• Title, Summary, Keyword: Big Date

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Building Linked Big Data for Stroke in Korea: Linkage of Stroke Registry and National Health Insurance Claims Data

  • Kim, Tae Jung;Lee, Ji Sung;Kim, Ji-Woo;Oh, Mi Sun;Mo, Heejung;Lee, Chan-Hyuk;Jeong, Han-Young;Jung, Keun-Hwa;Lim, Jae-Sung;Ko, Sang-Bae;Yu, Kyung-Ho;Lee, Byung-Chul;Yoon, Byung-Woo
    • Journal of Korean Medical Science
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    • v.33 no.53
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    • pp.343.1-343.8
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    • 2018
  • Background: Linkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases. Methods: Acute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006-2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA. Results: Of 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1-7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable. Conclusion: We could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.

Analyzing Box-Office Hit Factors Using Big Data: Focusing on Korean Films for the Last 5 Years

  • Hwang, Youngmee;Kim, Kwangsun;Kwon, Ohyoung;Moon, Ilyoung;Shin, Gangho;Ham, Jongho;Park, Jintae
    • Journal of information and communication convergence engineering
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    • v.15 no.4
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    • pp.217-226
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    • 2017
  • Korea has the tenth largest film industry in the world; however, detailed analyses using the factors contributing to successful film commercialization have not been approached. Using big data, this paper analyzed both internal and external factors (including genre, release date, rating, and number of screenings) that contributed to the commercial success of Korea's top 10 ranking films in 2011-2015. The authors developed a WebCrawler to collect text data about each movie, implemented a Hadoop system for data storage, and classified the data using Map Reduce method. The results showed that the characteristic of "release date," followed closely by "rating" and "genre" were the most influential factors of success in the Korean film industry. The analysis in this study is considered groundwork for the development of software that can predict box-office performance.

Hadoop System Design for Big data Processing of RFID Distribution (RFID/NFC 물류의 빅 데이터 처리를 위한 하둡 시스템의 설계)

  • Kim, Nam-Ho;Noh, Jin-Heon;Jeong, Hee-Ja
    • Smart Media Journal
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    • v.2 no.3
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    • pp.47-53
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    • 2013
  • Recently convergence of IT in logistics system as a typical application RFID/NFC technology is being used, such as, according to the distribution of the flow is generated by a lot of big data. The Hadoop distributed system to collect data items produced by the parallel processing capabilities of logistics information and logistics information for the record management can create. Hadoop system to support the design and development of prototypes were approaching the possibility of its utilization.

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A Study on Up-to-date Technology Development in Small & Medium Industries of Korea. (우리나라 중소기업의 첨단기술개발에 관한 연구)

  • 신현재;서승록
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.6 no.9
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    • pp.45-59
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    • 1983
  • This study focuses on the growth and development of small and medium industries of Korea, orienting to the development of up-to-date technology from now on and bolstering their competitive ability in the rapidly changing international markets. For this purpose, the small and medium industries should 1) develop high-level manpower of up-to-date technology, 2) make constant efforts to categorize and divide the fields of technology with big business groups to boost their competitiveness, 3) raise automation rate by turning all facilities into mechatronics, 4) positively develop software know-how, 5) jointly conduct researches in cooperation with venture capital and Governmental research institute, 6) categorize an systematize the industries. On the Governmental level, there should be 1) wide-ranging support and assistance in technology, finance, and the facilities, 2) positive opening of consumer market, 3) assistance in technical cooperation with other nations, 4) and such indirect assistance as fostering the fields of related technology.

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Design of a Smart Application using Big Data (빅 데이터를 이용한 스마트 응용의 설계)

  • Oh, Sun-Jin
    • The Journal of The Institute of Internet, Broadcasting and Communication
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    • v.15 no.6
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    • pp.17-24
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    • 2015
  • With the rapid growth of Information technology and up-to-date wireless network application technologies, huge and various types of data are produced in every moment, the value and significance of the analysis techniques using big data are increased recently. Big data, which were useless since they were too huge to manage in the past, enables us to get new inspirations and values in various practical application areas through the development of big data computing devices and analytic tools. Nowadays, however, it is true that most of the big data are still wasted without properly analyzed and used. In the long run, the preliminary stipulations for finding inspirations and extracting new values from big data are securing big data analysis and application techniques to process big data efficiently. In this paper, we study accurate data analysis techniques and data process technologies those are able to extract needed inspirations and values from big data efficiently, then design the smart application that adopts these techniques practically.

