• Journal of the Korean Society for Library and Information Science
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• v.32 no.3
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• pp.143-156
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• 1998

This paper reports the GEM (Gateway to Educational Materials) project whose goal is to develop an operational framework to provide the K-12 teachers in the world with 'one-stop/any-stop' access to thousands of lesson plans, curriculum units and other Internet-based educational resources. To the IS-element Dublin Core base package, the GEM project added an 8-element, domain-specific GEM package. The GEM project employed the conceptual data modeling approach to designing the GEM database, used the Sybase relational database management system (RDBMS) to construct the backend database for storing the metadata of educational resources, and also employed the active server page (ASP) technology to provide Web interfaces to that database. The consortium members catalog lesson plans and other Internet-based educational resources using a cataloging module program that produces HTML meta tags. A harvest program collects these meta tags across the Internet and outputs an ASCII file that conforms to the standard agreed by the consortium members. A parser program processes this file to enter meta tags automatically into appropriate relational tables in the Sybase database. The conceptual/logical schemas of Dublin Core and GEM profile are presented. The advantages of conceptual modeling approach to manage metadata are discussed. A prototype system that provides access to the GEM metadata is available at http://lis.skku.ac.kr/gem/.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.143-151
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• 2009

Forest type map is a main forest thematic map which shows forest type, age class, diameter class and density. This map has been used as a base data in various fields such as forest policy decision-making, land suitability assessment and eco map production etc. But the existing map had many kinds of errors and no metadata because there was no standard for digital map production. On this study, we developed standard for digital forest type map production consisting of 33 unit processes including DB schema design, mapping process, quality control and metadata input process. Based on this standard, country-wide digital forest type map can be produced with consistent quality and standard metadata.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.375-375
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• 2018

세계 수자원 시장은 연평균 6.5%씩 증가하고 있으며, 2025년 기준 1,038조원까지 급성장할 것으로 전문가들은 예상하고 있으나, 기후변화의 가속화로 인해 가뭄 및 홍수피해가 증가하여 수자원 관리가 더욱 어려워져지고 있다. 급속도로 변화는 환경에 대비하기 위해 국내에서는 수자원 및 기후변화에 대한 다양한 연구가 진행되고 있으나, 해외사업 진출 시에는 수자원 기초자료 수집에 대한 어려움을 겪고 있다. 이를 해결하기 위해 글로벌 수문기상자료 제공과 함께 GIS정보, 댐 및 저수지 관련 자료, 인문사회 자료, 물관련 통계자료, 물관련 재해자료 등을 웹으로 제공하는 글로벌 수자원 정보 시스템(GWB, Global World Bank)을 개발하고자 한다. 본 연구에서는 시스템의 통합 DB를 구축하고 관리방안을 도출하기 위해 수집된 메타데이터 속성 및 데이터구조를 파악하고, 세부항목별 자료 포맷을 분석 후 GIS기반 관측소 정보와 자료를 매칭하여 최종적으로 시스템 컨텐츠별로 DB를 맵핑하였다. 강수량과 기상자료는 33개국의 관측소 6,531개소의 일/월/연단위 관측자료와 10,977격자의 격자분석자료를 구축하였다. 수문자료는 33개국의 수문관측소 2,242개의 월/연단위 유량관측자료와 10,977격자의 월/연단위 직접유출, 기저유출, 잠재증발산의 격자분석자료를 구축하였다. 그리고, 수집된 강우와 기상자료는 기계 오작동, 자료 전송 오류 등으로 인한 결측치 및 이상치에 대해 자료품질분석을 통해 오자료에 대한 보정을 진행하였다. 해당자료는 MySQL를 활용하여 DB를 구축하였으며, GIS정보는 GeoServer를 활용하여 운영서버에 구축된 정보를 최종적으로 사용자에게 Web Browser로 표출하였다. 해당 시스템은 추후 전지구 수자원관련 정보를 제공하여 해외사업지역의 댐이나 보 등의 구조물 설계, 수자원산업의 해외 진출시 데이터 수집의 한계점 및 시간단축을 해결할 수 있어 수자원 분야에 기여 할 수 있을 것으로 판단된다.

