• 한국지능시스템학회논문지
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• 제11권7호
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• pp.675-679
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• 2001

In this paper, we present a new competitive learning algorithm called Dynamic Competitive Learning (DCL). DCL is a supervised learning method that dynamically generates output neurons and initializes automatically the weight vectors from training patterns. It introduces a new parameter called LOG (Limit of Grade) to decide whether an output neuron is created or not. If the class of at least one among the LOG number of nearest output neurons is the same as the class of the present training pattern, then DCL adjusts the weight vector associated with the output neuron to learn the pattern. If the classes of all the nearest output neurons are different from the class of the training pattern, a new output neuron is created and the given training pattern is used to initialize the weight vector of the created neuron. The proposed method is significantly different from the previous competitive learning algorithms in the point that the selected neuron for learning is not limited only to the winner and the output neurons are dynamically generated during the learning process. In addition, the proposed algorithm has a small number of parameters, which are easy to be determined and applied to real-world problems. Experimental results for pattern recognition of remote sensing data and handwritten numeral data indicate the superiority of DCL in comparison to the conventional competitive learning methods.

• Genomics & Informatics
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• 제4권4호
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• pp.173-181
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• 2006

Pattern finding is one of the important tasks in a protein or DNA sequence analysis. Alignment is the widely used technique for finding patterns in sequence analysis. BLAST (Basic Local Alignment Search Tool) is one of the most popularly used tools in bio-informatics to explore available DNA or protein sequence databases. BLAST may generate a huge output for a large sequence data that contains various sequence patterns. However, BLAST does not provide a tool to summarize and analyze the patterns or matched alignments in the BLAST output file. BLAST lacks of general and robust parsing tools to extract the essential information out from its output. This paper presents a pattern summary system which is a powerful and comprehensive tool for discovering pattern structures in huge amount of sequence data in the BLAST. The pattern summary system can identify clusters of patterns, extract the cluster pattern sequences from the subject database of BLAST, and display the clusters graphically to show the distribution of clusters in the subject database.

• 신재생에너지
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• 제18권4호
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• pp.64-69
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• 2022

Double-sided photovoltaic (PV) modules have received significant attention in recent years as a technology that can achieve higher annual energy production rates than single-sided modules. The shingled technology is a promising method for manufacturing high-density and high-power modules. These modules are divided by laser and joined with electrically conductive adhesives. The output efficiency of the divided cells depends on the division pattern and the electrode pattern, making it important to understand the output characteristics. In this study, the output characteristics of large-area double-sided light-receiving shingled cells with different split patterns and electrode patterns were investigated. The M6 size, with 6 divisions in the electrode pattern, had the highest efficiency when using 142 front fingers and 146 rear fingers. The M10 size, with 7 divisions, had the highest output when using 150 fingers equally in the front and rear. The M12 size, also with 7 divisions, showed the highest output characteristics when using 192 front fingers and 208 rear fingers.

• 한국광학회지
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• 제19권1호
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• pp.43-47
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• 2008

현재 TFT-LCD(Thin Film Transistor Liquid Crystal Display)에 사용되는 BLU(Back Light Unit) 패턴 크기는 수 십 ${\mu}m$인데 반해, 최근에는 BLU 패턴의 크기를 수 ${\mu}m$ 또는 그 이하로 조절함으로써 출력광의 휘도를 증가시키고 균일도를 향상시키고자 하는 연구가 진행되고 있다. 본 연구에서는 패턴의 크기, 분포 및 점유 면적이 출력광의 분포에 미치는 영향을 조사하였다.

• 전자공학회논문지B
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• 제31B권6호
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• pp.63-70
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• 1994

In this paper, we propose a fault simulation method based on primary output in combinational circuit. In the deterministic test pattern generation, each test pattern is genterated incrementally. The test pattern is applied to the primary inputs of circuit under test to simulate faults. We detect the faults with respect to each primary output. The fault detection with resptect to each primary output is reflected by the corresponding bit in the detection words, and efficient fault detection for the reconvergent fan-out stem is achieved with dynamic fault propagation. As an experimental result of the fault simulation with our method for the several bench mark circuits, we illustrated the good performance showing that the number of gates to be activated is much reduced as compared with other method which is not based on primary output.

