• 한국산업정보학회논문지
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• 제2권2호
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• 한국CDE학회논문집
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• 제22권1호
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• pp.80-88
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• 2017

Product data analytics (PDA) is a data-driven analysis method that uses product data management (PDM) databases as its operational data. It aims to understand and evaluate product development processes indirectly through the analysis of product data from the PDM databases. To educate and train PDA efficiently, this study proposed an approach that employs courses for both product development and PDA in a class. The participant group for product development provides a PDM database as a result of their product development activities, and the other group for PDA analyses the PDM database and provides analysis result to the product development group who can explain causes of the result. The collaboration between the two groups can enhance the efficiency of the education and training course on PDA. This study also includes an application example of the approach to a graduate class on PDA and discussion of its result.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2005년도 추계학술대회 및 정기총회
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• pp.65-70
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• 2005

Recently, Grid is embossed as a new issue according to the need of cooperation related to distributed resources, data sharing, Interaction and so on. It focuses on sharing of large scale resources, high-performance, applications of new paradigms, which improved more than established distributed computing. Because of the environmental specificity distributed geographically and dynamic, the most important problem in grid environment is to share and to allocate distributed grid resources. This paper proposes supply-driven strategies model that is applicable for resource management in grid environment and presents a optimal resource allocation algorithm based on resource demands. Supply-driven strategies model can offer efficient resource management by transaction allocation based on user demand and provider strategy. This paper implements the supply-driven strategies model on the DEVS modeling and simulation environment and shows the efficiency and excellency of this model by comparing with established models.

• 한국통신학회논문지
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• 제35권6B호
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• pp.867-874
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• 2010

무선 센서 네트워크에서는 멀티 홉 전송동안 높은 패킷 손실률이 발생하기 때문에 신뢰성 있는 데이터 전송방안이 필요하다. 특히, 화재 경보 시스템과 같은 event-driven 데이터가 발생하는 경우, 신뢰성 있는 데이터 전송을 위해서는 손실된 패킷을 복원하기 위한 재전송 방안이 제공되어야 한다. 손실된 데이터의 재전송은 데이터를 캐쉬하고 있는 노드에 요청이 되기 때문에, 데이터를 캐쉬하고 있는 노드는 모든 데이터 패킷을 버퍼에서 유지하고 있어야 한다. 그러나 일반적으로 센서 네트워크의 노드들은 제한된 자원을 가지 있다. 따라서 신뢰성 있는 데이터 전송을 위해서는 손실 패킷의 재전송 방안과 노드의 버퍼 관리 기법이 함께 제공되어야 한다. 본 논문에서는 전송 데이터의 신뢰도에 따라 데이터의 캐쉬지점을 결정하여 손실된 데이터를 복원하는 손실 복원 기법을 사용하는 데이터 전송에서의 효율적인 버퍼 관리기법을 제안하고, 컴퓨터 시뮬레이션을 통하여 제안하는 방안의 우수성을 검증하였다.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.496-500
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• 2015

International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2001년도 International Conference CALS/EC KOREA
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• pp.277-288
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• 2001

Nowadays, for the competitive power of an enterprise, there are many attempts to implement information system that could support business innovation by business process re-engineering. However, there is no effort to standardize the core business processes of enterprise based on standards of data, documents. These facts make it difficult to introduce and implement enterprise information system designed by business processes of the higher level. Therefore, standardization of business process by analyzing the functionality and relationships among them are important and necessary. The results of our research are summarized as process-driven standardization (standardization of core business processes) and development of a repository. In process-driven standardization, we proposed the reference model by analyzing the business processes of the leading enterprises for core business processes. The reference model focuses on core business processes, such as sales management, procurement management, production management, logistics management, and customer support in manufacturing industry. We developed a knowledge-based system as a repository for a integrated management system of business process. And this repository was built up web-based system for the purpose of both reference and management.

• 스마트미디어저널
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• 제11권11호
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• pp.63-74
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• 2022

Nowadays, lithium-ion battery has become more popular around the world. Knowing when batteries reach their end of life (EOL) is crucial. Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is needed for battery health management systems and to avoid unexpected accidents. It gives information about the battery status and when we should replace the battery. With the rapid growth of machine learning and deep learning, data-driven approaches are proposed to address this problem. Extracting aging information from battery charge/discharge records, including voltage, current, and temperature, can determine the battery state and predict battery RUL. In this work, we first outlined the charging and discharging processes of lithium-ion batteries. We then summarize the proposed techniques and achievements in all published data-driven RUL prediction studies. From that, we give a discussion about the accomplishments and remaining works with the corresponding challenges in order to provide a direction for further research in this area.

