• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.9-10
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• 2011

임베디드 시스템에서 저전력 공급, 칩사이즈 축소, 낮은 노이즈 마진 등 설계기법이 날로 향상됨에 따라 소프트에러가 기하급수적으로 늘어나고 있다. 본 논문에서는 VLIW 아키텍처에서 치명적인 오류를 일으키는 이런 소프트에러들을 검출하고 수정하는 기법을 제안하고자 한다.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.319-326
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• 2016

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. In this paper, we propose a new Kinect camera-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The moving-pigs are labeled as regions of interest. 3) A contour method is proposed and applied to solve the touching-pigs problem in the Kinect-depth image. The experimental results with the depth videos obtained from a pig farm located in Sejong illustrate the efficiency of the proposed method.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.89-100
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• 2000

Recently, studies on the mobile computing environments that enable mobile hosts to move while retaining its network connection are in progress. In these mobile computing environments, one of the necessary components is the distributed file system supporting mobile hosts, and there are several issues for the design and implementation of the shared file system. Among these issues, there are problems caused by network traffic on limited bandwidth of wireless media. Also, there are consistency maintenance issues that are caused by update-conflicts on the shared files in the distributed file system. In this paper, we propose TWB(Trickle Write-Back) scheme that utilizes weak connectivity for cache management of mobile clients. This scheme focuses on saving bandwidth, reducing waste of disk space, and reducing risks caused by disconnection. For such goals, this scheme lets mobile clients write back intermediate states periodically or on demand while delaying unnecessary write-backs. Meanwhile, this scheme is based on the existing distributed file system architecture and provides transparency.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.759-764
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• 2005

In this paper we describe a face recognition using EBGM(Elastic Bunch Graph Matching) method. Usally, the PCA and LDA based face recognition method with the low-dimensional subspace representation use holistic image of faces, but this study uses local features such as a set of convolution coefficients for Gabor kernels of different orientations and frequencies at fiducial points including the eyes, nose and mouth. At pre-recognition step, all images are represented with same size face graphs and they are used to recognize a face comparing with each similarity for all images. The proposed algorithm has less computation time due to simplified face graph than conventional EBGM method and the fuzzy matching method for calculating the similarity of face graphs renders more face recognition results.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.23-30
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• 2006

A recommender system for E-commerce site receives information from customers about which products they are interested in, and recommends products that are likely to fit their needs. In this paper, we investigate several methods for large-scale product purchase data for the purpose of producing useful recommendations to customers. We apply the traditional data mining techniques of cluster analysis and collaborative filtering(CF), and CF with reduction of product-dimensionality by use of latent semantic indexing(LSI). If reduced product-dimensionality obtained from LSI shows a similar latent trend of customers for buying products to that based on original customer-product purchase data, we expect less computational effort for obtaining the nearest-neighbor for target customer may improve the efficiency of recommendation performance. From simulation experiments on synthetic customer-product purchase data, CF-based method with reduction of product-dimensionality presents a better performance than the traditional CF methods with respect to the recall, precision and F1 measure. In general, the recommendation quality increases as the size of the neighborhood increases. However, our simulation results shows that, after a certain point, the improvement gain diminish. Also we find, as a number of products of recommendation increases, the precision becomes worse, but the improvement gain of recall is relatively small after a certain point. We consider these informations may be useful in applying recommender system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.39-40
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• 2015

