• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.24-27
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• 1996

The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.943-952
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• 2000

The surface reconstruction problem from a set of wire-frame contours is very important in diverse fields such as medical imaging or computer animation. In this paper, surface triangulation method is proposed for solving the problem. Generally, many optimal triangulation techniques suffer from the large computation time but heuristic approaches may produce very unnatural surface when contours are widely different in shape. To compensate the disadvantages of these approaches, we propose a new heuristic triangulation method which iteratively decomposes the surface generation problem from a band (a pair of vertices chain) into tow subproblems from two sub-bands. Generally, conventional greedy heuristic contour triangulation algorithm, suffer from the drastic error propagation during surface modeling when the adjacent contours are different in shape. Our divide-and-conquer algorithm, called band partitioning algorithm, processes eccentric parts of the contours first with more global information. Consequently, the resulting facet model becomes more stable and natural even though the shapes are widely different. An interesting property of our method is hat it supports multi-resolution capability in surface modeling time. According to experiments, it is proved to be very robust and efficient in many applications.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.46-56
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• 2016

Dynamic textures are videos that exhibit a stationary property with respect to time (i.e., they have patterns that repeat themselves over a large number of frames). These patterns can easily be tracked by a linear dynamic system. In this paper, a model that identifies the underlying linear dynamic system using wavelet coefficients, rather than a raw sequence, is proposed. Content based threshold filtering based on Set Partitioning in a Hierarchical Tree (SPIHT) helps to get another representation of the same frames that only have low frequency components. The main idea of this paper is to apply SPIHT based threshold filtering on different bands of wavelet transform so as to have more significant information in fewer parameters for singular value decomposition (SVD). In this case, more flexibility is given for the component selection, as SVD is independently applied to the different bands of frames of a dynamic texture. To minimize the time complexity, the proposed model is implemented on a graphics processing unit (GPU). Test results show that the proposed dynamic system, along with a discrete wavelet and SPIHT, achieve a highly compact model with better visual quality, than the available LDS, Fourier descriptor model, and higher-order SVD (HOSVD).

• 한국정보과학회논문지:시스템및이론
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• 제27권1호
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• pp.23-33
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• 2000

본 논문은 데이타 병렬 프로그램에서 효율적 통신을 위한 하나의 방법으로 통신과 계산 작업을 중첩하여 실행하는 모델을 제안한다. 이 중첩 모델에서는 통신 지연 시간 동안 중첩하여 수행할 계산 작업을 얻기 위해 주어진 루프 분할을 다시 세부 분할한다. 주어진 루프 분할은 다른 외부 데이타 분할을 참조하기도 하지만, 루프 분할의 모든 반복들이 항상 외부 데이타 참조를 필요로 하는 것은 아니다. 따라서 주어진 루프 분할을 외부 데이타를 요구하는 루프 반복들의 집합과 그렇지 않은 루프 반복들의 집합으로 나눌 수 있다. 이렇게 나누어진 루프 세부 분할은 효율적인 수행을 위해 메시지 도착 순서에 따라 동적으로 스케쥴링된다. 제안된 방법에 따라 IBM SP2에서 몇가지 프로그램으로 실험을 한 결과, 중첩 모델이 성능 향상을 보임을 확인할 수 있었다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2004년도 추계학술대회 및 정기총회
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• pp.389-392
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• 2004

The column generation process for the set-partitioning model of the vehicle routing problem requires repeated solutions of column generation subproblems which has a combinatorial structure similar to that of the traveling salesman problem. This limits the size of the problem that can be addressed. We introduce a new modeling approach, termed route-splitting, which splits each vehicle route into segments, and results in more tractable subproblems. A lower bounding scheme that yields an updated bound at each iteration of the column generation process is developed. Implementation issues, including a technique of controlling columns in the master problem, are explored. Lower bounds are computed on standard benchmark problems with up to 199 customers.

• 산업공학
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• 제10권3호
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• pp.179-187
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• 1997

The efficiency of material flow systems in terms of optimal network flow and minimum cost flow has always been an important design and operational goal in material handling and distribution system. In this research, an attempt was made to develop a new algorithm and the model to solve a stochastic material flow network with bidirectional and uncertain flows. A stochastic material flow network with bidirectional flows can be considered from a finite set with unknown demand probabilities of each node. This problem can be formulated as a special case of a two-stage linear programming problem which can be converted into an equivalent linear program. To find the optimal solution of proposed stochastic material flow network, some terminologies and algorithms together with theories are developed based on the partitioning and subgradient techniques. A computer program applying the proposed method was developed and was applied to various problems.

