• 한국의류학회지
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• 제47권6호
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• pp.1080-1095
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• 2023

Three-dimensional virtual fitting has become a trending practice in the fashion industry because of its productivity benefits, allowing garments to be virtually worn by avatar models without physical production. This study analyzed the variables influencing clothing pressure in both real and virtual fittings to expand the potential utility of pressure data derived from the latter. For this purpose, six sets of compression garments were created by combining two types of tricot fabrics and three types of reduced-pattern tops, with the clothing for real and virtual fittings having identical dimensions. Focus was directed to analyzing the correlation among clothing pressure, surface area deformation, and the mechanical properties of the fabrics. In real fittings, clothing pressure was influenced by multiple factors, including garment design, pattern reduction ratio, body shape, and fabric properties, consistent with existing knowledge. In virtual fittings, however, only the digital mechanical characteristics of the fabrics significantly influenced clothing pressure. The findings suggest that a more reliable implementation of clothing pressure in virtual fitting programs necessitates an approach that considers the complex structural information of garments.

• 천문학회지
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• 제34권1호
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• pp.1-8
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• 2001

We present a fast reduction method of survey data obtained using a single-dish radio telescope. Along with a brief review of classical method, a new method of identification and elimination of negative and positive bad channels are introduced using cloud identification code and several IRAF (Image Reduction and Analysis Facility) tasks relating statistics. Removing of several ripple patterns using Fourier Transform is also discussed. It is found that BACKGROUND task within IRAF is very efficient for fitting and subtraction of base-line with varying functions. Cloud identification method along with the possibility of its application for analysis of cloud structure is described, and future data reduction method is discussed.

• Journal of the Korean Statistical Society
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• 제12권1호
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1067-1076
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• 2006

Although the proportional hazards model is the most common approach used for studying the relationship of event times and covariates, alternative models are needed for occasions when it does not fit data. In the two-sample case, proportional odds models are useful for fitting data whose hazard rates converge asymptotically. In this thesis, we propose a new estimator of the relative odds ratio of the proportional odds model when two independent random samples are observed under uncensorship. We prove the asymptotic normality and consistency of the estimator by using martingale-representation. The efficiency of the proposed is assessed through a simulation study.

• Journal of the Korean Data and Information Science Society
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• 제7권2호
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• pp.203-210
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• 1996

A linear neural unit with a modified anti-Hebbian learning rule has been shown to be able to optimally fit curves, surfaces, and hypersurfaces by adaptively extracting the minor component of the input data set. In this paper, we study how to use the robust version of this neural fitting method for linear regression analysis. Furthermore, we compare this method with other methods when data set is contaminated by outliers.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.471-479
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• 2003

Moving averages are the most popular statistics in analyzing time-series data like stock indices. However, moving averages are quite sensitive to unusual observations. In other words, they are not robust against unusual observations. We introduce the moving averages in terms of an M-estimator, and show how we can take advantages of using the proposed moving averages in fitting the data more than usual moving averages.

• 품질경영학회지
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• 제25권1호
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• pp.44-55
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• 1997

In order to determine procedures for a, pp.opriate model selection of technological growth curves, numerous time series that were representative of growth behavior were collected according to data characteristics. Three different growth curve models were fitted onto data sets in an attempt to determine which growth curve models achieved the best forecasts for types of growth data. The analysis of the results gives rise to an a, pp.oach for selecting a, pp.opriate growth curve models for a given set of data, prior to fitting the models, based on the characteristics of the goodness of fit test.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.499-506
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• 2004

The Unscented Kalman Filter is known to outperform the Extended Kalman Filter for the nonlinear state estimation with a significance advantage that it does not require the computation of Jacobian but EKF has a competitive advantage to the UKF on the performance time. We compare both algorithms on training the artificial neural network. The validation data set is used to estimate parameters which are supposed to result in better fitting for the test data set. Experimental results are presented which indicate the performance of both algorithms.

• 한국의류산업학회지
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• 제19권6호
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• pp.749-758
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• 2017

The purpose of the present study is to develop a grading deviation, which is appropriate for the body type of women in thirties, by analyzing the three-dimensional body type. The materials for the study were adopted from the body measurement data of women in the age group of 30 to 39 years old, provided from Size Korea. By reflecting the factor analysis results using the three-dimensional shape measurement, deviations were derived. First, six factors influencing the changes in human body shape were derived as waist-hip length factor, bust-waist shape factor, back protrusion back shoulder factor, bust length factor, shoulder length factor, and frontal waist dart factor. The bust size and height, which can be easily utilized for the top original grading, were used for deriving a regression formula, and the deviation was set in accordance with the result. Second, by applying the deviation which reflects the changes in the body shape, the crimps which were generated due to the application of existing deviation were remarkably reduced, indicating that the grading of the present study is more fitting than the existing one. The deviation derived by the analysis of actual increase and decrease of body size was more fitting than the existing one. This was proved by actual wearing experiment, which represents the significance of this study.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2006년도 추계 종합학술대회 논문집
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• pp.520-523
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• 2006

최근 멀티미디어 데이터의 발달로 다양한 유무선 통신 환경에서 멀티미디어 데이터가 서비스되고 있다. 이러한 멀티미디어 데이터는 이동전화, PDA 노트북, PC 등 다양한 화면의 크기를 가지는 디스플레이 장치로 디스플레이 된다. 따라서 사용자의 디스플레이 장치에 따라 원영상의 크기를 조절할 필요성이 대두된다. 본 논문은 H.264 비디오를 사용자 화면에 적합하도록 크기를 변경하는 방법을 제안한다. 기존의 연구는 대부분이 영상의 크기를 줄이는 것이 대부분이었으나 본 논문에서는 해상도를 증가하여 서비스하는 방법에 관해 제안한다. 제안 방법을 CIF 및 QCIF 영상에 적용한 결과는 영상이 블록킹 현상 확대됨을 보여준다.