• 한국의류산업학회지
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• 제17권3호
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• pp.447-461
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• 2015

The purpose of this study is to develop a torso pattern that is highly representative for the proper body shape of women in their thirties. Size data of the women with age of 30 through 39 from the database of Size Korea 2004 were used for the study. In order to develop a master pattern which will be used as the benchmark for grading of research group, 4 existing torso block drafting methods were compared based on the data gathered and the block with the highest evaluation score was utilized as a reference point. For the analysis, data was divided into four types, only the data of 138 subjects which were evaluated at least by four or more experts as valid were used for the study. The major results can be summarized as follow. The women of bust girth of 91cm and height of 160cm which was turned out to be representative type of research group were used as standard measurement for the purpose of reflecting not only curve length of the 3D analysis measurement but also the difference between front and back thickness to the pattern. Dart locations were set based on front and back torso ease, shoulder area revisions, front sagging length 1.5cm and cross section crevice length analysis. According to the experts' appearance evaluation of the pattern was found to be better than the control pattern which was regarded as the best among 4 patterns created based on existing torso block drafting methods.

• 한국컴퓨터정보학회논문지
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• 제3권1호
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• pp.95-112
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• 1998

역전도 알고리즘은 연관 기억장치, 음성 인식, 패턴인식, 로보틱스등 여러 응용 분야에 다양하게 사용되고 있다. 그러나 새로운 학습 패턴을 추가적으로 학습시키려면 이전에학습했던 모든 패턴과 추가되는 패턴을 갖고 처음부터 새로운 학습을 수행하여야 한다. 이는 패턴의 개수가 점차 늘어날수록 학습에 소요되는 시간이 기하 급수적으로 길어지는 결과를 초래하게 된다. 따라서 주기적으로 다량의 데이터를 추가로 학습을 할 경우에 이러한 점진적 학습은 반드시 해결해야 할 문제점으로 간주된다. 본 논문에서는 기존의 신경망 구조는 그대로 유지하면서 대표 패턴을 추출해 추가 학습을 수행하는 방법을 제안하고 제안된 기법의 효율성을 위해 기계 학습 분야의 벤치마크로 많이 사용되는 Monk's data와 Iris data에 적용해 보았다.

• Communications for Statistical Applications and Methods
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• 제24권3호
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• pp.211-226
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• 2017

The chain-ladder method, for which run-off data is employed is popularly used in the rate-adjustment and loss-reserving practices of non-life-insurance and health-insurance companies. The method is applicable when the underlying assumption of a consistent development pattern is in regards to a cumulative loss payment after the occurrence of an insurance event. In this study, a modified chain-ladder algorithm is proposed for when the assumption is considered to be only partially appropriate for the given run-off data. The concept of a structural-change point in the run-off data and its reflection in the estimation of unpaid loss amounts are discussed with numerical illustrations. Experience data from private health insurance coverage in Korea were analyzed based on the suggested method. The performance in estimation of loss reserve was also compared with traditional approaches. We present evidence in this paper that shows that a reflection of a structural-change point in the chain-ladder method can improve the risk management of the relevant insurance products. The suggested method is expected to be utilized easily in actuarial practice as the algorithm is straightforward.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.111-122
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• 2018

The purpose of this study was to investigate the bodice prototype method suitable for the upper body shape of old-old aged women using the 3D anthropometric data. And it was to provide the basic data for the upper body garments of old-old aged women. In the overall appearance evaluation, the B pattern was rated as 4.00, and it was evaluated as the most suitable for the bodice prototype of the old-old aged woman. The E pattern was rated lower than normal, and the L pattern and the S pattern were found to be inadequate for older female bodice prototypes. As a result of the measurement of the waist and bust air gap of bodice prototype, the air gap of the bust was not significantly different between the patterns. But the waist air gap showed the largest difference between the L pattern and the S pattern. As a result of evaluating the appearance, the amount of space in the state of 3D simulation, and the air gap, the pattern B appeared to be the most appropriate prototype for the old-old aged women's body shape. However, there is a tendency that the shoulder end point is biased toward the back, so it is necessary to set the inclination of the back shoulder line to be more gentle. Conversely, the front shoulder should be more inclined. In the case of the 3D simulation, the B pattern showed that the other parts generally fit well. In the case of the 3D simulation program used in this study, it was evaluated that it is suitable only for the normal body shape because it is impossible to set the isometric angle which is one of the characteristics of the older female body shape. A study on the bodice prototype suitable for the bent body shape should be carried out through experiments on the actual body shape of various elderly women. In order to cope with the increase of elderly people who are familiar with digital, I think it is necessary to develop an avatar that reflects the old female body shape.

• 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.

• 한국의상디자인학회지
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• 제21권3호
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• pp.149-160
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• 2019

Body fit should be the first point considered for satisfying the functionality of clothes and thus it is the most essential condition. Based on previous research, this article studied the basic slacks pattern with a high body fit using body measurement of adolescent boys. The purpose of this study is to propose basic data for the production of slacks. Research was performed on the physical measurements of adolescent boys from 13-18 years old obtained from the '6th Korean National Physical Standard Reports' by SIZEKOREA. First, six types of experimental slacks basic patterns were produced applying the average body sizes of adolescent boys. Second, a single slacks basic pattern was selected, which received the best response based on appearance from the clothing evaluators. Then, the slacks basic pattern for adolescent boys was finalized by modifying and amending the selected pattern with two more clothing experiments. The data analysis was performed using descriptive statistics, ANOVA, and t-test using the SPSS program. The results of this study have been obtained as follows. The modifications and adjustments were done based on Crotch, Thigh Circumference, waist circumference, and hip circumference.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2005년도 종합학술대회
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• pp.147-153
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• 2005

