• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.100-106
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• 2022

A longitudinal study refers to a research method based on longitudinal data repeatedly measured on the same object. Most of the longitudinal analysis methods are suitable for prediction or inference, and are often not suitable for use in exploratory study. In this study, an exploratory method to analyze longitudinal data is presented, which is to find the longitudinal trajectory after determining the best number of clusters by clustering longitudinal data using self-organizing map technique. The proposed methodology was applied to the longitudinal data of the Employment Information Service, and a total of 2,610 samples were analyzed. As a result of applying the methodology to the actual data applied, time-series clustering results were obtained for each panel. This indicates that it is more effective to cluster longitudinal data in advance and perform multilevel longitudinal analysis.

• Journal of the Korea Safety Management & Science
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• v.26 no.2
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• pp.23-31
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• 2024

In the military, ammunition and explosives stored and managed can cause serious damage if mishandled, thus securing safety through the utilization of ammunition reliability data is necessary. In this study, exploratory data analysis of ammunition inspection records data is conducted to extract reliability information of stored ammunition and to predict the ammunition condition code, which represents the lifespan information of the ammunition. This study consists of three stages: ammunition inspection record data collection and preprocessing, exploratory data analysis, and classification of ammunition condition codes. For the classification of ammunition condition codes, five models based on boosting algorithms are employed (AdaBoost, GBM, XGBoost, LightGBM, CatBoost). The most superior model is selected based on the performance metrics of the model, including Accuracy, Precision, Recall, and F1-score. The ammunition in this study was primarily produced from the 1980s to the 1990s, with a trend of increased inspection volume in the early stages of production and around 30 years after production. Pre-issue inspections (PII) were predominantly conducted, and there was a tendency for the grade of ammunition condition codes to decrease as the storage period increased. The classification of ammunition condition codes showed that the CatBoost model exhibited the most superior performance, with an Accuracy of 93% and an F1-score of 93%. This study emphasizes the safety and reliability of ammunition and proposes a model for classifying ammunition condition codes by analyzing ammunition inspection record data. This model can serve as a tool to assist ammunition inspectors and is expected to enhance not only the safety of ammunition but also the efficiency of ammunition storage management.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.1-10
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• 2017

Longitudinal data of Korean child academic achievement have been used to find the significant exploratory variables under the assumption of independent repeated measured data. Using the exploratory variables in previous research works, we analyze the linear mixed model incorporating the fixed and random effects for child academic achievement to detect the significant exploratory variables. Korea welfare panel study data observed three times between 2006 and 2012 by additional survey for children. The child academic achievement is evaluated by the sum of academic achievements of Korean, English and Mathematics. We also investigate the multicollinearity and the missing mechanism and select some popular correlation matrices to analyze the linear mixed model.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.87-102
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• 2024

Digital transformation refers to the process by which a company or organization changes or innovates its existing business model or sales activities using digital technology. This requires the use of various digital technologies - cloud computing, IoT, artificial intelligence, etc. - to strengthen competitiveness in the market, improve customer experience, and discover new businesses. In addition, in order to derive knowledge and insight about the market, customers, and production environment, it is necessary to select the right data, preprocess the data to an analyzable state, and establish the right process for systematic analysis suitable for the purpose. The usefulness of such digital data is determined by the importance of pre-processing and the correct application of exploratory data analysis (EDA), which is useful for information and hypothesis exploration and visualization of knowledge and insights. In this paper, we reexamine the philosophy and basic concepts of EDA and discuss key visualization information, information expression methods based on the grammar of graphics, and the ACCENT principle, which is the final visualization review standard, for effective visualization.

• International Journal of Contents
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• v.8 no.4
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• pp.50-55
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• 2012

This study compared cross-national Twitter use between Korea and Japan. The main exploratory variables were a) cultural traits and b) disclosure of geographic information. Twitter use was measured by the degree of reciprocity and the numbers of Tweets, followings, and followers. Data were collected using API-based software and analyzed with independent samples t-tests. Content analysis was conducted to validate the findings. The results indicate that Korean and Japanese users employ their own communication strategies reflecting their cultural orientation.

