• 제목/요약/키워드: Mining Industry

검색결과 637건 처리시간 0.027초

국내 제조업 화재사고 데이터 분석을 통한 복합 유해·위험요인 확인 (Identifying Hazard of Fire Accidents in Domestic Manufacturing Industry Using Data Analytics)

  • 김경민;서용윤;이종빈;장성록
    • 한국안전학회지
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    • 제38권4호
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    • pp.23-31
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    • 2023
  • Revising the Occupational Safety and Health Act led to enacting and revising related laws and systems, such as placing fire observers in hot workplaces. However, the operating standards in such cases are still ambiguous. Although fire accidents occur through multiple and multi-step factors, the hazards of fire accidents have been identified in this study as individual rather than interrelated factors. The aim has been to identify multiple factors of accidents, outlining fire and explosion accidents that recently occurred in the domestic manufacturing industry. First, major keywords were extracted through text mining. Then representative accident types were derived by combining the main keywords through the co-word network analysis to identify the hazards and their relationships. The representative fire accidents were identified as six types, and their major hazards were then addressed for improving safety measures using the identification of hazards in the "Risk Assessment" tool. It is found that various safety measures, such as professional fire observers' training and clear placement standards, are needed. This study will provide useful basic data for revising practical laws and guidelines for fire accident prevention, system supplementation, safety policy establishment, and future related research.

데이터마이닝을 이용한 대학생들의 취업 로드맵에 관한 기초 연구 (A Basic Study on the Career Roadmap of University Students Using Data Mining)

  • 김효정;오새내
    • 디지털산업정보학회논문지
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    • 제19권1호
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    • pp.129-138
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    • 2023
  • The purpose of this study is to explore factors that directly affect the employment of college graduates. To this end, employment data of graduates of private four-year university in Daegu metropolitan area and Gyeongsangbuk-do province were collected from 2019 to 2021, filtered data using a RapidMiner, and analyzed by applying a decision tree model. As a result of the study, long-term internship for more than 12 weeks, TOEIC score of 787.5 or higher was advantageous for employment, and if there was no TOEIC score, the graduation average score was 3.67 or higher, so the possibility of employment was high. Even if the TOEIC score was low, it was advantageous for employment if participating in the contest and continuous professor counseling, and even if the average graduation score was low, the possibility of employment was high if actively participating in the comparison program. This study can present a job education guide based on actual data to university management and use it to establish policies to support employment of college students.

홍콩 영화에 관한 고객 리뷰의 텍스트 마이닝 기반 분석: 관객 선호도의 진화 발견 (Text Mining-Based Analysis of Customer Reviews in Hong Kong Cinema: Uncovering the Evolution of Audience Preferences )

  • 손화양;이정승
    • Journal of Information Technology Applications and Management
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    • 제30권4호
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    • pp.77-86
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    • 2023
  • This study conducted sentiment analysis on Hong Kong cinema from two distinct eras, pre-2000 and post-2000, examining audience preferences by comparing keywords from movie reviews. Before 2000, positive keywords like 'actors,' 'performance,' and 'atmosphere' revealed the importance of actors' popularity and their performances, while negative keywords such as 'forced' and 'violence' pointed out narrative issues. In contrast, post-2000 cinema emphasized keywords like 'scale,' 'drama,' and 'Yang Yang,' highlighting production scale and engaging narratives as key factors. Negative keywords included 'story,' 'cheesy,' 'acting,' and 'budget,' indicating challenges in storytelling and content quality. Word2Vec analysis further highlighted differences in acting quality and emotional engagement. Pre-2000 cinema focused on 'elegance' and 'excellence' in acting, while post-2000 cinema leaned towards 'tediousness' and 'awkwardness.' In summary, this research underscores the importance of actors, storytelling, and audience empathy in Hong Kong cinema's success. The industry has evolved, with a shift from actors to production quality. These findings have implications for the broader Chinese film industry, emphasizing the need for engaging narratives and quality acting to thrive in evolving cinematic landscapes.

변이할당분석을 이용한 충청남도 금강권 산업구조 특성 분석 (A Study on Characteristics of Industrial Structure by Shift-Share Analysis : The Case of Chungnam Geumgang Area)

  • 김성록;이종상
    • 농촌계획
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    • 제20권1호
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    • pp.127-134
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    • 2014
  • This study, in order to complement instability of analysis result stemming from the choice between reference point and comparison point which is pointed out as the defect of shift-share analysis, conducted shift-share analysis using Gross Regional Domestic Product (GRDP) trend of Geumgang area, Chungcheongnam-do for the period from 2000 to 2011. As a result of the analysis, (1) industries that had both the positive Regional Share Effect (RSE) and Industrial Mixed Effect (IME) were service industries such as manufacturing industry, electricity gas, transportation industry, art, etc., which are positively influencing the regional industry. (2) industries that had both the negative RSE and IME were other service industries such as wholesale and retail businesses, lodging industry, food industry, real estate business and leasing service, business service industry, public administration, etc., which provide basic livelihood services for the residents. (3) industries that had the positive RSE and negative IME were agriculture, forestry and fishery industry, mining industry, construction industry, and educational service industry. (4) industries that had the negative RSE and positive IME were info-communications industry, financial and insurance businesses, health industry, etc.

