• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1995년도 추계학술발표회논문집(1)
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• pp.293-299
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• 1995

A methodology is applied to identify tile learning trend related to the safety and availability of U.S. commercial nuclear power plants. The application is intended to aid in reducing likelihood of human errors. To assure that tile methodology ran be easily adapted to various types of classification schemes of operation data, a data bank classified by the Transient Analysis Classification and Evaluation(TRACE) scheme is selected for the methodology. The significance criteria for human-initiated events affecting tile systems and for events caused by human deficiencies were used. Clustering analysis was used to identify the learning trend in multi-dimensional histograms. A computer rode is developed based on tile K-Means algorithm and applied to find the learning period in which error rates are monotonously decreasing with plant age.

• 한국과학교육학회지
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• 제16권3호
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• pp.270-277
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• 1996

The purpose of this study is to classify and state of evaluating objectives using three-dimensional assessment framework of science inquiry. The first, as an attempt to provide a theoretical base for developing an assessment framework taxonomies and classificatory schemes of educational objectives were analyzed Bloom's taxonomy, Klopfer's specification, NAEP(National Assessment of Educational Progress), and APU(Assessment of Performance Unit) framework. The second, three-dimensional assessment framework use in this study has formed a clear definition of three-dimensional matrix. These three dimensions consists of content, context and process. The third, the model of three-dimensional taxonomy of science inquiry developed in this study is presented. In addition, an example of classification and statement of evaluating objectives based on the model is presented.

• 정보관리학회지
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• 제34권4호
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• pp.321-344
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• 2017

기록이나 문헌의 자동분류에 관한 연구는 오래 전부터 시작되었다. 최근에는 인공지능 기술이 발전하면서 기계학습이나 딥러닝을 접목한 연구로 발전되고 있다. 이 연구에서는 우선 문헌의 자동분류와 인공지능의 학습방식이 발전해 온 과정을 살펴보았다. 또 기계학습 중 특히 지도학습 방식의 특징과 다양한 사례를 통해 기록관리 분야에 인공지능 기술을 적용해야 할 필요성에 대해 알아보았다. 그리고 실제로 지도학습 방식으로 서울시의 결재문서를 ETRI의 엑소브레인을 통해 정부기능분류체계로 자동분류해 보았다. 이를 통해 기록을 다양한 방식의 분류체계로 자동분류하기 위한 각 과정의 고려사항을 도출하였다.

• Environmental Analysis Health and Toxicology
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• 제21권2호
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• pp.197-208
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• 2006

The hazards of chemicals can be classified using classification criteria that are based on physical, chemical and ecotoxicological endpoints. These criteria may be developed be iteratively, based on scientific or regulatory processes. A number of national and international schemes have been developed over the past 50 years, and some, such as the UN Dangerous Goods system or the EC system for hazardous substances, are in widespread use. However, the unnecessarily complicated multiplicity of existing hazard classifications created much unnecessary confusion at the user level, and a recommendation was made at the 1992 Rio Earth summit to develop a globally harmonized chemical hazard classification and compatible labelling system, including material safety data sheets and easily understandable symbols, that could be used for manufacture, transport, use and disposal of chemical substances. This became the globally harmonized system for the Classification and Labelling of Chemicals (GHS). The developmental phase of the GHS is largely complete. Consistent criteria for categorizing chemicals according to their toxic, physical, chemical and ecological hazards are now available. Consistent hazard communication tools such as labelling and material safety data sheets are also close to finalizations. The next phase is implementation of the GHS. The Intergovernmental Forum for Chemical Safety recommends that all countries implement the GHS as soon as possible with a view to have the system fully operational by 2008. When the GHS is in place, the world will finally have one system for classification of chemical hazards.

• 한국문헌정보학회지
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• 제45권4호
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• pp.309-326
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• 2011

There have been several milestones in the history of library classification but most of the schemes failed to meet the new challenges in the organisation of information. Dr. S. R. Ranganathan tried to revolutionise the whole thinking on classificatory approach, when he devised the Colon Classification (CC) in 1933. He developed the Colon Classification scheme with a sound theoretical background based on normative principles, Five laws of Library science, canons, etc. One important feature of CC is that, its use is not confined to information storage and retrieval alone. This paper presents an over view of different editions of the CC highlighting the salient features of the editions. Further the implication of Five Laws of Library Science has been described. The authors stressed that the features of such as greater hospitality, specificity and mixed notation has paved the way to design and develop the depth schedules on various micro level subjects and so far about 130 micro schedules have been published. The impressions by the leading LIS professionals during and after Ranganathan's time have been highlighted. The authors expressed the fear that when the library world would see the complete version of the seventh edition of CC? It may be due to lack of institutional support engaging in the research or financial constraints. The authors are of the opinion that any scheme to flourish needs a sound research body to bring out the revised editions as done in the case of Dewey Decimal Classification. The relevance of the CC in the contemporary world of Librarianship is discussed. Finally concludes that CC needs to be resuscitated as it is a precious national heritage; and still a force for the management of libraries.

