• Journal of the Korea Institute of Building Construction
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• v.16 no.4
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• pp.331-339
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• 2016

According to high-rise, complexation, and enlargement of buildings, various construction methods are being developed, and the significance of construction method selection about main work types has emerged as a major interest. However, it has been pointed out that hand-on workers cannot consider project characteristics carefully, and they lack an objective standard or reference for main construction method selection. Hence, the selection is being made depending on hand-on workers' experience and intuition. To solve this problem, various studies have proceeded for construction method selection of main work types using Artificial Intelligence like Fuzzy, AHP and Case-based reasoning. It is difficult to apply many different kinds of construction method selection to every main work type with consideration for characteristics of work types and condition of a construction site when selecting construction method in the field. Accordingly, this study proposed the decision-making model which can apply to fields easily. Using matrix analysis and liner transformation, this study verified consistency of study models applied in the process of soil retaining selection with a case study.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

• Journal of the Korean Society of Food Culture
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• v.28 no.2
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• pp.195-203
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• 2013

The aim of this study was to provide strategic implications for the coffee market in which competition got severer through IPA analysis based on the attributes of selection of a specialized franchise coffee shop. The results of a positive analysis conducted with undergraduates in their twenties were as follows: According to the evaluation of the importance of the attributes of selection of a specialized coffee shop, the most important were 'cleanliness and hygienic facilities inside the shop (6.09)' and 'taste and quality of the menu (coffee) (6.09)'. According to the performance analysis, those showing the highest performance were 'brand image (4.92)' and 'cleanliness and hygienic facilities inside the shop (4.92)'. According to the result of IPA analysis, what customers regarded as being the most important were 'taste and quality of the menu (coffee)', 'kindness of the staff', and 'cleanliness and hygienic facilities inside the shop', and, in fact, they showed great performances as well. However, 'price of the menu (coffee)' was regarded as being important but did not indicate a great performance; therefore, they showed dissatisfaction with it. Although they did not think 'environment around the shop', 'brand image', 'brand recognition' or 'interior size and scale of the shop' were important, the attributes did not appear to show great performances. Therefore, we need constant maintenance strate gies regarding the fact that consumers are considered to be very important for evaluation, and should make efforts to change the price in advance.

• Journal of Distribution Science
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• v.16 no.5
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• pp.17-29
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• 2018

Purpose - This study analyzed the success strategy of Korean small & medium cosmetics exporting companies to enter the Southeast Asian market. Research design, data, and methodology - The independent factors are classified into firm capacity, financial factor, institutional factor, and operational factor. The results of the selection of distributor partners of cosmetics related export companies as a were classified as financial performance and non - financial performance. In order to analyze this, 65 Korean small and medium export companies were recruited through structured online questionnaire for 44 days from September 18, 2017 to October 31, 2017. These data were analyzed by frequency analysis, correlation analysis, factor analysis and regression analysis using SPSS. Results - The Cronbach's alpha coefficient was found to be 0.846. Factor analysis between variables revealed that the eigen value exceeded 1 and was considered valid. As a result of the correlation analysis between the variables, the financial factor and the corporate's competence showed the highest correlation with 0.774. Conclusions - Among the factors influencing the financial performance of the exporting firms, the factors influencing the financial performance of the exporting companies are the factors that influence the non - financial performance rather than the financial performance.

• The Korean Journal of Zoology
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• v.26 no.2
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• pp.95-106
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• 1983

Selections for rapid and slow walking behavior were carried out with the populations, drived from Oregon-R and lethal free strain of Drosophila melanogaster. The behavior was measured by means of connected test-tube apparatus. The populations responded effectively to the artificial selection, and it reached the selection plateau after 7 generations. The realized heritability for the first 10 generations was estimated to be about $9\\sim14%$ for the rapid walking behavior, and those for slow walking behavior was about $11\\sim16%$. The results of hybridization analysis between selected populations at generations 8 and 10 indicated that some polygenes showing a slow walking behavior were partially dominant over polygenes controlled rapid trait. The populations selected for rapid and slow walking behavior were relaxed after 10 generations of selection. The response to natural selection of rapid population was completely returned to their neutral states after only 5 generations. Such phenomena would be explained by the genetic homeostasis resulted from an action of natural selection. However, the slow population did not make any difference from walking scores of their original artificial selection. It seems reasonable to assume that the slow walking behavior was possibly controlled by a major gene.

• Journal of Digital Convergence
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• v.6 no.3
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• pp.75-84
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• 2008

The purpose of our this research, based on the Media Selection Theory, the Technology Acceptance Model, and the Social Influence Theory, is to investigate the influential factors that affect media selection in banking transactions. Analyses showed that for location sensitive bank window's and ATMs (automatic teller machines), defined as offline-based transaction channels, convenience was the variable affecting media selection. However, in the case of online media not related to location, (phone banking, internet banking, and mobile banking) reliability was the significant variable influencing use. The findings show that banking organizations may benefit from identifying traits of media affecting use, and should differentiate customer services for competitive advantage.

• The Journal of Korean Association of Computer Education
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• v.6 no.3
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• pp.65-73
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• 2003

Most web-based learning is furnishing single side and consistent training resource to learner. Research was gone to apply item analysis method or to introduce web-based learning system using studying pattern. But, we need complicated algorithm or parameter setting etc, for apply these method. Therefore, in this research, we design and implement an item selection system in consideration of learner's incorrectness rate and problem frequency selection rate about question of item selection attribute. Also, as that embody business logic about item selection by EJB, efficient system development is available and we improved maintenance and reusability.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.471-483
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• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• Culinary science and hospitality research
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• v.14 no.3
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• pp.45-57
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• 2008

The purpose of this study is to initiate a systematic approach to maximize profits through continuous development of menu and build a strong image of Western restaurants located inside hotels by identifying their guests' knowledge and concern and menu selection behavior in well being trend. Findings from the analysis are as follows. First, among the Western menu selection behavior, organic grain and seafood, seasonal event menu, less spicy and more natural cooking methods are favored as the most important consideration. Second, customers' knowledge and concern in well being trend and menu selection behavior were found to be statistically significant. Third, customers' awareness in health and obesity were found to be statistically significant to the concern in well being trend. Fourth, demographical characteristics of customers such as gender, marital status, age, income level and education were tested for their relationships with knowledge and concern in well being trend.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1513-1521
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• 2015

Selecting relevant variables for a statistical model is very important in regression analysis. Recently, variable selection methods using a penalized likelihood have been widely studied in various regression models. The main advantage of these methods is that they select important variables and estimate the regression coefficients of the covariates, simultaneously. In this paper, we propose a simple procedure based on a penalized h-likelihood (HL) for variable selection in Poisson hierarchical generalized linear models (HGLMs) for correlated count data. For this we consider three penalty functions (LASSO, SCAD and HL), and derive the corresponding variable-selection procedures. The proposed method is illustrated using a practical example.