• Title/Summary/Keyword: and Parallel Processing

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Pedestrians Action Interpretation based on CUDA for Traffic Signal Control (교통신호제어를 위한 CUDA기반 보행자 행동판단)

  • Lee, Hong-Chang;Rhee, Sang-Yong;Kim, Young-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.5
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    • pp.631-637
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    • 2010
  • In this paper, We propose a method of motion interpretation of pedestrian for active traffic signal control. We detect pedestrian object in a movie of crosswalk area by using the code book method and acquire contour information. To do this stage fast, we use parallel processing based on CUDA (Compute Unified Device Architecture). And we remove shadow which causes shape distortion of objects. Shadow removed object is judged by using the hilbert scan distance whether to human or noise. If the objects are judged as a human, we analyze pedestrian objects' motion, face area feature, waiting time to decide that they have intetion to across a crosswalk for pdestrians. Traffic signal can be controlled after judgement.

Analysis of Slope Stability by Applying the Convergence of the Interstice Forces (분할편 경계내각 수렴에 의한 사면안정 해석)

  • 김팔규;김규문
    • Geotechnical Engineering
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    • v.3 no.4
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    • pp.21-30
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    • 1987
  • The purpose of this paper is to develop a method of slope stability analysis, using slice method The direction of interstice forces was assumed in two ways: 1) inclined interslice force parallel to the base of slice, 2) normal interslice force normal to the boundary surface of slice being used in the existing slice method. The deviation from the value of interstice force caused by assumption was removed in the Processing of analysis, and the factor of safety was obtained more accurately by deciding the location of interstice force acting on each slice. More rational validity of the method with inclined interslice force was proved by performing slope stability analyses with both methods. The factor of safety obtained by the proposed method was compared with that by the existing methods, and the influence of seismic coefficient was also analyzed.

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Small Crack Detection in Bolt Threads by Predictive Deconvolution (예측디콘볼루션에 의한 볼트 나삿니의 미세 균열 검출)

  • Suh, Dong-Man;Kim, Whan-Woo
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.1
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    • pp.5-9
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    • 1997
  • If small cracks in stud bolts are not detected early enough, they grow rapidly and cause total fracture. It is difficult to detect, prior to failure, flaws such as stress-corrosion cracking in thread roots and corrosion wastages using conventional ultrasonic testing methods during inservice inspection. This study show a method of detecting a small crack by digital signal processing. When ultrasonic beams travels into threads in parallel way, the echoes from each successive threads has almost the same intervals between any two signals. We can estimate the next thread signal based on previous thread signal by the predictive distance. The optimized operator is used to remove the predicted successive thread signals so that a small crack signal can be detected.

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Alarm Diagnosis of RCP Monitoring System using Self Dynamic Neural Networks (자기 동적 신경망을 이용한 RCP 감시 시스템의 경보진단)

  • Yu, Dong-Wan;Kim, Dong-Hun;Seong, Seung-Hwan;Gu, In-Su;Park, Seong-Uk;Seo, Bo-Hyeok
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.9
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    • pp.512-519
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    • 2000
  • A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

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The Procedure Transformation using Data Dependency Elimination Methods (자료 종속성 제거 방법을 이용한 프로시저 변환)

  • Jang, Yu-Suk;Park, Du-Sun
    • The KIPS Transactions:PartA
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    • v.9A no.1
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    • pp.37-44
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    • 2002
  • Most researches of transforming sequential programs into parallel programs have been based on the loop structure transformation method. However, most programs have implicit interprocedure parallelism. This paper suggests a way of extracting parallelism from the loops with procedure calls using the data dependency elimination method. Most parallelization of the loop with procedure calls have been conducted for extracting parallelism from the uniform code. In this paper, we propose interprocedural transformation, which can be apply to both uniform and nonuniform code. We show the examples of uniform, nonuniform, and complex code parallelization. We then evaluated the performance of the various transformation methods using the CRAY-T3E system. The comparison results show that the proposed algorithm out-performs other conventional methods.

Design of Parallel Rasterizer for 3D Graphics Accelerators (3D 그래픽 가속엔진을 위한 병렬 Rasterizer 설계)

  • O, In-Heung;Park, Jae-Seong;Kim, Sin-Deok
    • Journal of KIISE:Computer Systems and Theory
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    • v.26 no.1
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    • pp.82-97
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    • 1999
  • 3차원 그래픽 렌더링은 화면상의 각 화소에 대하여 색깔뿐만 아니라 깊이 정보가지 계산해야 하기 때문에 방대한 계산량과 메모리 접근, 그리고 데이터 전송량을 필요로 하기 때문이다. 따라서 실시간 3차원 그래픽 처리를 위해서 병렬 처리 기법을 도입한다. 그러나 기존 그래픽 가속엔진은 병렬처리 기법으로 영상-병렬성을 이용한 화면 분할 방식을 사용하기 때문에 크게 두 가지 단점이 발생한다. 첫 번재는 화면 영역의 경게에 위치하는 다각형들에 대한 중복계산이고, 두 번째는 낮은 PE(Processing Element) 활용도이다. 본 논문에서는 이러한 문제를 해결하기 위한 방법으로 객체 기반 렌더링(OBR : Object Based Rendering)방식을 바탕으로 하는 그래픽 가속엔진을 제안하였다. OBR 시스템의 목적은 화면 분할 방식의 불필요한 오버헤드를 제거하여 수행 성능을 높이고, 자원을 효율적으로 사용하여 하드웨어 구성비용을 줄이는 것이다. 본 논문에서는 시뮬레이션을 통하여 OBR 시스템이 화면 분할 방식의 대표적인 그래픽 가속기인 PixelFlow와의 성능을 상대적으로 비교하였다. 결론적으로 OBR 시스템은 화면 분할 방식보다 더 적은 하드웨어 자원으로 보다 효율적으로 렌더링을 수해하였다.