방송망의 효율적인 관리 및 운영을 위해 다양한 측정 및 모니터링 방법이 제안되고 있다. 특히 디지털 방송신호의 특징상 송신 장비의 열화가 진행되더라도 수신 장비의 채널 복호 및 오류정정, 다양한 형태의 페이딩(fading) 간섭으로 인해 이를 정확히 파악하기 어렵다. 또한 운영 인력의 축소, 관리 대상 매체의 증가 등 방송사의 인력관리의 문제등도 감안할 때, 다양한 매체의 종합적인 품질 관리를 위해서는 집약적이고 시간 지속적인 측정방법의 도입이 필요하다. 본 논문은 이러한 다매체 다채널 방송 환경에서 효율적인 측정 및 모니터링을 위해 집적화된 형태의 방송 모니터링 시스템의 구현 방법을 제안한다. 제안하는 시스템은 다양한 매체의 튜너를 하나의 제어기에 연결하고 이를 스케줄링 기법에 의해 순차적으로 측정한 후 방송 품질의 핵심 파라미터 측정결과를 네트워크를 통해 원격 서버로 전송한다. 이를 통해 단기 및 장기모니터링을 실시할 수 있으며, 일간, 월간, 연간 신호의 변화를 종합적으로 측정 및 모니터링 할 수 있어 시간 및 계절에 따른 신호 품질의 변화 및 순간적인 방송 신호의 변화 등을 감지할 수 있는 새로운 형태의 방송 품질 모니터링 시스템이다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.91-96
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• 2015

In this study, we introduce robust face recognition system with illumination variation realized with the aid of CT preprocessing method. As preprocessing algorithm, Census Transform(CT) algorithm is used to extract locally facial features under unilluminated condition. The dimension reduction of the preprocessed data is carried out by using $(2D)^2$PCA which is the extended type of PCA. Feature data extracted through dimension algorithm is used as the inputs of proposed radial basis function neural networks. The hidden layer of the radial basis function neural networks(RBFNN) is built up by fuzzy c-means(FCM) clustering algorithm and the connection weights of the networks are described as the coefficients of linear polynomial function. The essential design parameters (including the number of inputs and fuzzification coefficient) of the proposed networks are optimized by means of artificial bee colony(ABC) algorithm. This study is experimented with both Yale Face database B and CMU PIE database to evaluate the performance of the proposed system.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.303-312
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• 2004

In this paper, we propose a methodology solving the problem of the hardware-software partitioning in reconfigurable systems using a Y-chart design space exploration and implement a simulator according to the methodology. The methodology generates a mapping set between tasks and hardware elements using the hardware element model and the application model. We evaluate the throughput by simulating cases in each mapping set. With the throughput evaluation result, we can select the mapping case with the highest throughput. We also propose an heuristic improving the simulation time by reducing the mapping set on the basis of the relationship between workload and parallelism. Simulation results show that we can reduce the size of mapping set which poses difficulties on hardware-software partitioning by up to 80%.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.17-27
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• 2022

In this study, a deep learning-based network that can predict the aerodynamic characteristics of airfoils was designed, and the feasibility of the proposed network was confirmed by applying aerodynamic data generated by Xfoil. The prediction of aerodynamic characteristics according to the variation of airfoil thickness was performed. Considering the angle of attack, the coordinate data of an airfoil is converted into image data using signed distance function. Additionally, the distribution of the pressure coefficient on airfoil is expressed as reduced data via proper orthogonal decomposition, and it was used as the output of the proposed network. The test data were constructed to evaluate the interpolation and extrapolation performance of the proposed network. As a result, the coefficients of determination of the lift coefficient and moment coefficient were confirmed, and it was found that the proposed network shows benign performance for the interpolation test data, when compared to that of the extrapolation test data.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.429-439
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• 2006

A desktop grid, which is a computing grid composed of idle computing resources in a large network of desktop computers, is a promising platform for compute-intensive distributed computing applications. However, due to reliability and unpredictability of computing resources, effective scheduling of parallel computing applications on such a platform is a difficult problem. This paper proposes a new scheduling method aimed at reducing the total execution time of a parallel application on a desktop grid. The proposed method is based on utilizing the histories of execution behavior of individual computing nodes in the scheduling algorithm. In order to test out the feasibility of this idea, execution trace data were collected from a set of 40 desktop workstations over a period of seven weeks. Then, based on this data, the execution of several representative parallel applications were simulated using trace-driven simulation. The simulation results showed that the proposed method improves the execution time of the target applications significantly when compared to previous desktop grid scheduling methods. In addition, there were fewer instances of application suspension and failure.