• Title/Summary/Keyword: BigKinds database

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A Study on deduction of important factors for new infectious diseases through big data analysis (빅데이터 분석을 통한 신종감염병 중요 요인 도출)

  • Suh, Kyung-Do
    • Journal of Industrial Convergence
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    • v.19 no.3
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    • pp.35-40
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    • 2021
  • This study attempted to derive important factors of emerging infectious diseases by collecting and analyzing text data onto emerging infectious diseases. For this purpose, articles in the Naver News database were directly crawled, pre-processed, and used for data analysis. In addition, additional analysis was performed using Big Kinds. As a result of the priority analysis, the importance was shown in the order of corona, infectious disease, quarantine, vaccine, outbreak, virus, infection, and development. As a result of the proximity centrality analysis, the importance was shown in the order of government, death, and plan, and the analysis result of Big Kinds showed that Covid-19 and the Korea Centers for Disease Control and Prevention were important. Based on the results of this study, it can be said that the government's policy support is needed to raise public awareness of new infectious diseases, prevent disease, and develop vaccines and treatments.

Process and Quality Data Integrated Analysis Platform for Manufacturing SMEs (중소중견 제조기업을 위한 공정 및 품질데이터 통합형 분석 플랫폼)

  • Choe, Hye-Min;Ahn, Se-Hwan;Lee, Dong-Hyung;Cho, Yong-Ju
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.3
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    • pp.176-185
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    • 2018
  • With the recent development of manufacturing technology and the diversification of consumer needs, not only the process and quality control of production have become more complicated but also the kinds of information that manufacturing facilities provide the user about process have been diversified. Therefore the importance of big data analysis also has been raised. However, most small and medium enterprises (SMEs) lack the systematic infrastructure of big data management and analysis. In particular, due to the nature of domestic manufacturing companies that rely on foreign manufacturers for most of their manufacturing facilities, the need for their own data analysis and manufacturing support applications is increasing and research has been conducted in Korea. This study proposes integrated analysis platform for process and quality analysis, considering manufacturing big data database (DB) and data characteristics. The platform is implemented in two versions, Web and C/S, to enhance accessibility which perform template based quality analysis and real-time monitoring. The user can upload data from their local PC or DB and run analysis by combining single analysis module in template in a way they want since the platform is not optimized for a particular manufacturing process. Also Java and R are used as the development language for ease of system supplementation. It is expected that the platform will be available at a low price and evolve the ability of quality analysis in SMEs.

An Optimization Technique for Smart-Walk Systems Using Big Stream Log Data (Smart-Walk 시스템에서 스트림 빅데이터 분석을 통한 최적화 기법)

  • Cho, Wan-Sup;Yang, Kyung-Eun;Lee, Joong-Yeub
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.3
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    • pp.105-114
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    • 2012
  • Various RFID-based smart-walk systems have been developed for guiding disabled people. The system sends appropriate message whenever the disabled people arrived at a specific point. We propose universal design concept and optimization techniques for the smart-walk systems. Universal design concept can be adopted for supporting various kinds of disabled such as a blind person, a hearing-impaired person, or a foreigner in a system. It can be supported by storing appropriate messages set in the message database table depending on the kinds of the disabled. System optimization can be done by analyzing operational log(stream) data accumulated in the system. Useful information can be extracted by analyzing or mining the accumulated operational log data. We show various analysis results from the operational log data.

Secondary Analysis on Pressure Injury in Intensive Care Units

  • Hyun, Sookyung
    • International journal of advanced smart convergence
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    • v.10 no.2
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    • pp.145-150
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    • 2021
  • Patients with Pressure injuries (PIs) may have pain and discomfort, which results in poorer patient outcomes and additional cost for treatment. This study was a part of larger research project that aimed at prediction modeling using a big data. The purpose of this study were to describe the characteristics of patients with PI in critical care; and to explore comorbidity and diagnostic and interventive procedures that have been done for patients in critical care. This is a secondary data analysis. Data were retrieved from a large clinical database, MIMIC-III Clinical database. The number of unique patients with PI was 2,286 in total. Approximately 60% were male and 68.4% were White. Among the patients, 9.9% were dead. In term of discharge disposition, 56.2% (33.9% Home, 22.3% Home Health Care) where as 32.3% were transferred to another institutions. The rest of them were hospice (0.8%), left against medical advice (0.7%), and others (0.2%). The top three most frequently co-existing kinds of diseases were Hypertension, not otherwise specified (NOS), congestive heart failure NOS, and Acute kidney failure NOS. The number of patients with PI who have one or more procedures was 2,169 (94.9%). The number of unique procedures was 981. The top three most frequent procedures were 'Venous catheterization, not elsewhere classified,' and 'Enteral infusion of concentrated nutritional substances.' Patient with a greater number of comorbid conditions were likely to have longer length of ICU stay (r=.452, p<.001). In addition, patient with a greater number of procedures that were performed during the admission were strongly tend to stay longer in hospital (r=.729, p<.001). Therefore, prospective studies focusing on comorbidity; and diagnostic and preventive procedures are needed in the prediction modeling of pressure injury development in ICU patients.

