• Title/Summary/Keyword: computer algorithms

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A Study on Effective Bandwidth Algorithms for Mass Broadcasting Service with Channel Bonding (채널 결합 기반 대용량 방송서비스를 위한 유효 대역폭 추정 알고리즘에 대한 연구)

  • Yong, Ki-Tak;Shin, Hyun-Chul;Lee, Dong-Yul;You, Woong-Sik;Choi, Dong-Joon;Lee, Chae-Woo
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.49 no.3
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    • pp.47-61
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    • 2012
  • parallel transmitting system with channel bonding method have been proposed to transmit mass content such as UHD(Ultra High Definition) in HFC(Hybrid Fiber Coaxial) networks. However, this system may lead to channel resource problem because the system needs many channels to transmit mass content. In this paper, we analyze three effective bandwidth approximation algorithms to use the bonding channel efficiently. These algorithms are the effective bandwidth of Gaussian approximation method algorithm proposed by Guerin, the effective bandwidth based on statistics of video frames proposed by Lee and the effective bandwidth based on Gaussian traffic proposed by Nagarajan. We also evaluate compatibility of algorithms to the mass broadcasting service. OPNET simulator is used to evaluate the performance of the algorithms. For accuracy of simulation, we make mass source from real HD broadcasting stream.

Deterministic Multi-dimensional Task Scheduling Algorithms for Wearable Sensor Devices

  • Won, Jong-Jin;Kang, Cheol-Oh;Kim, Moon-Hyun;Cho, Moon-Haeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.10
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    • pp.3423-3438
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    • 2014
  • In recent years, wearable sensor devices are reshaping the way people live, work, and play. A wearable sensor device is a computer that is subsumed into the personal space of the user, and is always on, and always accessible. Therefore, among the most salient aspects of a wearable sensor device should be a small form factor, long battery lifetime, and real-time characteristics. Thereby, sophisticated applications of a wearable sensor device use real-time operating systems to guarantee real-time deadlines. The deterministic multi-dimensional task scheduling algorithms are implemented on ARC (Actual Remote Control) with relatively limited hardware resources. ARC is a wearable wristwatch-type remote controller; it can also serve as a universal remote control, for various wearable sensor devices. In the proposed algorithms, there is no limit on the maximum number of task priorities, and the memory requirement can be dramatically reduced. Furthermore, regardless of the number of tasks, the complexity of the time and space of the proposed algorithms is O(1). A valuable contribution of this work is to guarantee real-time deadlines for wearable sensor devices.

Partial AUC maximization for essential gene prediction using genetic algorithms

  • Hwang, Kyu-Baek;Ha, Beom-Yong;Ju, Sanghun;Kim, Sangsoo
    • BMB Reports
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    • v.46 no.1
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    • pp.41-46
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    • 2013
  • Identifying genes indispensable for an organism's life and their characteristics is one of the central questions in current biological research, and hence it would be helpful to develop computational approaches towards the prediction of essential genes. The performance of a predictor is usually measured by the area under the receiver operating characteristic curve (AUC). We propose a novel method by implementing genetic algorithms to maximize the partial AUC that is restricted to a specific interval of lower false positive rate (FPR), the region relevant to follow-up experimental validation. Our predictor uses various features based on sequence information, protein-protein interaction network topology, and gene expression profiles. A feature selection wrapper was developed to alleviate the over-fitting problem and to weigh each feature's relevance to prediction. We evaluated our method using the proteome of budding yeast. Our implementation of genetic algorithms maximizing the partial AUC below 0.05 or 0.10 of FPR outperformed other popular classification methods.

A Hybrid Approach on Matrix Multiplication

  • Tolentino Maribel;Kim Myung-Kyu;Chae Soo-Hoan
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06a
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    • pp.400-402
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    • 2006
  • Matrix multiplication is an important problem in linear algebra. its main significance for combinatorial algorithms is its equivalence to a variety of other problems, such as transitive closure and reduction, solving linear systems, and matrix inversion. Thus the development of high-performance matrix multiplication implies faster algorithms for all of these problems. In this paper. we present a quantitative comparison of the theoretical and empirical performance of key matrix multiplication algorithms and use our analysis to develop a faster algorithm. We propose a Hybrid approach on Winograd's and Strassen's algorithms that improves the performance and discuss the performance of the hybrid Winograd-Strassen algorithm. Since Strassen's algorithm is based on a $2{\times}2$ matrix multiplication it makes the implementation very slow for larger matrix because of its recursive nature. Though we cannot get the theoretical threshold value of Strassen's algorithm, so we determine the threshold to optimize the use of Strassen's algorithm in nodes through various experiments and provided a summary shown in a table and graphs.

