• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.89-114
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• 2021

This study analyzed the previous studies and utilization cases on library big data, and based on this, analyzed the collection/circulation data of the library big data platform and tried to derive meaningful analysis results. And five analysis indicators were selected: the increase rate of collections by annual, the composition of collections by subject, the composition of unborrowed collections by subject, the rate of borrowed collections, and use factor by subject. The analysis data is 6,722,603 cases of collection/circulation data from 33 public libraries in Busan. The main analysis results are as follows. First, it was found that the gap in the number of circulation was larger than the number of collection in the 33 public libraries. Second, the annual increase rate of collections also showed a clear decline. Third, each library showed a similar pattern in the composition of both the collections and the unborrowed collections by subject. Fourth, it was found that users' circulation were very different by subject and library. Fifth, in most libraries, the rate of circulation of collections and use factor in the natural science field were the highest.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.113-123
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• 2020

In this paper, big data analysis was conducted for past and present fashion trends and fashion cycle. We focused on daily look for ordinary people instead of the fashion professionals and fashion show. Using the social matrix tool, Textom, we performed frequency analysis, N-gram analysis, network analysis and structural equivalence analysis on the big data containing fashion trends and cycles. The results are as follows. First, this study extracted the major key words related to fashion trends for the daily look from the past(1980s, 1990s) and the present(2019 and 2020). Second, the frequence analysis and N-gram analysis showed that the fashion cycle has shorten to 30-40 years. Third, the structural equivalence analysis found the four representative clusters. The past four clusters are jean, retro codi, athleisure look, celebrity retro and the present clusters are retro, newtro, lady chic, retro futurism. Fourth, through the network analysis and N-gram analysis, it turned out that the past fashion is reproduced and evolves to the current fashion with certain reasoning.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.627-635
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• 2022

As the non-face-to-face situation continues for a long time due to COVID-19, the underlying technologies of the 4th industrial revolution such as IOT, AR, VR, and big data are affecting the metaverse platform overall. Such changes in the external environment such as society and culture can affect the development of academics, and it is very important to systematically organize existing achievements in preparation for changes. The Korea Educational Research Information Service (RISS) collected data including the 'metaverse platform' in the keyword and used the text mining technique, one of the big data analysis. The collected data were analyzed for word cloud frequency, connection strength between keywords, and semantic network analysis to examine the trends of metaverse platform research. As a result of the study, keywords appeared in the order of 'use', 'digital', 'technology', and 'education' in word cloud analysis. As a result of analyzing the connection strength (N-gram) between keywords, 'Edue→Tech' showed the highest connection strength and a total of three clusters of word chain clusters were derived. Detailed research areas were classified into five areas, including 'digital technology'. Considering the analysis results comprehensively, It seems necessary to discover and discuss more active research topics from the long-term perspective of developing a metaverse platform.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.13-24
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• 2021

This study used big data to analyze visitors' experiences in Fishing Experience Recreation Village. Through the portal site posting data for the past six years, the experience of visiting Fishing Experience Villages in Baekmi and Susan was analyzed. The analysis method used Text mining and Social Network Analysis which are Big data analysis techniques. Data was collected using Textom, and experience keywords were extracted by analyzing the frequency and importance of experience texts. Afterwards, the characteristics of the experience of visiting the Fishing Experience Village were identified through the analysis of the interaction between the experience keywords using 'U cinet 6.0' and 'NetDraw'. First, through TF and TF-IDF values, keywords such as "Gungpyeong Port", "Susan Port", and "Yacht Marina" that refer to the name of the port and the port facilities appeared at the top. This is interpreted as the name of the port has the greatest impact on the recognition of the Fishing Experience Villages, and visitors showed a lot of interest in the port facilities. Second, focusing on the unique elements of port facilities and fishing villages such as "mud flat experience", "fishing village experience", "Gungpyeong port", "Susan port", "yacht marina", and "beach" through the values of degree, closeness, and betweenness centrality interpreted as having an interaction with various experiences. Third, through the CONCOR analysis, it was confirmed that the visitor's experience was focused on the dynamic behavior, the experience program had the greatest influence on the experience of the visitor, and that the experience of the static and the dynamic behavior was relatively balanced. In conclusion, the experience of visitors in the Fishing Experience Villages is most affected by the environment of the fishing village such as the tidal flats and the coast and the fishing village experience program conducted at the fishing port facilities. In particular, it was found that fishing port facilities such as ports and marinas had a high influence on the awareness of the Fishing Experience Villages. Therefore, it is important to actively utilize the scenery and environment unique to fishing villages in order to revitalize the Fishing Experience Villages experience and improve the quality of the visitor experience. This study is significant in that it studied visitors' experiences in fishing village recreation villages using big data and derived the connection between fishing village and fishing village infrastructure in fishing village experience tourism.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.377-389
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• 2019

