• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.19-22
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• 2005

In order to achieve high capacity and reliable link quality in user communication, this paper proposes a new concept of virtual cell: the Dual Virtual Cell(DVC), and DVC employment strategy based on DWCS. The proposed system uses two kinds of virtual cell. One is the AVC(Active Virtual Cell) which exists for actual traffic and the other is the CVC(Candidate Virtual Cell) which contains a set of candidate antennas to protect user's link quality from performance degradation or interruption. And also this system aims to reduce MT's overloads and acheive a prompt link change successfuly by introducing DVC structure which makes it possible for network to monitor real-time channel and to conrol communication links. The proposed system constructs DVC by using antenna selection method and improves frame error performance with employing Space-Time Trellis Code(STTC).

• 경영과학
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• 제17권2호
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• pp.67-73
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• 2000

This paper describes a scheduling support system for a plant where the machine environment may be modeled as non-identical parallel machine lines (NPML). That is, there are a number of stages in series with various different-capability-machines at each stage. Arriving continuously are jobs with their specific due dates, processing times and candidate processing machines. We’ve developed a real-time scheduling module in conjunction with a supporting production information system which supplies necessary data to the module. This scheduling module is one of the 9 modules in this system, and is composed of both a scheduling interface and a production monitoring interface. This module allows users to generate many candidate schedules by selecting their business policies. The selective arguments which are available consist of allocation costs, batch sizes and machine selection intervals. They are now being implemented at a powder metallurgy plant.

• 대한전자공학회논문지
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• 제26권9호
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• pp.1395-1401
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• 1989

An efficient file allocation algorithm and a new method which calculate appraisal value of candidate computer site for distributed computer systems are proposed. The file allocation problem size is reduced by using the preassignment condition. The appraisal value of candidate node is calcualted as the user state array and node state array are varied according to control variables. As the selection criteria is applied to the candidates, the reasonable node is selected and assign state is determined. The proposed algorithm is heuriatic polynomial time algorithm. By performing algorithm for sample problems. It is shown that the proposed algorithm is superior to conventional method in terms of deviation from optimal solution.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2006년도 추계학술대회 발표논문집
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• pp.142-145
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• 2006

Discrimination between speech and music is important in many multimedia applications. Previously we proposed a new parameter for speech/music discrimination, the mean of minimum cepstral distances (MMCD), and it outperformed the conventional parameters. One weakness of it is that its performance depends on range of candidate frames to compute the minimum cepstral distance, which requires the optimal selection of the range experimentally. In this paper, to alleviate the problem, we propose a multi-dimensional MMCD parameter which consists of multiple MMCDs with different ranges of candidate frames. Experimental results show that the multi-dimensional MMCD parameter yields an error rate reduction of 22.5% compared with the optimally chosen one-dimensional MMCD parameter.

• 말소리와 음성과학
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• 제1권3호
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• pp.109-115
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• 2009

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. In this paper, we investigate several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. At first, word distance method based on phone and syllable distances are considered. These methods use just Levenstein distance on phones or double Levenstein distance algorithm on syllables of candidates. Next, word similarity approaches are presented that they use characters' position information of word candidates. Each character's position is labeled to inserted, deleted, and correct position after alignment between source and target string. The word similarities are obtained from characters' positional probabilities which mean the frequency ratio of the same characters' observations on the position. From experimental results, we can find that the proposed methods are effective for removing non-similar words without loss of system performance from the N-best recognition candidates of the systems.

• 말소리와 음성과학
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• 제2권4호
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• pp.153-161
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• 2010

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. The previous study [1,2] investigated several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. This paper discusses the various improving techniques of removing non-similar recognition results. The mentioned methods include comparison penalties or weights, phone accuracy based on confusion information, weights candidates by ranking order and partial comparisons. Through experimental results, it is found that some proposed method keeps more accurate recognition results than the previous method's results.

• Communications for Statistical Applications and Methods
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• 제22권5호
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• pp.507-518
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• 2015

It is not easy to select a linear mixed model since the main interest for model building could be different and the number of parameters in the model could not be clearly defined. In this paper, performance of conditional Akaike Information Criteria and its bias-corrected version are compared with marginal Bayesian and Akaike Information Criteria through a simulation study. The results from the simulation study indicate that bias-corrected conditional Akaike Information Criteria shows promising performance when candidate models exclude large models containing the true model, but bias-corrected one prefers over-parametrized models more intensively when a set of candidate models increases. Marginal Bayesian and Akaike Information Criteria also have some difficulty to select the true model when the design for random effects is nested.

• 한국가금학회:학술대회논문집
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• 한국가금학회 2003년도 제20차 정기총회 및 학술발표회
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• pp.129-130
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• 2003

본 연구는 proteomics의 방법을 이용하여 가금의 육질과 관련된 단백질을 찾고자 수행하였다. 인삼부산물 추출액을 급여한 실용 재래닭에서 육질과 관련된 것으로 추정되는 후보 단백질들이 선발되었으며, 이 결과는 가금의 육질을 향상시키는 단백질 Marker로서 이용될 수 있을 뿐만 아니라 현재까지 밝혀지지 않은 가금의 2D map을 만드는데 역시 중요하게 이용될 수 있다.

• 대한음성학회지:말소리
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• 제60호
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• pp.191-201
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• 2006

Discrimination between speech and music is important in many multimedia applications. Previously we proposed a new parameter for speech/music discrimination, the mean of minimum cepstral distances (MMCD), and it outperformed the conventional parameters. One weakness of MMCD is that its performance depends on range of candidate frames to compute the minimum cepstral distance, which requires the optimal selection of the range experimentally. In this paper, to alleviate the problem, we propose a multi-dimensional MMCD parameter which consists of multiple MMCDS with combination of different candidate frame ranges. Experimental results show that the multi-dimensional MMCD parameter yields an error rate reduction of 22.5% compared with the optimally chosen one-dimensional MMCD parameter.

• 한국콘텐츠학회논문지
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• 제10권5호
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• pp.1-9
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• 2010

이 논문은 특징 선택에 사용되는 개미 군락 최적화의 수렴 특성을 개선하기 위해 선택적 평가라는 새로운 기법을 제시한다. 이 방법은 불필요하거나 가능성이 덜한 후보 해를 배제함으로써 계산량을 줄인다. 이 방법은, 그런 해를 찾아내는데 사용할 수 있는 페로몬 정보 때문에 구현이 가능하다. 문제 크기에 따른 알고리즘의 적용가능성을 판단할 목적으로, 특징 선택에 사용되는 세 가지 알고리즘인 탐욕 알고리즘, 유전 알고리즘, 그리고 개미 군락 최적화의 계산 시간을 분석한다. 엄밀한 분석을 위해 원자 연산이라는 개념을 사용한다. 실험 결과는 선택적 평가를 채택한 개미 군락 최적화가 계산 시간과 인식 성능 모두에서 우수함을 보여준다.