Effective Utilization of Data based on Analysis of Spatial Data Mining (공간 데이터마이닝 분석을 통한 데이터의 효과적인 활용)

  • Kim, Kibum;An, Beongku
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.3
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    • pp.157-163
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    • 2013
  • Data mining is a useful technology that can support new discoveries based on the pattern analysis and a variety of linkages between data, and currently is utilized in various fields such as finance, marketing, medical. In this paper, we propose an effective utilization method of data based on analysis of spatial data mining. We make use of basic data of foreigners living in Seoul. However, the data has some features distinguished from other areas of data, classification as sensitive information and legal problem such as personal information protection. So, we use the basic statistical data that does not contain personal information. The main features and contributions of the proposed method are as follows. First, we can use Big Data as information through a variety of ways and can classify and cluster Big Data through refinement. Second. we can use these kinds of information for decision-making of future and new patterns. In the performance evaluation, we will use visual approach through graph of themes. The results of performance evaluation show that the analysis using data mining technology can support new discoveries of patterns and results.

Study of major issues and trends facing ports, using big data news: From 1991 to 2020 (뉴스 빅데이터를 활용한 항만이슈 변화연구 : 1991~2020)

  • Yoon, Hee-Young
    • Journal of Korea Port Economic Association
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    • v.37 no.1
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    • pp.159-178
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    • 2021
  • This study analyzed issues and trends related to ports with 86,611 news articles for the 30 years from 1991 to 2020, using BIGKinds, a big data news analysis service. The analysis was based on keyword analysis, word cloud, relationship diagram analysis offered by BIG Kinds. Analysis results of issues and trends on ports for the last 30 years are summarized as follows. First, during Phase 1 (1991-2000), individual ports such as Busan, Incheon, and Gwangyang ports tried to strengthen their own competitiveness. During Phase 2 (2001-2010), efforts were made on gaining more professional and specialized port management abilities by establishing the Busan Port Authority in 2004, the Incheon Port Authority in 2005, and the Ulsan Port Authority in 2007. During Phase 3 (2011-2020), the promotion of future-oriented, eco-friendly, and smart ports was major issues. Efforts to reduce particulate matters and pollutants produced from ports were accelerated, and an attempt to build a smart port driven by port automation and digitalization was also intensified. Lastly, in 2020, when the maritime sector was severely hit by the unexpected shock of the COVID-19 pandemic, a microscopic analysis of trends and issues in 2019 and 2020 was made to look into the impact the pandemic on the maritime industry. It was found that shipping and port industries experienced more drastic changes than ever while trying to prepare for a post-pandemic era as well as promoting future-oriented ports. This study made policy suggestions by analyzing port-related news articles and trends, and it is expected that based on the findings of this research, further studies on enhancing the competitiveness of ports and devising a sustainable development strategy will follow through a comparative analysis of port issues of different countries, thereby making further progress toward academic research on ports.

Images of Nurses Appeared in Media Reports Before and After Outbreak of COVID-19: Text Network Analysis and Topic Modeling (COVID-19 발생 전·후 언론보도에 나타난 간호사 이미지에 대한 텍스트 네트워크 분석 및 토픽 모델링)

  • Park, Min Young;Jeong, Seok Hee;Kim, Hee Sun;Lee, Eun Jee
    • Journal of Korean Academy of Nursing
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    • v.52 no.3
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    • pp.291-307
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    • 2022
  • Purpose: The aims of study were to identify the main keywords, the network structure, and the main topics of press articles related to nurses that have appeared in media reports. Methods: Data were media articles related to the topic "nurse" reported in 16 central media within a one-year period spanning July 1, 2019 to June 30, 2020. Data were collected from the Big Kinds database. A total of 7,800 articles were searched, and 1,038 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. Results: The number of media reports related to nurses increased by 3.86 times after the novel coronavirus (COVID-19) outbreak compared to prior. Pre- and post-COVID-19 network characteristics were density 0.002, 0.001; average degree 4.63, 4.92; and average distance 4.25, 4.01, respectively. Four topics were derived before and after the COVID-19 outbreak, respectively. Pre-COVID-19 example topics are "a nurse who committed suicide because she could not withstand the Taewoom at work" and "a nurse as a perpetrator of a newborn abuse case," while post-COVID-19 examples are "a nurse as a victim of COVID-19," "a nurse working with the support of the people," and "a nurse as a top contributor and a warrior to protect from COVID-19." Conclusion: Topic modeling shows that topics become more positive after the COVID-19 outbreak. Individual nurses and nursing organizations should continuously monitor and conduct further research on nurses' image.

