the mobile terminal. The GPRS will connect with IP web. This transmitting method is economic applied and efficient. The paper introduces web organization of this system and software composition in the mobile terminal. It explains the method about how to connecting with Internet by GPRS module. The paper particularly analyses the method of inbuilt web protocol stack.
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      Requirements change has become a great challenge in software development, in order to control requirements change more effectively, it's necessary to extend or improve the traditional Quality Function Deployment (QFD) method. Thus, a new methodology called Dynamic Quality Function Deployment (DQFD) is put forward in this study. Then, combining with the software structure design method of Quantification Method of Type 3, DQFD is applied to control requirements change, and an approach called software requirements change management based on DQFD is proposed. The applicability and validity of the proposed approach are testified through its application to an actual software development project, and these results further consummate the theory framework of this paper.
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      In this paper, we successfully predicted 4 microRNAs in genome of Avian metapneumovirus by using BNMir-P program, and further validity it in second round prediction using miPred software which based on machine-learned algorithm termed random forest (RF). By BLAST against reported mature sequences, these 4 AMPV microRNAs were regarded as novel microRNAs. Target prediction results showed total 23 target genes were found in chicken UTR database. Based their function, the targets could be divided in to 4 groups, including immunity system genes, lipid metabolism genes, ion-channel genes involving in Ca2+ and K+ transporting and gene expression regulators. This finding connected the AMPV infection mechanism and its harm effects with the disturbed gene expression and enzyme function, giving deep understand of the AMPV infection and providing novel clues for further research. Taken together, the result demostrated the prediction flow was accurate, sensitive and species indenpendent, and was suitable for microRNA prediction of other animal virus.
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      In this work, we analyze average daily air temperature records for 12 years for some cities. For each city, daily recodes are deeply influenced by the seasonal fluctuation. We attempted to remove this seasonality by subtracting a properly adjusted sine function. Nonlinear analysis of data will be attempted to find fractal and/or chaotic nature of daily average temperature of original data as well as the data after removal of seasonality and compare the results. Evidence of chaos is found through calculation of Lyapunov Exponent.
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      Inspired by the principles from neuroscience, a spiking neural network is proposed to perform characters image processing. The main units of spiking neural network are spiking neurons which utilize inter spike time intervals as sources of information. Research on spiking neural networks has gained momentum in the last decade due to their ability to mimic biological neural network signals and their efficient computational capabilities. A supervised learning algorithm for spiking neural networks which receive input spike trains (presynaptic inputs) is proposed. In this algorithm, learning is performed in two stages: mapping of the input spike train into a spatio-temporal pattern; and use of a simple learning criteria to change synaptic weights. The proposed algorithm is then used to classify various character images.
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      For many monitoring applications, the major goal of the sensors is to detect events in physical world. The events which cause consecutive outliers on sensor data constitute an important type of event to detect. However, some disturbed events may also caused outliers, which have adverse impact on the detection results. In addition, sensor data are usually uncertain due to the imperfection of physical devices and communication delay. This paper proposed a probabilistic model mapping- based event detection method which can reduce false positive warning caused by disturbed events with high efficiency. Experimental results show the good performance of our method.
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      A tool-condition-monitoring (TCM) system measures the operation of a machine tool so that any deviation from nominal operating conditions can be identified and hence appropriate correction procedures can be applied. This capability enables the production of precision, quality and consistent parts. This paper presents a methodology that combines and optimizes the abilities of genetic algorithms (GA) and the prediction characteristics of support vectors machine (SVM). The drive behind this work is to have a system with a fast running and training time besides its ability to handle large amount of unprocessed data.
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      A device that composed of two circuits include ultrasonic sensor and touch sensor, can be installed in some machines to protect human body from hurting. was proposed in this paper. The device has two ways to identify human body. One is to detect the near human body by ultrasonic sensor, the other one is to detect the touched human body by touch sensor. The device has double protection function with the two different ways. When the device finds that there is human body nearby or touched, a signal will be sent to control the relay connected between input power and the machine. The power of the machine will be cut and human body will be protected away from hurting. Experiment results verify the theory proposed in this paper.