스마트팩토리를 위한 운영빅데이터 분석 플랫폼 (Operational Big Data Analytics platform for Smart Factory)

  • 배혜림;박상혁;최유림;주병준;리스카;풀샤시;푸트라;타오픽;이상화;원석래
    • 한국빅데이터학회지
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    • 제1권2호
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    • pp.9-19
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    • 2016
  • ICT 융합에 대한 관심이 높아진 가운데 독일의 Industry 4.0을 시작으로 제조업과 ICT 융합에 대한 연구가 활발하게 진행되고 있다. 이를 통해 전통적인 제조업의 제조단가를 낮추고 극적인 품질향상을 기대할 수 있게 되었다. 최근 정부의 제조업 3.0 전략 등에 힘입어 국내에서도 제조업에 대한 고도화가 진행되고 있으며, 이러한 추세에 발맞추어 제조업 운영에서 발생하는 빅데이터에 대한 주문맞춤형 분석 플랫폼을 개발하고 이를 통해 제조 현장의 경쟁력을 높이고자 한다. 주문맞춤형 분석 플랫폼은 확장성을 고려하여 스프링 프레임워크를 기반으로 웹에서 실행되도록 설계되었으며, 제조업 현장에서 발생하는 다량의 데이터를 빠르게 처리하기 위하여 스파크와 하둡 파일 시스템을 이용한다. 실시간으로 스트리밍 된 데이터를 프로세스 마이닝 기반 알고리즘을 통해 처리하고 공장의 현황을 분석하여 제조업 현장의 문제를 파악하고 신속한 의사결정을 지원할 수 있다.

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Effect of Occupational Health and Safety Management System on Work-Related Accident Rate and Differences of Occupational Health and Safety Management System Awareness between Managers in South Korea's Construction Industry

  • Yoon, Seok J.;Lin, Hsing K.;Chen, Gang;Yi, Shinjea;Choi, Jeawook;Rui, Zhenhua
    • Safety and Health at Work
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    • 제4권4호
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    • pp.201-209
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    • 2013
  • Background: The study was conducted to investigate the current status of the occupational health and safety management system (OHSMS) in the construction industry and the effect of OHSMS on accident rates. Differences of awareness levels on safety issues among site general managers and occupational health and safety (OHS) managers are identified through surveys. Methods: The accident rates for the OHSMS-certified construction companies from 2006 to 2011, when the construction OHSMS became widely available, were analyzed to understand the effect of OHSMS on the work-related injury rates in the construction industry. The Korea Occupational Safety and Health Agency 18001 is the certification to these companies performing OHSMS in South Korea. The questionnaire was created to analyze the differences of OHSMS awareness between site general managers and OHS managers of construction companies. Results: The implementation of OHSMS among the top 100 construction companies in South Korea shows that the accident rate decreased by 67% and the fatal accident rate decreased by 10.3% during the period from 2006 to 2011. The survey in this study shows different OHSMS awareness levels between site general managers and OHS managers. The differences were motivation for developing OHSMS, external support needed for implementing OHSMS, problems and effectiveness of implementing OHSMS. Conclusion: Both work-related accident and fatal accident rates were found to be significantly reduced by implementing OHSMS in this study. The differences of OHSMS awareness between site general managers and OHS managers were identified through a survey. The effect of these differences on safety and other benefits warrants further research with proper data collection.

범죄발생 위험요소와 연관된 SNS 데이터의 효율적 추출 방법에 관한 연구 (A study on the efficient extraction method of SNS data related to crime risk factor)

  • 이종훈;송기성;강진아;황정래
    • 한국컴퓨터정보학회논문지
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    • 제20권1호
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    • pp.255-263
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    • 2015
  • 본 연구에서는 매년 증가하는 범죄에 대한 예방 측면에서 범죄발생 위험요소에 관한 정보를 사전에 파악하고 범죄발생을 예방하기 위해 SNS 데이터를 활용하는 방안을 제시한다. 최근에 SNS(Social Network Service) 데이터는 다양한 분야에서 선제적 예방 대응체계를 구축하는데 활용됨에 따라 그 중요성 또한 점점 증가하고 있다. 하지만 SNS 데이터를 단순 키워드로 수집하는 경우 관련되지 않은 데이터가 다수 포함되어 정확도 저하와 데이터 분석에 혼란을 초래할 우려가 있다. 이에, SNS 데이터의 텍스트 마이닝 분석을 통해 범죄발생 위험요소의 검색 정확도를 향상시켜 효율적으로 추출할 수 있는 방안을 제시한다.