• 한국도서관정보학회지
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• 제43권4호
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• pp.5-22
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• 2012

이 연구는, KDC 5판 360.1-.9(기초법학 및 법률학일반)의 전개체계를 개선하기 위한 것으로서, 먼저 법률학 전문 학술서적에 나타난 기초법학(이론법학)의 세부 학문체계를 기본바탕으로 하고, KDC 5판, DDC 23판 및 NDC 9판의 기초법학 부문을 비교 분석하여 추가로 반영하였으며, 마지막으로 국내 법학전문대학원 교과과정을 전수 조사하여 신규 주제항목(교과목 단위)을 추가하여 국내실정에 가장 적합한 개선방안을 마련하여 제시함으로써 KDC 6판에 일조하고자 한 것이다.

• 한국정보시스템학회지:정보시스템연구
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• 제29권3호
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• pp.1-34
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• 2020

Purpose Due to the complexity of policy environment in modern society, it is accepted as common basics of policy design to mix up a variety of policy instruments aiming the multiple functions. However, under the current situation of written-down policy specification, not only the public officers but also the policy researchers cannot easily grasp such frameworks as policy portfolio. The purpose of this study is to develop "Policy Attributes Taxonomy" identifying and classifying the public programs to help making decisions for allocative efficiency with effectiveness-based information. Design/methodology/approach To figure out the main scheme and classification criteria of Policy Attributes Taxonomy which represents characteristics of public policies, previous theories and researches on policy components were explored. In addition, to test taxonomic feasibility of certain information system, a set of "Feasibility Standards" was drawn from "requirements for well-organized criteria" of eminent taxonomy literatures. Finally, current government classification system in the area of social service was tested to visualize the application of Taxonomy and Standards. Findings Program Taxonomy Schemes were set including "policy goals", "policy targets", "policy tools", "logical relation" and "delivery system". Each program and project could be condensed into these attributes, making their design more easily distinguishable. Policy portfolio could be readily made out by extracting certain characteristics according to this scheme. Moreover, this taxonomy could be used for rearrangement of present "Program Budget System" or estimation of "Basic Income".

• 유통과학연구
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• 제17권4호
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• pp.27-32
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• 2019

Purpose - The business model is a method of creating corporate value, in existing "classification of business model", limitations and redundancy phenomena are applied when a new type flows in, and as consumer's purchasing decision of consumer behavior 5 steps. The classification schemes can be used for more accurate data analysis by proposing a new mapping technique in the fourth industry. Research design, data, and methodology - It was far more classified on the business model (BMS by BDS), and so on. Designing the new horizons of logistics, marketing, methodology by reclassifying these existing data to new useful data with the old methods, in order to analyze the areas where the problem has been raised for the point that the existing methods are not suitable configured. This will be applicable to the system of quaternary industry from the perspective of the buyer. Results - The mapping results of the consumer purchase decision were as follows,the 1^st stage (interest) was 23.73%, 2^nd stages (publicity) 33.90%, 3^rd stages (sales) 13.56%, 4^th stages (decision) 11.86%, 5^th stages (repurchaser) 16.95%. This verified that "the business model can be classified through "BMS by BDS". Conclusions - This structural classification is the basis of logistics marketing in the 4th industry, and proposes a innovative and effective model of constructing theory.

• 한국정보통신학회논문지
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• 제10권3호
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• pp.614-621
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• 2006

PROSPECTOR에서 사용한 규칙 형태의 분류 규칙을 습득하기 위한 유전 알고리즘 기반 귀납적 학습 환경에서 다중 분류기 학습법을 구현하였다. 다중 분류기 학습법은 주어진 사례 집합에 대해 다수의 분류기를 습득한 후 이를 이용하여 분류 시스템을 구축함으로써 시스템의 성능을 향상시키는 기법이다. 다중 분류기 학습법의 구현을 위해서는 분류기의 분류 결과를 취합하여 최종 결론을 도출해 내기 위한 기법이 필요하다. 본 논문에서는 각각의 클래스에 대해 분류기가 제공하는 사후 가능성을 취합하여 결론을 도출해 내는 기법과 순위에 기반을 둔 보우팅 기법을 소개하고 다중 분류기 학습법이 유전 알고리즘 기반 귀납적 학습 환경에 미치는 영향을 다수의 사례 집합을 이용하여 평가하였다.

• 대한원격탐사학회지
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• 제34권4호
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• pp.601-610
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• 2018

The national accuracy of global land cover (GLC) products is of great importance to ecological and environmental research. However, GLC products that are derived from different satellite sensors, with differing spatial resolutions, classification methods, and classification schemes are certain to show some discrepancies. The goal of this study is to assess the accuracy of four commonly used GLC datasets in South Korea, GLC2000, GlobCover2009, MCD12Q1, and GlobeLand30. First, we compared the area of seven classes between four GLC datasets and a reference dataset. Then, we calculated the accuracy of the four GLC datasets based on an aggregated classification scheme containing seven classes, using overall, producer's and user's accuracies, and kappa coefficient. GlobeLand30 had the highest overall accuracy (77.59%). The overall accuracies of MCD12Q1, GLC2000, and GlobCover2009 were 75.51%, 68.38%, and 57.99%, respectively. These results indicate that GlobeLand30 is the most suitable dataset to support a variety of national scientific endeavors in South Korea.