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      Deterministic global optimization methods generally have a complex optimization process, and usually make some assumptions regarding the problem to be solved. These approaches can be computationally tedious and difficult for general practitioners to implement. To overcome these drawbacks, stochastic optimization methods have been developed, such as genetic algorithms, artificial immune systems and simulated annealing (SA) algorithm. However, this study aims at SA algorithm. This study presents an advanced SA (ASA) algorithm based on penalty function. The proposed ASA algorithm is used to three benchmark nonlinear programming (NLP) problems. Numerical results indicate that the ASA algorithm can find a global solution for a NLP problem.
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      As defined as the blending of online learning activities and traditional face-to-face learning activities, blended learning is becoming a common practice in higher educational as a result of the integration of learning management systems (LMS) into traditional teaching [5]. Along with the new Internet technologies such as Web 2.0, blended learning environment (BLE) has increased the complexity of higher education teaching and learning. While BLE is still evolving and under-researched, more theoretical elaboration followed by empirical studies are needed. This study articulates on the important conceptual constructs of BLE in terms of complexity, transactional distance, instructional design, Web 2.0 implications and the challenges to BLE framework construction. A five-layer conceptual framework for BLE instruction design is then proposed in order to serve as a groundwork for further BLE theoretical and empirical studies.
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      Based on an optimized perceptual model of the zero tree structure, propose one watermarking algorithms,which embeds a watermark of Gaussian sequence, and the blind detector is based on correlation. In order to maximum embedding watermark bits, the two proposed algorithms embed watermark bits in all of the significant wavelet coefficients, including the coefficients of lowest pass sub-band, and provide a good tradeoff between the transparency and the robustness of watermarks based on the perceptual model. Experiments show that the proposed algorithms is effective and robust to common image processing operations, especially to JPEG and wavelet compression.
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      Due to the rapid growth in the size of the web, web search engines are facing enormous performance challenges. This paper presents an inverted file method to improve the effectiveness of retrieving documents. It integrates the effects of the document identifier data and document weight data to improve the efficiency of retrieving process. Moreover, we propose the Hybrid Trie-Inverted file (HTI) index because the evaluation of containment queries relies on merge-joining the inverted lists, and then we conduct several experiments to evaluate our proposed approach. The experimental results show that it can get higher performance than traditional Inverted file index.
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      An increasing number of applications of dynamic neural networks has been developed for digital signal processing (DSP), dynamic neural networks are feedforward neural networks with commonly used scalar synapses replaced by linear filters. This provides feedforward neural networks with the capability of performing dynamic mappings, which depend on past input values, dynamic neural networks are suitable for time series prediction, nonlinear system identification, and signal processing applications.Their most popular types are Finite Impulse Response (FIR) neural networks, which are obtained by replacing synapses with finite impulse response filters. Due to their guaranteed stability characteristic and easy to minimize error surface they have been used with great success in many applications such as signal enhancement, noise cancellation, classification of input patterns, system identification, prediction, and control..Most of the works on system identification using neural networks are based on multilayer feedforward neural networks with backpropagation learning or more efficient variations of this algorithm, an elegant method for training layered networks. This paper is based on work in a Dynamic System Modeling (DYSMO) and as an application for speed control of DC motor drive.
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      The 21st century is a highly internationalized, scientific, and diversified knowledge economy era. It makes everybody aware of the superiority of modern educational technologies and the more and more important role of modern education technologies in the quality education. At present stage, in many schools, the investment has been enlarged into teaching hardware equipments, such as the equipping of computer multimedia, the adding of projectors and scanners, and the construction of gymnasiums. Besides, there are various opportunities to train teachers' computer level. Therefore, there are basic conditions for the bringing of the computer assisted instruction into physical education classrooms. With the rapid development of science and technologies, the knowledge economy has become the main and unique characteristic of the current society. As a result, how to cultivate students into high-quality and all-round developed talents becomes the important topic and task for all educational workers. Physical education, as an important part of the quality education, should also comprehensively and steadily develop. From the implementation of the idea of new curriculum reform till now when the quality education is being fully carried out and promoted, with the broad application of computer multimedia technologies to the classroom teaching, as a important index of standards to evaluate the classroom teaching, the traditional physical education teaching was is facing increasingly severe challenge, and disadvantages of the traditional physical education teaching have been completely disclosed. Therefore, the complementary action of computer multimedia in the physical education teaching is particularly requisite.
