• Title/Summary/Keyword: BIG4

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A Proposal for SmartTV Development Plan by Applying Big Data Analysis Methodology (빅데이터 분석 방법을 적용한 스마트 TV의 발전 방안에 관한 제언)

  • Park, Nam-Gue;Kim, Sun-Bae
    • Journal of Digital Convergence
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    • v.12 no.1
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    • pp.347-358
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    • 2014
  • A smart TV is able to show terrestrial broadcasting and also can be used as a computer -VOD, games, image communications, application utilities and so on. In order to carry out Smart TV business, it has to contains contents, platforms, network terminal unit. If ill-equipped with any of these aboves, it must cooperate with other licensee. Therefore, Smart TV business is necessary to cooperate with each business agent. In this paper, we will look into domestic/foreign country Smart TV market, policy, vitalization strategy, and suggest the application of big data analysis methodology for Smart TV vitalization method - 1) hardware infrastructure building based on cloud computing 2) Network upgradability acceptable traffic increase 3) Technical development cooperation between each licensee 4) Variable Smart TV contents supply 5) Cooperation with party interested individuals in using UX/UI for N-Screen, network traffic estimation may increase, customized supply smart contents for consumer in real time.

Development of Distributed Smart Data Monitoring System for Heterogeneous Manufacturing Machines Operation (이종 공작기계 운용 관리를 위한 분산 스마트 데이터 모니터링 시스템 개발)

  • Lee, Young-woon;Choi, Young-ju;Lee, Jong-Hyeok;Kim, Byung-Gyu;Lee, Seung-Woo;Park, Jong-Kweon
    • Journal of Digital Contents Society
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    • v.18 no.6
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    • pp.1175-1182
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    • 2017
  • Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

Analysis of Personal Information Protection Circumstances based on Collecting and Storing Data in Privacy Policies (개인정보처리방침의 데이터를 활용한 개인정보보호 현황 분석)

  • Lee, Jae-Geun;Kang, Sang-Ug;Youm, Heung-Youl
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.23 no.4
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    • pp.767-779
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    • 2013
  • A field of privacy protection lacks statistical information about the current status, compared to other fields. On top of that, since it has not been classified as a concrete separate field, the related survey is only conducted as a part of such concrete areas. Furthermore, this trend of being regarded as a part of fields such as informatization, information protection and law will continue in the near future. In this paper, a novel and practical way for collecting and storing a big amout of data from 110,000 privacy policies by data controller is proposed and the real analysis results is also shown. The proposed method can save time and cost compared with the traditional survey-based method while maintaining or even advancing the accuracy of results and speediness of process. The collected big personal data can be used to set up various kinds of statistical models and they will play an important role as a breakthrough of observing the present status of privacy information protection policy. The big data concept is incorporated into the privacy protection and we can observe the method and some results throughout the paper.

A Study on Big Data Based Investment Strategy Using Internet Search Trends (인터넷 검색추세를 활용한 빅데이터 기반의 주식투자전략에 대한 연구)

  • Kim, Minsoo;Koo, Pyunghoi
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.4
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    • pp.53-63
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    • 2013
  • Together with soaring interest on Big Data, now there are vigorous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, however, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other areas like Korea can be a disturbing task. This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.

Breast reconstruction statistics in Korea from the Big Data Hub of the Health Insurance Review and Assessment Service

  • Kim, Jae-Won;Lee, Jun-Ho;Kim, Tae-Gon;Kim, Yong-Ha;Chung, Kyu Jin
    • Archives of Plastic Surgery
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    • v.45 no.5
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    • pp.441-448
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    • 2018
  • Background Previously, surveys have been used to investigate breast reconstruction statistics. Since 2015, breast reconstruction surgery after mastectomy has been covered by the National Health Insurance Service in Korea, and data from breast reconstruction patients are now available from the Health Insurance Review and Assessment Service (HIRA). We investigated statistics in breast reconstruction in Korea through statistics provided by the HIRA Big Data Hub. Methods We investigated the number of cases in mastectomy and breast reconstruction methods from April 1, 2015 to December 31, 2016. Data were furnished by the HIRA Big Data Hub and accessed remotely online. Results were tabulated using SAS Enterprise version 6.1. Results The 31,155 mastectomy cases included 7,088 breast reconstruction cases. Implant-based methods were used in 4,702 cases, and autologous methods in 2,386. The implant-based reconstructions included 1,896 direct-to-implant and 2,806 tissue-expander (2-stage) breast reconstructions. The 2-stage tissue-expander reconstructions included 1,624 expander insertions (first stage) and 1,182 expander-to-permanent-implant exchanges (second stage). Of the autologous breast reconstructions, 705 involved latissimus dorsi muscle flaps, 498 involved pedicled transverse rectus abdominis myocutaneous (TRAM) flaps, and 1,183 involved free-tissue transfer TRAM flaps, including deep inferior epigastric perforator free-tissue transfer flaps. There were 1,707 nipple-areolar complex reconstructions, including 1,565 nipple reconstructions and 142 areola reconstructions. The 1-year mean number of breast reconstructions was 4,050. Conclusions This was the first attempt to evaluate the total number of breast reconstruction procedures using accurate, comprehensive data, and our findings may prove valuable as a foundation for future statistical studies of breast reconstruction procedures in Korea.

