• Safety and Health at Work
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• 제12권1호
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• pp.1-9
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• 2021

This review article addresses the role of safety professionals in the diffusion strategies for predictive analytics for safety performance. The article explores the models, definitions, roles, and relationships of safety professionals in knowledge application, access, management, and leadership in safety analytics. The article addresses challenges safety professionals face when integrating safety analytics in organizational settings in four operations areas: application, technology, management, and strategy. A review of existing conventional safety data sources (safety data, internal data, external data, and context data) is briefly summarized as a baseline. For each of these data sources, the article points out how emerging analytic data sources (such as Industry 4.0 and the Internet of Things) broaden and challenge the scope of work and operational roles throughout an organization. In doing so, the article defines four perspectives on the integration of predictive analytics into organizational safety practice: the programmatic perspective, the technological perspective, the sociocultural perspective, and knowledge-organization perspective. The article posits a four-level, organizational knowledge-skills-abilities matrix for analytics integration, indicating key organizational capacities needed for each area. The work shows the benefits of organizational alignment, clear stakeholder categorization, and the ability to predict future safety performance.

• 한국항행학회논문지
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• 제18권5호
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• pp.524-531
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• 2014

본 논문에서는 클라우드 컴퓨팅 자원을 이용하여 빅데이터의 일종인 LOD (linked open data)를 가공 및 분석하는 방법을 제안한다. LOD는 공공 데이터를 공유 및 재활용하기 위한 웹기반의 오픈 데이터이다. 특히 BA(business analytics)와 Info-graphic을 위한 시각화 (visualization) 기술을 제공하는 새로운 SaaS (software as a service) 비즈니스 영역을 InforgraaS (Info-graphic as a service)라고 정의한다. 본 연구의 목표는 시각화 및 비즈니스 전문가 없이 비전문가 또는 초보자가 사용할 수 있도록 하는 것이다. 데이터 시각화 (data visualization)는 데이터 분석 결과를 쉽게 이해할 수 있도록 시각적으로 표현하고 전달되는 과정을 말한다. 데이터 시각화의 목적은 챠트와 그래프를 통해 정보를 명확하고 효과적으로 전달하는 것이다. 공공기관의 빅데이터를 클라우드 컴퓨팅 자원과 오픈 소스인 하둡, R, 기계학습, 데이터 마이닝 등을 이용하여 다양한 처리 결과를 이해하기 쉬운 그래픽 또는 챠트로 표현하고 공유한다.

• 한국조리학회지
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• 제24권2호
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• pp.34-43
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• 2018

The objective of this study was to acquire a general and text-based awareness and recognition of cruise food hygiene through big data analytics. For the purpose, this study collected data with conducting the keyword "food hygiene, cruise" on the web pages and news on Google, during October 1st, 2015 to October 1st, 2017 (two years). The data collection was processed by SCTM which is a data collecting and processing program and eventually, 899 kb, approximately 20,000 words were collected. For the data analysis, UCINET 6.0 packaged with visualization tool-Netdraw was utilized. As a result of the data analysis, the words such as jobs, news, showed the high frequency while the results of centrality (Freeman's degree centrality and Eigenvector centrality) and proximity indicated the distinct rank with the frequency. Meanwhile, as for the result of CONCOR analysis, 4 segmentations were created as "food hygiene group", "person group", "location related group" and "brand group". The diagnosis of this study for the food hygiene in cruise industry through big data is expected to provide instrumental implications both for academia research and empirical application.

• Journal of Multimedia Information System
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• 제5권3호
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• pp.171-178
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• 2018

According to the National Health Insurance Corporation in 2008, there were 17,764,428 physical therapy patients, exceeding 31 percent for the population covered by health insurance. This means that three out of 10 Koreans received physical therapy. And now, 10 years later, due to the aging population and the increase in the sports population, the number of patients with physical therapy is expected to be much more than a decade ago. Among them, many physical therapy patients were orthopedic and neurologic disorder. However, in the medical field applied to physical therapy, it is widely applied across all medical fields, including orthopedics, neurosurgery, pediatrics, gynecology, thoracic surgery and dentistry. It is believed that various cases of patients receiving physical therapy will be secured. as mentioned earlier, there will be a large number of patients with physical therapy treatments, making big data analytics easier. based on this, physical therapy applications are thought to be helpful in the analogy of disease and the development of effective physical therapy and will ultimately promote the development of physical therapy.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.513-516
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• 2022

본 논문에서는 텍스트 마이닝 기법을 이용하여 MZ 세대를 이해하는 키워드를 도출하고자 한다. MZ 세대의 비중이 높아지면서, MZ 세대를 분석하려고 하는 많은 연구들이 수행되고 있다. 이에 본 연구에서는 MZ 세대를 이해하기 위하여 네이트 판의 연령별 게시판 크롤링을 통해 빅데이터를 수집하였다. 그리고 텍스트 마이닝 기법을 활용하여 10대, 20대, 30대의 각각의 키워드를 도출할 수 있었다. 본 논문에서 도출된 키워드는 이는 MZ 세대를 이해하는데 중요한 키워드로 볼 수 있을 것이다. 향후 연구로는 MZ 세대와 기성 세대를 비교하기 위하여 추가 크롤링을 통해 세대 간 비교 연구를 수행하고자 한다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• 정보과학회지
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• 제30권6호
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• pp.33-39
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• 2012

• 디지털융복합연구
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• 제15권9호
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• pp.167-178
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• 2017

빅데이터는 기업에게 있어 미래의 핵심자산이며 물류부문에도 새로운 경쟁력을 높일 수 있는 핵심적인 요소이다. 그러나 지금까지 물류에서 빅데이터를 어떻게 수집하고 분석하며 활용해야 할지에 대한 연구는 아직 부족하다. 이러한 상황에서 본 연구는 기존 선행연구와 DHL의 연구에서 나타난 물류에서의 빅데이터 분석 및 활용에 대한 결과를 바탕으로 물류기업에게 적용 가능한 하나의 가치모델을 개발하였다. 본 연구의 목적은 물류에서 빅데이터 분석의 활용을 통하여 물류기업의 운영효율성 및 고객경험의 극대화 수준을 향상키시고 빅데이터 활용에 따른 경쟁적 지위와 경쟁력을 향상시키고 새로운 사업기회를 개발하는 데에 있다. 이러한 연구는 물류부문에서 빅데이터 분석의 활용을 위한 가치모델을 새롭게 창출하는 의의가 있으며 향후 물류부문 뿐만 아니라 타 업종에도 적용가능한 시사점을 제공할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1146-1165
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• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• Educational Technology International
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• 제18권1호
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• pp.1-25
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• 2017

Educational applications of big data analysis have been of interest in order to improve learning effectiveness and efficiency. As a basic challenge for educational applications, the purpose of this study is to develop a comprehensive data set scheme for learning analytics in the context of digital textbook usage within the K-12 school environments of Korea. On the basis of the literature review, the Start-up Mega Planning model of needs assessment methodology was used as this study sought to come up with negotiated solutions for different stakeholders for a national level of learning metrics framework. The Ministry of Education (MOE), Seoul Metropolitan Office of Education (SMOE), and Korean Education and Research Information Service (KERIS) were involved in the discussion of the learning metrics framework scope. Finally, we suggest a proposal for the national learning metrics framework to reflect such considerations as dynamic education context and feasibility of the metrics into the K-12 Korean schools. The possibilities and limitations of the suggested framework for learning metrics are discussed and future areas of study are suggested.