• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.267-272
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• 2012

IT convergence, social media, and the companies' customer service industry advancement, data collection activities, explosion of multimedia content with increased smartphone penetration, SNS activation networks to expand the pool of things, 10 years ago, the amount of data eunneun evenly across industries, EDW (Enterprisehad increased the demand for the Data Warehouse).Recent proliferation of SNS users and applied research background with Big Data as a new study is proposed to proceed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1341-1346
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• 2015

Nowadays, many small businesses have experienced the failure of business or hardship. In this point, specific and integrated information for startup business should be required to decrease the rate of failure and to increase the rate of success. This study is to suggest the integration of various data which various public institutions have separately. For this purpose, it is to classify the data types in constructing big-data for start-up business and to suggest a way of data integration, analysis method, and web or services of information system for supporting startup businesses.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.593-606
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• 2017

This study aims to provide preliminary data capable of suggesting directivity of an initiating start by understanding consumer awareness through analysis of SNS social big data on marine sports. This study selected windsurfing, yacht, jet ski, scuba diving and sea fishing as research subjects, and produced following results by setting period of total 1 month from January 22 through February 22, 2017 on the SNS (twitter, blog) through the Social MatrixTM service of Daumsoft Co., Ltd., and analyzing frequency of mention, associated words etc. First, sports that was mentioned the most out of marine sports was yacht, which was 3,273 cases on twitter and 2,199 on blog respectively. Second, the word which was shown the most associated with marine sports was the attribute showing unique characteristic of marine sports, which was 6,261 cases in total.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.98-108
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• 2022

In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords "travel destination" and "travel trend" based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.

• Journal of The Korean Astronomical Society
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• v.35 no.3
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• pp.143-149
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• 2002

In this paper we present a methodology to derive the temporal change of the magnetic shear angle from a series of vector magnetograms, with a high time cadence. This method looks for the minimum change of the shear angle between a pair of magnetograms, free from the $180^{\circ}$ ambiguity, and then accumulates this change over many successive pairs to derive the temporal change of magnetic shear. This methodology will work well if only the successive magnetograms occurred in an active region are well aligned and its helicity sign is reasonably determined. We have applied this methodology to a set of vector magnetograms of NOAA Active Region 9661 on October 19, 2001 by the new digital magnetograph at the Big Bear Solar Observatory (BBSO). For this work we considered well aligned magnetograms whose cross-correlation values are larger than 0.95. As a result, we have confirmed the recent report of Wang et al. that there was the abrupt shear change associated with the X1.6 flare. It is also demonstrated that the shear change map can be an useful tool to highlight the local areas that experienced the abrupt shear change. Finally, we suggest that this observation should be a direct support of the emergence of sheared magnetic fields.

• Culinary science and hospitality research
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• v.24 no.2
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• pp.34-43
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• 2018

The objective of this study was to acquire a general and text-based awareness and recognition of cruise food hygiene through big data analytics. For the purpose, this study collected data with conducting the keyword "food hygiene, cruise" on the web pages and news on Google, during October 1st, 2015 to October 1st, 2017 (two years). The data collection was processed by SCTM which is a data collecting and processing program and eventually, 899 kb, approximately 20,000 words were collected. For the data analysis, UCINET 6.0 packaged with visualization tool-Netdraw was utilized. As a result of the data analysis, the words such as jobs, news, showed the high frequency while the results of centrality (Freeman's degree centrality and Eigenvector centrality) and proximity indicated the distinct rank with the frequency. Meanwhile, as for the result of CONCOR analysis, 4 segmentations were created as "food hygiene group", "person group", "location related group" and "brand group". The diagnosis of this study for the food hygiene in cruise industry through big data is expected to provide instrumental implications both for academia research and empirical application.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.57-68
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• 2018

This paper presents a smart firefighting appliances monitoring system based on big data analytics platform using GS1 for Smart City. Typical firefighting appliances are fire hydrant, fire extinguisher, fire alarm, sprinkler, fire engine, etc. for the fire of classes A/B/C/D/E. Among them, the dry chemical fire extinguisher have been widely supplied and 6 millions ones were replaced for the aging ones over 10 years in the past year. However, only 5% of them have been collected for recycling of chemical materials included the heavy metals of environment pollution. Therefore, we considered the trace of firefighting appliances from production to disposal for the public open service. In the paper, we suggest 1) a smart firefighting appliances system using GS1, 2) a big data analytics platform and 3) a public open service and visualization with the analyzed information, for fire extinguishers from production to disposal. It can give the information and the visualized diagrams with the analyzed data through the public open service and the free Apps.

• Korea Journal of Hospital Management
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• v.23 no.4
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• pp.26-39
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• 2018

Purposes: The purpose of this study is to analyze the issue of interest in patient medical service of small and medium hospitals using big data. Methods: The method of this study was implemented by data mining and social network using SNS big data. The analysis tool were extracted key keywords and analyzed correlation by using Textom, Ucinet6 and NetDraw program. Findings: In the results of frequency, the network-centered and closeness centrality analysis, It was shown that the government center is interested in the major explanations and evaluations of the technology, information, security, safety, cost and problems of small and medium hospitals, coping with infections, and actual involvement in bank settlement. And, were extracted care for disabilities such as pediatrics, dentistry, obstetrics and gynecology, dementia, nursing, the elderly, and rehabilitation. Practical Implications: Future studies will be more useful if analyzed the needs of customers for medical services in the metropolitan area and provinces may be different in the small and medium hospitals to be studied, further classification studies.

• Korean Journal of Childcare and Education
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• v.18 no.6
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• pp.145-162
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• 2022

Objective: The purpose of this study was to examine the differences in parental involvement and parenting stress according to the father's personality type. Methods: The subjects of this study were 302 fathers with children aged three to five living in Seoul, and a survey was conducted on their Big Five personality types, parental involvement, and parenting stress.The collected data were analyzed using K-means cluster analysis and covariance analysis. Results: In this study, fathers' personality types were classified into four types: 'sincerity, friendship, openness'(21.5%), 'neuroticism'(27.8%), 'sincerity'(29.4%), and 'low sincerity'(21.1%). These are the exact same Fathers in the 'sincere, friendly, open' group showed higher parental involvement and lower parental stress, while fathers in the 'neurotic' group showed lower parenting involvement and higher parenting stress. Conclusion/Implications: There was a difference in parental involvement and parenting stress according to the father's personality type.Based on these results, it is expected that the understanding of the father's personality will be come clearer and the foundation for constructing a program related to parenting which considers personality types will be established.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.999-1005
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• 2016

The advent of big data brings the opportunity to answer many open scientic questions but also presents some interesting challenges. Main features of contemporary datasets are the high dimensionality and massive sample size. In this paper, we give an overview of major challenges caused by these two features: (1) noise accumulation and spurious correlations in high dimensional data; (ii) computational scalability for massive data. We also provide applications of big data in various fields including forecast of disasters, digital humanities and sabermetrics.