• 대한임베디드공학회논문지
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• 제5권4호
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• pp.206-216
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• 2010

Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. A spatial clustering may reduce energy consumption of data collection by partitioning the WSN into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to a base station (BS). The BS may predict the missed data of non-samplers using the spatial correlations between sensor nodes. ASAP is a representative data collection algorithm using the spatial clustering. It periodically reconstructs the entire network into new clusters to accommodate to the change of spatial correlations, which results in high message overhead. In this paper, we propose a new data collection algorithm, name EPDC (Energy-efficient Periodic Data Collection). Unlike ASAP, EPDC identifies a specific cluster consisting of many dissimilar sensor nodes. Then it reconstructs only the cluster into subclusters each of which includes strongly correlated sensor nodes. EPDC also tries to reduce the message overhead by incorporating a judicious probabilistic model transfer method. We evaluate the performance of EPDC and ASAP using a simulation model. The experiment results show that the performance improvement of EPDC is up to 84% compared to ASAP.

• 한국정보과학회논문지:소프트웨어및응용
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• 제34권12호
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• pp.1045-1055
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• 2007

잠재토픽모델(latent topic model)은 데이타에 내재된 특징적 패턴이나 데이타 정의 자질들 간의 상호 관련성을 확률적으로 모델링하고 자동 추출하는 모델로서 최근 텍스트 문서로부터의 의미 자질 자동 추출, 이미지를 비롯한 멀티미디어 데이타 분석, 생물정보학 분야 등에서 많이 응용되고 있다. 이러한 잠재토픽모델의 대규모 데이타에 대한 적용 시 그 효과 증대를 위한 중요한 이슈 중의 하나는 모델의 효율적 학습에 관한 것이다. 본 논문에서는 대표적 잠재토픽모델 중의 하나인 PLSA (probabilistic latent semantic analysis) 기법을 대상으로 점진적 EM 알고리즘을 활용한, 기본 EM 알고리즘 기반의 기존 학습에 대한 학습속도 증진 기법을 제안한다. 점진적 EM 알고리즘은 토픽 추론 시 전체 데이타에 대한 일괄적 E-step 대신에 일부 데이타에 대한 일련의 부분적 E-step을 수행하는 특징이 있으며 이전 데이터 일부에 대한 학습 결과를 바로 다음 데이타 학습에 반영함으로써 모델 학습의 가속화를 기대할 수 있다. 또한 이론적인 측면에서 지역해로의 수렴성이 보장되고 기존 알고리즘의 큰 수정 없이 구현이 용이하다는 장점이 있다. 논문에서는 해당 알고리즘의 기본적인 응용과 더불어 실제 적용과정 상에서의 가능한 데이터 분할법들을 제시하고 모델 학습 속도 개선 면에서의 성능을 실험적으로 비교 분석한다. 실세계 뉴스 문서 데이타에 대한 실험을 통해, 제안하는 기법이 기존 PLSA 학습 기법에 비해 유의미한 수준에서 학습 속도 증진을 달성할 수 있음을 보이며 추가적으로 모델의 병렬 학습 기법과의 조합을 통한 실험 결과를 간략히 제시한다.

• 한국전자파학회지:전자파기술
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• 제4권1호
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• pp.20-27
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• 1993

본 논문에서는 디지탈 무선통신을 위한 전송방식으로 집합분할에 의한TCM/M-PSK와pragmatic 부호에 의한 M 진 PSK 시스댐을 실현하였다. 전송채널에 AWGN과 Rayleigh 페이딩이 존재하는 경우 시스댐의 성능을 오율 관점에서 해석하였으며, 이를 위한 오율식을 유도하여 제시하였다. 그 결과 Rayleigh 페이덩이 많은 영향을 미치는 이동무선통신에서 pragmatic 부호에 의한 방식은 부호화하지 않고 곧바로 전송되는 정보데이터에 의해 발생하는 병렬쌍때문에 시스템 전체의 성능을 저하시키게 됨을 알 수 있었다. 하지만 AWGN만 고려하는 무선통신에서 pragmatic 방식은 단일 부호기/복호기를 사용하므로 시스템이 간단해지는 장점이 있다.