• 통상정보연구
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• 제7권1호
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• pp.55-74
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• 2005

Recently, many enterprises have attempted to construct data warehousing systems for decision-support. Data warehouse is an intelligent store of data that can aggregate vast amounts of information. Building DW requires two important development issues:(i) DW for the decision making of business users and (ii) metadata within it. Most DW development methodologies have not considered metadata development; it is necessary to adopt a DW development methodology which develops a DW and its metadata simultaneously. Metadata is a key to success of data warehousing system and is critical for implementing DW. That is, metadata is crucial documentation for a data warehousing system where users should be empowered to meet their own information needs; users need to know what data exists, what it represents, where it is located, and how to access it. Furthermore, metadata is used for extracting data and managing DW. However, metadata has failed because its management has been segregated from the DW development process. Metadata must be integrated with data warehousing systems. Without metadata, the decision support of DW is under the control of technical users. Therefore, integrating data warehouse with its metadata offers a new opportunity to create a more adaptive information system. Therefore, this paper proposes a DW development methodology from a metadata perspective. The proposed methodology consists of five phases: preparatory, requirement analysis, data warehouse (informational database) development, metastore development, and maintenance. To demonstrate the practical usefulness of the methodology, one case is illustrated

• 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.

• 한국군사과학기술학회지
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• 제20권2호
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• pp.187-196
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• 2017

The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

• 정보처리학회논문지D
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• 제11D권1호
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• pp.173-182
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• 2004

소프트웨어의 개발 노력을 추정하기 위한 연구가 지속적으로 이루어지고 있다. 그러나 이러한 개발 노력 추정을 위한 가장 이상적인 모델을 제시하기 위해서 실험자료를 얻어야 하나 이러한 실험자료를 얻는 것은 그리 쉬운 일이 아니다. 또한 이러한 실험자료가 얻어지면 실험자료에 대한 분석 또한 상당히 중요한 연구과제라고 볼 수 있다. 본 연구에서는 1990년대에 개발된 789개의 소프트웨어 개발 프로젝트들에 관련된 데이터를 이용하여 개발 노력에 영향을 미치는 요인별 데이터 분석을 실시하여 그 특징을 추출하고자 한다. 개발 소프트웨어의 규모가 다양하고 소프트웨어의 개발에 참여한 개발 팀의 규모도 차이가 있기 때문이다. 이와 같은 특징을 고려하여 주어진 자료에 대한 분석을 통해서 요인별 특징을 파악하고 파악된 자료를 중심으로 개발 노력을 단계별로 추정하려고 한다. 따라서, 본 연구에 사용된 789개 프로젝트 데이터를 개발형태(Development Type), 개발환경(Development Environment), 개발언어(Development Language) 등으로 분류하여 개발 노력(Development Effort)에 차이가 있음을 증명하고 팀 규모(Team Sire)와 기능점수(Function Point)에 따른 교차분석(Crosstabs Analysis)을 실시하여 보았다.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1998년도 국제 컨퍼런스: 국가경쟁력 향상을 위한 디지틀도서관 구축방안
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• pp.448-474
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• 1998

Data warehouse (DW) is important for analytical processing. Metadata is a key to its architecture. This paper proposes an architecture that consists of seven components. To illustrate data warehouse environment (DWE), this Paper proposes taxonomies having four flows. on the basis or the taxonomies and metadata, this paper proposes a methodology for building the data warehouse and metadata simultaneously. This integrated development methodology (IDM) consists of seven phases: (i) preparatory phase, (ii) requirement analysis phase, (iii) data warehouse development phase, (iv) operational data store development phase, (v) data mart development phase, (vi) metastore development phase, and (vii) maintenance phase. A metastore system is Proposed to help develop metadata interactively. An illustrative example is investigated to demonstrate the usefulness of IDM.

• Genomics & Informatics
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• 제1권2호
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• pp.65-74
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• 2003

Data mining differs primarily from traditional data analysis on an important dimension, namely the scale of the data. That is the reason why not only statistical but also computer science principles are needed to extract information from large data sets. In this paper we briefly review data mining, its characteristics, typical data mining algorithms, and potential and ongoing applications of data mining at biopharmaceutical industries. The distinguishing characteristics of data mining lie in its understandability, scalability, its problem driven nature, and its analysis of retrospective or observational data in contrast to experimentally designed data. At a high level one can identify three types of problems for which data mining is useful: description, prediction and search. Brief review of data mining algorithms include decision trees and rules, nonlinear classification methods, memory-based methods, model-based clustering, and graphical dependency models. Application areas covered are discovery compound libraries, clinical trial and disease management data, genomics and proteomics, structural databases for candidate drug compounds, and other applications of pharmaceutical relevance.

