• 대한한의학회지
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• 제38권4호
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• pp.104-109
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• 2017

Objectives: Epicardial fat is true visceral fat that is known to be associated with metabolic syndrome, high abdominal fat, insulin resistance, coronary artery diseases, low coronary flow reserve and subclinical atherosclerosis. Dampness-Phlegm pattern is one of the pattern diagnosis of traditional Korean medicine. Previous studies showed that Dampness-Phlegm pattern is associated with hypertension, dyslipidemia, metabolic syndrome. This study is intended to find association between Dampness-Phlegm pattern and epicardial fat thickness. Methods: This study was a community-based single center trial. Ischemic stroke patients within 30 days after their ictus were enrolled. Epicardial fat thickness was measured using transthoracic echocardiography. Other measured and obtained variables are medical history, weight, height, body mass index, fasting blood glucose, cholesterol, triglycerol, high density lipoprotein, lipid and low density lipoprotein. Results: Three hundred sixty six were enlisted, and one hundred forty were diagnosed with the Dampness-Phlegm pattern. Dampness-Phlegm pattern group had significantly thicker epicardial fat. Binary logistic regression also showed statistically significant result. Conclusions: This study showed close association between epicardial fat and Dampness-Phlegm pattern. This result suggests a clue to standardization of pattern identification.

• 한국의류산업학회지
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• 제12권1호
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• pp.1-9
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• 2010

A purpose of this study was to find out how the casual and formal style clothes of stripe pattern giving variety by pattern direction, pattern width, and contrast coloration have an effect on image of wearers. 432 stimuli were made and 2,800 testee evaluated them using semantic differential scale. As a result, five image dimensions were drawn as a factor of attractiveness, activeness, gracefulness, visibility, and tenderness. In consequence of analysing the image difference by stripe pattern and clothing style, the stripe pattern and clothing style affect image presentation as a significant clue. And besides, as a result of positioning stimuli by image, pattern direction, coloration, and tone combination were important clues that decide image. Consequently, clothing style, stripe pattern, and contrast coloration were made clear as an efficient parameter in image presentation of clothing wearers.

• 한국의류산업학회지
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• 제12권5호
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• pp.642-649
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• 2010

This study was designed to generate briefs pattern for women in their twenties using 3D parametric body model. 151 women in their 20's were random sampled and measured using Martine's anthropometry. And one subject was chosen as the representative subject for 3D scanning. Parametric model was generated of using CATIA P3, Unigraphics NX4.0, Rapidform 2006. And the 3D surface of parametric body model was flattened onto the 2D plane. 3 downscale ratios(0%, 10%, 15%) were applied to generated pattern to figure out what downscale ratio was suitable to make briefs with stretch fabric. 4 kinds of experimental briefs were made with stretch fabrics(0%, 10%, 15% downscale) and worn on the dressform. Subjective evaluation on the appearance was done and the data was analyzed by ANOVA with post-hoc test. Briefs pattern was generated through the process of flattening the parametric surface and arranging the patches to make briefs pattern by dart manipulation. The different ration of outline and area between 3D surface and 2D pattern were 0.22% and 0.09% respectively. It showed that a parametric model could provide a desirable pattern with minute size error. The results of subjective evaluation on the appearance of 4 experimental briefs showed that stretch briefs with 15% downscale ratio was evaluated most highly in most items. Findings imply that it is feasible to apply 3D parametric model to generate patterns for various items considering various fabric properties.