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      In this paper, through the research on the basic principles and algorithms of data mining, a program of applying data mining technology in university decision system is proposed. And then this program is used to carry through data mining for the data warehouse of the university, generate an effective decision rule, and analyze it. The results show that this decision rule is really effective. Therefore, the study has some practical significance to promote the level of university decision-making.
  • Session 14

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      The purpose of this study was to investigate the factors that influenced teachers' attitudes to use ICT (Information and Communication Technology) into the teaching innovation. The literature review, questionnaire survey, and the in-depth interview were used in this study. In this study, the interview questions were semi-structured; interview data emerged from 10 volunteered Taipei Municipal vocational high school teachers in Taiwan. The study also used the proportionate stratified sampling method to select 250 Taipei Municipal vocational high school teachers from 19 schools in different areas of Taipei. There were 218 valid questionnaires, and the data were analyzed by using the factor analysis, descriptive statistics, independent sample t-test, one-way analysis of variance (ANOVA), and Pearson's correlation coefficients. Based on the results of this study, the factors influenced teachers' attitudes to use ICT which included administrative support, teachers' ICT confidence, technical skills in ICT, and lack of time. Some related discussions and suggestions were offered for the future studies.
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      Mashup has become a major part of the Web 2.0 technologies. It requires shared meaning to enable the creation of new applications by combining or reusing different resources on the Web. However, most Web 2.0 applications share meaning based on XML-based metadata that still short of knowledge representation in handling computer-interpretable effects. This study attempts to integrate ontology technologies into Web 2.0 Mashups by defining a semantic multiple-layered architecture. Based on the proposed framework, Ontology-based Map Wiki (OMWiki) is developed to combine Google Maps with Wiki system. To illustrate the OMWiki applications, we implemented a commerce domain map-based wiki that offers dynamic geographic placemarks based on user preferences to finding interest stores. Additionally, the study also realizes how ontology technologies can be integrated into Web 2.0 Mashups.
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      This paper presents a discrete particle swarm optimization to solve the task assignment problem using discrete binary variables. The particle swarm optimization involves a population of particles through a problem space on the basis of information about each particle's local best solution and global best solution of all particles. Most versions of the particle swarm have operated in continuous variables. The task assignment problem of distributed system is to assign some tasks to distributed processors system, which relative tasks have to exchange information on different processors. The objective is to minimize the maximum cost of the processors, which includes computing cost and communication cost. Simulation results show the assignment problem can be solved by the proposed method efficiently.
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      Through the research of existing computer network status, in this paper a design program of the computer network management system based on SNMP protocol is proposed, and then the program is achieved. This design program has a simple structure, occupies less of the resources and is easy to expand.
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      In this paper, we introduce a new approach for computing the support of itemsets, which is an important component of data mining. Using the computed support values, confidence of association rules can then be found. Our approach uses standard relational algebra to compute the support values. Using the relational algebra for mining association rules enables us to uniformly apply data mining techniques to a wide spectrum of relational databases. This is because relational algebra is a standard interface for accessing relational data.
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      The purpose of this study was to explore the current state of information literacy (IL) training and to identify the strategies and methods used by the Canadian public libraries in improving information literacy skills for their staff and patrons. Also, the study sought to identify problems associated with the development of information literacy training. This study employed document analysis, observations, and focus group interviews to collect research data. The focus group interview consisted of six library staff members. The research findings revealed that Canada's public libraries valued their roles as IL training providers and paid careful attention to staff development in order to provide efficient IL instruction for the public. Another issue explored in this study is that public libraries build partnerships with other organizations to extend their IL teaching responsibilities. Additionally, a major challenge, based on the research findings, is that public libraries need to let their staff understand the learning theories associated with IL education and adult learning in order to enhance the quality of this training.
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      This study investigates the impacts of information and communications technology adoption on business process reengineering and the associated performance from a dynamic resource-based perspective. The framework is tested using survey data from a sample of 436 chief information officers or senior information system managers. ICT technologies facilitate firms to optimize business processes. Moreover, business process re-engineering has significant positive impacts on internal process performance, and then internal process performance has significant impacts on organizational learning and growth and customer satisfaction correspondingly.