This study conducted social network big data analysis to investigate consumer's perception of Japanese sporting goods related to Japanese boycott and to extract problems and variables by recognition. Social network big data analysis was conducted in two areas, "Japanese boycott" and "Japanese sporting goods". Months of data were collected and investigated. If you specify the research method, you will identify the issues of the times - keyword setting using social network analysis - clustering using CONCOR analysis using TEXTOM and Ucinet 6 programs - variable selection through expert meetings - questionnaire preparation and answering - and validity of questionnaire Reliability Verification - It consists of hypothesis verification using the structural model equation. Based on the results of using the big data of social networks, four variables of relevant characteristics, nationality, attitude, and consumption behavior were extracted. A total of 30 questions and 292 questionnaires were used for final hypothesis verification. As a result of the analysis, first, the boycott-related characteristics showed a positive relationship with nationality. Specifically, all of the characteristics related to boycotts (necessary boycott, sense of boycott, and perceived boycott benefits were positively related to nationality. In addition, nationality was found to have a positive relationship with consumption behavior.

• The Journal of Bigdata
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• v.6 no.2
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• pp.71-84
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• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• Convergence Security Journal
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• v.20 no.2
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• pp.145-153
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• 2020

The aviation safety policy master plan is promoting the development of aviation safety management technology applying the 4th industrial revolution technology with the goal of establishing a flawless aviation safety management system and establishing a future aviation safety infrastructure. The master plan includes the establishment of various aviation safety management systems such as aircraft fault management using AI & Big data and flight training system using VR/AR. Currently, the Air Force is promoting a flight safety management system using new technology under the goal of building smart air force. Therefore, this study intends to apply the 4th Industrial Revolution technology to the aircraft condition check system that finally checks the safety of the aircraft before flight. The Air Force conducts airframe flaw checks and pre-flight aircraft check. In this study, we architect the airframe flaw check system using AI and drones, and the pre-flight aircraft condition check system using the IoT and big data for more precise and detailed check of aircraft condition and flawlessness check.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1117-1128
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• 2015

In order to secure an important competitive advantage in manufacturing business, an automation and information system from manufacturing process has been introduced; however, small and medium enterprises have not met the power of information in the manufacturing fields. They have been managing the manufacturing process that is depending on the operator's experience and data written by hand, which has limits to reveal cause of defective goods clearly, in the case of happening of low-grade goods. In this study, we analyze critical factors which affect the quality of some manufacturing process in terms of 4M. We also studied the automobile parts processing of the small and medium manufacturing enterprises controlled with data written by hand so as to collect the data written by hand and to utilize sensor data in the future. Analysis results show that there is no deference in defective quantity in machines, while raw materials, production quality and task tracking have significant deference.