SPDX Document Generation Visual Studio Plug-in development for Invigorating Blockchain based Software Distribution Platform (블록체인 기반의 소프트웨어 유통 플랫폼의 활성화를 위한 SPDX 문서 생성 Visual Studio용 플러그인 개발)

  • Yun, Ho-Yeong;Joe, Yong-Joon;Shin, Dong-Myung
    • Journal of Software Assessment and Valuation
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    • v.13 no.2
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    • pp.9-17
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    • 2017
  • Software compliance is an essential process when Open Source Software is included in software development to avoid such as license violation issue. However, analyzing quite big software which involves many developers requires enormous time and hard difficulty. To resolve these kinds of problem, SPDX formalizes and standardize the metadata about the software package. When the use of SPDX is activated, software package analysis would be simple and could contribute fair Open Source Software distribution. In this paper, we develop blockchain based SPDX distribution platform which fulfills the requirement of SPDX lifecycle to provide SPDX database which does not depend on particular centralized service but serve as distributed ledger and control by user's certification and their purpose. Moreover, to contribute invigoration of blockchain based SPDX distribution platform, we develop SPDX document generation plug-in for integrated development environment such as Visual Studio.

Analysis of Regional Smart Tourism Status Using Topic Modeling and Network Analysis: Focused on News Articles (토픽 모델링과 네트워크 분석을 활용한 지역별 스마트관광 현황 분석: 뉴스 기사를 중심으로)

  • MuMoungCho Han
    • Smart Media Journal
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    • v.13 no.9
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    • pp.9-17
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    • 2024
  • This study aims to analyze the current status of smart tourism in various regions. To achieve this, 599 news articles containing the keyword 'smart tourism' were collected from national daily newspapers in the BigKinds database, covering the period from January 2014 to June 2024. The collected data was subject to topic modeling based on location, and network analysis was performed using the keyword frequencies in each topic. The topic modeling results identified six major topics: 'Jeju,' 'Incheon,' 'Daegu_Busan_Ulsan,' 'Gyeongju,' 'Suwon,' and 'Yangyang.' It was found that the development of smart tourism in all these regions is centered around tourism projects led by government and local authorities. The network analysis results revealed that 'platform' and 'content' are key keywords related to smart tourism technology across all topics, indicating that these concepts are interconnected to provide services to individual tourists. The findings of this study are expected to provide valuable information for formulating policies and strategies to promote smart tourism in various regions and contribute to the realization of sustainable smart tourism.

A Study on the Effective VTS Communications Analysis by the Method of VCDF in Busan Port (VCDF 방식을 통한 효율적인 VTS 통신 데이터 분석에 관한 연구 - 부산항을 대상으로 -)

  • Kim, Bong-Hyun;Park, Young-Soo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.22 no.4
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    • pp.311-318
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    • 2016
  • The VTS concept was located as a principal methods of maritime safety administration in world's major harbors and expected to become the pivotal role for the future of the maritime and harbor society with e-Navigation epoch. If recent limelight concept of big-data has been included in aspect of information gathering and analysis with various studies, it's required advanced studies to improve the information analysis capability and application range of the data that can be mining by the VTS. In this study, contrast to other studies that aimed quantitative analysis as communication number, it can be mining the time information and each of the communication VTS for the target vessel, including qualitative analysis, such as the purpose or the type of communication. This comparison across multiple items of the collected information, and presenting the VTS data mining model (VCDF) that can be analyzed for the purpose of analyzing way, type and number of communication by ship's type, also number of violations through VTS communication. First, In Busan port case, it shows frequently information service and shows frequently communicating with particular types of vessels. Second, Passive VTS carried out notwithstanding many kinds of traffic violations due to communication congestion. This arranged information can be used as data for the analysis, as possible the level of traffic for VTSO situational awareness, which pointed to the 'workloads' in 'IALA Guideline' and could be used as a database for future research of e-Navigation.