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Computer Engineering and Technology, 2009. ICCET '09. International Conference on

Date 22-24 Jan. 2009

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Displaying Results 1 - 25 of 131
  • [Front cover - Vol 2]

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

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

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

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

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

    Page(s): xiv - xv
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  • ICCET 2009 Committee Members - Volume 2

    Page(s): xvi
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  • ICCET 2009 Organizing Committees - Volume 2

    Page(s): xvii
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  • Improved Error Metric of Terrain Rendering for Flying High Over the Terrain

    Page(s): 3 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (539 KB) |  | HTML iconHTML  

    Error metric is the key problem for generating level of detail of terrain surface, which affects the deviation between the number of triangles and triangular mesh. After analyzing various present methods of calculating error metric, we present an improved algorithm based on roughness. This paper takes the roughness which expresses relief amplitude to be an factor, by which we calculate the error metric, form the sphere of error according to the position of viewpoint, choose appropriate LOD model for each frame. The improved error metrics is applied to the high-altitude terrain when flying high over the terrain. The experiment results show that our algorithm reduces the number of required triangles in terrain rendering, and ensures correct rendering of the entire outline of high steep terrain. View full abstract»

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  • Adaptive Step-size and Block-size FBLMS Algorithm

    Page(s): 8 - 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (302 KB) |  | HTML iconHTML  

    In this paper, we present a novel adaptive step-size and block-size frequency-domain block least mean square (ASB-FBLMS) algorithm. The convergence speed and the steady stage error are two conflicting factors in the traditional frequency-domain block least mean square (FBLMS) algorithm. While our algorithm optimally increase the convergence speed while maintaining or reducing the steady stage error by using an adaptive variable step-size and an adaptive variable block-size, it can also reduce the computational complexity effectively in a high transmission rate by utilizing an adaptive variable block-size. Through the simulation on the Matlab platform, the results demonstrated that our algorithm outperformed FBLMS algorithms currently reported in the literature in terms of faster convergence, smaller steady stage error and lower computational complexity. View full abstract»

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  • A Preliminary Workload Analysis of SPECjvm2008

    Page(s): 13 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (148 KB) |  | HTML iconHTML  

    SPECjvm2008 is a new benchmark program suite for measuring client-side Java runtime environment. It replaces JVM98, which has been used for the same purpose for more than ten years. It consists of 38 benchmark programs grouped into eleven categories and has wide variety of workloads from computation-intensive kernels to XML file processors. In this paper, we present the results of running SPEC-jvm2008 on three machines that have CPUs with the same microarchitecture and different cache sizes and clock speeds. The result of measurements include instruction and data cache reference and miss rates, and the effect of the multi-threading. We relate these workload parameters to the SPECjvm2008 performance metrics. Roughly speaking, an L2 cache of 1MB sufficiently lows the cache miss rates of SPECjvm2008 and compared to the single-core, 1.5 to 2 times speed-ups are achieved by dual-core executions. View full abstract»

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  • Objective Quality Metric Based on Perception for Video

    Page(s): 20 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (309 KB) |  | HTML iconHTML  

    Objective quality assessment plays a very important role in the video applications, as they promise the means to evaluate the performance of acquisition, display, coding and communication systems. Objective video quality assessment still has a long way to go before it reaches the level of success. In this paper, we propose novel quality metrics for video sequences. These metrics are capable of capturing spatial distortions in video sequences, in addition to temporal artifacts. And they can quantify the spatial distortion and differentiate the type of distortion. Furthermore the metrics correlate well with the subjective quality measures because perception distortions of human have been taken into consideration. Experimental results show that our perceptual quality metric performs better than the existing methods. View full abstract»

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  • Study on the Key Technologies of Intelligent Coal Enterprises Integrated Statistical System

    Page(s): 24 - 27
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (262 KB) |  | HTML iconHTML  

    According to the actual situation in the integrated statistical work of coal enterprise in our country now, we determined using the exploitation method of combining SAD and object oriented by analyzing the system's function characteristic, has established the composite structure model which C/S and B/S unify. The system has realized many essential functions such as the technical specification dynamic management, the integrated information intelligence analysis, the report form continual calculation and the printing, the data balancing and so on. View full abstract»

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  • Particle Swarm Optimization for Run-Time Task Decomposition and Scheduling in Evolvable MPSoC

    Page(s): 28 - 32
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (415 KB) |  | HTML iconHTML  