최근 인터넷 쇼핑몰에서 상품을 구매하는 고객들에게 편의성과 효율성을 제공하기 위하여 구매자들의 선호도나 가격에 맞는 상품을 추천해 주는 연구들이 활발하게 진행되고 있지만추천된 상품들의 구매시점에 관한 연구는 찾아보기 어렵다. 이에 본 논문에서는 인터넷 쇼핑몰의 적극적인 마케팅 일환으로 판매가격의 흐름을 시계열 패턴으로 분석하여 상품의 구매시점 정보를 제공하는 방안을 제안한다. 이를 위하여 과거의 판매 기록 데이터베이스에 있는 판매가격의 기준이 되는 패턴과 유사한 변화를 보이는 패턴을 정규화된 유사도로써 검색하고, 검색된 가격 패턴을 기준으로 미래의 가격 패턴의 변화를 분석하여, 미래 가격 패턴의 변화 폭에 따라 상품에 대한 구매시점을 제공한다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제2권8호
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• pp.565-570
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• 2013

기존의 순차 패턴 마이닝 기법은 주로 시점 기반 이벤트를 중심으로 연구되었다. 그러나 실생활에는 시작 시점과 종료 시점과 같은 시간 간격을 갖는 인터벌 이벤트가 많이 발생한다. Allen 연산자를 기반으로 두 인터벌 이벤트 사이의 인터벌 패턴을 탐사하는 기존의 기법은 세 개 이상의 인터벌 이벤트 사이에서 인터벌 패턴이 여러 의미로 해석될 수 있는 문제점을 가지고 있다. 이 논문은 인터벌 패턴 탐사에서 모호성 제거를 위한 효율적인 순차 탐색 마이닝 기법인 I_TPrefixSpan 알고리즘을 제안한다. 제안하는 기법은 인터벌 이벤트에 대한 이벤트 시퀀스를 생성함으로써 모호성을 제거하고 이벤트 시퀀스에 존재하는 항목만을 대상으로 순차 탐색함으로써 후보 집합 생성을 최소화 할 수 있다. 성능 평가를 통하여 제안하는 방법이 기존의 방법에 비하여 보다 효율적임을 보인다.

• Journal of Ecology and Environment
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• 제40권1호
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• pp.34-44
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• 2016

Background: Little is known about how chemical water quality is associated with ecological stream health in relation to landuse patterns in a watershed. We evaluated spatial characteristics of water quality characteristics and the ecological health of Dongjin-River basin, Korea in relation to regional landuse pattern. The ecological health was assessed by the multi-metric model of Index of Biological Integrity (IBI), and the water chemistry data were compared with values obtained from the health model. Results: Nutrient and organic matter pollution in Dongjin-River basin, Korea was influenced by land use pattern and the major point sources, so nutrients of TN and TP increased abruptly in Site 4 (Jeongeup Stream), which is directly influenced by wastewater treatment plants along with values of electric conductivity (EC), bacterial number, and sestonic chlorophyll-a. Similar results are shown in the downstream (S7) of Dongjin River. The degradation of chemical water quality in the downstream resulted in greater impairment of the ecological health, and these were also closely associated with the landuse pattern. Forest region had low nutrients (N, P), organic matter, and ionic content (as the EC), whereas urban and agricultural regions had opposite in the parameters. Linear regression analysis of the landuse (arable land; $A_L$) on chemicals indicated that values of $A_L$ had positive linear relations with TP ($R^2=0.643$, p < 0.01), TN ($R^2=0.502$, p < 0.05), BOD ($R^2=0.739$, p < 0.01), and suspended solids (SS; ($R^2=0.866$, p < 0.01), and a negative relation with TDN:TDP ratios ($R^2=0.719$, p < 0.01). Conclusions: Chemical factors were closely associated with land use pattern in the watershed, and these factors influenced the ecological health, based on the multimetric fish IBI model. Overall, the impairments of water chemistry and the ecological health in Dongjin-River basin were mainly attributes to point-sources and land-use patterns.

• 한국측량학회지
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• 제24권1호
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• pp.131-138
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• 2006

최근 점사상을 활용하는 GIS 분야에서 많은 양의 점사상 축적과 함께 점분포 패턴을 정량적으로 평가하기 위한 알고리즘의 개발이 이루어지고 있다. 여러 연구에서 K-지표를 활용하여 점사상의 공간적 밀집 여부의 검증이 가능하며, 사건과 배경의 상호 관련성 평가가 가능함을 증명하고 있다. 한편 GIS 데이터로서의 점사상은 측량에 의해 실좌표가 관측된 사상보다는 주소와 같은 위치참조에 의해 간접적으로 좌표가 주어지는 경우가 많으며, 경우에 따라서는 통계자료와 같이 행정구역과 같은 지역단위의 집계자료로 대표되어 점사상 각각이 좌표를 가지지 못하는 경우도 많다. 본 연구에서는 GIS를 이용한 공간 분석 기법으로서 K-지표를 계산할 때, 집계자료의 사용이 K-지표의 산출에 미치는 영향을 평가하기 위하여, 원데이터(지번단위), 지형적인 집계(블록 단위), 행정적인 집계(행정구역 단위) 등 세 가지 형태의 데이터로부터 산출된 K-지표를 비교, 분석하였다. 연구결과 가까운 거리에서 밀집이 심하게 일어나는 점사상의 경우에는 행정구역과 같은 큰 지역단위를 이용하면 결과의 왜곡이 심하게 발생하여 활용이 곤란하나, 블록단위의 K-지표는 원데이터의 K-지표와 거의 유사함을 알 수 있었다.