• 한국정보통신학회논문지
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• 제15권10호
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• pp.2188-2194
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• 2011

무선 네트워크 기술의 발달로, 시공간 오브젝트의 위치 정보를 저장하는 것은 아주 필수적인 일이 되었다. 하지만, 시공간 오브젝트의 움직임은 필요하지 않은 너무 많은 위치 정보를 포함하기 때문에 모든 위치 정보를 저장하는 것은 검색에 있어서 아주 비효율적이다. 따라서 본 논문에서는 시공간 오브젝트에서 필요하지 하지 않는 정보를 제거하여 검색의 효율을 높일 수 있는 효율적인 궤적을 분할하는 방법을 제시한다. 이 선형병합 분할 알고리즘은 EMBR을 이용하여 MBR들의 면적을 최소로 하는 궤적을 분할 알고리즘이다. 실험의 결과로 제시하는 분할 방법이 다른 알고리즘보다 더 효율적인 것을 알 수 있다.

• 한국통신학회논문지
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• 제29권2C호
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• pp.324-332
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• 2004

최근 영상 전체를 전송ㆍ복원하기보다는 영상의 일부 특정 영역이나 사용자 위주의 관심영역(ROI)에 대한 우선적 처리 요구가 웹 브라우징, 이미지 데이터베이스, 원격진료 등과 같은 응용 분야에서 증가하고 있다. 본 논문에서는 기존의 JPEG2000 Part1에서 사용한 Maxshift 방식을 이용하여 둘 이상의 ROI를 가지는 multiple-ROI 코딩 기법을 제안한다. 제안한 기법은 기존의 방식에서처럼 하나의 ROI 뿐만 아니라, multiple ROI를 가지는 영상 전송이 가능함을 보여준다. 또한 웨이브렛 변환(Wavelet Transform)을 이용한 점진적 전송 방식을 사용하기 때문에 낮은 대역폭에서도 사용자가 원하는 ROI를 non-ROI 보다 좀 더 우수한 품질로 전송ㆍ복원 할 수 있고 효율적인 압축이 가능함을 시뮬레이션을 통하여 확인하였다.

• 대한원격탐사학회지
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• 제34권1호
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• pp.89-99
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• 2018

Spatial downscaling is often applied to coarse scale satellite products with high temporal resolution for environmental monitoring at a finer scale. An area-to-point regression kriging (ATPRK) algorithm is regarded as effective in that it combines regression modeling and residual correction with area-to-point kriging. However, an open source tool or package for ATPRK has not yet been developed. This paper describes the development and code organization of an R-based spatial downscaling tool, named R4ATPRK, for the implementation of ATPRK. R4ATPRK was developed using the R language and several R packages. A look-up table search and batch processing for computation of ATP kriging weights are employed to improve computational efficiency. An experiment on spatial downscaling of coarse scale land surface temperature products demonstrated that this tool could generate downscaling results in which overall variations in input coarse scale data were preserved and local details were also well captured. If computational efficiency can be further improved, and the tool is extended to include certain advanced procedures, R4ATPRK would be an effective tool for spatial downscaling of coarse scale satellite products.

• 대한조선학회논문집
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• 제42권6호
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• pp.654-665
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• 2005

In this paper, we present a non-linear integer programming by genetic algorithm (GA) for available sizes of stiffener or thickness of plate in a job site. GA can rapidly search for the approximate global optimum under complicated design environment such as ship. Meanwhile it can handle the optimization problem involving discrete design variable. However, there are many parameters have to be set for GA, which greatly affect the accuracy and calculation time of optimum solution. The setting process is hard for users, and there are no rules to decide these parameters. In order to overcome these demerits, the optimization for these parameters has been also conducted using GA itself. Also it is proved that the parameters are optimal values by the trial function. Finally, we applied this method to compass deck of ship where the vibration problem is frequently occurred to verify the validity and usefulness of nonlinear integer programming.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1411-1417
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• 2014

An MPEG-2 AAC Huffman decoding method based on the fixed length compacted codeword tables, where each codeword can contain multiple number of Huffman codes, was proposed. The proposed method enhances the searching efficiency by finding multiple symbols in a single search, i.e., a direct memory reading of the compacted codeword table. The memory usage is significantly saved by separately handling the Huffman codes that exceed the length of the compacted codewords. The trade-off relation between the computational complexity and the amount of memory usage was analytically derived to find the proper codeword length of the compacted codewords for the design of MPEG-2 AAC decoder. To validate the proposed algorithm, its performance was experimentally evaluated with an implemented MPEG-2 AAC decoder. The results showed that the computational complexity of the proposed method is reduced to 54% of that of the most up-to-date method.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1821-1830
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• 2018

With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.