Enhanced Graph-Based Method in Spectral Partitioning Segmentation using Homogenous Optimum Cut Algorithm with Boundary Segmentation

  • S. Syed Ibrahim;G. Ravi
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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    • pp.61-70
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    • 2023
  • Image segmentation is a very crucial step in effective digital image processing. In the past decade, several research contributions were given related to this field. However, a general segmentation algorithm suitable for various applications is still challenging. Among several image segmentation approaches, graph-based approach has gained popularity due to its basic ability which reflects global image properties. This paper proposes a methodology to partition the image with its pixel, region and texture along with its intensity. To make segmentation faster in large images, it is processed in parallel among several CPUs. A way to achieve this is to split images into tiles that are independently processed. However, regions overlapping the tile border are split or lost when the minimum size requirements of the segmentation algorithm are not met. Here the contributions are made to segment the image on the basis of its pixel using min-cut/max-flow algorithm along with edge-based segmentation of the image. To segment on the basis of the region using a homogenous optimum cut algorithm with boundary segmentation. On the basis of texture, the object type using spectral partitioning technique is identified which also minimizes the graph cut value.

Generating Local Addresses for Block-Cyclic Distributed Array (블록-순환으로 분배된 배열의 지역 주소 생성)

  • Kwon, Oh-Young;Kim, Tae-Geun;Han, Tack-Don;Yang, Sung-Bong;Kim, Shin-Dug
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.11
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    • pp.2835-2844
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    • 1998
  • Most data parallel languages provide the block-cyclic distribution (cyclic(k)) that is one of the most general regular distributions. In order to generate local addresses for an array section A(l:h:s) with block-cyclic distribution, efficient compiling methods or run-time methods are required. In this paper, two local address generation methods for the block-cyclic distribution are presented. One is a simple scan method that is modified from the virtual-block scheme. The other is a linear-time ${\Delta}M$ table that contains the local memory access information construction method. This method is simpler than other algorithms for generating a ${\Delta}M$ table. Experimental results show that a simple that a simple scan method has poor performance but a linear-time ${\Delta}M$ table generation method is faster than other algorithms in ${\Delta}M$ table generation time and access time for 10,000 array elements.

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A Vectorization Technique at Object Code Level (목적 코드 레벨에서의 벡터화 기법)

  • Lee, Dong-Ho;Kim, Ki-Chang
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.5
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    • pp.1172-1184
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    • 1998
  • ILP(Instruction Level Parallelism) processors use code reordering algorithms to expose parallelism in a given sequential program. When applied to a loop, this algorithm produces a software-pipelined loop. In a software-pipelined loop, each iteration contains a sequence of parallel instructions that are composed of data-independent instructions collected across from several iterations. For vector loops, however the software pipelining technique can not expose the maximum parallelism because it schedules the program based only on data-dependencies. This paper proposes to schedule differently for vector loops. We develop an algorithm to detect vector loops at object code level and suggest a new vector scheduling algorithm for them. Our vector scheduling improves the performance because it can schedule not only based on data-dependencies but on loop structure or iteration conditions at the object code level. We compare the resulting schedules with those by software-pipelining techniques in the aspect of performance.

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An Efficient Clustering Method based on Multi Centroid Set using MapReduce (맵리듀스를 이용한 다중 중심점 집합 기반의 효율적인 클러스터링 방법)

  • Kang, Sungmin;Lee, Seokjoo;Min, Jun-ki
    • KIISE Transactions on Computing Practices
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    • v.21 no.7
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    • pp.494-499
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    • 2015
  • As the size of data increases, it becomes important to identify properties by analyzing big data. In this paper, we propose a k-Means based efficient clustering technique, called MCSKMeans (Multi centroid set k-Means), using distributed parallel processing framework MapReduce. A problem with the k-Means algorithm is that the accuracy of clustering depends on initial centroids created randomly. To alleviate this problem, the MCSK-Means algorithm reduces the dependency of initial centroids using sets consisting of k centroids. In addition, we apply the agglomerative hierarchical clustering technique for creating k centroids from centroids in m centroid sets which are the results of the clustering phase. In this paper, we implemented our MCSK-Means based on the MapReduce framework for processing big data efficiently.