• Korean Journal of Computational Design and Engineering
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• v.10 no.1
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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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• v.6 no.4
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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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• v.23 no.1
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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.

• Journal of the Semiconductor & Display Technology
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• v.15 no.2
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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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• v.26 no.3
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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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• v.6 no.1
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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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• 2008.02b
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• pp.158-164
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• 2008

This study was conducted for raising the considering the dynamical context of mobile phone use environment in the mobile-phone research. For this I identified the characteristic of the mobile phone use. The first characteristic is that the mobile phone is the context sensitive device. Also, it reflects the user's life pattern because it is the very personal device. I defined the context of mobile phone use with the basis on this identification of those characteristics. I referenced the definition, 'situational context', defining the mobile phone use context. Also, I set up the research scope within the user task that is influential from the situational context, I named this kind of task as the 'contextual task'. I developed the Contextual Task Model in this study. I named the model as the 'ESR Model'. The reason that I developed this contextual task model is that this model can help novice designers and designers unfamiliar with an application domain understand the user behavior and user centered design. And also this model can be effective to communicate each other, I identified the user's contextual tasks three kinds of model. First, the Extend Model includes user tasks that related to extending from user physical working space to the virtual level. Second model is Synchronize Model, which includes issues that lesson the blocking when use several functions at a time or sequentially. Third model is Replace Model, which is come from the characteristic of user life pattern to use the mobile phone. Finally, I proposed an application of this model, CIQ. Through the process to make CIQ I proved the effectiveness of this ESR Model.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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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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• v.15 no.5
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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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• v.8 no.3
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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.