• 한국CDE학회논문집
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• 제10권1호
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• pp.49-60
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• 2005

Existing CAD systems have configured geometry data and it is necessary to extend the configured geometry into a knowledge-based system. An intelligent CAD system emerged to provide such a knowledge-based system. However the intelligent CAD system has a limited product model to represent various knowledge models. This paper presents a model, called extended intelligent CAD model, which can extend the product model of the intelligent CAD system into further detailed knowledge model. The extended intelligent CAD model includes a whole design process knowledge and an efficiency of the model has been verified via a knowledge based wiper design system. The model can improve the functionality and efficiency of the existing CAD systems.

• Genomics & Informatics
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• 제6권4호
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• pp.202-209
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• 2008

Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.

• Asia pacific journal of information systems
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• 제23권1호
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• pp.65-86
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• 2013

Understanding success factors in electronic banking is important to helping banks succeed. In this study, we extend DeLone and McLean's IS success model to the electronic banking by adding trust as a success variable. We tested the extended model by comparing internet banking and mobile banking in Indonesia. Using a structural equation modelling approach. We found that system quality had positive impacts on perceived usefulness and end-user satisfaction for both internet banking and mobile banking. The development of e-banking (internet banking and mobile banking) in Indonesia is in its initial stage. Finally, although we tested for the common method bias to relieve concern, further research may use multiple methods when collecting the data. This study investigated the role of each dimension of IS success in the electronic banking environment. While the original IS success model emphasizes individual and organizational impacts, we have argued that trust is an important indicator of IS impact on an individual socially in the banking industry. The contribution of our study is two-fold. Conceptually, the study is the first to extend the IS success model to the e-banking context. We provide an extension of the updated IS success model by adding trust as an outcome variable in the research model.

• 반도체디스플레이기술학회지
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• 제15권2호
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• pp.61-65
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• 2016

Facial feature detection is a fundamental function in the field of computer vision such as security, bio-metrics, 3D modeling, and face recognition. There are many algorithms for the function, active shape model is one of the most popular local texture models. This paper addresses issues related to face detection, and implements an efficient extraction algorithm for extracting the facial feature points to use on iOS platform. In this paper, we extend the original ASM algorithm to improve its performance by four modifications. First, to detect a face and to initialize the shape model, we apply a face detection API provided from iOS CoreImage framework. Second, we construct a weighted local structure model for landmarks to utilize the edge points of the face contour. Third, we build a modified model definition and fitting more landmarks than the classical ASM. And last, we extend and build two-dimensional profile model for detecting faces within input images. The proposed algorithm is evaluated on experimental test set containing over 500 face images, and found to successfully extract facial feature points, clearly outperforming the original ASM.

• Communications for Statistical Applications and Methods
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• 제26권3호
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• pp.325-336
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• 2019

In this article we extend the discrete Weibull regression model in the presence of missing data. Discrete Weibull regression models can be adapted to various type of dispersion data however, it is not widely used. Recently Yoo (Journal of the Korean Data and Information Science Society, 30, 11-22, 2019) adapted the discrete Weibull regression model using single imputation. We extend their studies by using multiple imputation also with several various settings and compare the results. The purpose of this study is to address the merit of using multiple imputation in the presence of missing data in discrete count data. We analyzed the seventh Korean National Health and Nutrition Examination Survey (KNHANES VII), from 2016 to assess the factors influencing the variable, 1 month hospital stay, and we compared the results using discrete Weibull regression model with those of Poisson, negative Binomial and zero-inflated Poisson regression models, which are widely used in count data analyses. The results showed that the discrete Weibull regression model using multiple imputation provided the best fit. We also performed simulation studies to show the accuracy of the discrete Weibull regression using multiple imputation given both under- and over-dispersed distribution, as well as varying missing rates and sample size. Sensitivity analysis showed the influence of mis-specification and the robustness of the discrete Weibull model. Using imputation with discrete Weibull regression to analyze discrete data will increase explanatory power and is widely applicable to various types of dispersion data with a unified model.

• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.117-130
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• 1999

Nayak(1994) suggested a combined randomized response model that combined the Warner's model and greenberg et al.'s model. In this paper we extend Nayak's model to two sample case of including unknown unrelated character also propose some combined models such W-M model and G-M model that modify the Nayak's model. We suggest the efficiency conditions of our models for Nayak's model, also find the efficiency condition of G-M model for the W-M model.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 2부
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• pp.158-164
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• 2008

본 논문은 모바일폰의 사용성 연구에 있어서 모바일폰의 사용 특성을 충분히 반영할 수 있도록 추후 연구를 돕기 위한 목적으로 진행되었다. 모바일폰의 사용 특성은 무엇보다 컨텍스의 영향에 매우 민감하다는 것과, 1인 1디바이스로서 개인적인 라이프 패턴을 많은 부분 수용한다는 것이다. 이러한 전제로부터 모바일폰이 사용되는 컨텍스트를 정의하였다. 특별히 컨텍스트의 정의에 있어서 상황적 컨텍스트(situational context)라는 정의를 도입하였으며, 모바일폰으로 할 수 있는 다양한 task 중 특별히 situational context의 영향을 직접적으로 받는 task를 contextual task로 이름하였다. 연구 결과물로써 contextual task의 모델을 제작하였다. 이는 디자인 종사자들과 타 업계의 종사자들이 모두 사용자의 실제적 행태를 이해할 수 있도록 하여 동일한 컨셉을 가지고 사용자 중심의 디자인을 진행할 수 있도록 한다. 또한, 이러한 사용자 사용 행태에 대한 통일한 컨셉은 디자인을 위한 서로의 의사전당에도 효과적일 젓이다. 수집된 사용자 task 들은 3가지 모델로 그 패턴을 정의할 수 있다. 사용자의 공간 확장과 관련되어 다양한 패턴을 구조화한 Extend Model, 기능의 컨버전스로 인해서 각 기능의 충돌을 최소화하여 사용성을 높일 수 있는 기회를 제공하기 위해 이와 관련된 task 들의 패턴을 구조화한 Synchronize Model, 마지막으로 사용자의 라이프 패턴을 반영하여 기존의 object를 대체하는 결과를 가져오는 task들의 패턴을 구조화한 Replace Model 로 Contextual Task를 정의하였다. 마지막으로 각 모델의 구체적 용도를 보이기 위해 Context 를 반영한 Interview 를 시행할 수 있는 질문지 제작을 진행하였다.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.177-186
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• 2003

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the correlated response variables are intrested, we have to extend the univariate zero-inflated regression model to multivariate model. In this paper, we study and simulate the multivariate zero-inflated regression model. A real example was applied to this model. Regression parameters are estimated by using MLE's. We also compare the fitness of multivariate zero-inflated Poisson regression model with the decision tree model.

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.793-798
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• 2008

Extreme value inference deals with fitting the generalized extreme value distribution model and the generalized Pareto distribution model, which are recently combined to give a single model, namely a two-dimensional non-homogeneous Poisson exceedance point process model. In this paper, we extend the two-dimensional non-homogeneous Poisson process model to include non-stationary effect or dependence on covariates and then derive the likelihood for the extended model.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.753-765
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• 2001

We suggest a quantitative conditional unrelated question model that can be used in obtaining more sensitive information. For whom say "yes" about the less 7han sensitive question .B we ask only about the more sensitive variable X. We extend our model to two sample case when there is no information about the true mean of the unrelated variable Y. Finally we compare the efficiency of our model with that of Greenberg et al.′s.