• Quality Improvement in Health Care
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• v.7 no.1
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• pp.106-116
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• 2000

Background : Severance Hospital is an university hospital which has 1,580 beds. A LAN system was installed in the Medical Record Department in 1992 and discharge abstract data have been added to the discharge abstract database(DB) The previous work flow in the Medical Record Department had 5 levels: 1) chart collection from wards, 2) assembling, 3) abstracting data from medical record on worksheet by 2 RRAs, 4) checking deficiencies and coding diagnosis and procedures by 4 RRAs, 5) inputting the data into the discharge abstract data base by 1 RRA. The average processing time took 19.3 days from the patient discharge date. It had the production of monthly statistical report delayed. Besides, it caused the users in the hospital to complain. Methods : A CQI team was organized to find a way to shorten the processing time less than 10 days. The team identified the factors making the processing time long and integrated three levels from the 3rd level into one. Each of 7 RRAs performed the integrated level on her workstation instead of taking one of three separate levels. The comparison of processing time before and after the changes was made with 3'846 discharges of April, 1999 and 4,189 discharges of August, 1999. Results : The average processing time was shortened from 19.3 days to 8.7 days. Especially the integrated level took only 3.6 days, compared with 12.3 days before the change. The percentage of finishing up the whole processing within 10 days from discharge was increased up to 77.6%, which was 2.4% before the integration. The prevalence of error in data input was not increased in the new method. Conclusions : The integrated processing method has the following advantages: 1) the expedition of production of monthly statistical report, 2) the increase of utilizing rate of dischare abstract data by Billing Dept, Emergency Room, QI Dept., etc., 3) the improvement of intradepartmental work follow, 4) the enhancement of medical record quality by checking the deficiencies earlier than before.

• Solar Energy
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• v.18 no.3
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• pp.31-39
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• 1998

Selection of a right weather data set has been considered as one of important factors for a successful building energy audit process. A set of 30 year raw weather data base for six major cities has been developed to provide the weather data file for building energy audit and retrofit analysis in Korea. The program named as KWDP(KIER Weather Data Processor) uses the DB to produce a right data set for a specific building energy performance simulation program like DOE2.1E. A program called WMAKE has been developed to generate the right set of input parameters for DOE2.1E weather utility program. The set of the programs could provide the right weather data for specific building energy audit and retrofit analysis.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.509-521
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• 2016

A novel Samples Balanced Genetic Algorithm combined with Extreme Learning Machine (SBGA-ELM) for Parkinson's Disease diagnosis and detecting bio-markers is presented in this paper. Proposed approach uses genes' expression data of 22,283 genes from open source ParkDB data base for accurate PD diagnosis and detecting bio-markers. Proposed SBGA-ELM includes two major steps: feature (genes) selection and classification. Feature selection procedure is based on proposed Samples Balanced Genetic Algorithm designed specifically for genes expression data from ParkDB. Proposed SBGA searches a robust subset of genes among 22,283 genes available in ParkDB for further analysis. In the "classification" step chosen set of genes is used to train an Extreme Learning Machine (ELM) classifier for an accurate PD diagnosis. Discovered robust subset of genes creates ELM classifier with stable generalization performance for PD diagnosis. In this research the robust subset of genes is also used to discover 24 bio-markers probably responsible for Parkinson's Disease. Discovered robust subset of genes was verified by using existing PD diagnosis approaches such as SVM and PBL-McRBFN. Both tested methods caused maximum generalization performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.271-275
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.49-52
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• 1994

We have developed a biological signal measurement, archiving, and communication system (SiMACS). The front end of the system is the intelligent data processing unit (IDPU) which includes ECG, EEG, EMG, blood pressure, respiration, temperature measurement modules, module control and data acquisition unit, real-time display and signal processing unit. IDPUS are connected to central data base unit through LAN(Ethernet). Workstations which receive signals from central DB and provide various signal analysis tools are also connected to the network. The developed PC-based SiMACS is described.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.353-359
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.331-333
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• 2001

분산되고 이질적인 환경에서의 정보 소스들을 통합하려는 노력은 끊임 없이 계속되어 왔다. 이질적인 다중 정보소스로부터 추출된 정보를 통합하는 도구를 개발하는 것은 인터넷 기반에서 다양한 정보들을 실시간으로 사용할 수 있다는 측면에서 아주 흥미로운 일이다. 이러한 도구를 개발하는데 있어서의 주된 문제점은 서로 다른 정보소스에 존재하지만 실제적으로는 같은 실세계의 개념을 가지고 있는 정보를 어떻게 효과적으로 표현할 것인가 하는 것이다. 이러한 의미적 이질성을 해결하기 위해서 WordNet이나 Common Thesaurus 등을 이용한 개념 기반의 접근방법이 많이 제안되었다. 하지만 이들은 스키마 이질성을 해결하는 방법을 제시 할 뿐, 데이터의 이질성을 해결 하는 방법은 보여주지 않는다. 본 논문에서는 GSN(Global Semantic Network)을 이용해서 스키마 이질성을 해결해야 데이터베이스 시스템에서 발생하는 데이터 이질성의 예를 제시하고 이러한 데이터 이질성을 해결할 수 있는 기법을 제안한다.