• 한국의류학회지
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• 제32권5호
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• pp.846-858
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• 2008

This study was designed to propose a method to draft bodice block pattern from 3D body scan data. Subjects were ten elderly women in their 60's, who wear basic size(B: 94cm, W: 82cm) garment. Scanning was done using 3D whole body scanner(WB4, Cyberware). Measurements for 3D data and cross section were attained using Auto CAD, by which a upper bodice pattern for elderly women was drawn on the basis of short measured method. The results are as following: As for most items, no significant differences were shown between measurements from Martin's anthropometry and those from 3D scan data, suggesting measurement from 3D scan data could be used to draft a pattern. The drafting equations acquired were as follows; width of pattern=B/2+5.5, width of waist=W/2+3.5cm, dart amount=8cm. Dart distributions were 23%(B.P.) : 20%(front armpit) : 17%(side seam) : 18%(back armpit) : 15%(back protruded point) : 7% (center back line). Through wearing test using 5-point Likert scale, resultant pattern was evaluated as appropriate for elderly women's pattern to get over 4 point. As a result, it might be said that 3D scanning application is effective for elderly women in that it doesn't take time so much as Martin's anthropometry and that their body shape vary compared with those of young women.

• 대한산업공학회지
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• 제28권1호
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• pp.112-127
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• 2002

A useful pattern is a pattern that contributes much to learning. For a classification problem those patterns near the class boundary surfaces carry more information to the classifier. For a regression problem the ones near the estimated surface carry more information. In both cases, the usefulness is defined only for those patterns either without error or with negligible error. Using only the useful patterns gives several benefits. First, computational complexity in memory and time for learning is decreased. Second, overfitting is avoided even when the learner is over-sized. Third, learning results in more stable learners. In this paper, we propose a pattern 'utility index' that measures the utility of an individual pattern. The utility index is based on the bias and variance of a pattern trained by a network ensemble. In classification, the pattern with a low bias and a high variance gets a high score. In regression, on the other hand, the one with a low bias and a low variance gets a high score. Based on the distribution of the utility index, the original training set is divided into a high-score group and a low-score group. Only the high-score group is then used for training. The proposed method is tested on synthetic and real-world benchmark datasets. The proposed approach gives a better or at least similar performance.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2000년도 춘계종합학술대회
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• pp.296-300
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• 2000

ATM 망에서 전송률 기반의 ABR(Available Bit Rate) 흐름제어를 위한 스위치는 크게 EFCI(Explicit Forward Congestion Indication)와 ER(Explicit Rate) 스위치로 구분하고 있다. 기존의 논문에서는 효율적인 ABR 트래픽 관리를 위해 EFCI와 ER 스위치 방식의 상호 혼용 운영의 타당성을 밝히고 ABR 트래픽을 poisson 패턴으로 간주하고 EFCI와 ER 스위치 알고리즘에 적용했었다. 그러나 최근 네트워크 환경에서는 트래픽 패턴이 poisson 패턴 보다는 self-similar 패턴에 더 가깝다는 것이 입증되어 왔다. 본 논문에서는 self-similar 트래픽 패턴을 적용시켜 기존의 poisson 패턴의 ATM 망 내에서의 EFCI와 ER 스위치 상의 ABR 트래픽 성능분석을 비교, 고찰 하고자 한다.

• 한국콘텐츠학회논문지
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• 제8권5호
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• pp.44-51
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• 2008

시계열 데이터에서 패턴을 찾고 검색하는 문제는 여러 분야에서 오랫동안 관심을 가지고 연구되어 왔다. 본 논문은 시간의 흐름에 따라 값의 변화를 나타내는 시계열 형태의 주식 데이터에 적용할 수 있는 새로운 패턴 매칭 방법을 제안한다. 우선, 의미를 기반으로 패턴을 정의하고 정의된 패턴에 일치하는 데이터들을 추출하여 학습모델을 작성한다. 그리고 새로운 질의 시퀀스가 어떤 종류의 패턴과 일치하는가는 각 학습 모델과의 유사도를 측정하여 결정하게 된다. 학습 모델은 시계열을 잘 설명하는 것으로 알려진 은닉 마코프 모델을 사용하여 작성하였다. 실험 결과 은닉 마코프 모델의 특성을 사용하여 생성된 각 학습 모델은 주어진 의미를 잘 나타내는 패턴을 생성하였으며, 새로운 시퀀스가 주어졌을 때 일치하는 패턴에 따라서 시퀀스가 가진 의미를 파악할 수 있었다.