• 산업경영시스템학회지
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• 제41권3호
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• pp.90-96
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• 2018

This paper proposed data driven techniques to forecast the time point of water management of the water reservoir without measuring manganese concentration with the empirical data as Juam Dam of years of 2015 and 2016. When the manganese concentration near the surface of water goes over the criteria of 0.3mg/l, the water management should be taken. But, it is economically inefficient to measure manganese concentration frequently and regularly. The water turnover by the difference of water temperature make manganese on the floor of water reservoir rise up to surface and increase the manganese concentration near the surface. Manganese concentration and water temperature from the surface to depth of 20m by 5m have been time plotted and exploratory analyzed to show that the water turnover could be used instead of measuring manganese concentration to know the time point of water management. Two models for forecasting the time point of water turnover were proposed and compared as follow: The regression model of CR20, the consistency ratio of water temperature, between the surface and the depth of 20m on the lagged variables of CR20 and the first lag variable of max temperature. And, the Box-Jenkins model of CR20 as ARIMA (2, 1, 2).

• 건설관리
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• 제19권2호
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• pp.63-68
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• 2018

• 항공우주정책ㆍ법학회지
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• 제33권2호
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• pp.345-366
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• 2018

국제민간항공협약 37조는 ICAO에서 제정하는 국제표준 및 권고에 따라 각국의 사정에 맞는 입법을 할 것을 요구하고 있다. 국제표준 및 권고는 매년 개정되고 있으므로 각 회원국은 적기에 해당 내용을 자국 항공법규에 반영할 필요가 있다. 최근에는 데이터 기반 국제표준이 만들어지고 있으며 그 이유는 인적요소를 주축으로 하여 사고예방을 위해서는 항공안전 데이터와 정보에 기반한 입법이 중요하게 되었기 때문이다. 데이터 기반 입법의 예로 안전관리시스템과 승무원 피로위험관리시스템이 검토 되었다. 안전관리시스템은 부속서 19가 2013년 채택되었으며 관련 매뉴얼 제5장에는 안전데이터의 수집과 분석 시스템에 기술되어 있다. 안전데이터와 정보의 분석을 통하여 의사결정권자는 데이터에 기반한 결정을 할 수 있다. 대한민국은 항공안전법 제58조에 따라 모든 항공사, 정비업체, 공항공사 등이 안전관리시스템을 도입하고 이행하여야 한다. 이러한 안전관리시스템을 뒷받침하기 위해서는 의무보고와 자발적 안전보고 시스템이 활성화 될 필요가 있으며 현재까지는 안전관리시스템 도입 위반에 대한 행정처분 기준은 아주 미미한 상태이다. 미국과 유럽도 안전관리시스템의 적절한 입법을 위하여 다양한 규정이 개발되어 시행되고 있다. 피로위험관리시스템의 경우 2009년 Colgan 항공기 추락을 계기로 미국교통안전위원회는 미연방항공청에 조종사 피로위험을 확인하고 관리할 수 있는 시스템 구축을 권고하였으며 2010년 미연방항공청에서 발행한 입법예고에는 약 8,000여개의 제안이 있었다. 2011년 최종법안이 통과되었으며 조종사의 조종사가 업무를 시작한 시간, 보조 승무원의 탑승여부, 휴식시설의 등급 등에 따라 승무시간을 차등 적용하는 입법이 이루어지게 되었다. 이러한 입법과정에 수많은 데이터와 정보가 분석되었으며 그 내용이 승무시간에 반영되었다. 최종 입법이 이루어지기 이전에 비용 대비 효과 분석이 실시되었으며 10년간 운영할 경우 비용보다는 효과가 더 크다는 결론이 이루어졌다. 대한민국도 승무원 피로위험 관련 항공안전법 조항이 있으며 항공사는 전통적인 승무시간 제한 방법 또는 피로위험관리시스템 둘 중 하나를 선택할 수 있다. 데이터 기반 입법을 위하여 미국의 경우 항공입법위원회를 구성하여 운영하고 있는데 이는 대한민국에도 도입이 필요한 내용이며 유럽에서 시행하고 있는 D4S도 고려할 만한 시스템이다. 비용 대비 효과 분석은 입법을 견고하게 할 수 있어 필요하다고 판단되며 데이터 기반 입법의 실효성을 제고하기 위해서는 전문 인력의 보강, 보다 자세한 점검표 작성 등이 필요하다.