• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 춘계학술대회
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• pp.481-490
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• 2000

First, in order to improve selecting method of quality characteristic level desired by customers, S/H(Signal-to-Noise) ratio of Taguchi in larger-the-better characteristics was applied. Second, the Matrix classification standard of ACE(Attribute Categorization Evaluation) is presented using KANO model on difference analysis of importance and satisfaction through questionnaire from customers. This is for reflecting the diverse EC which customers want in EC quality sufficiently. Also, establishing sales point will be helpful in business strategy through presenting types that are able to decide planning quality. Third, the important measure of EC about correlation among quality characteristics and a new weight o( EC are calculated depending on importance of EC and the weight of customer attribute and materials of relationship matrix through correlation matrix analysis.

• 전자공학회논문지S
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• 제36S권3호
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• pp.57-67
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• 1999

본 논문에서는 영상 부호화시 전처리 과정을 수행함으로써 잡음을 제거하는 새로운 알고리듬을 제안하였다. 제안한 알고리듬은 영상의 선명도를 유지할뿐아니라 전체적인 부호화 효율을 높여준다. 효율향상 과정은 다음과 같다. 첫째 블록 특성에 다라 영역을 분류하며, 둘째로는 Canny 연산자와 Sobel 연산자를 이용하여 경계선 방향을 얻는다. 세 번째로 블록 특성과 경계선 방향에 따라 방향성 형태학적 필터를 구한다. 형태학적 필터링은 영상내 존재하는 잡음을 제거하고, 표준 영상의 경우 인간이 시각적으로 느낄 수 없는 성분을 제거한다. 형태학적 필터링은 경계선 성분을 손실시키는 결과가 발생하지만, 제안한 알고리듬은 손실된 경계선 영역을 복원하는 과정을 거친다. 그러한 과정의 결과로, 전체적인 부호화 효율이 향상된다. 특히, 제안한 알고리듬을 적용한 표준영상의 경우, 약 50-50%의 비트 발생량이 줄어드는 결과를 나타내었다. 잡음 분산값을 달리하여 만든 잡음 영상에 제안한 방법을 적용한 결과, 영상의 선명도를 유지하였다. 제안한 알고리듬은 인간의 시각 특성을 고려한 미세한 잡음 제거 방법에서 우수한 성능을 나타내었으며, 영상의 선명도를 유지하는 것을 보여 주었다.

• ETRI Journal
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• 제28권6호
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• pp.761-769
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• 2006

In this paper, we address the problem of closely spaced source localization using sensor array processing. In particular, the performance efficiency (measured in terms of the root mean square error) of the unconditional maximum likelihood (UML) algorithm for estimating the direction of arrival (DOA) of near-field sources is evaluated. Four parameters are considered in this evaluation: angular separation among sources, signal-to-noise ratio (SNR), number of snapshots, and number of sources (multiple sources). Simulations are conducted to illustrate the UML performance to compute the DOA of sources in the near-field. Finally, results are also presented that compare the performance of the UML DOA estimator with the existing multiple signal classification approach. The results show the capability of the UML estimator for estimating the DOA when the angular separation is taken into account as a critical parameter. These results are consistent in both low SNR and multiple-source scenarios.

• 대한전자공학회논문지
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• 제27권6호
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• pp.929-936
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• 1990

This paper describes the method of the Korean character recognition by means of feature points extraction. Also, the preprocessing neural chip for noise elimination, smoothing, thinning and feature point extraction has been designs. The subpatterns were separated by means of advanced index algorithm using mask, and recognized by means of feature points classification. The separation of the Korean character subpatterns was abtained about 97%, and the recognition of the Korean characters was abtained about 95%. The preprocessing neural chip was simulated on SPICE and layouted by double CMOS 2\ulcorner design rule.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.525-528
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• 1999

Abstract - In this paper, a segmentation method for brain Magnetic Resonance(MR) image using region clustering technique with statistical distribution of gradient image and fuzzy rules is described. The brain MRI consists of gray matter and white matter, cerebrospinal fluid. But due to noise, overlap, vagueness, and various parameters, segmentation of MR image is a very difficult task. We use gradient information rather than intensity directly from the MR images and find appropriate thresholds for region classification using gradient approximation, rayleigh distribution function, region clustering, and merging techniques. And then, we propose the adaptive fuzzy rules in order to extract anatomical structures and diseases from brain MR image data. The experimental results shows that the proposed segmentation algorithm given better performance than traditional segmentation techniques.