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      This paper explores adult learning types which in turn provide a better understanding on individual learning difference and the application of adequate teaching and learning method in practice. The outcome of this research can be adapted for an effective learning and for reaping certain learning purpose. This research analyzed adult learning types based on the data of the required English classes from the continuing affiliated department of a Technology University located in the middle Taiwan. The research used quantitative methodology to sort out the extreme individual of learning type by a sample of 171 participate students, and further used an in-depth interview of a qualitative methodology to investigate the learning experience, learning characteristics and leaning difficulties of different learning types. The findings of this research form the comprehensive reference for curriculum designs and strategy of teachers on one hand, and elevate the quality and development of adult learning on the other.
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      Dynamic time warping (DTW) has been widely used in various pattern recognition and time series data mining applications. However, as examples will illustrate, both the classic DTW and its later alternative, derivative DTW, may fail to align a pair of sequences on their common trends or patterns. In this paper, we propose a Feature Based Dynamic Time Warping (FBDTW) algorithm that evaluates the distance of two data points based on both the local and global features that these two points present in their sequences. With the same time complexity as the classic and derivative DTW algorithms, FBDTW outperforms both on pairwise similarity evaluation of time series sequences based on the experiments conducted on the UCR time series classification/clustering test bed.
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      The aim of the investigation was to determine the influence of rendering intents on the gamut volume and the visual evaluations in digital proofing. According to that, the corresponding test form was used for the needs of investigation and printed on Epson style pro 7800 with the application of ICC standard rendering intents (perceptual, saturation, relative colorimetric and absolute colorimetric). Based on the results obtained by spectrophotometer measurements, the gamut of the digital proofing was illustrated with the ColorThink software in CIE L*a*b* color space. The analysis in relation to the results of visual evaluations shows the difference influence of the rending intents to digital image quality.
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      Knowledge discovery is the process of automatically searching large volume of data for patterns that can be considered knowledge about the data. This is described as deriving knowledge from the input data. Knowledge discovery is defined as “the non-trivial extraction of implicit, unknown, and potentially useful information from the data”. Knowledge discovery is one of the key components of knowledge management system. Today's World Wide Web has large volume of data - billions of documents. So it is a time consuming process to discover effective knowledge from the input data. Here define knowledge discovery meta model (KDM) which defines an ontology for the software and their relationships for the purpose of performing knowledge discovery of existing data. Although search engine technology has improved in recent years, there are still many types of searches that return unsatisfactory results. This situation can be greatly improved if web pages uses a semantic markup language to describe their content, this paper describe SHOE a set of simple HTML ontology Extensions. SHOE allows World-Wide Web authors to annotate their pages with ontology-based knowledge about page contents. This paper contains an examples showing how the use of SHOE can support a new generation of knowledge-based search and knowledge discovery tools that operate on the World-Wide Web. Identifying patterns as the process of knowledge discovery in an university ontology is taken as case study.
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      In a typical network, an attacker usually breaks into the network through a chain of exploits, resulting from its inherent vulnerabilities. Such a chain of exploits represents an attack path and for a network all such chains of exploits taken together form an attack graph. Attack graphs are tools which aid in the identification of risks associated with a network as a whole. The use of attack graphs in the context of multi-stage network security is an active research area. Various approaches have been reported in literature for generation of attack. In this paper, we present a novel approach to enumerate all the acyclic attack paths in a network using a custom algorithm over a model checker's solution.
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      Development and implementing robust IT Governance is a basic requirement for a majority of modern organizations. It is all about using technology resources to deliver business capability that basically aligns with strategic goals and objectives. Effective IT governance can significantly improve business performance by increasing productivity, ensuring quality and boosting profitability. In this paper we aim to claim that the deployment of IBM PRM-IT while considering a number of points and criteria can provide a well-matured reference model for the governance of IT while covering nearly all requirements ofTT Governance fundamentals.
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      Service oriented architecture and especially web services play the main role in nowadays internet enabled business. By the appearance of semantic web, the new concept of semantic web services becomes the base of the next generation of WWW. The developers of semantic web services (SWS) promise that the process of discovery will become more automated and more intelligent. So, we propose a new discovery mechanism that based on clustered SWS repository. The clustered SWS repository will seed up the process of service discovery. In addition, the proposed mechanism has the ability to find composite solutions consist of more that one service to achieve the service requester goals.
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      In this paper, based on the research of the existing traditional software testing, according to the characteristics of Web service itself, a Web system testing model is given and achieved. And the experimental results show that the model is effective and feasible, and this model is simple and easy to achieve, which has a certain practical significance.
