• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.2
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• pp.105-113
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• 2022

Purpose - An increase in automation has been as a result of digital technologies. The data will be instrumental in the determination of the services that are more necessary so that more resources can be allocated for them. The purpose of the current research is to investigate how big data utilization will help increase the profitability in the industry 4.0 era. Research design, Data, and methodology - The present research has conducted the comprehensive literature content analysis. Quantitative approaches allow respondents to decide, but qualitative methods allow them to offer more information. In the next step, respondents are given data collection equipment, and information is collected. Result - The According to qualitative literature analysis, there are five ways in which big data utilization will help increase the profitability in the industry 4.0 era. The five solutions are (1) Better Customer Insight, (2) Increased Market Intelligence, (3) Smarter Recommendations and Audience Targeting, (4) Data-driven innovation, (5) Improved Business Operations. Conclusion - Modern companies have been seeking a competitive advantage so that they can have the edge over other companies in the same industries providing the same services and products. Big data is that technology that businesses have always wanted for an extended period of time to revolutionize their operations, making their businesses more profitable.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.646-654
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• 2014

The aim of this study was to investigate the patterns of the elementary school students' interests to animals and plants based on affinity toward animals and plants, and curiosity about animals and plants by using a cluster analysis. In addition, the differences of the big five personality traits by the identified clusters was examined. A total number of 411 elementary school students participated in the study. The students were clustered into four distinct interest groups with respect to the level of interests to animals and plants. Cluster 1 'Developed Interest to Organisms group' showed high levels in the interest to both animals and plants. Cluster 2 'Developed Interest to Animals group' showed high interest to animals and relatively low interest to plants whereas cluster 3 'Developed Interest to Plants group' showed high interest to plants and relatively low interest to animals. Lastly, cluster 4 were identified as 'Lack of Interest to Organisms group' by showing low levels of interest to both animals and plants. The four identified groups also showed different distributions of students according to gender and school year. These results support gender difference in the interest to animals and plants and suggest the decreased and specialized interest with school year. The Big Five personality traits excluding neuroticism were positively related with the interest to organisms and the identified groups showed significant differences in the traits. These findings indicate that agreeableness, conscientiousness, extraversion, and openness can be significant predictors of the interests to animals and plants.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.8
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• pp.491-498
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• 2016

This paper proposes a visualization method that expresses users' MBTI personality types based on the categorization method called 'Big Five Personality Traits' and their representative celebrities' facial images. This system has significance for visualizing traits from texts to images effectively. The entire system is composed of making backgrounds to represent traits of each MBTI category using 'Big Five Personality Traits' and showing facial images of celebrities with corresponding MBTI personality types. First, 'Big Five Personality Traits' classifies 16 MBTI types into four categories and each of category traits lays the foundation to make background using visual elements such as colors and lines. Second, celebrities' facial images are substituted for the corresponding literal explanation of each MBTI type. By adjusting the color saturation, users can distinguish relationship between the types intuitively. As a result, this system enables users to take information for their own / opposite / similar MBTI types simultaneously.

• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.115-132
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• 2023

Previous studies on emotion have repeatedly suggested that alexithymia is an important predictor of depression. Therefore, this study examined whether the relationship between these two variables can be moderated by personality factors, focusing on the Big five personality traits. An online survey of 312 college students, including alexithymia, depression, and Big five personality traits (Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Openness to Experience) was conducted. As the results, as expected, alexithymia predicted depression, which was in line with the existing research flow. In addition, moderation analysis revealed that agreeableness, emotional stability, and openness to experience moderated the relationship between alexithymia and depression, while extraversion and conscientiousness did not. This study has an important implication in that it discriminated which specific personality traits function as moderators in the process of increasing depression due to alexithymia.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.1-9
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• 2014

This research describes strategies to promote the growth of the Big Data industry and the companies within the ecosystem. In doing so, we identify the roles and responsibilities of various objects of this ecosystem and Big Data concepts. We describe the five components of the Big Data ecosystem: governance, data holders, service users, service providers and infrastructure providers. Related to the Big Data industry, the paper discusses 13 business strategies between the five components in the ecosystem. These strategies directly respond to areas of research by the Big Data industry leading experts on its early development. These strategies focus on how companies can gain competitive advantages in a growing new business environment of Big Data. The strategy topics are as follows: 1) the government's long term policy, 2) building Big Data support centers, 3) policy support and improving the legal system, 4) improving the Privacy Act, 5) increasing the understanding of Big Data, 6) Big Data support excavation projects, 7) professional manpower education, 8) infrastructure system support, 9) data distribution and leverage support, 10) data quality management, 11) business support services development, 12) technology research and excavation, 13) strengthening the foundation of Big Data technology. Of the proposed strategies, establishing supportive government policies is essential to the successful growth of thee Big Data industry. This study fosters a better understanding of the Big Data ecosystem and its potential to increases the competitive advantage of companies.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.36.3-37
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• 2018

By utilizing large-scale graph analytic tools in the modern Big Data platform, Apache Spark, we investigate the topological structures of five different multiverses produced by cosmological n-body simulations with various cosmological initial conditions: (1) one standard universe, (2) two different dark energy states, and (3) two different dark matter densities. For the Big Data calculations, we use a custom build of stand-alone Spark cluster at KIAS and Dataproc Compute Engine in Google Cloud Platform with the sample sizes ranging from 7 millions to 200 millions. Among many graph statistics, we find that three simple graph measurements, denoted by (1) $n_\k$, (2) $\tau_\Delta$, and (3) $n_{S\ge5}$, can efficiently discern different topology in discrete point distributions. We denote this set of three graph diagnostics by kT5+. These kT5+ statistics provide a quick look of various orders of n-points correlation functions in a computationally cheap way: (1) $n = 2$ by $n_k$, (2) $n = 3$ by $\tau_\Delta$, and (3) $n \ge 5$ by $n_{S\ge5}$.

