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Computers, Networks, Systems and Industrial Engineering (CNSI), 2011 First ACIS/JNU International Conference on

Date 23-25 May 2011

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Displaying Results 1 - 25 of 115
  • [Front cover]

    Page(s): C1
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  • [Title page i]

    Page(s): i
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  • [Title page iii]

    Page(s): iii
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  • [Copyright notice]

    Page(s): iv
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  • Table of contents

    Page(s): v - xiii
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  • Message from the General Chair

    Page(s): xiv
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  • Message from the Conference Chairs

    Page(s): xv
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  • Message from the Program Chairs

    Page(s): xvi
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  • Program Committee

    Page(s): xvii
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  • List of Reviewers

    Page(s): xviii - xx
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  • Keynote speakers

    Page(s): xxi - xxii
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (135 KB)  

    These keynote speeches discuss the following: A Vision of Smarter Cities: Challenges and Opportunities; and Computational Complex Material Design. View full abstract»

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  • Conference Supporters

    Page(s): xxiii
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  • An Efficient Key Management for Secure Multicast in Sensor-Cloud

    Page(s): 3 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (421 KB) |  | HTML iconHTML  

    Nowadays, in Publish/Subscribe system, the number of subscriptions from customers can be large, the events happening in such a system are more frequent and the notification load is heavy. Combining with cloud computing that is becoming increasingly popular for scalability and availability it promises, called Sensor-Cloud, there are many approaches that improve data delivery issues in such scenario efficiently. However, there are few approaches that consider secure data delivery while security plays an important role in Sensor-Cloud. In this paper, we propose an efficient secure multicast approach by combining Group-key and Time-key (CoGKTK) to minimize number of updated key for such dynamic scenario in Sensor-Cloud. We analytically show the performance and scalability benefits of our approach over data delivery infrastructure in Sensor-Cloud. View full abstract»

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  • Robust Facial Expression Recognition Against Illumination Variation Appeared in Mobile Environment

    Page(s): 10 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1046 KB) |  | HTML iconHTML  

    Smart phones such as the iPhone and Android phones have become increasingly popular in the recent market. Diverse applications can be implemented on smart phones since their performance has been improved. One of the promising application areas would be reading the emotional state of a human being and using it for communicating with the computer. In this paper, we present a robust facial expression system implemented on a smart phone, which has employed the Active Appearance Model (AAM). To fix degradation of the AAM's performance against illumination variation, a Difference Of Gaussian (DOG) kernel was used before the AAM stage. A neural network, which had been trained with the Cohn-Kanade Database, was used for classification of facial expression states. Results and future work are described. View full abstract»

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  • A Quantitative Analysis-Based Algorithm for Optimal Data Signature Construction of Traffic Data Sets

    Page(s): 14 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (823 KB) |  | HTML iconHTML  

    In this paper, a new set of data signatures is derived to obtain better Vector Fusion 2D visualizations of a time series and periodic nD traffic data set as compared with previous work. The latter had used the entire Power Spectrum components for visualization purposes to produce 2D representations of each subset of the data. With the feasibility of obtaining a smaller representation of the data set in obtaining better cluster models compared to using the original n-dimensions, we now explore this feasibility for visualization purposes. We propose an algorithm that determines, in quantitative terms, how good the selected set of signatures represents the nD data set in 2 dimensions. We use the Vector Fusion visualization algorithm in transforming each signature from its n dimensions into 2 dimensions. An improved set of qualitative criterion is drawn to measure the goodness of the 2D data signature-based visual representation of the original nD data set. Finally, we provide empirical testing and discuss the results. View full abstract»

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  • Risk Factors Associated with Methamphetamine Production: A Spatial Predictive Modeling Approach

    Page(s): 20 - 25
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (589 KB) |  | HTML iconHTML  