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      A system able to capture coherence of sequential foci based on an absolute expression called “CEE”, detecting and disambiguating multiple contextual knowledge representations arising in complex sentences / adnominal phrases / co-occurrence expressions / main and subordinate clauses / emoticons, is described in this paper. In the e.g. [Though the memory capacity of this hard disk is big (positive), its clatter is big (negative).], the same word “big” appears twice, however, because the latter have different meaning according to context, its evaluation polarity reverses. Furthermore, in order to capture the whole meaning of this sentence, detecting the antecedent of “its” (This antecedent is “hard disk”), an anaphor, becomes also necessary. The ratio of correct evaluation from 2500 customer reviews is 75.0 %.
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      The most important problem to be solved in questionnaire dealing is the laborsaving of the method. In particular, in dealing with open-ended questionnaire are time-consuming and laborious. This study proposes a Delphi web-based opinion survey system, which is designed based on the method for convergence opinion from multiple experts with unstructured data. To demonstrate and evaluate the proposed unstructured data mining methods, Electronic Record Management Systems' questionnaires are adopted. In the experiments, the free-form survey responses are mined on the basis of Chinese word structures. The platform makes opinion convergence more convenient. Finally, we also compare and analyze the results of the manual processing of open-ended questionnaire, and hope this information will be helpful to the survey industry.
  • Session 15

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      This work presents the performance of ultra wideband T-shaped monopole antenna loaded with an annular dielectric resonator for wireless sensor network applications. The antenna shows 10 dB impedance bandwidth over 4.5 GHz – 15.5 GHz. The antenna also shows phase linearity and constant radiation pattern over the frequency bandwidth and is found suitable for wireless sensor network applications. The results are simulated using the electromagnetic software WIPL-D Pro v5.1. The result for return loss is verified with the measured data from a prototype antenna.
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      Multilingual corpora are becoming an essential resource for work in multilingual natural language processing. The aim of this paper is to investigate the effects of applying a clustering technique to parallel multilingual texts. It is interesting to look at the differences of the cluster mappings and the tree structures of the clusters. The effect of reducing the set of terms considered in clustering parallel corpora is also studied. After that, a genetic-based algorithm is applied to optimize the weights of terms considered in clustering the texts to classify unseen examples of documents. Specifically, the aim of this work is to introduce the tools necessary for this task and display a set of experimental results and issues which have become apparent.
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      As the number of available Web Service (WS) providers expands, redundancy will become prevalent with many service providers offering the same or similar service. In this paper, we propose a Web service recommendation framework which in this paper is referred to as recommender that analyzes the created generalized WSDL based on the functional and non-functional requirements (i.e. QoS) and then recommends it to selected Web service providers to increase their retrieval probability in the related queries. The proposed framework gives Web services consumers and providers some confidence about the quality of service of the discovered and published Web services.
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      With technology developing fast, the industrial sector will be extensive use of SDL to archive the MAC of advanced wireless technology. In this paper, the data flow model of UWB MAC was studied in-depth, and the MAC layer was designed in system-level using SDL. Further, the key blocks of UWB MAC were designed and programmed. The whole design shortened the development cycle and reduced the difficulty of developing.
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      In new generation of Intelligent Network Control System (NCS), network communications system is brought in the controller and field devices and it enhances connectivity between the controller and the field devices, so it takes up an extremely important position. This paper introduces network control communications systems based on ARM embedded microprocessor LPC2214, including the LPC2214 main circuit design and the external communication circuit, etc. Among them, the main circuit includes the power supply circuit, clock circuit, the system reset circuit, the system memory expanding circuit, the external communication circuit including serial RS-485 and RS-232 communication circuit, Ethernet communication circuit and system development and debugging (JTAG) circuit.
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      Factors such as climate, oxidizing, corroding or ageing during the period of the bridge working, with the long range suffers and a breakdown under effect being loaded, will affect the health situation of a bridge, whose intensity and stiffness may reduce when the time goes, this not only has affected a safe driving, but also may shorten the life time of the bridge. Therefore, it is important to monitor the situation of the bridge. In our bridge monitoring system, we use software bus to build a unified platform for multiple single's bridge monitoring systems. In this way, we lead into loose coupling and distributed supervisory control of multiple bridges of one MAN city. Compared with traditional bridge monitoring systems and present bridge health monitoring systems based on standard network interface, which support remote data acquisition through network too, it also has better monitoring efficiency and more functions. At present, application research in this field is at the starting experimental stage both home and abroad.