• Korean Journal of Child Studies
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• v.36 no.5
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• pp.173-188
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• 2015

The main purpose of this study was to investigate the effects of a mother's big five personality factors and playfulness on maternal parenting behavior. The participants consisted of 270 mothers with young children, aged 3-6 years old. The subjects completed questionnaires on IPIP(International Personality Item Pool), PAS(Playfulness Scale for Adults) and Parenting Behavior. The results were as follows. First, regarding the relationships of the mother'personality and parenting behavior, higher levels of neuroticism(N) in the mothers resulted in lower levels of warmth acceptance(W A) in parenting behavior. Higher levels of extroversion(E), openness(O), agreeableness(A), and conscientiousness(C) resulted in higher levels of W A. In terms of the relationships of the mother's playfulness and parenting behavior, higher levels of playfulness resulted in higher levels of W A. and lower levels of permissiveness nonintervention(P N) and rejection restriction(R R). Second, N, E, C, and a maternal sense of humor had an effect in W A. C was found to have an effect in P N and N was observed to have an effect in R R.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1798-1806
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• 2020

In this study, we investigated whether there is a significant relationship between the natural radiation dose rate and the cancer incidences in Korea by using a big data analysis. The natural dose rate data for this analysis were the measurement data obtained from the 171 monitoring posts of the 113 administrative districts in Korea over the 10 years from 2007 to 2016. The relative cancer incidences for this analysis were the difference in the cancer patients per hundred thousand people year-on-year in the administrative districts with the five highest and the five lowest natural gamma dose rates each year over the same period. To analyze the correlation between the two variables, Spearman's rank correlation coefficient between the two rates was derived using R, a well-known big data analysis tool. The analysis showed that Spearman's rank correlation coefficient was more than 0.05 and that the correlation between the two variables was not statistically significant.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.1-14
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• 2016

This study analyzes consumers' preference trend, positive and negative factors in regards to luxury brands by researching changes in the consumer awareness of luxury brands, preference trends and psychological awareness based on big data to suggest a creative business strategy for corporations that can help Korean brands enter global luxury brand markets. The study results are as follows. Preferred items (consumer) psychology, positive awareness and negative awareness were derived based on the last five years of social big data on Korean consumers' preferred brands. First, the Korean consumers' preferred brands for the recent five years indicated that Dolce & Gabbana (2013), ESCADA (2012), Gucci (2011, 2009) and Chanel (2010) were most preferred and Prada, Louis Vuitton, Hermes, Burberry, Fendi, Givenchy and Dior were also shown to be preferred brands. Second, bags (such as shoulder bags) were shown to be the most preferred items for luxury brand items that consumers wished to own. Third, it was analyzed that keywords for consumer psychology in regards to luxury brands included: diverse, new, outstanding, overwhelming, luxurious, glamorous, worldwide, famous, success and good. Fourth, consumers' positive awareness regarding luxury brands included: diverse, luxury, famous, outstanding, perfect, bright and luxurious. Fifth, negative awareness included: price factors of expensive, high price and excessive as well as factors to be improved upon such as old, bland, flashy, crude, unfriendly and fake.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.219-227
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• 2017

The purpose of this study is to verify the mediating effects of self-efficacy in correlation between conscientiousness and neuroticism among the Big Five personality traits and stress coping strategies. The following two study questions were formulated. Study Question 1: What is the correlation between the Big Five personality traits, stress coping strategies, and self-efficacy Study Question 2: Among the Big Five personality traits, conscientiousness and neuroticism are selected as clinically very meaningful variables that represent mental health in undergraduates. If so, does self-efficacy play a mediating role in the correlation between conscientiousness and neuroticism and stress coping strategies To verify the two study questions, the Big Five personality traits, stress coping strategies scale, and self-efficacy scale were measured for a sample of 462 freshmen attending D University located in Chungcheong. First, according to the results of correlation analysis, neuroticism and self-efficacy showed a negative correlation, and conscientiousness showed a positive correlation. Regarding the Big Five personality traits and stress coping strategies, conscientiousness showed a negative correlation with avoidance-orientation among stress coping strategies. Neuroticism showed a negative correlation with social support and problem solving-orientation among stress coping strategies. Second, according to the results of analyzing the mediating effects of self-efficacy through hierarchical regression analysis, self-efficacy exerted partial mediating effects only in correlation between neuroticism and avoidance-orientation. This study is significant in its anticipation of undergraduates' stress coping, personality factors can be usefully employed as psychological constructs, and particularly, when an undergraduate reveals the neuroticism factor, which is one of the predictors for mental health, and the tendencies of avoidance among stress coping strategies, educational interventions for self-efficacy are needed to reduce their mental stress.