• 창의정보문화연구
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• 제7권4호
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• pp.265-277
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• 2021

인공지능 기술의 핵심은 데이터다. 기술의 발달로 데이터의 양이 이전보다 폭발적으로 증가하면서 인공지능 기술 또한 빠르게 발전하고 있다. 하지만 인공지능 교육에 대한 높은 관심에 비해 인공지능과 연계된 데이터 교육 연구는 아직 부족하다. 기존의 인공지능 데이터 교육의 사례 분석 결과, 데이터 과학의 과정 및 일부를 교육하는 사례를 확인할 수 있었으나, 데이터 수집과 관련된 연구는 많지 않았다. 피지컬 컴퓨팅 교구의 활용이 초등학생의 인공지능 교육에 긍정적인 영향을 줄 것이라는 연구와 함께 피지컬 도구를 활용한 데이터 수집 사례를 연구하였으나, 데이터 수집과 관련한 연구 사례 또한 드물었다. 따라서 본 연구에서는 피지컬 도구를 활용한 효율적인 데이터 수집 방법을 설계하였다. 모듈형 피지컬 컴퓨팅 교구인 코블S를 활용하여 데이터 수집 프로그램의 구조도를 만들고 서비스 측면과 사용자 측면의 프로그램 화면의 예시를 구성하였다. 본 연구는 설계 측면의 제안으로 향후 프로그램 제작 및 프로그램과 연동하여 사용할 수 있는 인공지능 교육 플랫폼 구축이 되어야 한다는 점에서 제한점이 있다.

• 한국학교수학회논문집
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• 제8권2호
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• pp.167-181
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• 2005

통계학을 좀 더 쉽게 이해하며 흥미를 가지고 접근할 수 있도록 하기 위해 다양한 통계교육 방법의 연구가 계속되어지고 있다. 그러나 동계교육에 있어서 항상 겪는 어려운 점 중의 하나는 학생들이 쉽게 받아들일 수 있는 실제 자료가 많지 않다는 것이다. 이는 학생들에게 통계학을 현실과 전혀 관계없는 학문으로 인식시키며 학습 의욕을 저하시키고 통계학을 재미없는 학문으로 인식하게 되는 부정적 결과를 낳게 하였다. 본 연구에서는 웹과 데이터베이스를 활용한 자료 수집 및 공유 프로그램을 활용하여 수업에서 현실감 있고 학생들과 관련이 높은 자료를 활용할 수 있도록 하고 엑셀을 활용하여 학생들이 통계학의 개념과 응용에 더 집중할 수 있는 통계교육 수업방안을 제안한다.

• ETRI Journal
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• 제43권5호
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• pp.835-855
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• 2021

With the recent increase in data disclosure, the Comprehensive Knowledge Archive Network (CKAN), which is an open-source data distribution platform, is drawing much attention. CKAN is used together with additional extensions, such as Datastore and Datapusher for data management and Harvest and DCAT for data collection. This study derives the problems of CKAN itself and Harvest Extension. First, CKAN causes two problems of data inconsistency and storage space waste for data deletion. Second, Harvest Extension causes three additional problems, namely source deletion that deletes only sources without deleting data themselves, job stop that cannot delete job during data collection, and service interruption that cannot provide service, even if data exist. Based on these observations, we propose herein an improved CKAN that provides a new deletion function solving data inconsistency and storage space waste problems. In addition, we present an improved Harvest Extension solving three problems of the legacy Harvest Extension. We verify the correctness and the usefulness of the improved CKAN and Harvest Extension functions through actual implementation and extensive experiments.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.956-961
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• 2009

When construction engineers perform their work in the jobsite, they have to record as-built conditions in the project log (Data Collection). On the other hand, the engineers often have to refer to the construction documents when necessary at the job faces (Data Access). The practice of Data Collection and Data Access in the jobsite can be greatly enhanced by utilizing mobile computing with wireless communications. In this paper, two cases of mobile computing applications for construction field management are presented; Mobile Specifications System and Mobile Data Collection System. The demonstration of the process for developing two mobile applications is the primary purpose of the paper. The problems and issues involved with adopting mobile computing for construction field are also presented. The simple information framework for mobile computing has been also proposed as an outcome of the research. As for development tools, readily available relational database and wireless network have been used. The use of commercial mobile broadband was examined for data communication where local area network is not available.