• 한국산학기술학회논문지
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• 제10권11호
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• pp.3080-3086
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• 2009

피라미드 패턴이 가공된 도광판(LGP: Light Guide Plate)의 광출력 특성을 전산 모사를 통하여 조사하였다. 피라미드 패턴의 크기, 패턴의 면적 점유율, 피라미드 에칭각 등이 도광판 출력에 미치는 영향을 각각 조사하였으며, 이를 일반적으로 사용되는 반구형 패턴과 비교하였다. 반구형 패턴과의 비교 결과 패턴의 모양은 출력의 세기에 큰 영향을 주지 않는 것으로 나타났다. 또한 각 변수들의 영향을 분석한 결과, 패턴의 크기 변화는 출력에 거의 영향을 주지 않는 반면에 패턴의 면적 점유율과 피라미드 에칭각은 도광판의 출력에 비교적 큰 영향을 주는 것으로 나타났다. 따라서 패턴의 면적 점유율 및 에칭각을 조절함으로써 도광판 성능을 개선할 수 있는 것으로 조사되었다.

• 태양에너지
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• 제19권4호
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• pp.63-69
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• 1999

The conventional grid connected PV(Photovoltaic) system has a unstable output pattern due to its dependence on the weather condition, although solar-cell array averagely has a regular output characteristics to have a peak output nearly at noon. Therefore assuming the high density grid connection in the future, this unstable output pattern can be one of the main reasons to generate power disturbance such as voltage variation, frequency variation and harmonic voltage generation in low voltage distribution line. However general grid connected solar-cell system do not have functions to cope with these disturbances. Therefore this study proposed a advanced type grid connected PV system with functions to suppress output power fluctuation due to solar-cell array output variation and showed the levelling effect of fluctuation due to instantaneous array output variation.

• 한국광학회지
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• 제21권3호
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• pp.97-102
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• 2010

전산모사를 통하여 LGP 출력 분포를 조절할 수 있는 패턴 밀도 함수를 찾고 그 효과를 조사하였다. 패턴 밀도 함수, 즉 패턴 간격은 [Pexp(-y/70)+Qexp(+y/25)]R로 조사되었다. 이 함수를 이용하여 패턴의 간격을 조절하는 방식으로 반구형 패턴이 장착된 도광판을 설계하여 도광판 출력 분포를 분석한 결과 출력 분포가 등간격 패턴에 의한 출력 분포에 비하여 확연히 개선되는 것을 확인하였다. 또한 이 함수를 피라미드 패턴에 적용하여 도광판의 출력을 조사하였는데, 반구형 패턴의 경우와 마찬가지로 출력 분포가 개선되는 것을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.407-408
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• 2007

In this paper, we present a new method for classifying object using LVQ (Learning Vector Quantization) with flexible output layer. The proposed LVQ is a supervised learning method that dynamically generates output neurons and initializes automatically the weight vectors from training patterns. If the classes of the nearest output neuron is different from the class of the training pattern, a new output neuron is created and the given training pattern is used to initialize the weight vector of the created neuron. The proposed method is significantly different from the previous competitive learning algorithms in the point that the output neurons are dynamically generated during the learning process.

• 생물환경조절학회지
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• 제20권4호
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• pp.277-282
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• 2011

정확한 오이의 형상 및 위치를 인식하기 위하여 형상인식 알고리즘에 대한 연구를 수행하였다. 실제 영상에서 오이의 형상과 위치를 판정할 수 있도록 알고리즘을 개발한 결과, 다음과 같은 결론을 얻었다. 오이의 특징형상 검출은 $15{\times}15$ 간격으로 자동검출 되도록 처리하였다. 오이로 인식된 출력패턴 중에서 오검출된 출력패턴의 비율은 0.1~4.2%로 나타났다. 오류역전파 알고리즘은 영상크기를 $445{\times}363$, $501{\times}391$, $300{\times}421$, $450{\times}271$, $297{\times}421$의 크기에 따라 출력패턴을 얻은 결과 영상의 크기에 따른 검출 값의 변화는 없는 것으로 나타났다. 학습패턴 수가 25개로 증가하면 영상에서 다른 패턴을 검출하는 비율이 16.02%로 나타났다. 또한 학습패턴이 2개인 경우 40개의 영상에서 8개의 오이를 검출하지 못하였다. 학습패턴의 수가 7~9개인 경우 오이의 검출이 가장 좋은 것으로 나타났다.