• Journal of Distribution Science
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• v.13 no.8
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• pp.49-59
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• 2015

Purpose - This purpose of this research is to verify the influence of the care workers' environment on their job satisfaction and on their voluntary behavior. Research design, data, and methodology - Data were collected from care workers at elderly medical and home care facilities in Korea in Seoul and Kyung-ki. Of 367 total respondents, 285 responses were used. This study performed exploratory factor analysis in order to verify the validity and credibility of the data. Regression analysis was conducted to verify the influence of the working environment, which encompasses the worker's relationship with the agency and with the elderly, on job satisfaction. Results - The hypothesis results were: First, from analyzing the influence of the working environment on the worker's job satisfaction, both relationship with the agency (p<.001) and relationship with the elderly (p<.05) positively affect job satisfaction; second, the exploratory analysis verifies the influence or the working environment on job satisfaction. Conclusions - The results indicate that the relationship with the agency (p<.001) and relationship with the elderly (p<.001) both positively affect the voluntary behavior of the workers.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.15-31
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• 2003

In this study, we will construct a statistical model which considered the irregularity of observed time sequence in order to analyze sets of bioindex data gathered from stations in Lake Ontario for a number of years. We fit a linear model to account for the trend and seasonal component in an exploratory way and draw variogram and correlogram for further confirmatory studies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.205-215
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• 2012

Due to a rapid change of business environment, many firms are eager to find the competitiveness by information technology adoption and diffusion. In this exploratory study, we examined the applicability of a previously proposed model to evaluate IT competitiveness based on the innovativeness and verified it's propriety with empirical data. As suggested by previous studies, the proposed model considers a variety of corporate and market characteristics concerned with IT adoption, and it consists of several internal and external impacting factors, which have influence on technology diffusion and its performance. For the empirical analysis, the survey data of domestic ERP adoption cases were adopted from 128 small and medium-sized enterprises(: SMEs) in IT and electrical engineering industry, and analyzed by partial least squares(: PLS) - a popular structural modeling and multivariate projection technique to latent variables. The results indicated positive supports for the research model of external and internal IT adoption factors' influences on innovativeness' performances. However, there are a couple of limitations not to show the reliability of selected measurement items and the generality of model proposed in this exploratory study.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.87-107
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• 2018

With more than 10 million inhabitants, in particular, Seoul, the capital of Korea, has already experienced a number of severe heat wave. To alleviate the potential impacts of heat wave and the vulnerability to heat wave, policy-makers have generally considered the option of heat wave strategies containing adaptation elements. From the perspective of sustainable planning for adaptation to heat wave, the objective of this study is to identify the elements of vulnerability and assess heat wave-vulnerability at the dong level. This study also performs an exploratory investigation of the spatial pattern of vulnerable areas in Seoul to heat wave by applying exploratory spatial data analysis. Then this study attempts to select areas with the relatively highest and lowest level of adaptive capacity to heat wave based on an framework of climate change vulnerability assessment. In our analysis, the adaptive capacity is the relatively highest for Seongsan-2-dong in Mapo and the relatively lowest for Changsin-3-dong in Jongno. This study sheds additional light on the spatial patterns of heat wave-vulnerability and the relationship between adaptive capacity and heat wave.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.384-404
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• 2019

This study investigates the multidimensional structure of apparel design evaluation criteria and the details of each criterion by exploring how female college students majoring in apparel design in their 20s evaluate apparel design based on an exploratory approach. Data were analyzed through a categorization method of qualitative data after collecting from a literature review and three focus group interviews. The results identified the six evaluation criteria of apparel design (functional usefulness, convenience, aesthetics, psychological self suitability, social activity usefulness, and fashion trend). Functional usefulness and convenience assessed the extent to which primary features of apparel are reflected in apparel design, and aesthetics evaluated the aesthetic beauty of apparel design. Psychological self suitability estimated the extent to which apparel design expressed psychological self properly, and social activity usefulness appraised the extent to which apparel design contributed to the social activities of wearers. Last, fashion trend assessed the extent to which apparel design reflected fashion trend. The study results provide meaningful implications towards an apparel industry that wants to develop apparel design that appeals to consumers, educational institutions that aim to cultivate well-trained professionals in the apparel industry, and consumers who want to purchase clothes of satisfactory design.