• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.317-320
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• 2015

Documenting work-in-progress on construction sites using images captured with smartphones, point-and-shoot cameras, and Unmanned Aerial Vehicles (UAVs) has gained significant popularity among practitioners. The spatial and temporal density of these large-scale site image collections and the availability of 4D Building Information Models (BIM) provide a unique opportunity to develop BIM-driven visual analytics that can quickly and easily detect and visualize construction progress deviations. Building on these emerging sources of information this paper presents a pipeline for model-driven visual analytics of construction progress. It particularly focuses on the following key steps: 1) capturing, transferring, and storing images; 2) BIM-driven analytics to identify performance deviations, and 3) visualizations that enable root-cause assessments on performance deviations. The information requirements, and the challenges and opportunities for improvements in data collection, plan preparations, progress deviation analysis particularly under limited visibility, and transforming identified deviations into performance metrics to enable root-cause assessments are discussed using several real world case studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.340-367
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• 2018

Storage services integration can be done for achieving high availability, improving data access performance and scalability while preventing vendor lock-in. However, multiple services environment management and interoperability have become a critical issue as a result of service architectures and communication interfaces heterogeneity. Storage federation model provides the integration of multiple heterogeneous and self-sufficient storage systems with a single control point and automated decision making about data distribution. In order to integrate diverse heterogeneous storage services into a single storage pool, we are proposing a storage service federation framework named BoxBroker. Moreover, an automated decision model based on a policy-driven data distribution algorithm and a service evaluation method is proposed enabling BoxBroker to make optimal decisions. Finally, a demonstration of our proposal capabilities is presented and discussed.

• 아태비즈니스연구
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• 제15권1호
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• pp.131-143
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• 2024

Purpose - The purpose of this study was to analyze cases of big data-driven business in the financial industry, focusing on organizational structure and business processes using big data in banking industry. Design/methodology/approach - This study used a case study approach. To this end, cases of two banks implementing big data-driven business were collected and analyzed. Findings - There are two things in common between the two cases. One is that the central tasks for big data-driven business are performed by a centralized organization. The other is that the role distribution and work collaboration between the headquarters and business departments are well established. On the other hand, there are two differences between the two banks. One marketing campaign is led by the headquarters and the other marketing campaign is led by the business departments. The two banks differ in how they carry out marketing campaigns and how they carry out big data-related tasks. Research implications or Originality - When banks plan and implement big data-driven business, the common aspects of the two banks analyzed through this case study can be fully referenced when creating an organization and process. In addition, it will be necessary to create an organizational structure and work process that best fit the special situation considering the company's environment or capabilities.

• 한국콘텐츠학회논문지
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• 제20권6호
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• pp.220-229
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• 2020

최근 디지털 기술의 발전으로 연구 패러다임이 데이터 중심으로 변화하고 있다. 연구데이터의 국가적 관리와 활용은 연구의 투명성과 효율성을 제고하고, 나아가 데이터 기반으로 급변하는 사회에 대비하기 위한 필수 요소이다. 주요 선진국에서는 공적 지원에 의해 수행된 연구에서 생산되는 연구데이터의 공유·활용을 위한 정책과 인프라 구축이 적극적으로 추진되고 있다. 국내에서도 2019년 국가연구개발과제 제안시 데이터 관리 계획을 제출하도록 관련 규정이 개정되었다. 데이터 관리 계획 제도가 효과적으로 실행되고 지속성을 유지하기 위해서는 연구자에게 다양한 지원 여건이 필요하다. 또한 데이터 관리 계획 가이드라인과 이행 절차는 국가 또는 기관 차원의 연구데이터 관리·활용을 위해 필수적이다. 이 연구에서는 데이터 관리 계획의 개요와 국내의 추진 현황 및 이슈를 살펴보고, 작성 가이드라인과 체크리스트, 적용프로세스, 그리고 연구기관에서의 이행방안을 제시한다.