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Gate Management System by Face Recognition using Smart Phone (스마트폰을 이용한 얼굴인식 출입관리 시스템)

  • Kwon, Ki-Hyeon;Lee, Hyung-Bong
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.11
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    • pp.9-15
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    • 2011
  • In this paper, we design and implement of gate management system by face recognition using smart phone. We investigate various algorithms for face recognition on smart phones. First step in any face recognition system is face detection. We investigated algorithms like color segmentation, template matching etc. for face detection, and Eigen & Fisher face for face recognition. The algorithms have been first profiled in MATLAB and then implemented on the Android phone. While implementing the algorithms, we made a tradeoff between accuracy and computational complexity of the algorithm mainly because we are implementing the face recognition system on a smart phone with limited hardware capabilities.

A Design of Controller for 4-Wheel 2-D.O.F. Mobile Robot Using Fuzzy-Genetic algorithms

  • Kim, Sangwon;Kim, Sunghoe;Sunho Cho;chongkug
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.607-612
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    • 1998
  • In this paper, a controller using fuzzy-genetic algorithms is proposed for pat-tracking of WMR. A fuzzy controller is implemented so as to adjust appropriate crossover rate and mutation rate. A genetic algorithms is also implemented to have adaptive adjustment of control gain during optimizing process. To check effectiveness of this algorithms, computer simulation is applied.

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Notes on Conventional Neuro-Fuzzy Learning Algorithms

  • Shi, Yan;Mizumoto, Masaharu
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.391-394
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    • 1998
  • In this paper, we try to analyze two kinds of conventional neuro-fuzzy learning algorithms, which are widely used in recent fuzzy applications for tuning fuzzy rules, and give a summarization of their properties. Some of these properties show that uses of the conventional neuro-fuzzy learning algorithms are sometimes difficult or inconvenient for constructing an optimal fuzzy system model in practical fuzzy applications.

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THE OPTIMAL SEQUENTIAL AND PARALLEL ALGORITHMS TO COMPUTE ALL HINGE VERTICES ON INTERVAL GRAPHS

  • Bera, Debashis;Pal, Madhumangal;Pal, Tapan K.
    • Journal of applied mathematics & informatics
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    • v.8 no.2
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    • pp.387-401
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    • 2001
  • If the distance between two vertices becomes longer after the removal of a vertex u, then u is called a hinge vertex. In this paper, a linear time sequential algorithm is presented to find all hinge vertices of an interval graph. Also, a parallel algorithm is presented which takes O(n/P + log n) time using P processors on an EREW PRAM.

Parallel Computing For Computational Geometry (컴퓨터 기하학을 위한 병렬계산)

  • O, Seung-Jun
    • Electronics and Telecommunications Trends
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    • v.4 no.1
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    • pp.93-117
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    • 1989
  • Computational Geometry is concerned with the design and analysis of computational algorithms which solve geometry problems. Geometry problems have a large number of applications areas such as pattern recognition, image processing, computer graphics, VLSI design and statistics since they involve inherently geometric problems for which efficient algorithms have to be developed. Several parallel algorithms, based on various parallel computation models, have been proposed for solving geometric problems. We review the current status of the parallel algorithms in computational geometry.

Analysis of the LMS Algorithm Family for Uncorelated Gaussian Data

  • Nam, Seung-Hyon
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.3E
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    • pp.19-26
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    • 1996
  • In this paper, convergence properties of the LMS, LMF, and LVCMS algorithms are investigated under the assumption of the uncorrelated Gaussian input data. By treating these algorithms as special cases of more general algorithm family, unified results on these algorithms are obtained. First the upper bound on the step size parameter is obtained. Second, an expression for misadjustment is obtained. These theoretical results confirm earlier LMS works. Further, the results explain why the LMS and LVCMS algorithms are experiencing difficulties with plant noise having heavier tailed densities. Simulation results agree with theoretical expectation closely for various plant noise statistics.

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