• 스마트미디어저널
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• 제7권4호
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• pp.30-36
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• 2018

DataLake 프레임워크와 같은 단일 도메인 모델은 비즈니스 시스템의 규모 확장과 대량의 다양한 데이터들이 생성되는 빅데이터 환경, 그리고 데이터를 보다 스마트하게 처리하여 효율성 및 활용도를 높일 수 있는 방법으로 주목 받고 있다. 특히, 논리적인 단일 도메인 모델은 컴퓨팅 리소스의 유한함과 공유 경제에 의한 물리적으로 분할된 멀티 사이트의 데이터 처리를 위한 네트워크, 스토리지, 그리고 컴퓨팅 자원의 효율적 운영이 매우 중요하다. 기존의 Data Lake 프레임워크의 장점들을 기반으로 다양한 영역의 멀티 사이트들을 통합 및 데이터의 라이프 사이클을 관리하기 위한 DataLake 프레임워크의 Connected Data Architecture 개념과 기능들의 확장을 통한 다양한 응용 영역에 활용 가능한 CDA 기반 AI 서비스의 초안 설계 및 시나리오를 제안하고자 한다.

• 한국조경학회:학술대회논문집
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• 한국조경학회 2021년도 춘계학술대회 논문집
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• pp.115-117
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• 2021

• 한국빅데이터학회지
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• 제1권2호
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• pp.91-102
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• 2016

전통적인 환경에서 데이터 생명주기는 데이터-정보-지식-지혜 전환과정으로 요약된다. 반면에 빅데이터 환경에서 데이터 생명주기는 데이터-통찰-실행 전환과정으로 요약된다. 이러한 전환과정의 차이점은 데이터 생명주기를 지원하는 데이터 자원 관리에도 변화를 요구한다. 본 논문에서는 전통적인 데이터 자원 관리와 비교하여 빅데이터 환경을 위한 데이터 자원 관리를 연구한다. 특히 빅데이터 자원관리를 위한 주요 구성요소를 제안한다.

• 대한산업공학회지
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• 제41권2호
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• pp.162-172
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• 2015

This paper proposes a Product Data Management (PDM) system architecture that supports end-user computing for small and medium businesses (SMBs) in Korea to build and maintain efficient and sustainable information systems for their product development. Its open database with relational tables enables existing common application programs such as Microsoft office suites to access product data in PDM systems. In addition, the interactive query processor provided by database management systems helps design engineers to build ad hoc queries in standard SQL database language to response different data requirements during their product development. The PDM architecture with the open database allows design engineers or technical staffs in SMBs to build and maintain their application programs for product development by themselves. To show the feasibility of the proposed architecture, this study implemented a prototype PDM system based on the architecture and database, and represents real-world product data with the implemented PDM system.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.559-563
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• 2015

Identification of energy use patterns in buildings has a great opportunity for energy saving. To find what energy use patterns exist, clustering analysis has been commonly used such as K-means and hierarchical clustering method. In case of high dimensional data such as energy use time-series, data reduction should be considered to avoid the curse of dimensionality. Principle Component Analysis, Autocorrelation Function, Discrete Fourier Transform and Discrete Wavelet Transform have been widely used to map the original data into the lower dimensional spaces. However, there still remains an ongoing issue since the performance of clustering analysis is dependent on data type, purpose and application. Therefore, we need to understand which data reduction techniques are suitable for energy use management. This research aims find the best clustering method using energy use data obtained from Seoul National University campus. The results of this research show that most experiments with data reduction techniques have a better performance. Also, the results obtained helps facility managers optimally control energy systems such as HVAC to reduce energy use in buildings.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 2007년도 춘계학술대회 논문집
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• pp.270-274
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• 2007

Clearing trace of symbol which was gone with a series of pre-modern architecture history since the modern architecture (pursuing true nature from tradition which is repeated and imitated unconsciously). That is, What is the course of deconstruction? In the early part of the 20th century, We still accept the necessity of decoration in spite of its existence at one time being threaten. This means, even though symbolism in architecture has relative importance by situation of Times, it plays an important role to add the past to current style through 'Symbol'. The history of Times, a carrier which reflects Present on New Futures, makes memory by gathering data but we can not amplify our historical imagination with only data. Data is a past memory and evidence but we can not substitute that for historical experience. And it is difficult for future generations who don't live through that history to change their historical recognition with recollecting memories. They have to draw history with data but it is very limited in itself. However, They can collect historical memory through symbol in architecture. In this study, We pay attention to the symbolism of a memorial hall architecture. So We'll analyze dichotomy concept of Barthes's signifiant and signifie, visual sign and course of symbolic meaning on basis of Daniel Libeskind's Jewish Museum.

