• Title/Summary/Keyword: BIG4

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The Prediction of Floodplain Using Web GIS (Web GIS를 이용한 침수범위 예측)

  • 강준묵;윤희천;이형석;강영미
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.19 no.4
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    • pp.337-342
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    • 2001
  • A natural disaster occupies a considerable part among various damages, and the damage of human lifes and property by heavy rain extends to hundreds, and billions in every you. In old times, flood was mainly occurred in big river or sudden slope, but these days, the damage of concentrated heavy rain is being extended to a city. Recently, very big floods occurred continuously, so real time submersion expectation system which can expect the inundation boundary according to the scale is needed so as to protect lifes and property. In this study, in and around Jungrang river, where the damage of flood is big, is chosen as a sample, and the submersion of that area is expected by analyzing the flux and overflowing using DEM, and connecting with Web GIS in real time.

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Survey of Shoes Wearing Reality and Old Males Foot Types

  • Shim, Boo-Ja;Yoo, Hyun
    • Journal of Fashion Business
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    • v.11 no.3
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    • pp.1-14
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    • 2007
  • This research to reveal the foot types of old males consisted of two parts. First, a questionnaire was given for 180 old men in their 60s and above who live in Busan. Second, based on this survey on the reality of shoes wearing, direct and indirect measurement were held for 200 old gentlemen. The findings are as follows: 1. Survey Results of Shoes Wearing Reality In the investigation into the reality of shoes possession and wearing, most of old males favored active casual shoes with comfortable materials (40.8%). Hardened skin (23.6%) was the greatest in foot deformation and side effects resulting from shoes wearing, while the big toe (20.1%) was most uncomfortable. The greatest requirement for comfortable shoes was shoes making feet comfortable with a good sense of wear (41.0%), followed by shoes with the soft sole to absorb shock (31.7%), shoes with diverse sizes according to shoes width (13.7%), and shoes made of soft materials in consideration of various foot shapes. 2. Results of Foot Measurement Experiments Busan's males in their 60s and above were 166.31cm (Height), 63.51kg (weight), 23.94cm (foot length), 9.75cm (foot width), and 24.26cm (instep girth). The big toe angle of old males was $11.22^{\circ}$ and the little toe angle $14.70^{\circ}$. Four foot types were classified: 1 (long big foot), 2 (small inside-developed foot), 3 (toe-tip-gathered foot), and 4 (thin flat foot).

Research Trends Analysis of Big Data: Focused on the Topic Modeling (빅데이터 연구동향 분석: 토픽 모델링을 중심으로)

  • Park, Jongsoon;Kim, Changsik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.1
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    • pp.1-7
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    • 2019
  • The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

An Automatic Urban Function District Division Method Based on Big Data Analysis of POI

  • Guo, Hao;Liu, Haiqing;Wang, Shengli;Zhang, Yu
    • Journal of Information Processing Systems
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    • v.17 no.3
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    • pp.645-657
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    • 2021
  • Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.

Classification of Inverter Failure by Using Big Data and Machine Learning (빅데이터와 머신러닝 기반의 인버터 고장 분류)

  • Kim, Min-Seop;Shifat, Tanvir Alam;Hur, Jang-Wook
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.3
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    • pp.1-7
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    • 2021
  • With the advent of industry 4.0, big data and machine learning techniques are being widely adopted in the maintenance domain. Inverters are widely used in many engineering applications. However, overloading and complex operation conditions may lead to various failures in inverters. In this study, failure mode effect analysis was performed on inverters and voltages collected to investigate the over-voltage effect on capacitors. Several features were extracted from the collected sensor data, which indicated the health state of the inverter. Based on this correlation, the best features were selected for classification. Moreover, random forest classifiers were used to classify the healthy and faulty states of inverters. Different performance metrics were computed, and the classifiers' performance was evaluated in terms of various health features.

Covid 19 News Data Analysis and Visualization

  • Hur, Tai-Sung;Hwang, In-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.4
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    • pp.37-43
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    • 2022
  • In this paper, we calculate the word frequency by date and region using news data related to COVID-19 distributed for about 8 months from December 2019 to July 2020, and visualized the correlation with the current state data of COVID-19 patients using the results. News data was collected from Big Kids, a news big data system operated by the Korea Press Promotion Foundation. The visualization system proposed in this paper shows the news frequency of the selected region compared to the overall region, the key keyword of the selected region, the region of the main keyword, and the date change of the selected region. Through this visualization, the main keywords and trends of COVID-19 confirmed and infected people can be identified for previous events.