• 산업경영시스템학회지
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• 제39권3호
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• pp.139-146
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• 2016

This study proposes a methodology to analyse social networks among participating design engineers during product development projects. The proposed methodology enables product development managers or the participating design engineers to make a proper decision on product development considering the performance of participating design engineers. It considers a product development environment where an integrated product data management (PDM) system manages the product development data and associated product development processes consistently in its database, and all the design engineers share the product development data in the PDM database for their activities in the product development project. It provides a novel approach to build social networks among design engineers from an operational product development data in the PDM database without surveys or monitoring participating engineers. It automatically generates social networks among the design engineers from the product data and relationships specified by the participants during the design activities. It allows analysts to gather operational data for their analysis without additional efforts for understanding complex and unstructured product development processes. This study also provides a set of measures to evaluate the social networks. It will show the role and efficiency of each design engineers in the social network. To show the feasibility of the approach, it suggests an architecture of social network analysis (SNA) system and implemented it with a research-purpose PDM system and R, a statistical software system. A product configuration management process with synthetical example data is applied to the SNA system and it shows that the approach enables analysts to evaluate current position of design engineers in their social networks.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제36권2호
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• pp.253-286
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• 2022

본 연구는 학교 현장에서 교원학습 공동체 프로그램에 참여한 동일교 소속 교사들 네 명이 실천적이고 공유 가능한 수업 자료 개발을 목표로 윤리와 수학 과목에서 플라톤이라는 인물을 연계 고리로 하여 교과 간 연계·융합 자료 개발한 연구이다. 이때 자료 개발 절차는 '자료 개발 계획 수립, 자료 개발, 개발 자료의 검증, 검증 의견을 반영한 최종 자료 개발'과 같은 네 가지 절차를 따랐으며, 자료 개발 단계에서는 주제기반 설계 모형에 따라 자료를 개발하였다. 개발한 자료는 현장 교사들을 대상으로 개발 자료의 타당성과 수업 적용 가능성을 중심으로 CVR 검증을 실시하였고, 검증 결과를 반영하여 개발 자료의 수정을 거쳐 최종 개발 자료 결과물을 제시하였다. 특히 본 연구에서는 단순하게 개발한 자료를 소개하는 것이 아니라, 자료 개발 과정의 절차와 그 과정에서의 개발자들의 시행착오와 고민도 함께 기술하여 자료 개발을 시도하는 다른 현장 연구자들에게 기초 연구 성격의 정보를 제공하고자 하였다.

• Toxicological Research
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• 제18권2호
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• pp.167-174
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• 2002

Historical control data have been shown to be valuable in the proper interpretation and validation of reproductive toxicology studies. The present data were compiled from rat fertility and early embryonic development studies conducted at Korea Institute of Toxicology during the 1994∼2001 period. These data were assembled in order to provide background information for the general and reproductive data collected in 11 fertility and early embryonic development studies using Sprague-Dawley rats obtain-ing from the Breeding Facility, Korea Institute of Toxicology, Korea. A total of 274 males and 274 females were used in these studies during the eight-year period. Parameters of fertility and early embryonic development included clinical sign, body weights, food consumption, organ weights, estrus cycle, copulation index, precoital time, fertility index, pregnancy index, sperm parameters, and early embryonic development parameters. Most of the values were comparable to the previous historical control data reported by other investigators. These data can be wed not only as a historical data base for the meaningful interpretation of data from reproductive and developmental toxicity studies, but also as a contribution to biological characterization of Sprague-Dawley rats.

• 한국사회복지학
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• 제54권
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• pp.245-272
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• 2003

본 연구는 종합사회복지관의 프로그램 개발과정에 있어서 프로그램 개발자들의 정보수집정도 및 유형을 파악하고, 이러한 정보수집정도에 영향을 미치는 예측 변인이 무엇인지를 밝히는 데 조사의 목적이 있다. 조사방법으로는 전국의 335개의 종합사죄복지관의 청소년(아동)부서의 프로그램 개발을 책임지고 있는 사회복지사를 응답자로 하여 우편으로 설문조사를 실시하였다. 연구의 주요한 결과를 살펴보면, 우선 기술분석결과에서 첫째, 현장에서 프로그램 개발활동이 활발하다는 것이 밝혀졌다. 둘째, 복지관에서 프로그램 개발을 주로 나이와 기관의 근무경험이 부족한 직원들이 개발을 맡고 있다. 셋째, 개발자들이 비공식적인 정보보다는 공식적 정보들을 더 많이 수집하고 있다. 넷째, 개발자들이 프로그램 개발관련지식을 공식적 교육프로그램을 통해서 획득한 '공식적' 훈련보다는 '비공식적' 훈련으로 통해서 더 많은 지식을 습득하고 있는 것으로 나타나고 있다. 회귀분석결과를 살펴보면, '전체적인 정보수집활동'에 영향을 미치는 요인으로서 업무의 자율성, 업무의 부담감, 공식적 교육정도, 개방성 등이 중요한 변수로서 나타났다. 특히, '전체적인 정보수집활동'에서 중요하게 영양을 미치는 업무의 부담감의 변수는 흥미롭게도 '전체적인 정보수집활동'을 세부적으로 구분한 '공식적 정보수집활동'과 '비공식적 정보수집활동'으로 구분하여 살펴본 회귀분석결과에 유일하게 다르게 영양을 미치는 요인으로 나타났다. 주요 결과를 바탕으로 이론적 및 실천적인 함의를 논하였다.