• Journal of Welding and Joining
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• 제13권4호
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• pp.132-146
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• 1995

Flaw classification(determination of the flaw type) and flaw sizing (prediction of the flaw shape, orientation and sizing parameters) are very important issues in ultrasonic nondestructive evaluation of weldments. In this work, new techniques for both classification and sizing of flaws in weldments are described together with extensive review of previous works on both topics. In the area of flaw classification, a methodology is developed which can solve classification problems using probabilistic neural networks, and in the area of flaw sizing, a time-of-flight equivalent(TOFE) sizing method is presented.

• Communications for Statistical Applications and Methods
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• 제29권5호
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• pp.603-614
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• 2022

The naive Bayes classifier is one of the most straightforward classification tools and directly estimates the class probability. However, because it relies on the independent assumption of the predictor, which is rarely satisfied in real-world problems, its application is limited in practice. In this article, we propose employing sufficient dimension reduction (SDR) to substantially improve the performance of the naive Bayes classifier, which is often deteriorated when the number of predictors is not restrictively small. This is not surprising as SDR reduces the predictor dimension without sacrificing classification information, and predictors in the reduced space are constructed to be uncorrelated. Therefore, SDR leads the naive Bayes to no longer be naive. We applied the proposed naive Bayes classifier after SDR to build a recommendation system for the eyewear-frames based on customers' face shape, demonstrating its utility in the top-k classification problem.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.1003-1008
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• 2001

In beamforming method, source positions are predicted by MUSIC (Multiple Signal Classification) power method and composite sound fields can then be decomposed into each partial field by beamforming, detenninistically without restriction of the distance between reference microphones and sources. However, reference microphone array shape is important in both MUSIC and beamforming method. Thus the present paper describes the effect of the reference microphone array shape.

• 한국의상디자인학회지
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• 제22권3호
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• pp.99-110
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• 2020

In terms of junior high school girls' growth patterns during early adolescence, are unlike childhood when relatively balanced growth patterns are found and high school years in which the normal adult body type is nearly reached, growth patterns displayed are imbalanced and rapid. In fact, diverse size changes by body part growth occur significantly different from individual to individual. Therefore, it has been hard for junior high school students to select their proper size when buying school uniforms. This study attempted to acquire basic data needed to address adolescent body shapes and school uniform patterns for junior high school girls, using the data from the 7th Size Korea Survey (2015). Specifically, it provides basic data for the development of school uniform patterns through the classification of their body into particular types, After extracting body shape components and a cluster analysis using ANOVA. According to a factor analysis conducted to determine body shape components, six factors were obtained: Factor 1: bulk and horizontal size, Factor 2: body height and length, Factor 3: shoulder shape and length, Factor 4: shape of upper body, Factor 5: lower drop, Factor 6: upper drop with a variance of 81.46%. To classify junior high school girls' body shape and determine their characteristics, a cluster analysis was performed with the variables obtained using factor analysis. Body shape was classified into three different types: Type 1 accounted for 30.7%. This was a short, slender body with the smallest bulk, size, and upper drop. Type 2 accounted for 24.9%. This was the largest in bulk and horizontal size and highest and length as well. Type 3 accounted for 44.5%. This type was close to average in terms of horizontal size, length and height, and high drop values. To develop school uniforms with great accuracy and body fit for junior high school students, there should be further studies on changes in body shape and their causes. The study results can serve as basic data for comparing branded school uniform patterns for junior high school girls and developing school uniform patterns based on body shape, using 3D virtual clothing simulations.

• 지능정보연구
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• 제18권3호
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• pp.1-12
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• 2012

길 옆이나 공원 또는 조경시설에는 많은 나무들을 포함하고 있다. 비록 많은 나무들이 쉽게 우리 주변에서 보이지만, 일반인들이 그 나무의 이름, 종류 및 정보들을 얻기가 힘든 경우도 있다. 나무의 이름이나 정보를 얻기 위하여 인터넷이나 서적을 이용하여 찾아 분류하여야 한다. 나무의 구성 요소는 잎, 꽃, 수피 등이 있는데, 일반적으로 나무의 잎을 이용하여 분류할 수 있다. 이는 잎이 형태, 잎맥 등의 정보를 포함하고 있기 때문이다. 잎의 형태는 나무의 종류를 결정하는데 중요한 역할을 하며, 또한 잎맥을 포함한 텍스쳐도 나무의 종류를 분류하는데 유용하게 사용된다. 본 논문에서는 형태와 텍스쳐를 조합한 특징들을 이용한 잎 분류 시스템에 대한 성능을 평가하였다. 형태 특징으로는 푸리에 기술자를 이용하였고, 텍스쳐 특징으로는 GLCM 또는 웨이브릿 기술자, 그리고 그들의 조합을 사용하였다. 그리고 사용된 데이터는 인터넷에서 용이하게 구할 수 있고, 분류 성능평가에 사용되는 Flavia 잎 데이터 셋을 사용하였다. 형태와 텍스쳐를 기반으로 하는 다양한 조합을 가진 분류 시스템의 성능을 인식률과 PR(precision-recall) 지수로 평가하고, 성능을 비교하였다. 성능평가 결과, 형태와 텍스쳐를 조합한 특징들을 갖는 시스템의 성능이 조합하지 않은 시스템의 성능보다 나아짐을 알 수 있었다.