• 한국의료질향상학회지
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• 제5권2호
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• pp.224-237
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• 1998

Background : This is an investigative study to analyse the importance of works perceived by Quality Improvement(QI) Coordinators and to evaluate their current work performances using the questionnaires developed by the investigator. Methods : The data were collected from 37 subjects over two weeks period from Oct. 1 to Oct. 17, 1998 and analysed by the descriptive statistics of SPSS program. The items of questionnaire are consisted of 13 work domains including 73 activities based on Quality Management(QM) Coordinator's job description of National Association for Healthcare Quality:data collection & analysis, communication, monitoring, evaluation, accreditation, tool development, policy development, program development, self development, education & trainning, system design, planning, and consultation & support. Results : 1) Of the performances in 13 work domains, the frequencies of the work performed were accreditation(89%), planning(88%), communication(83%), data collection & analysis(82%), monitoring(76%), policy development(72%), consultation & support (71%), education & trainning(70%), self development(68%), evaluation(63%), tool development(61%), program development(44%) and system design(43%) in order. 2) For the importances (1=not important, 5=very important), the policy development(4.46) scored highest then monitoring(4.42), planning(4.41), education & trainning(4.38), communication(4.35), evaluation(4.34) tool development (4.30), data collection & analysis(4.29), program development(4.22), consultation & support(4.22), accreditation(4.15), self development(4.05) and system design(3.98) in order. 3) There was a difference between the work performance and the perceived importance. The results showed the low performances in policy development, monitoring, education & trainning and evaluation which ranked high by the perceived importance and the high performances in accreditation, data collection & analysis, self development, communication and consultation & support which ranked middle to low by the perceived importance. 4) The reasons for low performances of QI Coordinators were the lack of clear assignment for the responsibility and allowed authority for work to QI Coordinators(30.8%), insufficient member of QI Coordinators(13.9%), lack of hospital director's interest(11.5%), low motivation of QI Coordinators (10.6%) and insufficient knowledge & experience of QI Coordinators (8.8%). Conclusion : Most works were perceived important by QI Coordinators, but there was a difference in the work performance. The works performed over 70% were related with accreditation, data collection & analysis, communication, planning and monitoring, on the other hand under 50% in performances were related with system design, program development, tool development and evaluation.

• 한국방재학회 논문집
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• 제1권1호
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• pp.91-102
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• 2001

본 연구에서는 체계화되지 못한 중소도시의 쓰레기 수집 수송의 자료를 정리, 현장 조사를 통한 쓰레기 수집 수송 관리를 위한 프로그램을 작성하였다. 대상은 C시로 하였으며, 수집구역을 주택, 아파트, 상가지역으로 한정지어 현장 조사를 실시하였고, 폐기물 관리 프로그램을 작성하였다. 연구 결과는 쓰레기 수집 수송단계의 필요한 인자와 중소도시에 적용 가능한 평균 값을 도출하였고, 중소도시의 쓰레기 수집 수송단계를 체계화하는 단계와 expert system을 구축하였다. 또한, Visual Basic을 이용한 쓰레기 수집 수송 관리 프로그램을 개발하였다. 결과적으로 본 연구로 개발되어진 도시폐기물의 수집 수송 관리 시스템은 다른 지역의 현장 Data를 추가함으로서 광범위하게 이용될 수 있을 것이다.