    The estimated national cost due to methamphetamine (meth) abuse is 23.4 billion each year. Current law enforcement of dealing with the meth abuse is by 'fire fighting' strategy, that is, to direct the enforcement to the location after the problem occurs. A better strategy is to develop a proactive predictive model based strategy. This study attempts to develop a model to predict the risk of meth production for the seven most severe states in USA. Modern data mining supervised modeling techniques, including Decision Tree, Generalized Logistic Regression and Neural Network are applied to model the risk level of meth at the block group geographical area. The final best model found is a neural network model. The prediction accuracy is found at 87.5%. Fourteen important inputs are identified, which are further classified into three factor groups: culture, socio-economic and geographical factor groups. It is found that the culture factors, which reflects the specific behavioral models of people, are the most important for contributing to the risk of meth, and that the meth production activity is highly associated with crimes. View full abstract»

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  • Semantic Context Enrichment and Shifting Based on Multi-dimensional Association

    Page(s): 26 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (527 KB) |  | HTML iconHTML  

    Contexts are appreciated as localized background knowledge for operations in knowledge management and applications. However, current context representations ignore the characters that contexts have different size, have multi-layer contextual dimensions, and contain both metadata and instances. In order to improve context representation, this paper proposes a novel context representation approach based on multi-dimensional association, and further proposes context enrichment and shifting approaches for context operations. This paper first defines multi-dimensional association in knowledge and association-based context in which core Entity is a set for key concepts, relations and properties, and then introduces three context enrichment operations including context supplement, context expansion, and context contraction, and introduces three context shifting operations including lifting and lowering, core Entity changing, and merging. The representation can be used in various knowledge application scenarios. The context enrichment and shifting operations can ensure the consistency of context and value the connections between contextual entities in association. View full abstract»

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  • An Architecture of Real-Time, Historical Database System for Industrial Process Control and Monitoring

    Page(s): 31 - 34
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (433 KB) |  | HTML iconHTML  

    In process control system, Process database is a main component for real-time, historical data processing. Recently, the concern on process database is increasing. From now, With process database, Historian or Memory DB with Relational Data model are mainly used. But, each has both advantages and disadvantages. Especially, on performance and flexibility, they have to complement each other. In this paper, we analyze past process databases in detail, and propose an architecture of new process database with both flexibility and performance. View full abstract»

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  • Forest Fire Smoke Detection in Video Based on Digital Image Processing Approach with Static and Dynamic Characteristic Analysis

    Page(s): 35 - 39
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (444 KB) |  | HTML iconHTML  

    In this paper, propose a method for forest fire smoke detection in video based on digital image processing approach with static and dynamic characteristic analysis. The proposed method is composed of four steps. The first step is to detect the area of change in the current input frame against the background image. Second step is to locate regions of interest (ROIs) by connected component algorithm, calculate area of ROI by convexhull algorithm and segment the area of change from image. Third step is to analysis and calculate static and dynamic characteristic. Finally, we decide whether the objects that have changed in that picture is the smoke or not. The experimental result with simulated forest fire smoke and the moving object video show that our method effectively and accuracy detect fire smoke. View full abstract»

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  • Applying Enhanced Confusion Line Color Transform Using Color Segmentation for Mobile Applications

    Page(s): 40 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1473 KB) |  | HTML iconHTML  

    This paper proposes separating confusion line method in Lab color space using color segmentation for protanopia and deuteranopia. It uses hue information, we segment regions that grouped by neighborhood pixels with similar color information. For this, we use region growing method, so we pick seed points that could be selected pixels, which is peaking at points in after applying the low pass filter in the histogram. Furthermore, for CVD(Color Vision Deficiency)'s making confusion line Map, we made 512 virtual boxes in RGB color space, so that we can classify boxes in same confusion line easily. After this we check whether the regions place in same confusion line or not, and it performs the color transformation in Lab color space to make all of neighboring regions be placed in diverse confusion line so that we can give the best effect of color classification for CVD. Furthermore, we apply this algorithm in the smart phone so that we provide our algorithm to protanopia and deuteranopia easily. View full abstract»

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  • Application of ZnO Nanowires for the Photodegradation of Resazurin

    Page(s): 45 - 48
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (482 KB) |  | HTML iconHTML  