• 복식문화연구
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• 제8권1호
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• pp.133-144
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• 2000

The purpose of this study was to classify women's face types by visual distinction and to analyze the measurement of face types. A survey was conducted by subjects of 167 women's college students in Kwangju City and Chonnam area. Data were analyzed by Frequencies, Mean, one way ANOVA and Ducan's Multiple Range Test. The major results were as followed ; ·Women's face types were classified by 7 types and there were oblong shape(28.3%), egg shape(25.7%), round shape(23.9%), square shape(12.4%), inverted triangle shape(5.3%), diamond shape(3.5%), triangle shape(0.8%) in the subjects. ·From the measurements of the women's face, index of face length to face breadth was 1.38, it means that the index was different from the other refferences. And the lower face length was longer than the upper and the middle face lengths. ·Differences From those measurements like forehead breadth, face length/bizigion breath(p〈.001), bizigion breadth, bignathion slopper, stature(p〈.01) and trichion breadth, tragion-menton length(p〈.05) were significant in the classified face types.

• 한국컴퓨터그래픽스학회논문지
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• 제24권5호
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• pp.31-39
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• 2018

본 논문에서는 흉부 CT 영상에서 결절의 밝기값, 재질 및 형상 증강 영상 기반의 GGN-Net을 이용해 간유리음영 결절 자동 분류 방법을 제안한다. 첫째, 입력 영상에 결절 내부의 고형 성분의 유무 및 크기 정보가 포함될 수 있도록 밝기값, 재질 및 형상 증강 영상의 활용을 제안한다. 둘째, 다양한 입력 영상을 여러 개의 컨볼루션 모듈을 통해 획득한 특징맵을 내부 네트워크에서 통합하여 훈련하는 GGN-Net를 제안한다. 제안 방법의 분류정확성 평가를 위해 순수 간유리음영 결절 90개와 고형 성분의 크기가 5mm 미만인 혼합 간유리음영 결절 38개, 5mm 이상 고형 성분의 크기를 가지는 혼합 간유리음영 결절 23개의 데이터를 사용하였으며, 입력 영상이 간유리음영 결절 분류 결과에 미치는 영향을 비교하기 위해 다양한 입력 영상을 구성하여 결과를 비교하였다. 실험 결과, 밝기값, 재질 및 형상 정보가 함께 고려된 입력 영상을 사용한 제안 방법이 정확도가 82.75%로 가장 좋은 결과를 보였다.

• 한국정밀공학회지
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• 제32권5호
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• pp.463-470
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• 2015

Solar cell is typical representative of renewable green energy. Silicon wafer contributes about 66 percent to its cost structure. In its manufacturing, micro-cracks are often occurred due to manufacturing process such as wire sawing, grinding and cleaning. Their detection and classification are important to process feedback information. In this paper, a classification method of micro-cracks is proposed, based on the fusion of principal component analysis(PCA) and neural network. The proposed method shows that it gives higher results than single application of two methods, in terms of shape and size classification of micro-cracks.

• 한국컴퓨터정보학회논문지
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• 제20권8호
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• pp.15-21
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• 2015

This study proposed a Sasang constitution classification system that can increase the objectivity and reliability of Sasang constitution diagnosis using the image of frontal face, in order to solve problems in the subjective classification of Sasang constitution based on Sasang constitution specialists' experiences. For classification, characteristics indicating the shapes of the eyes, nose, mouth and chin were defined, and such characteristics were extracted using the morphological statistic analysis of face images. Then, Sasang constitution was classified through a SVM (Support Vector Machine) classifier using the extracted characteristics as its input, and according to the results of experiment, the proposed system showed a correct recognition rate of 93.33%. Different from existing systems that designate characteristic points directly, this system showed a high correct recognition rate and therefore it is expected to be useful as a more objective Sasang constitution classification system.

• 한국ITS학회 논문지
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• 제22권3호
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• pp.160-174
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• 2023

자율주행차량에서 핵심적인 역할을 수행하는 LiDAR의 주변 환경 검지 시인성을 향상시키기 위해서는 LiDAR 성능의 개선 뿐만 아니라, 검지 물체의 개선도 필요하다. 이에 본 연구는 LiDAR 센서를 통해 수집되는 point cloud 데이터 기반의 형상인식 알고리즘을 활용하여 자율주행차량이 인식하기에 유리한 교통안전표지 형상과 개선방안을 제시하였다. 실험을 위해 point cloud 활용 연구에서 보편적으로 활용되는 DBSCAN 기반의 도로표지 인식·분류 알고리즘을 개발하고 실도로 환경에서 32ch LiDAR를 활용, 도로표지 5종에 대한 인식 성능 실험을 수행하였다. 연구결과, 정사각형이나 원형보다는 상하 비대칭이 있는 정삼각형, 직사각형과 같은 형상이 보다 적은 점군의 수로도 검지가 가능하고, 83% 이상의 높은 분류 정확도를 보였다. 또한, 정사각형 표지의 크기를 1.5배 확대할 경우, 분류 정확도를 향상시킬 수 있었다. 이러한 결과는 미래 자율주행 시대의 센서를 위한 전용 도로·교통안전시설물 개선 및 신규 시설물 개발에 활용될 수 있을 것으로 기대된다.