• 한국해양공학회지
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• 제34권1호
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• pp.26-36
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• 2020

An extreme value analysis of metocean data which include wave, wind, and current data is a prerequisite for the operation and survival of offshore structures. The purpose of this study was to provide information about the return wave, wind, and current values for the Barents Sea using extreme value analysis. Hindcast datasets of the Global Reanalysis of Ocean Waves 2012 (GROW2012) for a waves, winds and currents were obtained from the Oceanweather Inc. The Gumbel distribution, 2 and 3 parameters Weibull distributions and log-normal distribution were used for the extreme value analysis. The least square method was used to estimate the parameters for the extreme value distribution. The return values, including the significant wave height, spectral peak wave period, wind speed and current speed at surface, were calculated and it will be utilized to design offshore structures to be operated in the Barents Sea.

• 정보화연구
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• 제9권2호
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• pp.187-197
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• 2012

정보화 투자의 증가는 정보기술자원의 복잡성을 증대시켰으며, 이로 인해 중복투자 및 정보시스템 관리의 비효율성이 대두 되었다. 이에 정보기술 자원에 대한 효율적 도입과 관리를 위하여 EA(Enterprise Architecture) 사상이 발전하였다. 하지만, 데이터 영역에 대해서는 EA 사상이 발전한 이후에도 한동안 체계적인 지침의 제공이 미흡하였다. 따라서, 이제는 프로세스에 숨어있는 데이터를 도출, 관리하여 공공부문 각 기관 간 데이터의 공유성 및 재활용성을 높이기 위한 데이터 참조모형(DRM : Data Reference Model)의 활용이 필요하다. 이에 본 연구에서는 데이터 참조모형 중 가장 활용도가 높은 데이터 분류체계에 대한 개선의 필요성을 인식하고, 분류체계 재정립을 위한 방향성 및 연구 방법을 제시해 보려 한다.

• 교육녹색환경연구
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• 제7권1호
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• pp.39-55
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• 2008

The purpose of this study is to suggest improvement of certification standards of environment friendly architecture in ecological environment field by surveying and analyzing actual status of actual certification schools of environment friendly architecture per ecological environment elements through extracting ecological environment elements which is possible to analyze in quantity certification standards of environment friendly architecture. As contents of the study, first, certification as an examination on certification system of environment friendly architecture, summary of certification system of environment friendly architecture, ecological environment elements which is possible for quantitative analysis of ecological environment certification standards were extracted. Second, actual status of ecological environment elements per school grade, region, and population increase by collecting actual data of certification schools of environment friendly architecture. Third, using analysis data of ecological environment elements, ecological area ratio of certification schools of environment friendly architecture per weighted values of space types was calculated and the results were analyzed as the follows. (1) In case of preliminary certification out of total objects of investigation schools was average 34.06% but in this case of certification, it was reduced to 33.07%. However, it is difficult to make judgment as actual evidence data since ecological area ratio of actual preliminary certification is data based on drawing planes. Therefore, in case of this certification, elementary schools was investigated at average 33.11%, middle schools 34.81%, and high schools 31.28% and middle school showed the highest relatively. (2) Besides, average composition ratio of ecological area ratio was 63.04% in case of this certification regardless of school grade and region and it was analyzed that about 70% of ecological area ratio is composed of the natural based green area including pure natural based green land and 6.89% of ecological learning institute.

• 대한산업공학회지
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• 제39권1호
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• pp.1-9
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• 2013

The current manufacturers have generated tremendous amount of digitized product data to efficiently share and exchange it with other stakeholders or various software systems for product development. The digitized product data is a valuable asset for manufacturers, and has a potential to support high level strategic decision makings needed at many stages in product development. However, the lack of studies on extraction of key performance indicators(KPIs) from product data management(PDM) databases has prohibited manufacturers to use the product data to support the decision makings. Therefore this paper examines a possibility of an architecture that supports KPIs for evaluation of product development performances, by applying multidimensional product data model and on-line analytic processing(OLAP) to operational databases of product data management. To validate the architecture, the paper provides a prototype product data management system and OLAP applications that implement the multidimensional product data model and analytic processing.