데이터 분석 기반 미래 신기술의 사회적 위험 예측과 위험성 평가 (Data Analytics for Social Risk Forecasting and Assessment of New Technology)

  • 서용윤
    • 한국안전학회지
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    • 제32권3호
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    • pp.83-89
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    • 2017
  • A new technology has provided the nation, industry, society, and people with innovative and useful functions. National economy and society has been improved through this technology innovation. Despite the benefit of technology innovation, however, since technology society was sufficiently mature, the unintended side effect and negative impact of new technology on society and human beings has been highlighted. Thus, it is important to investigate a risk of new technology for the future society. Recently, the risks of the new technology are being suggested through a large amount of social data such as news articles and report contents. These data can be used as effective sources for quantitatively and systematically forecasting social risks of new technology. In this respect, this paper aims to propose a data-driven process for forecasting and assessing social risks of future new technology using the text mining, 4M(Man, Machine, Media, and Management) framework, and analytic hierarchy process (AHP). First, social risk factors are forecasted based on social risk keywords extracted by the text mining of documents containing social risk information of new technology. Second, the social risk keywords are classified into the 4M causes to identify the degree of risk causes. Finally, the AHP is applied to assess impact of social risk factors and 4M causes based on social risk keywords. The proposed approach is helpful for technology engineers, safety managers, and policy makers to consider social risks of new technology and their impact.

데이터 마이닝을 이용한 제주 양식 넙치(Paralichthys olivaceus)의 스쿠티카증 발생 패턴 분석 (Data Mining for Scuticociliatosis Outbreak Patterns in Cultured Olive Flounder Paralichthys olivaceus in Jeju, Korea)

  • 김해란;정성주;김성현;박정선;정희택;한순희
    • 한국수산과학회지
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    • 제53권5호
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    • pp.740-751
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    • 2020
  • In the aquaculture industry, few studies are analyzing big data for intrinsic meaning. Fishcare Laboratory (www.fishcare.kr) diagnostic data from 2016-2018 was analyzed for scuticociliatosis (caused by Miamiensis avidus) outbreak patterns in cultured olive flounder Paralichthys olivaceus in Jeju, Korea. The scuticociliatosis monthly occurrence ratio is reported in the summary table after preparing and filtering the basic dataset model. Nonparametric test results suggest differences in the water temperature, body length, and weight between groups with and without scuticociliatosis. Data distribution visualization revealed that shorter body length and lighter weight increased the occurrence of scuticociliatosis. The association rule mining technique was applied to determine the primary clinical signs of mixed scuticociliatosis and bacterial infections. Venn diagrams were used to report clinical signs and suggest commonalities. These results may help diagnose and treat fish and provide a decision-making reference.

자동차 재구매 증진을 위한 데이터 마이닝 기반의 맞춤형 전략 개발 (Development of Customized Strategy for Enhancing Automobile Repurchase Using Data Mining Techniques)

  • 이동욱;최근호;유동희
    • 한국정보시스템학회지:정보시스템연구
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    • 제26권3호
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    • pp.47-61
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    • 2017
  • Purpose Although automobile production has increased since the development of the Korean automobile industry, the number of customers who can purchase automobiles decreases relatively. Therefore, automobile companies need to develop strategies to attract customers and promote their repurchase behaviors. To this end, this paper analyzed customer data from a Korean automobile company using data mining techniques to derive repurchase strategies. Design/methodology/approach We conducted under-sampling to balance the collected data and generated 10 datasets. We then implemented prediction models by applying a decision tree, naive Bayesian, and artificial neural network algorithms to each of the datasets. As a result, we derived 10 patterns consisting of 11 variables affecting customers' decisions about repurchases from the decision tree algorithm, which yielded the best accuracy. Using the derived patterns, we proposed helpful strategies for improving repurchase rates. Findings From the top 10 repurchase patterns, we found that 1) repurchases in January are associated with a specific residential region, 2) repurchases in spring or autumn are associated with whether it is a weekend or not, 3) repurchases in summer are associated with whether the automobile is equipped with a sunroof or not, and 4) a customized promotion for a specific occupation increases the number of repurchases.