• Journal of Society of Preventive Korean Medicine
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• v.3 no.2
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• pp.25-53
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• 1999

This study was conducted to provide basic data for policy of Oriental medicine by analyzing community residents' consciousness of taking herb medicine and its related factors. Data were collected from 1478 residents from March 2, 1999 to May 31, 1999. The results of this study are summarized as follows. 1. According to general characteristics of the subjects, 52.3% of the subjects was 'female'; 25.0% 'fifties of age'; 21.4% 'forties of age'; 20.9% 'thirties of ages'; 69.1% 'married'; 60.1% 'resident in a big city'; 12.1% 'residents in a small town or village'; 39.0% 'highschool graduate'; 35.9% 'above college graduate'; 23.4% 'housewife'; 23.4% 'professional' 34.1% 'Buddhist'; 81.1% 'middle class'. 2. The rate of experience of taking herb medicine was 85.2%(88.2% of 'male'; 82.5% of 'female'). It appeared to be significantly higher in the groups of 'the married', 'housewife', and 'Buddhist'. As the age increased, so the rate of experience of taking herb medicine was significantly high. 3. In case of purpose of taking herb medicine, taking herb medicine as a restorative(66.8%) was much higher than taking it as a curative medicine. Taking herb medicine as a curative medicine appeared to be significantly higher in the groups of 'male', 'thirties of age', 'resident in a town or village', 'above college graduate', 'professional technician', 'Christian', and 'the upper class'. 4. 52.1% of the respondents satisfied with the effect of herb medicine. The groups of 'male', 'older age', 'residents in a big city', 'insurant in company', and 'the employed' showed significantly high rate in satisfying with herb medicine than the other groups. 5. According to the reason for preferring herb medicine, 36.7% of the respondents preferred herb medicine because the herb medicine was effective, while 27.8% preferred it because its side effect was low. 16.7% preferred it. because persons around them recommended it. The preference for the herb medicine displayed significantly higher rate in the groups 'sixties of age', 'the unmarried', 'resident in a big city', 'office clerk', and 'the lower class'. 6. 42.6% of the respondents did not want to take the herb medicine because the price of the herb medicine was high. Also 20.6% of the respondents did not want to take herb medicine because it is uneasy to take herb medicine. 15.8% did not want to take it because certain foods should not be taken during the period of taking it. 9.4% did not want to take it because it tasted bitter. 7. In case of opinions on side effects of herb medicine, 40.8% of the respondents thinks that herb medicine is free from side effects, while 37.5% thinks that it causes side effects. There were significant difference in the opinions on side effects by sex, age, marital status, resident area, education level, occupation, and type of health insurance. 8. 60.7% of the respondents thinks the price of herb medicine is not resonable, while only 10.9% thinks it is resonable. 9. 14.2% of the respondents thinks health foods which contain herbs are good, while 16.8% thinks it is bad. 76.7% thinks that medicinal herbs in packages must be included in health insurance coverage, while only 3.0% thinks it needs not be included in health insurance coverage. 10. 45.2% of the respondents uses packs of decocted herbs although they think the packs of decocted herb are a little low effective because decocting herbs in home is bothersome. 45.2% uses packs of decocted herbs because they are convenient, being not related to the effect. 7.6% takes medicinal herbs after decocting them in a clay pot because they think the packs of decocted herbs have low effect. 11. According to the level of satisfaction with Oriental medical care, the respondents marked $3.47{\pm}0.64$ points on the base of 5 points. It was significantly higher in the groups of 'male', 'the married, resident in a big city', 'highschool graduate', 'the unemployed', 'office clerk', 'growing up in a big city', 'insurant in region', and 'the middle class'. 12. According to the result of a regression analysis of factors influencing preference for herb medicine, the factors displayed significant difference by sex, age, education level, health status, and times of receiving Oriental medical care. As shown in the above results, the community residents satisfy with the effect of herb medicine. Therefore, the method of taking herb medicine without difficulty must be devised. The medicinal herbs in packages need to be included in health insurance coverage and resonable price of herb medicine must be set. Also, education program for community residents must be developed in order to provide right information in herb medicine. Therefore, related public authority, associations, and professionals must make efforts, forming organic cooperative system.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.445-447
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• 2007

This paper is seeing as one big cause that reduce Life Time of sensor node become soft if BackOff Time is prolonged in CDMA/CA of competition way that consist at data transmission of each sensor nodes base sensor network environment. So solution method uses GTS, wish to reduce competition Node's, and minimise data transmission delay.