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      In this paper, on the basis of the research on the current MIMO system and its detection algorithm, a MIMO signal detection improvement algorithm based on iteration is presented. Based on the existing tree search, the algorithm prioritizes all the sub nodes at the same layer from small to large according to their weights, and after the inter-layer sequence it adopts branch-and-bound algorithm to search. This method can filter out the tree nodes with larger weight, thus the tree search scope is reduced and the search pace is speeded up. Finally, the experimental results show that the algorithm is feasible and effective.
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      Based on J2EE system, this paper adopts a new technology and architecture to construct an easy-to-use customer relationship management system based on B/S structure to meet the demands of small and medium-sized enterprises. Based on the design idea “center on serving customers, improve the ability to integrate and interact with other systems”, this paper puts forward its own design prototype of CRM system, emphatically introduces the overall design of CRM in J2EE environment and introduces the designs of various modules of the system from various aspects. such as database and program flow, etc.
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      As a Embedded real-time operating system released by Microsoft, WinCE, with features of good man-machine interface, high reliability and short development cycle, open and convenience to connect with various equipments fast, makes itself the first choice for operating embedded system. This paper are described the development process and methods of WinCE operating system in the three aspects of the start program, OAL layer and the driver program, focusing on design principles and implementation methods of key drive modules such as the serial port driver and NANDFlash driver, and gives a detailed implementation project.
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      Different scheduling strategies are extensively examined in this paper to compare their performance under a variety of data stream scenarios. These strategies include the Chain, Dynamic Chain and FIFO algorithms. The performance is judged in terms of Quality of Service (QoS) requirements such as tuple latency, memory requirements and system throughput. Scenarios of synthetic and real data streams are considered. The simulation results indicate that no specific algorithm can satisfy all QoS requirements in all scenarios of data streams. Therefore, an Intelligent policy should be adopted in a DSMS to switch between these algorithms according to the critical performance criterion and stream scenarios.
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      In this paper, based on the research on the existing semantic web service discovery, a service discovery program based on semantic matching and service quality filtration is presented, and then this program is implemented. The experimental results show that: under the premise of no affecting on the accuracy of the service discovery, the program can greatly save user time of waiting for service.
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      The paper introduces an intelligent remote control system based on a PSTN (public telephone network), the project mainly based on MT8870 DTMF decoder and Atmel 89S52 MCU. When this system connects to the phone line it monitor the status of the phone line and take the control of phone line when it detects the ringer, after that user may be able to control multiple household electric appliances by DTMF. The system hardware and software are designed based on the telephone standards.
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      The paper introduces a method of reservoir water level detection based on distributed optical fiber temperature sensor (DTS). First it introduces the working principle of DTS and the water-level determination principle by measuring the surface temperature of optical fiber. Then it gives different ways of laying optical fibers and gets the most cost-effective to meet the precision requirement. The result from engineering application shows that the positioning precision can reach to 10mm.
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      With the development of modern science and technology, I2C bus technology has been applied in a wide range for its advantages of simple, powerful, designed to facilitate, particularly it showed its strong vitality in the field of television, and now, it has gradually replaced the traditional television's control methods. This paper introduced the characteristics and principle of I2C bus, and also analyzed the troubleshooting of television system controlled by I2C bus.
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      Along with the flooding of spam, various kinds of spam filtering techniques develop rapidly, but there are still some deficiencies, such as too high false report rate and poor overall filtering effect of filtering system, etc. This paper proposes a kind of two-stage cooperative filtering system combining generalized spam filter with personalized spam filter to realize the personalized filtering of mails, thereby solving the above problems.
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      On the basis of an intensive study of crossover probability and mutation probability of genetic algorithm, this paper puts forward a kind of fuzzy clustering algorithm based on adaptive genetic algorithm and this algorithm overcomes the dependence of fuzzy clustering algorithm on initial clustering center, gives full play to the global optimization ability of genetic algorithm and the local optimization ability of fuzzy clustering algorithm and effectively balances its ability to explore and develop the cluster space, and meanwhile, compared to SGA fuzzy clustering algorithm, it is more prominent in calculating speed and efficiency. Experiments show that AGA fuzzy clustering algorithm is a kind of efficient and feasible clustering algorithm.

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