• 간호행정학회지
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• 제21권3호
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• pp.308-316
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• 2015

Purpose: The purpose of this study was to identify the level of project perception for those nurses from research-driven hospitals and to analyze the effect of research-relevant performance in the health care field focusing on the mediated effect of research capacity and job satisfaction. Methods: Data were collected from June, 2014 to July, 2014, and participants were 106 research nurses in Research-driven hospitals. Descriptive statistics, Independent t-test, One-way ANOVA, structural equation modeling (SEM). Results: As a result, Research-relevant performance according to project perception of research nurses from Research-driven Hospitals was not statistically significant, but research capacity and job satisfaction had a mediating role. Evaluation System Perception was significantly different from Research Capacity (p<.001), Research Capacity was significantly different from Job Satisfaction (p<.001), Job Satisfaction was significantly different from Research Performance (p<.001) Conclusion: The results indicate that research capacity building and job security research nurses are able to contribute to improving research performance of research-driven hospitals.

• 정보화정책
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• 제28권3호
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• pp.95-111
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• 2021

데이터 기반 정책의사결정시스템 구현을 목표로 현재 기획재정부는 관련 추진단을 구성하여 활발히 구축 중에 있다. 본 시스템은 현재 단순 재정행정업무 지원을 벗어나 데이터 기반의 재정업무가 가능하도록 구축 중이다. 미국은 증거 기반의 정책의사 결정법을 제정하여 관련 업무를 적극 추진 중이다. 우리나라도 작년부터 데이터기반 행정법이 시행되어 데이터 기반 행정업무를 할 수 있도록 법제도적 근거가 마련되었다. 차세대 예산회계시스템이 데이터 기반의 시스템으로 그 역할을 다하려면 많은 정책과 노력이 필요하다. 데이터 관리, 법제도, 관련 시스템 구축 등 다양한 부분에서 혁신과 변화가 필요하다. 이런 상황에서 우리나라보다 먼저 재정시스템을 구축하여 운영하고 있는 미국, 영국 등 세계 선진국의 재정시스템과 정책을 거버넌스 차원에서 비교 분석하는 것은 매우 시기적절하다고 볼 수 있다. 이들의 재정정보시스템을 비교 분석하여 차세대 예산회계시스템에 적용한다면 한층 더 나은 시스템이 될 것으로 기대한다. 본 연구에서는 미국, 영국, 프랑스, 캐나다 등 주요 선진국을 대상으로 데이터 거버넌스를 정책적, 시스템적, 법제도적, 추진체계, 서비스적 차원에서 비교 분석하였다. 그리고 결론에서는 디지털 대전환시대, 코로나19 등 최근 어려운 경제위기 환경에 대해 신속히 대처하고 국민이 원하는 국가재정정책시스템으로서의 역할과 방향도 제안하였다.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• 한국콘텐츠학회논문지
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• 제17권12호
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• pp.117-126
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• 2017

최근 연구 환경과 연구 패러다임이 데이터 중심(Data-Driven)으로 변화되고 있다. 특히, 공공 연구성과의 개방과 공유에 기반한 오픈 사이언스(Open Science)가 과학 연구의 글로벌 어젠다로 새롭게 부각되고 있다. 해외에서는 공적 지원에 의해 수행된 연구에서 생산되는 과학데이터의 공유 활용을 위한 정책이 적극적으로 시행되고 있어, 국내에서도 '오픈 연구데이터'를 위한 정책과 인프라 구축이 시급한 상황이다. 본 연구에서는 국내 과학기술 분야 연구기관의 과학데이터 생산, 관리, 활용 현황을 조사했다. 국가과학기술연구회 소속 22개 정부출연 연구기관과 국내 20개 대학의 연구자를 대상으로 과학데이터 생산, 관리, 활용현황, 과학데이터 공유 활용 참여 의지, 과학데이터 공유 활용 요구사항 등 5개 관점의 심층인터뷰를 실시했다. 이를 기반으로 과학데이터 공유 활용을 위한 시사점과 개선방향을 도출했다.

• 항공우주시스템공학회지
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• 제15권4호
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• pp.7-10
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• 2021

Including 425 Program, which is Korean military surveillance and reconnaissance satellite, there were mostly civil-driven space programs in Korea. However, there are increasing numbers of military demand-driven space program in nowadays. Furthermore, it is positive effects on launch vehicle development in Korea that the termination of Korea-U.S. missile guideline. In this paper, it emphasizes the needs of system engineering(SE) management method which meets both defense system's characteristics and space's characteristics. These characteristics are such as non-fixable after the launch, the security issue in defense system. And it also introduces SE tool, methodology and its philosophy. There are several functions that data management, issue management, risk management, and technical requirement management. Also describing its implications and direction of improvement.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회(1)
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• pp.174-175
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• 2005