• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.470-472
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• 1998

본 논문에서는 노이즈와 블러링에 의해 오염된 영상의 비 지도 분할 방법을 제안한다. 본 논문에서는 Markov random field (MRF) model을 사용하는데, 이것은 오염된 여상에 처리하는데 효율적이다. MRF는 연산적으로 복잡하기 때문에 이를 해결하기 위해서 효율적이라는 것과 교통량 측정과 같은 영상 처리에 응용 가능함을 보여준다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.36-38
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• 2000

디스크상의 개별 파일들은 디스크에 추가, 변경, 그리고 삭제됨에 따라 디스크의 서로 다른 영역으로 분산될 수 있다. 이러한 경우 개별 파일을 구성하고 있는 모든 조각들을 찾는 조각모음은 많은 파일 블록의 이동 때문에 근본적으로 많은 시간이 요구되는 작업이다. 그러나 기존의 방법은 공통적으로 조각모음을 수행하는데 각 조각파일의 모음 순서를 고려하지 않는다. 즉, 조각난 차례대로 조각모음을 수행한다. 이 논문에서는 유전자알고리즘(Genetic Algorithm)을 이용하여 가장 효율적인 조각모음 순서를 결정하는 방법을 제안하고 평가한다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1807-1808
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• 2007

본 연구에서는 반도체 플라즈마 공정감시와 제어에 응용될 수 있는 모델을 제안한다. 본 모델은 광반사분광기(OES)정보와 신경망을 이용해서 개발하였으며, OES의 차수를 줄이기 위해 주인자 분석을 세 종류의 분산 (100, 99, 98%)에 대해서 적용하였다. 모델의 예측성능은 유전자 알고리즘을 이용하여 최적화하였다. 제안하는 모델링 방식은 MERIE를 이용한 Oxide 식각공정에 적용하였으며, 개발된 모델은 발표된 이전의 모델에 비해 증진된 예측성능을 보였다.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.1
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• pp.51-62
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• 2017

A design optimization method is applied for the flow path design of RBCC engine, an important factor for the determining the propulsion performance operating at air-breathing mode. A design optimization was carried out to maximize the specific impulse of the RBCC engine by using a genetic algorithm based on the Kriging model. Results are analyzed using ANOVA and SOM. Design conditions of ramjet and scramjet mode are selected as Mach number 4 at 20 km altitude and Mach number 7 at 30 km, respectively. The optimized design presents that the specific impulse is increased by 7% and 10% on each condition than the baseline design.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.1-9
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• 2009

In recent years, a film restoration has gained increasing attention by many researchers, to support multimedia service of high quality. In general, an old film is degraded by dust, scratch, flick, and so on. Among these, the common factors are scratch and blotch, so that many researchers have been investigated to restore these degradations. However, the methods in literature have one major limitation: A method is working well in dealing with scratches, however it is poorly working in processing the blotches. The goal of this work is to develop a robust technique to restore images degraded by both scratches and blotches. For this, we use MRF-MAP (Markov random field - maximum a posteriori) framework, so that the restoration problem is considered as the minimization problem of the posteriori energy function. As the minimization is one of complex combinatorial problem, we use distributed genetic algorithms (DGAs) that effectively deal with combinatorial problems. To asses the validity of the proposed method, it was tested on natural old films and artificially degraded films, and the results were compared with other methods. Then, the results show that the proposed method is superior to other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.70-77
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• 2008

This paper proposes a new text candidate region detection method that uses genetic algorithm based on information of the segmented regions. In image segmentation, a classification of the pixels at each color channel and a reclassification of the region-unit for reducing inhomogeneous clusters are performed. EWFCM(Entropy-based Weighted C-Means) algorithm to classify the pixels at each color channel is an improved FCM algorithm added with spatial information, and therefore it removes the meaningless regions like noise. A region-based reclassification based on a similarity between each segmented region of the most inhomogeneous cluster and the other clusters reduces the inhomogeneous clusters more efficiently than pixel- and cluster-based reclassifications. And detecting text candidate regions is performed by genetic algorithm based on energy and variance of the directional edge components, the number, and a size of the segmented regions. The region information-based detection method can singles out semantic text candidate regions more accurately than pixel-based detection method and the detection results will be more useful in recognizing the text regions hereafter. Experiments showed the results of the segmentation and the detection. And it confirmed that the proposed method was superior to the existing methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1105-1116
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• 2014

A stochastic rainfall model, NSRPM (Neyman-Scott Rectangular Pulse Model), is able to reflect the cluster characteristics of rainfall events which is unable in the RPM (Rectangular Pulse Model). Therefore NSRPM has advantage in the hydrological applications. The NSRPM consists of five model parameters and the parameters are estimated using optimization techniques such as DFP (Davidon-Fletcher-Powell) method and genetic algorithm. However the DFP method is very sensitive in initial values and is easily converge to local minimum. Also genetic algorithm has disadvantage of long computation time. Nelder-Mead method has several advantages of short computation time and no need of a proper initial value. In this study, the applicability of parameter estimation methods was evaluated using rainfall data of 59 national rainfall networks from 1973-2011. Overall results demonstrated that accuracy in parameter estimation is in the order of Nelder-Mead method, genetic algorithm, and DFP method.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.396-400
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• 2009

During periods of large data transmission, routing selection methods are used to efficiently manage data traffic and improve the speed of transmission. One approach in routing selection is AntNet that applies the Ant algorithm in transmissions with uniform probability. However, this approach uses random selection, which can cause excessive data transmission rates and fail to optimize data This paper presents the use of the Genetic Algorithm (GA) to efficiently route and disperse data transmissions, during periods with "unnecessary weight increases for random selection". This new algorithm for improved performance provides highly accurate estimates of the transmission time and the transmission error rate.

• Journal of Life Science
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• v.23 no.4
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• pp.595-601
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• 2013

The clusters of orthologous groups of proteins (COG) algorithm was applied to identify essential proteins in eukaryotes and to measure the degree of conservation. Sixty-three orthologous groups, which were conserved in 66 microbial genomes, enlarged to 104 eukaryotic orthologous groups (KOGs) and 71 KOGs were conserved at the nuclear genome of 7 eucaryotes. Fifty-four of 71 translation-related genes were conserved, highlighting the importance of proteins in modern organisms. Translation initiation factors (KOG0343, KOG3271) and prolyl-tRNA synthetase (KOG4163) showed high conservation based on the distance value analysis. The genes of Caenorhabditis elegans appear to harbor high genetic variation because the genome showed the highest variation at 71 conserved proteins among 7 genomes. The 71 conserved genes will be valuable in basic and applied research, for example, targeting for antibiotic development.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.6
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• pp.555-568
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• 2000

The World Wide Web has become the largest virtual system that is almost universal in scope. In recent research, it has become effective to utilize idle hosts existing in the World Wide Web for running applications that require a substantial amount of computation. This novel computing paradigm has been referred to as the advent of global computing. In this paper, we implement and propose a mobile object-based global computing framework called Tiger, whose primary goal is to present novel object-oriented programming libraries that support distribution, dispatching, migration of objects and concurrency among computational activities. The programming libraries provide programmers with access, location and migration transparency for distributed and mobile objects. Tiger's second goal is to provide a system supporting requisites for a global computing environment - scalability, resource and location management. The Tiger system and the programming libraries provided allow a programmer to easily develop an objectoriented parallel and distributed application using globally extended computing resources. We also present the improvement in performance gained by conducting the experiment with highly intensive computations such as parallel fractal image processing and genetic-neuro-fuzzy algorithms.