• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.435-442
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• 1997

The roof crane system is used for transporting a variable load to a target position. The goal of crane control system is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid tansportation is required. In this paper, we developed a simple fuzzy controller which has been introduced expert's knowledge base for anti-swing and rapid tranportation to goal position. In particular, we proposed the synthesis reasoning method which synthesizes on the basis of expert knowledge of the angle control input and position control input which are inferenced parallel and simultaneously. And we confirmed that the performance of the developed controller is effective as a result of applying it to crane simulator and also verified whether the proposed synthesis rules have been applied correctly using clustering algorithm from the measured data.

• IE interfaces
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• v.11 no.1
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• pp.183-190
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• 1998

This paper is concerned with the bicriteria vehicle routing problems with time window constraints(BVRPTW). The BVRPTW is to determine the most favorable vehicle routes that minimize the total vehicle travel time and the total customer wait time which are, more often than not, conflicting. We construct a linear goal programming (GP) model for the BVRPTW and propose a heuristic algorithm to relieve a computational burden inherent to the application of the GP model. The heuristic algorithm consists of a parallel insertion method for clustering and a sequential linear goal programming procedure for routing. The results of computational experiments showed that the proposed algorithm finds successfully more favorable solutions than the Potvin an Rousseau's method that is known as a very good heuristic for the VRPs with time window constraints, through the change of target values and the decision maker's goal priority structure.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.189-196
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• 2003

Among the optimization method, GA (genetic algorithm) is a very powerful searching method enough to compete with design sensitivity analysis method. GA is very easy to apply, since it dose not require any design sensitivity information. However, GA has been computationally not efficient due to huge repetitive computation. In this study, parallel computation is adopted to improve computational efficiency. Paralleled GA is introduced on a clustered LINUX based personal computer system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.401-409
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• 2002

인터넷과 같은 대량의 정보에 대응할 수 있는 고성능 정보검색시스템을 구축하기 위해서는 지금까지 고가의 중대형 컴퓨터를 주로 활용하여 왔으나, 최근 가격대 성능비가 높은 PC 클러스터 시스템을 활용하는 방안이 경제적인 대안으로 떠오르고 있다. PC 클러스터 상에서의 병렬정보검색시스템을 효율적으로 운영하기 위해서는 사용자가 입력한 질의를 처리하는데 요구되는 개별 PC의 디스크 I/O 및 검색관련 연산을 모든 PC에 가능한 균등하게 분배할 필요가 있다. 본 논문에서는 같은 질의에 동시에 등장할 가능성이 높은 색인어들끼리 군집 화하고 생성된 군집을 활용하여 색인어들을 각 PC에 분산저장함으로써 보다 높은 수준의 병렬화를 달성할 수 있는 방안을 제시한다. 대용량 말뭉치를 활용한 실험결과 본 논문에서 제시하는 분산저장기법이 충분한 효율성을 가지고 있음을 확인하였다.

• The Journal of Information Technology
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• v.5 no.2
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• pp.17-26
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• 2002

On this paper, we propose SOSL(Self-Organized Supervised Learning) and it's architecture SOSL is hybrid type neural network. It consists of several CBP (Component Back Propagation) neural networks, and a modified PCA neural networks. CBP neural networks perform supervised learning procedure in parallel to clustered and complex input patterns. Modified PCA networks perform it's learning in order to transform dimensions of original input patterns to lower dimensions by clustering and local projection. Proposed SOSL can effectively apply to neural network learning with large input patterns results in huge networks size.

• Annual Conference of KIPS
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• 2002.04a
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• pp.389-392
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• 2002

광선 추적 기법은 컴퓨터를 활용하여 사진과 같은 고해상도의 영상을 얻어내기 위한 렌더링 기법 중 하나이다. 그러나 이 기법은 이미지를 생성할 때 각 접마다 시뮬레이션을 하여 계산해 내므로 접의 수에 따른 계산량이 증가되고 그에 따른 계산 시간이 많이 소요된다는 단점이 있다. 이러한 많은 계산량을 처리하기 위해 병렬처리 기법을 활용할 수 있다. 본 논문에서는 MPI(Message Passing Interface)를 이용한 병렬 광선 추적 기법을 제시하고 그러한 기법을 여러대의 PC를 이용한 PC Clustering 기법에 적용시켜봄으로써 복잡한 계산에 소요되는 시간을 단축시키고자 하였다. 또한 작업의 크기의 변화에 따른 작업 시간과 노드 수의 증가에 따른 속도 향상률을 알아보았다. 이러한 실험을 위해 병렬 프로그래밍 도구로는 Windows NT 기반의 MPICH를 사용하였고 노드의 수는 3대에서 30대까지 증가시켰다. 노드의 수가 증가함에 따라 렌더링에 소요되는 시간이 선형적으로 감소함을 알 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.168-170
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• 1999

