• 전기학회논문지
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• 제56권12호
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• pp.2265-2267
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• 2007

The purpose of this work is to compare the local fitting and global fitting approaches while applying regression model to the PTT-BP data for the prediction of exercise blood pressures. We used linear and nonlinear regression models to represent the PTT-BP relationship during exercise. PTT-BP data were acquired both under resting state and also after cycling exercise with several load conditions. PTT was calculated as the time between R-peak of ECG and the peak of differential photo-plethysmogram. For the identification of the regression models, we used local fitting which used only the resting state data and global fitting which used the whole region of data including exercise BP. The results showed that the global fitting was superior to the local fitting in terms of the coefficient of determination and the RMS (root mean square) error between the experimental and estimated BP. The nonlinear regression model which used global fitting showed slightly better performance than the linear one (no significant difference). We confirmed that the wide-range of data is required for the regression model to appropriately predict the exercise BP.

• 한국국방경영분석학회지
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• 제25권2호
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• pp.158-169
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• 1999

This paper is concerned with the application of generalized linear interactive modelling(GLIM) to the binary categorical data. To analyze the categorical data given by a contingency table, finding a good-fitting loglinear model is commonly adopted. In the case of a contingency table with a response variable, we can fit a logit model to find a good-fitting loglinear model. For a given $2^4$ contingency table with a binary response variable, we show the process of fitting a loglinear model by fitting a logit model using GLIM and SAS and then we estimate parameters to interpret the nature of associations implied by the model.

• 패션비즈니스
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• 제17권5호
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• pp.57-69
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• 2013

The purpose of this study is to compare the traditional shopping model and virtual avatar fitting model with regards to credibility and favorable impression effects on shopping mall satisfaction, product preferences, and purchasing intentions of apparel e-commerce. Questionnaires are distributed to 10-30s years old consumers who live in Seoul. Data are analyzed by descriptive statistics, Cronbach's ${\alpha}$, and regression analysis. The results are that the provoked credibility and favorable impression from the traditional shopping model affects the consumers' shopping mall satisfaction and buying intention in descending order. In additional, the credibility from traditional shopping model affects the product preference. The provoked credibility from the virtual fitting model influences the consumers' product preferences, and buying intentions. The favorable impression from the virtual fitting model affects shopping mall satisfaction. In general, provoked credibility from virtual avatar fitting model and traditional shopping model play key roles which could influence the consumers' buying intention.

• 공업화학
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• 제29권6호
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• pp.789-798
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• 2018

고분자전해질 연료전지(PEMFC)의 성능을 예측할 수 있는 empirical equation의 역할이 중요하게 대두되고 있다. 본 연구에서는 polarization curve에서 activation loss, ohmic loss, mass transfer loss 영역을 분리하였고, 현재까지 개발된 model 중 Kim의 model과 Hao의 model을 선정하여 각 영역의 fitting을 시행하였다. 온도, 압력, 산소 농도 및 막 두께를 운전변수로 설정하여 조건 변화에 대한 각 loss의 변화를 비교하였다. 기존 model은 전반적으로 좋은 fitting 정확도를 보였지만, 분리된 loss 영역에서는 부정확한 fitting 결과를 보이기도 하였다. 연료전지 성능 예측의 정확도를 개선하기 위하여 converge coefficient를 도입한 새로운 model을 제안하였다. 본 연구에서 제안한 model을 연료전지 성능 예측에 적용한 경우에 신뢰도 평가에서 개선된 결과를 얻을 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.159-161
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• 2003

Fitting the projected wire-frame model to the detected edge pixels on images by using least-squares approach, called Least-squares Model-image Fitting (LSMIF), is the key of the Model-based Building Extraction (MBBE). It is implemented by iteratively adjusting the model parameters to minimize the squares sum of distances from the extracted edge pixels to the projected wire-frame. This paper describes a series of experiments and studies on various factors affect the fitting results, including the edge detectors, the weighting rules, the initial value of parameters, and the number of overlapped images. The experimental result is not only helpful to clarify the influences of each factor, but is also able to enhance the robustness of the LSMIF algorithm.

• 감성과학
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• 제5권4호
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• pp.1-10
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• 2002

개인별 신체 특성을 나타내는 가상피팅모델을 이용하여 제공되는 가상 착용 서비스는 웹을 기반으로 한 인터넷 의류 쇼핑의 흥미를 더해준다. 본 연구의 연구자들은 2000년과 2002년에 개발된 미국의 가상피팅모델과 국내에서 개발되었던 가상피팅모델의 개발 기술의 특성과 변화를 분석하였다. 연구결과는 가상피팅모델의 구축을 위해서는 인체의 치수, 형태, 얼굴의 특징들에 관한 정보 입력이 필요하며, 이때 요구되는 정보는 미국과 한국의 사이트에서 차이가 있음을 밝혔다. 미국의 사이트는 정면이나 측면의 실루엣에 대한 정보의 입력이 요구되는 반면 한국의 사이트는 더 많은 인체 치수 관련 정보를 요구하였다. 2000년에 개발되었던 한국의 가상피팅모델은 길고 좁은 프로포션으로 표현되어 사실적인 표현이 부족하였던 반면 2002년 미국에서 개발한 가상피팅모델은 다양한 인종의 특성을 반영하며, 그래픽 기술의 발전으로 사실적으로 표현된 가상피팅모델을 제공하는 것으로 나타났다.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.841-849
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• 2001

The influence in fitting an equicorrelation model is investigated using the influence function. The influence functions for the model parameters are derived and its sample versions are used for investigating the influence of observations on the estimators of the parameters. Some relationships among the sample versions are found. We will derive a measure for identifying observations that have a large influence on the test of fitting the equicorrelation model using the influence function method. An example is given for illustration.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2010-2014
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• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• Journal of Information Processing Systems
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• 제2권1호
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

• Current Optics and Photonics
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• 제2권1호
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• pp.69-78
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• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.