A Study on the Frequency and Intensity Variations of Okhotsk High: Focused on the Korean Peninsula (오호츠크해고기압의 출현일과 강도의 변동에 관한 연구 -한반도에 영향을 미친 날을 중심으로-)

  • Cho, Li-Na;Lee, Seung-Ho
    • Journal of the Korean Geographical Society
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    • v.46 no.1
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    • pp.36-49
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    • 2011
  • This paper aims to investigate the frequency and intensity variations of Okhotsk high pressure system focused on the Korean Peninsula. Weather chart (00UTC), daily weather data and reanalysis data were used. The first occurrence date of Okhotsk high pressure system tends to be earlier in those years that surrounding land air temperature in April is high. The frequency of Okhotsk high has recently decreased, and its intensity tends to be stronger when the difference between sea surface temperature and surrounding land air temperature is big. The frequency of Okhotsk high in April, May, June and July increases when surrounding land air temperature is high, and its intensity grows when the difference between surrounding land air temperature and sea surface temperature is big. The frequency of Okhotsk high may increase and its intensity may increase when the first occurrence date comes earlier. In June, however, the reverse may apply.

A Study on the Development of the Use Index of Closed School Facilities Using Big Data -Focused on Text-Mining Techniques- (빅데이터를 활용한 폐교시설의 지표 개발에 관한 연구 -텍스트마이닝 기법을 중심으로-)

  • Kim, Jae-Young;Lee, Jong-Kuk
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.18 no.2
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    • pp.1-11
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    • 2019
  • The purpose of this study is to make objective decisions in the use of closed schools through the development of utilization indicators for the efficient use of closed schools, which is expected to increase continuously. The research phase was largely carried out by drawing preliminary indicators for use in closed schools, drawing final indicators using big data, and quantifying indicators, and finally objectifying them through quantification. The institution intends to apply and verify the facility based on future indicators. This study has implications for the application of big data analysis methods that have not been attempted in planning and research for the use of closed school facilities to date.

Fire detection system and alarm system using wild boars (동물들을 이용한 재난 조기 경보 시스템의 설계 및 분석)

  • Jeong, Eui-Jong;Lee, Goo-Yeon
    • Proceedings of the IEEK Conference
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    • pp.719-720
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    • 2006
  • Ad hoc networks does not need any wired network infrastructure. Therefore, they have been developed in temporary networks or mainly in military networks. Infostations offer geographically intermittent coverage at high speeds. Up-to-date there have been frequent big forest fires in Korea mountain areas. It is very important to detect them early to prevent them from being big disasters. In this paper, we propose a disaster emergency management system using sensor attached wild boars' mobility combined with infostation system. We also make a numerical analysis of the performance of the system.

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An Effective Data Model for Forecasting and Analyzing Securities Data

  • Lee, Seung Ho;Shin, Seung Jung
    • International journal of advanced smart convergence
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    • v.5 no.4
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    • pp.32-39
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    • 2016
  • Machine learning is a field of artificial intelligence (AI), and a technology that collects, forecasts, and analyzes securities data is developed upon machine learning. The difference between using machine learning and not using machine learning is that machine learning-seems similar to big data-studies and collects data by itself which big data cannot do. Machine learning can be utilized, for example, to recognize a certain pattern of an object and find a criminal or a vehicle used in a crime. To achieve similar intelligent tasks, data must be more effectively collected than before. In this paper, we propose a method of effectively collecting data.

The wireless CDMA ALOHA System Concept for the Voice/Data Integrated Transmission and Its traffic Analysis (음성/데이터 통합 전송을 위한 무선 CDMA ALOHA 시스템 구상과 그 트래픽 분석)

  • Kwon, Ki-Hyung
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.173-179
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    • 2010
  • Currently, the communication systems are progressing two ways as the wireless and multimedia and these need big transmission capacity then before. In these circumstance, communication services existed as two different service forms which have different rates and characteristics. For example Voice/Video Services accept some errors but transmit on realtime, but Date Services don't need to transmit on realtime but have to retransmit if these have only one bit error. In Voice/Date Integrated traffics, it has big throughput that realtime voice/video data which could have some errors if integrated traffic is increased rapidly have transmission priority, then Data traffics which delay is accepted is sent after that. In this paper, I introduce the calculation method for various traffic when voice/data mixed traffics is transmitted to asynchronous unslotted ALOHA CDMA system proposed and the result is presented. And We can easily theoretical analysis for the system traffic and changing traffic using proposed solution in this paper.

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