    Decomposition and scheduling are two major challenges in hardware and software developments of multiprocessor systems. The introduced EvoMP (Evolvable MultiProcessor) is a novel NoC-based homogeneous MPSoC system that performs decomposition and scheduling using evolutionary algorithms at run-time. A hardware genetic core was used in first version of this platform to perform these two tasks. This core tries to find an efficient solution for decomposition and scheduling of the target application among available computational resources. This paper presents the new version of this system in which a hardware particle swarm optimization (PSO) core is exploited to perform evolutionary decomposition and scheduling. The principle of operation and architecture of the EvoMP platform and the PSO core is briefly explained in this paper. The simulation and synthesis results of this PSO-based EvoMP is also presented and compared with prior genetic-base approach. View full abstract»

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  • High Performance Simulation Platform for Switching and Scheduling

    Page(s): 33 - 38
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (423 KB) |  | HTML iconHTML  

    Simulation is a significant way for performancespsila evaluations in switching and scheduling. The simulation software currently being existed has somewhat limitations in inheritability and extensibility. Based on current switching fabrics, by employing system level design method and object oriented technology, we designed and implemented a simulation platform called SPES for switching and scheduling. Input queuing, output queuing, combined input output queuing and combined input cross-point queuing and corresponding scheduling policies are integrated. Inheritability and extensibility attributes are obtained by designing traffic sources, switching fabrics and scheduling policies separately, and it can support multi-fabric, variable size packets and quality of service modelpsilas simulations. By configuring the platform through a uniform view, users can easily fulfill their concrete simulation environment. View full abstract»

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  • Design and Realization of Embedded Web Gateway Server

    Page(s): 39 - 42
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (308 KB) |  | HTML iconHTML  

    Information and digital age presents tremendous opportunity to the development of embedded products and shows the embedded market a prosperous prospect, Web server embedded in equipment can provide uniform operation and control interface based on browser mode for any legal user accessing to its network, browser has become the front control board of equipment and a hot spot for development in recent years. This paper introduces in detail the transplantation and system software design of embedded Web server, methods of constructing Boa Web server under a constructed ARM+muCLinux development platform and design and realization process of remote monitoring application program. View full abstract»

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  • Motorcycle and License Plate Detection Using Fixed-Size Vertical Projection and Multi-Part Mean Analysis

    Page(s): 43 - 47
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (873 KB) |  | HTML iconHTML  

    This paper proposed methods for motorcycle and license plate detection using fixed-size vertical projection and multi-part mean analysis. The method consisted of two parts: a motorcycle detection and a license plate detection. Fixed-size vertical projection and neural network were used in the motorcycle detection process. Vertical and horizontal scanning was used to extract features for the neural network. Later, a rough filter and a thorough filter were used to approximately locate and finally confirm a license plate, respectively. These methods were tested on both motorcycles with license plates and motorcycles without license plates. The experimental results gave accuracy of 93.20% for motorcycle detection, 93.33% for motorcycles with license plates, and 87.23% for motorcycles without license plates. View full abstract»

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  • Design of Non-Critical Path Resource Distributor for SMT Processors

    Page(s): 48 - 52
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (301 KB) |  | HTML iconHTML  

    The performance in simultaneous multithreading (SMT) processors is mainly determined by the distribution of the common resources among the threads. However, resource distribution methods often take cycles to calculate a resource allocation solution. Implementing a many-cycles resource distributor in the critical pipeline path will result in an innegligible impact on SMT processor performance. This work proposes a design of non-critical path resource distributor (NCPRD) for SMT processors, which separates the resource distribution from the critical pipeline path to avoid the clock wastage caused by the computation on the allocation solution. Our limit case study shows that, NCPRD benefits from its asynchronous work mode under both throughput and fairness metric in all type workloads but the memory-intensive workloads, and obtains more gains over the critical-path-involved resource distributor when the computation on the allocation solution spends more cycles. View full abstract»

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  • Prediction of MPEG Traffic Data Using a Bilinear Recurrent Neural Network with Adaptive Training

    Page(s): 53 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (278 KB) |  | HTML iconHTML  

    A time-series prediction model using a Bilinear Recurrent Neural Network (BRNN) is proposed in this paper. The BRNN model used in this paper is the Multiresolution architecture with an adaptive training mode. The Multiresolution Bilinear Recurrent Neural Network (MBRNN) is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The proposed MBRNN-based predictor is applied to real-time MPEG video traffic data. The performance of the proposed MBRNN-based predictor is evaluated and compared with the conventional MultiLayer Perceptron Type Neural Network (MLPNN)-based predictor and BRNN-based predictor. When compared with the MLPNN-based predictor and the BRNN-based predictor, the proposed MBRNN-based predictor shows significant improvement in terms of the Normalized Mean Square Error (NMSE) criterion. View full abstract»