• 대한산업공학회지
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• 제26권4호
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• pp.363-375
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• 2000

In this paper we propose a content-based image retrieval method that can search large image databases efficiently by color, texture, and shape content. Quantized RGB histograms and the dominant triple (hue, saturation, and value), which are extracted from quantized HSV joint histogram in the local image region, are used for representing global/local color information in the image. Entropy and maximum entry from co-occurrence matrices are used for texture information and edge angle histogram is used for representing shape information. Relevance feedback approach, which has coupled proposed features, is used for obtaining better retrieval accuracy. Simulation results illustrate the above method provides 77.5 percent precision rate without relevance feedback and increased precision rate using relevance feedback for overall queries. We also present a new indexing method that supports fast retrieval in large image databases. Tree structures constructed by k-means algorithm, along with the idea of triangle inequality, eliminate candidate images for similarity calculation between query image and each database image. We find that the proposed method reduces calculation up to average 92.9 percent of the images from direct comparison.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 B
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• pp.923-928
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• 1993

Genetic algorithms are powerful optimization methods based on the mechanism of natural genetics and natural selection. Genetic algorithms reduce chance of searching local optima unlike most conventional search algorithms and especially show good performances in complex nonlinear optimization problems because they do not require any information except objective function value. This paper presents a new model based on sexual reproduction in nature. In the proposed Sexual Reproduction model(SR model), individuals consist of the diploid of chromosomes, which are artificially coded as binary string in computer program. The meiosis is modeled to produce the sexual cell(gamete). In the artificial meiosis, crossover between homologous chromosomes plays an essential role for exchanging genetic informations. We apply proposed SR model to optimization of the design parameters of Single-sided Linear Induction Motor(SLIM). Sequential Unconstrained Minimization Technique(SUMT) is used to transform the nonlinear optimization problem with many constraints of SLIM to a simple unconstrained problem, We perform optimal design of SLIM available to FA conveyer systems and discuss its results.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1564-1573
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• 2016

With the spread of social media and mobile devices, people spend more time on online than ever before. As more people participate in various online activities, much research has been conducted on how to make use of the time effectively and productively. In this paper, we propose two methods which can be used to extract highlights and make searchable media indexes using online social data. For highlight extraction, we collected the comments from the online baseball broadcasting website. We adopted peak-finding algorithm to analyze the frequency of comments uploaded on the comments section of the website. For each indexes, we collected postings from soap opera forums provided by a popular web service called DCInside. We extracted all the instances when a character's name is mentioned in postings users upload after watching TV, which can be used to create indexes when the character appears on screen for the given episode of the soap opera The evaluation results shows the possibility of the crowdsourcing-based media interaction for both highlight extraction and index building.

• 한국지능시스템학회논문지
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• 제17권5호
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• pp.679-683
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• 2007

Vapnik의 통계적 학습이론은 분류, 회귀, 그리고 군집화를 위하여 SVM(support vector machine), SVR(support vector regression), 그리고 SVC(support vector clustering)의 3가지 학습 알고리즘을 포함한다. 이들 중에서 SVC는 가우시안 커널함수에 기반한 지지벡터를 이용하여 비교적 우수한 군집화 결과를 제공하고 있다. 하지만 SVM, SVR과 마찬가지로 SVC도 커널모수와 정규화상수에 대한 최적결정이 요구된다 하지만 대부분의 분석작업에서 사용자의 주관적 경험에 의존하거나 격자탐색과 같이 많은 컴퓨팅 시간을 요구하는 전략에 의존하고 있다. 본 논문에서는 SVC에서 사용되는 커널모수와 정규화상수의 효율적인 결정을 위하여 차분진화를 이용한 DESVC(differential evolution based SVC)를 제안한다 UCI Machine Learning repository의 학습데이터와 시뮬레이션 데이터 집합들을 이용한 실험을 통하여 기존의 기계학습 알고리즘과의 성능평가를 수행한다.