지리정보시스템과 같은 공간 데이터베이스에서 다루는 데이터는 대용량이며, 사용자의 다양한 질의에 따라 빠르게 접근할 수 있어야 한다. 그런데 이때 성능의 대부분이 디스크 접근시간에 의해 영향을 받으므로 접근시간을 줄이는 기술이 필요하다. 이는 다수의 디스크 공간에 데이터를 분산하여 저장하는 디클러스터링 방법을 사용함으로써 효과적인 성능 향상을 기대할 수 있다. 효과적인 디클러스터링 방법은 주어진 질의에 대하여 동시에 접근될 가능성이 있는 공간 객체를 다른 디스크에 각각 저장함으로써 한번에 접근하는 병렬성을 높일 수 있다. 그러나 하나의 디스크에게 할당 가능한 공간 객체들을 서로 다른 디스크에 할당하는 것은 오히려 성능의 저하를 초래할 수 있다. 이러한 두 가지 조건을 동시에 만족하기 위해서는 공간 객체들을 클러스터링 한 후, 크러러스터 단위로 디스크로 할당하는 것이 효과적이다. 이전에 제시된 디클러스터링 방법들은 이러한 요소를 고려하지 않았다. 이에 본 논문에서는 주어진 공간 객체들에 대해서 일정한 크기의 클러스터를 만들고 클러스터 단위로 디클러스터링 하여 효율적인 성능 향상을 보이는 새로운 방법에 대해서 제시하고자 한다. 또한 이전에 제시되어졌던 여러 가지 디클러스터링 방법들과의 비교실험을 통해, 본 논문에서 제시한 방법이 가장 효과적인 방법임을 밝히고자 한다.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.183-194
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• 2002

The clustering environment with heterogeneous workstations provides the cost effectiveness and usability for executing applications in parallel. Load balancing is considered a necessary feature for a cluster of heterogeneous workstations to minimize the turnaround time. Previously, static load balancing that assigns a predetermined weight for the processing capability of each workstation, or dynamic approaches which execute a benchmark program to get relative processing capability of each workstation were proposed. The execution of the benchmark program, which has nothing to do with the application being executed, consumes the computation time and the overall turnaround time is delayed. In this paper, we present efficient methods for task distribution and task migration, based on the relative load index. We designed and implemented a load balancing system for the clustering environment with heterogeneous workstations. Turnaround times of our methods and the round-robin approach, as well as the load balancing method using a benchmark program, were compared. The experimental results show that our methods outperform all the other methods that we compared.

• Spatial Information Research
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• v.11 no.3
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• pp.213-226
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• 2003

With the increasing demand of processing massive geographic data, conventional GISs based on the single processor architecture appear to be problematic. Especially, performing complex GIS operations on the massive geographic data is very time consuming and even impossible. This is due to the processor speed development does not keep up with the data volume to be processed. In the field of GIS, this PC clustering is one of the emerging technology for handling massive geographic data effectively. In this study, a MPI(Message Passing Interface)-based parallel processing approach was conducted to implement the existing raster GIS operations that typically requires massive geographic data sets in order to improve the processing capabilities and performance. Specially for this research, four types of raster CIS operations that Tomlin(1990) has introduced for systematic analysis of raster GIS operation. A data decomposition method was designed and implemented for selected raster GIS operations.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.379-386
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• 2014

In this paper, the processing speed of Grabcut algorithm in order to efficiently improve the GPU (Graphics Processing Unit) for processing the data from the method. Grabcut algorithm has excellent performance object detection algorithm. Grabcut existing algorithms to split the foreground area and the background area, and then background and foreground K-cluster is assigned a cluster. And assigned to gradually improve the results, until the process is repeated. But Drawback of Grabcut algorithm is the time consumption caused by the repetition of clustering. Thus GPGPU (General-Purpose computing on Graphics Processing Unit) using the repeated operations in parallel by processing Grabcut algorithm to effectively improve the processing speed of the method. We proposed method of execution time of the algorithm reduced the average of about 95.58%.