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  • An Image Coding Algorithm Based on Nonredundant Contourlet Transform and Visual Characteristics

    Page(s): 58 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (468 KB) |  | HTML iconHTML  

    This paper presents an image coding technique based on contourlet transform. The redundancy of the contourlet transform is eliminated by switching the LP decomposition step to separable wavelet transform. The transform is then optimized through a wavelet coefficient weighting process in order to enhance the visual quality in the image domain, and with that the directional filter bank(DFB) are employed to high frequency wavelet subbands. At last, all the resulted subbands are efficiently coded with EBCOT. At the same bit rates, a gain of up to 0.3~0.6 dB over JPEG2000 has been observed for standard images with directional features. View full abstract»

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  • A Dynamic Approach for Discovering Maximal Frequent Itemsets

    Page(s): 62 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (237 KB) |  | HTML iconHTML  

    We present a novel method, which reads the database at regular intervals as in dynamic itemsets counting technique and creates a tree called dynamic itemset Tree containing items which may be frequent, potentially frequent and infrequent. This algorithm requires less time to discover all maximal frequent itemsets since it involves a method for reducing the size of the database. This method prunes the transactions and items of the transactions which are not of our interest after every scan of the database. Also, this method is independent of the order of the items. View full abstract»

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  • Deriving User Interfaces from UML Models and Object -Z

    Page(s): 67 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (410 KB) |  | HTML iconHTML  

    In this paper, we discuss a method for generating a set of user interfaces from business model and use case model. A set of rules that derives "CRUD" UI forms from business model is given. The method uses object-Z formal language to add preciseness and semantic richness both to the business and use case UML models in order to enhance UI usability. The derived UI prototype allows the early validation of requirements, and can be used as a basis for subsequent developments. View full abstract»

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  • Behavioral Fault Model for Neural Networks

    Page(s): 71 - 75
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (316 KB) |  | HTML iconHTML  

    The term neural network (NN) originally referred to a network of interconnected neurons which are basic building blocks of the nervous system. Fault tolerance is known as an inherent feature of artificial neural networks (ANNs). Wide attention has been given to the problem of fault-tolerance in VLSI implementation domain and not enough attention has been paid to intrinsic capacity of survival to faults. In this work we focus on the impact of faults on the neural computation in order to show neural paradigms cannot be considered intrinsically fault-tolerant. A high abstraction level (corresponding to the neural graph) error model is introduced in this paper. We propose fault model and present an analysis of the usability of our method for fault masking. Simulation results show with this new fault model, the fault with less significant contribution is masked in output. View full abstract»

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  • Embedded Smart Camera Performance Analysis

    Page(s): 79 - 83
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (521 KB) |  | HTML iconHTML  

    Increasingly powerful integrated circuits are making an entire range of new applications possible. Recent technological advances are enabling a new generation of smart cameras that represent a quantum leap in sophistication. While todaypsilas digital cameras capture images, smart camera capture high-level descriptions of the scene and analyze what they see. A smart camera combines video sensing, high-level video processing and communication within a single embedded device. Smart cameras not only capture images, they further perform high-level image processing on-board, and transfer the data via network. In this project, embedded smart camera utilizing the use of single board computer (SBC) and GNU/Linux is presented. This paper presents the performance analysis on processing speed and CPU utilization for embedded smart camera using three different computer platforms. Two Single Board Computers from Technologic System, TS-5500 and TS-7200 are being introduced in this paper. The hardware and software design as well as the experimental results are also presented. View full abstract»

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  • Face Recognition Combining 3-channel Filter Bank and 2DLDA

    Page(s): 84 - 87
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (424 KB) |  | HTML iconHTML  

    In this paper, a novel 3-channel orthogonal filter bank was proposed at first, and then an efficient face recognition method combining the filter bank and 2DLDA (two-dimensional linear discriminant analysis) was presented. The framework of the proposed method consists of two steps: First, each face image was decomposed into nine sub images by using the 3-channel filter bank, and then 2DLDA was used to extract the features for face classification from the sub images. Better performance of the proposed method is confirmed by the Yale face database. View full abstract»

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