• Journal of Welding and Joining
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• v.12 no.3
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• pp.71-81
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• 1994

Laser cutting is experiencing a rising worldwide acceptance in the industry. Expert systems are necessary for the systematic arrangement and searching of experimental data existing in journal papers, job handbooks, etc.. This paper proposes an expert system for the selection of the appropriate laser cutting variables from the available database. Optimum cutting conditions according to the given cutting velocity were searched and qualitative comments which are difficult to be used as database variables were shown at each velocity using the binary and fuzzy inference. These comments could be informative to unskilled operators of the laser cutting process. Typical cutting conditions of the mild steel and stainless steel were included and the working range and quality variations were displayed graphically. The proposed algorithm was implemented in an IBM compatible personal computer as an expert system for CO$_{2}$ laser cutting to derive the optimum cutting conditions by using the turbo prolog.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.47-55
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• 2019

It is important to identify informative variables in high dimensional data analysis; however, it becomes a challenging task when covariates are contaminated by measurement error due to the bias induced by measurement error. In this article, we present a two-step approach for variable selection in the presence of measurement error. In the first step, we directly select important variables from the contaminated covariates as if there is no measurement error. We then apply, in the following step, orthogonal regression to obtain the unbiased estimates of regression coefficients identified in the previous step. In addition, we propose a modification of the two-step approach to further enhance the variable selection performance. Various simulation studies demonstrate the promising performance of the proposed method.

• Fashion & Textile Research Journal
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• v.15 no.2
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• pp.210-218
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• 2013

This study examined the degree of appearance interest and clothing conformity, the impacts of appearance interest on clothing conformity, and the effects of appearance interest and demographic variables on clothing conformity. A questionnaire survey collected data from October $3^{rd}$ to $27^{th}$ 2011. A convenience sample was drawn from adults between the ages of 17 and 76 who lived in the Daegu and Gyeongbuk regions of South Korea. A total of 513 responses produced complete and usable questionnaires. Data were tested through factor analysis and regression analysis, using SPSS 20.0. The results of this study are as follows : First, three factors were extracted from clothing conformity (normative, informative, identifiable conformity). The appearance interest was relatively high and normative conformity was the highest level among three factors of clothing conformity. Second, appearance interest was significant predictors of clothing conformity. Third, demographic variables such as gender, marital status, age and education levels had significant effects on the relationship between appearance interest and clothing conformity.

• Journal of Distribution Science
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• v.20 no.3
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• pp.13-22
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• 2022

Purpose: Thisstudy aims to measure the attitudes of Generation Z in Jakarta towards advertisements containingCOVID-19 information. Research design, data and methodology: This study is a quantitative method with partial least square structural equation modeling (PLS-SEM) with SMART PLS as an analytical tool. The sample size is 216 participants was obtained randomly through a questionnaire distributed online. This study consisted of exogenous variables (advertising content, value, irritation, and economic benefits), endogenous variables (attitudes towards advertising), and some moderating roles. Results: The results of thi study explain that this generation's attitude towards advertising is affected by the content and value aspects embedded in advertisements. Value can be formed from creativity in making advertising content as interesting and informative as possible. Interestingly, this study also found that the irritation aspect and economic benefits had no effect on the audience's attitude towards the advertisement. Neither the irritating aspect of advertising nor the economic value that is formed acts as a moderator of the content and the value of the ad. Conclusions: The ongoing pandemic and periodic adjustments to government policies regarding COVID-19, these results can be compared with other advertisements for future studies, especially those using the same variables as this study.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.112-123
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• 2002

The purpose of this study was to establish the strategy for Internet fashion homepage advertising that attracts consumers attention and discloses clothing brand to consumers continually. In this paper, the following subjects were set up: (a) to classify the structure and evaluation factors of the fashion homepage advertising, (b) to analyze the effect of demographic variables and clothing involvement of consumer on fashion homepage advertising structures and evaluation factors. A random sample of 553 people in the age group 16-34s living in Seoul and Kyungki region during March 2000 was selected from Internet users. SPSS package was used for data analysis. Frequency, Percentage, Factor analysis, ANOVA, Duncan test and regression analysis were applied. The results of this research were as follows: First, in the process of classifying the dimension of the fashion homepage advertising, homepage advertising structure was composed of 5 factors: interactive, amusing factor, professional information, fashion information and useful information. And homepage advertising evaluating factors were interesting, information and irritation. Second, it was found that clothing involvement influenced fashion homepage advertising. High involvement group preferred the fashion information factor of the homepage advertising structure and low involvement group was useful information factor of the homepage advertising structure. Both high and low involvement groups preferred interesting factor of the homepage advertising evaluation. Third, demographic variables also influenced fashion homepage advertising Females manifested greater interests in informative factor of homepage advertising than males. Findings from this study provide an insight into fashion homepage advertising strategy related to consumers clothing behavior.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.993-1004
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• 2017