    ZnO nanowires were synthesized via a vapor transport synthesis route. These nanowires were characterized by X-ray diffraction (XRD), field scanning electron microscopy (FESEM) and UV -- vis spectroscopy. The results of XRD revealed that monophasic nature of ZnO. The observation of FESEM images showed that the obtained ZnO nanowires were homogenous with average diameter of 30 nm. The photocatalytic activity of ZnO nanowire samples was studied by the degradation of Resazurin. The observed results showed that ZnO nanowires had a remarkable effect on the degradation of Resazurin under UV light. These results prove the potential use of ZnO nanowires for industrial waste water treatment. View full abstract»

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  • Breast Image Registration of 3D Suface-Point Using Iterative Closet Point (ICP) Method

    Page(s): 49 - 52
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB) |  | HTML iconHTML  

    Breast cancer is a cancer which occurs commonly for women of the entire world. In this thesis, in order to find cancer by using image conformation technology, computer tomography (CT), positron emission tomography (PET) and magnetic resonance imaging (MRI) images were used. For conforming the images of each the different modalities, surface points, which become common feature of MRI and CT images were extracted and they were registered in 3D by using iterative closet point. (ICP). View full abstract»

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  • Real-Time Face-Detection Engine for Robustness to Variable Illumination and Rotated Faces

    Page(s): 53 - 58
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3395 KB) |  | HTML iconHTML  

    In this paper, we proposes a novel hardware architecture and FPGA implementation method of high performance real-time face-detection engine for robustness to variable illumination and rotation. The proposed face detection algorithm improved its performance by using MCT (Modified Census Transform), rotation transformation and AdaBoost learning algorithm. For implementation, we used a QVGA class camera, LCD display, and Virtex5 LX330 FPGA made by Xilinx Corporation. The verification results showed that it is possible to detect at least 32 faces in a wide variety of sizes at a maximum speed of 43 frames per second in real time. This finding can be applied to artificial intelligence robots for human recognition, conventional security systems for identity certification, and cutting-edge digital cameras using image processing techniques. View full abstract»

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  • Analyzing Risk Dependencies on RFID-driven Global Logistics Processes

    Page(s): 59 - 64
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (459 KB) |  | HTML iconHTML  

    In this paper, we try to formally analyze risk dependencies on a global logistics process that is made up of a set of RFID-driven biz-steps2. In enacting a global logistics process, it is very important to control and trace each bizstep's execution as well as to visualize its status. Moreover, for the sake of improving QoS (the quality of services), it ought to be crucial for the system to provide an autonomous error-detection functionality on its running exceptions and very safe self-recovery mechanisms, as well, for the exceptional and risky situations. In resolving the QoS issue, the essential technologies might be RFID and BPM/workflow technologies; workflow is for representing a global logistics process in a natural, and RFID is for implementing each biz-step's application program tagging the logistics information. Also, the essential theory of the self-recovery mechanisms must be on the roll-back mechanism that determines up to where the roll-back operations have to be applied among the previous performed biz-steps on the corresponding global logistics process. As an essential theory of implementing a reasonable roll-back mechanism, the paper particularly formalizes a risk dependency analysis algorithm that is able to produce a set of risk dependency knowledge existing among biz-steps of a RFID-driven global logistics process, and that is eventually used for realizing the self-recovery mechanisms. View full abstract»

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  • Development of Integrated Insider Attack Detection System Using Intelligent Packet Filtering

    Page(s): 65 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2212 KB) |  | HTML iconHTML  

    External threats to the cyber-infrastructure of an organization are constantly evolving. The greatest threat, however, is the problem of insiders who misuse their privileges for malicious purposes. These days, private information has often been leaked because of increased IT outsourcing, administrator's moral problems, multiple root accounts, and root accounts shared by many users, etc. Accordingly, organizations have employed insider attack detection systems to protect their critical information from break-ins by insider attack and hackers. In this paper, we developed an integrated insider attack detection system which was composed of a minimized hardware appliance and a software package using TCP tunneling. It could be configured as a gateway between users and the legacy servers in order to protect the important internal information in the legacy servers. And it could control the access of users on the servers, who were connected by Telnet or FTP, and would block the theft of confidential information using intelligent packet filtering. Also, it should provide an audit using the packet logging on the legacy servers. View full abstract»

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