A Study on Big data Utilization Policy by the Complex System Theory: Focused on 2030 Seoul City Comprehensive Plan (복잡계이론에서의 빅데이터 활용방안에 관한 연구 (『2030 서울도시기본계획』을 중심으로))

  • Eum, Hee-Kyoung;Choi, Doo-Jin;Park, Sung-Chan;Chang, Hye-Jung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.4
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    • pp.281-298
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    • 2015
  • From the complexity system theory, City is dynamic system which has evolved through evolution and adaptation in initial conditions and different situation. So people's active should involve in decision-making processes in the urban planning. And this suggests that responding to the demands of its citizens are important factors influencing the process of urban planning. The implications of this study are following: using big data helps people understand current social phenomena. Specifically, it figured out latent needs of citizens that traditional survey methods could not before. we can make the most of new opportunities given by digital data and prevent potential dangers in advance. They are complementary and do not replace one another.

A Leading-price Analysis of Wando Abalone Producer Prices by Shell Size Using VAR Model (VAR 모형을 이용한 크기별 완도 전복가격의 선도가격 분석)

  • Nam, Jongoh;Sim, Seonghyun
    • Ocean and Polar Research
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    • v.36 no.4
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    • pp.327-341
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    • 2014
  • This study aims to analyze causality among Wando abalone producer prices by size using a vector autoregressive model to expiscate the leading-price of Wando abalone in various price classes by size per kg. This study, using an analytical approach, applies a unit-root test for stability of data, a Granger causality test to learn about interaction among price classes by size for Wando abalone, and a vector autoregressive model to estimate the statistical impact among t-1 variables used in the model. As a result of our leading-price analysis of Wando abalone producer prices by shell size using a VAR model, first, DF, PP, and KPSS tests showed that the Wando abalone monthly price change rate by size differentiated by logarithm were stable. Second, the Granger causality relationship analysis showed that the price change rate for big size abalone weakly led the price change rate for the small and medium sizes of abalone. Third, the vector autoregressive model showed that three price change rates of t-1 period variables statistically, significantly impacted price change rates of own size and other sizes in t period. Fourth, the impulse response analysis indicated that the impulse responses of structural shocks for price change rate for big size abalone was relatively more powerful in its own size and in other sizes than shocks emanating from other sizes. Fifth, the variance decomposition analysis indicated that the price change rate for big size abalone was relatively more influential than the price change rates for medium and small size abalone.

User Information Needs Analysis based on Query Log Big Data of the National Archives of Korea (국가기록원 질의로그 빅데이터 기반 이용자 정보요구 유형 분석)

  • Baek, Ji-yeon;Oh, Hyo-Jung
    • Journal of the Korean Society for information Management
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    • v.36 no.4
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    • pp.183-205
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    • 2019
  • Among the various methods for identifying users's information needs, Log analysis methods can realistically reflect the users' actual search behavior and analyze the overall usage of most users. Based on the large quantity of query log big data obtained through the portal service of the National Archives of Korea, this study conducted an analysis by the information type and search result type in order to identify the users' information needs. The Query log used in analysis were based on 1,571,547 query data collected over a total of 141 months from 2007 to December 2018, when the National Archives of Korea provided search services via the web. Furthermore, based on the analysis results, improvement methods were proposed to improve user search satisfaction. The results of this study could actually be used to improve and upgrade the National Archives of Korea search service.

Study on the Development of Congestion Index for Expressway Service Areas Based on Floating Population Big Data (유동인구 빅데이터 기반 고속도로 휴게소 혼잡지표 개발 연구)

  • Kim, Hae;Lee, Hwan-Pil;Kwon, Cheolwoo;Park, Sungho;Park, Sangmin;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.4
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    • pp.99-111
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    • 2018
  • Service areas in expressways are very important facilities in terms of efficient expressway operation and the convenience of users. It needs a traffic management strategy to inform drivers in advance about congestion in service areas so as to distribute users of service areas. But due to the lack of sensors and data on numbers of people in the service areas, congestion in service areas had not been measured and managed appropriately. In this study, a congestion index for service areas was developed using telecommunication floating population big data. Two alternative indices (i.e., density of service areas and floating population V/c of service areas) were developed. Finally, the floating population V/c of service areas was selected as a congestion index for service areas for reasons of the ease of understanding and comparison.

An Exploratory Analysis on the User Response Pattern and Quality Characteristics of Marketing Contents in the SNS of Regional Government (지역마케팅 콘텐츠의 사용자 반응패턴과 품질특성에 관한 탐색적 분석: 지방자치단체가 운영하는 SNS를 중심으로)

  • Jeong, Yeon-Su;Jeong, Dae-Yul
    • The Journal of Information Systems
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    • v.26 no.4
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    • pp.419-442
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    • 2017
  • Purpose The purpose of this study is to explore the pattern of user response and it's duration time through social media content response analysis. We also analyze the characteristics of content quality factors which are associate with the user response pattern. The analysis results will provide some implications to develop strategies and schematic plans for the operator of regional marketing on the SNS. Design/methodology/approach This study used mixed methods to verify the effects and responses of social media contents on the users who have concerns about regional events such as local festival, cultural events, and city tours etc. Big data analysis was conducted with the quantitative data from regional government SNSs. The data was collected through web crawling in order to analyze the social media contents. We especially analyzed the contents duration time and peak level time. This study also analyzed the characteristics of contents quality factors using expert evaluation data on the social media contents. Finally, we verify the relationship between the contents quality factors and user response types by cross correlation analysis. Findings According to the big data analysis, we could find some content life cycle which can be explained through empirical distribution with peak time pattern and left skewed long tail. The user response patterns are dependent on time and contents quality. In addition, this study confirms that the level of quality of social media content is closely relate to user interaction and response pattern. As a result of the contents response pattern analysis, it is necessary to develop high quality contents design strategy and content posting and propagation tactics. The SNS operators need to develop high quality contents using rich-media technology and active response contents that induce opinion leader on the SNS.