A stratified sampling method is generally used with a sample selected using the same sample weight in each stratum in order to improve the accuracy of the sampling survey estimation. However, the weight should be adjusted to reflect the response rate if the response rate is affected by the value of the variable of interest. It may be also more effective to adjust the weights by subdividing the stratum rather than using the same weight if the variable of interest has a linear relationship with the continuous auxiliary variables. In this study, we propose a method to increase the accuracy of estimation using an informative sampling design technique when the response rate is an exponential function of the variable of interest and the variable of interest has a linear relationship with the auxiliary variable. Simulation results show the superiority of the proposed method.

• Journal of Korean society of Dental Hygiene
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• v.14 no.6
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• pp.935-942
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• 2014

Objectives: The purpose of the study was to investigate the related factors of clinical practice satisfaction and social support in dental hygiene students. Methods: A self-reported questionnaire was filled out by 420 dental hygiene students in Gwangju and Jeonnam from March 8 to April 8, 2014. Except 26 incomplete answers, 394 data were analyzed. The instrument consisted of general characteristics of the subjects(7 questions), social support(7 questions), and satisfaction level with clinical practice(22 questions). The instrument for satisfaction level with clinical practice included self-esteem(1 question), interest and usefulness(2 questions), knowledge application(1 question), place of clinical practice(1 question), and influence by practice leader(1 question). Cronbach alpha was 0.773 in the study. The instrument of social support was adapted from Park and reconstructed. Social support included emotional support(11 questions), self-esteem support(7 questions), and informative support(4 questions). Social support was score by Likert 5 scale and higher score showed the higher social support. Results: The dental hygiene students got a mean of $3.11{\pm}0.55$ in clinical practice satisfaction. They got 3.35 points in satisfaction with major and 3.32 in satisfaction with curricula(p<0.001). They got a mean of $3.68{\pm}0.55$ in social support. They got $3.69{\pm}0.57$ in emotional support; $3.81{\pm}0.59$ in self-esteem support; and $3.53{\pm}0.66$ in informative support. The influencing variables on satisfaction with clinical practice were self-esteem support(B=0.202), satisfaction with major(B=0.234), and satisfaction with curricula (B=0.128). Conclusions: There was a close relationship between satisfaction with clinical practice and social support. In order to enhance the satisfaction with clinical practice, it is necessary to connect self-esteem support with major satisfaction and curricula satisfaction.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.821-834
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• 2013

Law et al. (2004) proposed a normal distribution based salient mixture model for variable selection in clustering. However, this model has substantial problems such as the unidentifiability of components an the inaccurate selection of informative variables in the case of a small cluster size. We propose an alternative method to overcome problems and demonstrate a good performance through experiments on simulated data and real data.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.87-100
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• 2002

Poorly-posed problems in the balanced discriminant analysis was considered. We restrict consideration to the case of observations and the number of variables are the same and small. When these problems exist, we do not use a maximum likelihood estimates(MLE) to estimate covariance matrices. Instead of MLE, an alternative estimate for the covariance matrices are proposed. This alternative method make good use of two regularization parameters, $\lambda$} and $\gamma$. A new test rule for the discriminant function is suggested and examined via limited hut informative simulation study. From the simulation study, it is shown that the suggested test rule gives better test result than other previously suggested method in terms of error rate criterion.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.51-59
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• 2006

So far, there is no technique of quantitative evaluation on danger related to industrial accidents. Therefore, as an endeavor for obtaining technique of quantitative evaluation, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze feature of industrial accidents, a retrospective analysis was performed in 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work chosen from data related to manufacturing businesses during three years $(2002\sim2004)$ in Korea. The analysis results were very informative since those enable us to know the most important variables such as occurrence type, company size, and occurrence time which can affect injured people. Also, it is found that classification using QUEST algorithm which was performed in this study is very reliable.