• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.323-325
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• 2021

In this article, we have improved the prediction of hypertension detection using the feature selection method for the Korean national health data named by the KNHANES database. The study identified a variety of risk factors associated with chronic hypertension. The paper is divided into two modules. The first of these is a data pre-processing step that uses a factor analysis (FA) based feature selection method from the dataset. The next module applies a predictive analysis step to detect and predict hypertension risk prediction. In this study, we compare the mean standard error (MSE), F1-score, and area under the ROC curve (AUC) for each classification model. The test results show that the proposed FIFA-OE-NB algorithm has an MSE, F1-score, and AUC outcomes 0.259, 0.460, and 64.70%, respectively. These results demonstrate that the proposed FIFA-OE method outperforms other models for hypertension risk predictions.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.101-113
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• 2013

The concern on environmental quality makes the landscape analysis more important than before ever. For the landscape analysis, selection of viewpoint is one of most important stage. Because of its subjectiveness, the conventional viewpoint selection method often missed some viewpoints of importance. The purpose of this study is to develop a viewpoint selection method for landscape analysis using GIS data and techniques. During the viewpoint selection process, spatial and attribute data from several GIS systems were hired. Query and overlay methods were mainly adapted for analysis to find out meaningful viewpoints. The 3D simulation analysis on DEM(Digital Elevation Model) was used for every selected viewpoint to examine wether the view target is screened out or not. Application study at a sample site showed some omissions of good viewpoints without any screening. It also exhibited the possibility to reduce time and cost for the viewpoint selection process of landscape analysis. For the progress of applicability, GIS data analysis process have to be improved and more modules such as automatic screening analysis system on selected viewpoint have to be developed.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1077-1085
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• 2017

In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.3
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• pp.320-324
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• 2008

We investigated the effect of ESR gene-based selection on an improvement of litter size in the herds in real (non-experimental) conditions. The pigs were selected for three years. In the tested population the pigs were mated according to a breeding scheme where the individuals with at least one ESR-B allele were preferred in the selection. In the control group (CP; n = 140) the pigs were mated just according to a breeding scheme without knowledge of the ESR genotype. We observed a significant increase in litter size (total number of born, number of born alive and number of weaned piglets per litter) in the final tested ESR-selected population (LP; n = 184) and an insignificant increase in CP as compared with the original population (OP; n = 155). After the selection we could observe a significant increase in the frequency of allele B in LP. Frequency of the genotypes AB and BB increased in both LP and CP; the distribution of the genotypes changed significantly only in LP. An association analysis of the ESR gene effects on reproductive traits in LP showed no significant differences between the genotypes. The results of our study suggest that ESR gene-based selection can be successful also in small herds, under real (non-experimental) conditions with a respect for general breeding principles and limitations and during a short period. An examination of a larger sample population as well as an analysis of selection consequences on other traits (meat and carcass quality) could bring a more conclusive evaluation of ESR-based selection. Nevertheless, the results are encouraging especially for small breeding farms taking a perspective of better litter size improvement.

• Fashion & Textile Research Journal
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• v.8 no.1
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• pp.55-63
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• 2006

The purpose of this study examines difference of cunsumer satisfaction by expected selection attribute of wedding dress and bride make-up. It is looking into influencing variables in consumer satisfaction, and is supplying real information to wedding market. The subjects of this study were 241 women getting married within one year of Daegu. The data were analyzed by using frequency, mean, the standard deviation, ANOVA, duncan test, correlation analysis, cross-analysis. Conclusion obtained from the results and discussions of the research are as follows: 1) In the attribution of expected selection according to occupation, blue-collar women are concerned about cost factor but they are low content with the perceptual satisfaction factor. 2) When selecting places for wedding dresses and wedding make-up, in the attribute of expected selection about the number of visiting the shop for wedding dresses and make-up, people who visit over 7 dress shops are highly interested in the appearance fancy degree, advertisements effect factors. But they are concerned with advertisements effect factor, cost factor in the perceptual satisfaction factor about wedding dress. Besides, the more they get chances to visit many dress shops, they are concerned with advertisements, cost factors, and satisfied with both the effect of advertisements and appearance factor degree in the attribution of expected selection about wedding make-up. 3) In the attribution of expected selection about the cost of wedding dresses and make-up, the lower the cost paid, people are interested in price factor. Furthermore, in the attribution of expected selection about the wedding dress and make-up cost, those who spent over 150 million Won are interested in quality, others influence factor, and the case of less than 120~150 million Won, people are highly interested in the appearance fancy degree, advertisements effect factor, and the women are satisfied with the advertisement effect factor in the perceptual satisfaction factor of wedding make-up.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• Journal of the Korean Society of Clothing and Textiles
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• v.12 no.2 s.27
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• pp.159-167
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• 1988

The purpose of this study was to investigate the relationship between Self-concept, Personal variables and Clothing selection behavior. Self-concept was measured with Choi Jung Hun's 'Perceptual Orientation Scale' and Clothing selection behavior scale was prepared for this study. The questionnaire were completed by 389 women in Taegu. Statistical analysis was performed using F-test, Scheffe's test. The results were as follows; 1. There was significant relationship between Self-concept and Clothing selection behavior. (individuality, conformity, economy, modesty). 2. There was significant difference in clothing selection behavior variables according to age. 3. There was significant difference in individuality and economy according to marital status. 4. There was significant difference in individuality, economy and modesty according to education level. 5. There was significant difference in clothing selection behavior variables according to monthly clothing expenses.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.195-205
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• 2005

In decision tree analysis, C4.5 and CART algorithm have some problems of computational complexity and bias on variable selection. But QUEST algorithm solves these problems by dividing the step of variable selection and split point selection. When input variables are continuous, QUEST algorithm uses ANOVA F-test under the assumption of normality and homogeneity of variances. In this paper, we investigate the influence of violation of normality assumption and effect of the transformation of variables in the QUEST algorithm. In the simulation study, we obtained the empirical powers of variable selection and the empirical bias of variable selection after transformation of variables having various type of underlying distributions.

• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.82-91
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• 2015

Recently, due to the increasing concern of environmental factors and low carbon usage, the use of natural gas has been inclining steadily. In order to meet the growing demand of natural gas, government have established strategies to secure the sufficient amount of gas that is mainly used by industries, power generation and residential use by constructing additional receiving terminals for Liquid Natural Gas (LNG). In the process of selecting the optimal site for the terminals, the characteristics of the terminals are not considered where the decision making is done through internal meetings or outsourcing. In respect to site selection, researches are done to derive the factors that are considered for optimal site selection. However, there have not yet been researches in creating a systematic model for analyzing the optimal site selection. To this aim, the paper aims to propose a model for site selection of LNG receiving terminals that considers the characteristics of the terminal construction. Total of 47 factors considered in site selection is derived through interviews with experts and analyzing the previous cases of site selection by various firms. Furthermore, the derived 47 factors are used for the survey for the previous LNG terminals in PT, IC, TY, SC and BR areas where the survey data is analyzed by factor analysis and multiple regression models to depict the optimal site. By applying the model for site selection, practitioners are able to make decisions for site selection in a systematic approach for new candidates of sites.