A Trend Analysis of Changes in Housework due to Technological Innovation and Family Change

  • LEE, Hyun-Ah;KWON, Soonbum
    • East Asian Journal of Business Economics (EAJBE)
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    • v.10 no.1
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    • pp.109-121
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    • 2022
  • Purpose - This study attempted to analyze news big data in order to examine the trend of change in housework due to technological innovation and family changes. Research design, data, and methodology - News big data was collected from Bigkinds for the purpose of trend analysis. A total of 8,270 articles containing 'housework' were extracted from news articles between January 1, 1990 and December 31, 2021. 11 general daily newspapers and 8 business newspapers were selected and were analyzed by dividing them into five-year units. Result - The change of trends in housework that appeared through news big data analysis can be summarized as below. First, the tendency to regard housework as work of women or housewives is gradually weakening. Instead, the centrality of connection with double income is increasing. Second, there is a tendency to strengthen the institutional approach to evaluation of the productivity of housework. Third, the possibility of market substitution for housework is expanding. Conclusion - In the era of the 4th industrial revolution, examining the impact of technological innovation and family change on housework not only enables the prospect of an industry, but also provides implications for policies related to housework. In addition, this study is differentiated in that it contributed to expand the field of housework research previously limited to analyzing survey data.

Design of Public Transportation Route Guidance System for Wheelchair Users Utilizing Public Data of Seoul City

  • Geumbi, Lee;Humberto, Villalta;Seunghyun, Kim;Kisu, Kim;Jaehyeong, Go;Yongjoo, Jun;Kwang Sik, Kim
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.1
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    • pp.97-112
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    • 2023
  • The purpose of this study is to design and test a new way of public transportation route guidance system for persons with disabilities, including wheelchair users. The guidance system is smartphone app-based, using, routes that involve disabled-friendly facilities in the vicinity can be searched. A database that contains publicly available data on low-floor bus services, location and extent of disabled-friendly facilities, and suitable subways and stations, was developed for this purpose. The app uses the database to access and query the required information. A pilot study was conducted to test the effectiveness of the guidance system. It was found that the system was able to convey information about the disabled-friendly routes and related guidance information even inside subway stations, effectively. The performance of the system was compared with route guidance services that do not explicitly use data on disabled-friendly services. A notable difference was observed in the travel time estimated by this program and other guidance services. The difference was around 4 to 15 minutes. This is significant savings for persons with disabilities if they use the app and service. The study thus shows that exclusive use of disabled-friendly data in route guidance will bring more benefits for persons with disabilities.

Development of Mission and Vision of College of Korean Medicine Using the Delphi Techniques and Big-Data Analysis

  • Yeo, Sanghee;Choi, Seong Hun;Chae, Su Jin
    • The Journal of Korean Medicine
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    • v.42 no.4
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    • pp.176-184
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    • 2021
  • Objectives: The purpose of this study is to introduce the procedures and methods for mission and vision development at a College of Korean Medicine (CKM), which established its mission and vision using Delphi techniques and big data analysis on various members and stakeholders. Methods: A total of 754 participated in the Delphi survey. A Delphi survey was conducted with professors, students, parents, and alumni stakeholders to establish Daegu Haany University CKM's mission and vision. The data were analyzed through content analysis and big data analysis of keywords. Results: As a result of the study, the most important keywords to be included in the mission and vision were "professionalism" and "morality." Included in the mission were the concepts of "morality" and "professionalism," which were emphasized by the four groups. All surveyed stakeholders regarded "scientific," and "global" as important themes to be included in the vision. Conclusions: The present study confirmed that there were themes commonly prioritized by all stakeholders for college mission and vision, and a difference in demand for educational goals between professors and students was also affirmed. Therefore, institutions of higher learning should develop their mission and vision by appropriately reflecting the needs of the interest groups.

Korean Coreference Resolution at the Morpheme Level (형태소 수준의 한국어 상호참조해결 )

  • Kyeongbin Jo;Yohan Choi;Changki Lee;Jihee Ryu;Joonho Lim
    • Annual Conference on Human and Language Technology
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    • 2022.10a
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    • pp.329-333
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    • 2022
  • 상호참조해결은 주어진 문서에서 상호참조해결 대상이 되는 멘션(mention)을 식별하고, 동일한 개체(entity)를 의미하는 멘션들을 찾아 그룹화하는 자연어처리 태스크이다. 최근 상호참조해결에서는 BERT를 이용하여 단어의 문맥 표현을 얻은 후, 멘션 탐지와 상호참조해결을 동시에 진행하는 End-to-End 모델이 주로 연구가 되었다. 그러나 End-to-End 방식으로 모델을 수행하기 위해서는 모든 스팬을 잠재적인 멘션으로 간주해야 되기 때문에 많은 메모리가 필요하고 시간 복잡도가 상승하는 문제가 있다. 본 논문에서는 서브 토큰을 다시 단어 단위로 매핑하여 상호참조해결을 수행하는 워드 레벨 상호참조해결 모델을 한국어에 적용하며, 한국어 상호참조해결의 특징을 반영하기 위해 워드 레벨 상호참조해결 모델의 토큰 표현에 개체명 자질과 의존 구문 분석 자질을 추가하였다. 실험 결과, ETRI 질의응답 도메인 평가 셋에서 F1 69.55%로, 기존 End-to-End 방식의 상호참조해결 모델 대비 0.54% 성능 향상을 보이면서 메모리 사용량은 2.4배 좋아졌고, 속도는 1.82배 빨라졌다.

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