• 전자공학회논문지B
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• 제31B권9호
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• pp.142-149
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• 1994

Hangul is expressed by the basic elements, twenty-four characters. Because these characters are composed of a circle and lines, Hough transform(HT), which has a powerful performance on the noise in extracting lines, is introduced. Many difficulties often occur when the original HT is used to extract strokes and it's direction, position and length from handwritten Hangul characters. Original HT has eight direction selected as samples in the transformed image should be calculated for these eight directions. In this paper, the generalized sampling rule is suggested. According to the rule, those directions which are possible to a line are the only thing to be calculated. The experoment result turned out to be higher than the method that Chen suggested in sampling rate. Anogher experiment result is done on the 1800 handwritten Hangul characters that 10 persons wrote. By feature extracting the oritinal HT and sampling HT. And as a result of six type classification, the suggested method came out higher than original HT.

• 대한전자공학회논문지SP
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• 제38권4호
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• pp.118-118
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• 2001

본 논문에서는 블록 분류와 적응적 필터링을 이용하여 블록 기반 부호화에서의 양자화 잡음을 제거하는 후처리 방법을 제안하였다. 제안한 방법에서는 블록 분류, 적응적인 블록 간 필터링, 및 블록 내 필터링의 단계로 이루어진다. 먼저, 각 블록을 8x8 DCT 계수 분포에 따라 7개의 클래스로 분류하고, 인접한 두 클래스 정보에 따라 적응적인 블록 간 필터링을 수행한다. 그리고 에지 블록으로 분류된 블록에 대하여 에지맵을 이용한 블록 내 필터링을 수행한다. 실험결과로부터 제안한 방법이 기존의 방법에 비하여 객관적 화질 측면에서는 유사하지만, 주관적 화질 측면에서 보다 우수함을 확인하였다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 2001년도 추계학술발표대회 논문집 제20권 2호
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• pp.349-352
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• 2001

본 논문은 수중방사소음을 이용한 선박 클래스 식별을 위하여 비선형매핑법을 제안한다. 수중방사소음으로부터의 특성벡터 추출과정은 신호의 주파수영역 변환, 규준화, 및 특성추출 과정들을 포함하며, 비선형매핑법은 이러한 과정을 통하여 추출된 특성벡터를 입력으로 선박의 클래스를 분류한다. 제안된 비선형매핑법은 인공적으로 생성한 데이터들을 이용한 시뮬레이션을 통해 검증되고, 실제 데이터를 이용한 테스트 결과들은 본 논문에서 제시한 방법이 식별을 위해 사용될 수 있음을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.3050-3065
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• 2016

Neural networks (NNs) are extensively used in applications requiring signal classification and regression analysis. In this paper, a NN based threshold selection algorithm for 60 GHz millimeter wave (MMW) time of arrival (TOA) estimation using an energy detector (ED) is proposed which is based on the skewness, kurtosis, and curl of the received energy block values. The best normalized threshold for a given signal-to-noise ratio (SNR) is determined, and the influence of the integration period and channel on the performance is investigated. Results are presented which show that the proposed NN based algorithm provides superior precision and better robustness than other ED based algorithms over a wide range of SNR values. Further, it is independent of the integration period and channel model.

• 소음진동
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• 제3권4호
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• pp.361-371
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• 1993

A psychological experiment is conducted by using the method of selected description to find out appropriate terms for expressing the attributes of sounds. It is true that the term is an important clue to estimate the sensation or emotion of sounds even though it does not directly express them. On the basis of the results, it is found in the subjective impression that adjectives are classified into 8 types of group: "pleasant and bright", "weak", "mild and beautiful", "shocking", "unpleasant", powerful", "dark", and "dull" feeling. Also, it is found that "loud", "noisy" and "annoying" terms have the meaning of "strong, powerful and magnificant", "metallic and clamorous", and "unpleasant and unpleasing" feeling as a meaning Korean language respectively.ot;, "metallic and clamorous", and "unpleasant and unpleasing" feeling as a meaning Korean language respectively.nguage respectively.