• 대한교통학회지
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• 제6권1호
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• pp.33-41
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• 1988

The Wisconsin Department of Transportation currently has a Datalog Information System which facilitates the collection of geometric characteristics at every 0.01 mile high way section. The objectives of this study are to develop the plan and profile drawing of a highway section utilizing the Datalog Information system and to develop a methodology of investigating the safety aspects associated with the highway section being considered. For this purpose, two of the highway design elements, the minimum stoping sight distance as well as passing sight distance based on the AASHTO requirements, were applied in this study. A computer program was also developed to facilitate the data processing activity. The results from the computer program and from a manual analysis which adopted the identical methodology used in the computer program were in a good agreement. a few discrepancies between the two results were due to the data collection error and they were believed to be negligible. Using the computerized methodology developed in this study one does not need the plan and profile drawing to investigate the safety of a highway section, which appears to be an essential progress to the Computer Aided design and Draft in highway engineering field.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1995년도 춘계학술대회논문집
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• pp.117-123
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• 1995

The anthropometric data are one of the most important factors to be considered for an aircraft systems design. Rescently, co-development program between the countries is considered frequently as a type of aircraft acquisition in aircraft industry. Consequently, the comparision of anthropometric data beteen the countries for the cockpit design is essential. In this paper, we simpoly compares anthropometric data of Korean air force pilots with those of Japan air force pilots. Although further collection of data are reauired, the result shows a few differences and it shows the possibility of future co-development program between the countries.

• 정보관리학회지
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• 제37권3호
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• pp.25-50
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• 2020

2016년 1월 1일부터 공공도서관 빅데이터 플랫폼이 서비스되기 시작하여 도서관 빅데이터가 공공도서관 업무 개선에 활용되고 있다. 본 논문은 도서관 빅데이터 플랫폼 활용사례들을 살펴보고 도서관 빅데이터 플랫폼의 활용효과를 높일 수 있는 개선방안을 도출하고자 한다. 이를 위해 먼저, 도서관 빅데이터 플랫폼을 활용한 사례들에서 활용한 빅데이터와 활용유형분석 및 도출된 서비스/시행정책을 살펴본다. 다음으로, 현재 공공도서관에서 사용하는 통합도서관리시스템(ILUS)과 도서관 빅데이터 플랫폼 각각의 자료분석 방식을 비교함으로써 도서관 빅데이터 플랫폼의 한계점과 이점을 살펴본다. 사례분석 결과, 프로그램 기획 및 수행, 장서, 수서, 기타의 유형으로 빅데이터를 활용하였고 서비스/시행정책은 이용자 맞춤형 테마서가 및 독서진흥프로그램 진행, 장서활용도 증대, 특화주제에 기반한 수서 및 대출현황 데이터 공개로 요약되었다. 비교분석결과, ILUS는 자관의 자료실현황분석에 특화되어 있으며, 빅데이터 플랫폼은 다양한 속성(연령, 성별, 지역, 대출시기 등)에 따른 선택적 분석이 가능하여 분석시간단축과 유연한 분석이 가능하다. 마지막으로 사례분석과 비교분석에서 밝혀진 특징 및 한계점을 정리하고 개선방안을 제시한다.

• 의학교육논단
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• 제22권2호
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• pp.131-142
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• 2020

A systematic educational program evaluation system for continuous quality improvement in undergraduate medical education is essential. Monitoring and evaluation (M&E) are two distinct but complementary processes referred to in an evaluation system that emphasizes formative purpose. Monitoring involves regular data collection for tracking process and results, while evaluation requires periodic judgment for improvement. We have recently completed implementing an educational evaluation using the M&E concept in a medical school. The evaluation system consists of two loops, one at the lesson/course level and the other at the phase/graduation level. We conducted evaluation activities in four stages: planning, monitoring, evaluation, and improvement. In the planning phase, we clarified the purpose of evaluation, formulated a plan to engage stakeholders, determined evaluation criteria and indicators, and developed an evaluation plan. Next, during the monitoring phase, we developed evaluation instruments and methods and then collected data. In the evaluation phase, we analyzed results and evaluated the criteria of the two loops. Finally, we reviewed the evaluation results with stakeholders to make improvements. We have recognized several problems including excessive burden, lack of expertise, insufficient consideration of stakeholders' evaluation questions, and inefficient data collection. We need to share the value of evaluation and build a system gradually.