• Journal of the Korean Society for Library and Information Science
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• v.42 no.1
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• pp.335-358
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• 2008

According to Wayne A. Wiegand in the 1998, he research to The "Amherst Method": The Origins of the Dewey Decimal Classification Scheme. Although a debate about the origins of the Dewey Decimal Classification Scheme has been going on for generations, historical consensus remains elusive. This paper contributes information to the historiography on the origins of the scheme: 1) by grounding an account of Dewey's thinking as he was crafting the DDC on an analysis of a large body of sources than previous classification historians have consulted; and 2) by expanding and deepening historical understanding of the contextual forces influencing on the classification structure. Because the DDC idea as it first occurred to M. Dewey in Amherst in 1872-73 is an important in the history of library development in the world. He outlined the first draft of his decimal scheme and submitted it to the Amherst College Library Committee on 8 May 1873. This paper analysis to "Three Genetic Paper", that is 1) The Merits of the System, 2) Library Classification System, 3) Its Special Adaption to our Library.

• Journal of Korean Library and Information Science Society
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• v.42 no.3
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• pp.5-24
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• 2011

The purpose of this study aims to provide possible suggestions for the improvement KDC 5th ed. as a system. After analyzing and evaluating time & space devices of KDC 5th ed.(including DDC 22th ed. and NDC 9th ed.). such as main schedules, common auxiliary tables, internal tables and notes, suggestions for the improvement were proposed. If above suggestions are adopted, effective literature classification scheme which is suited to domestic circumstances will be certainly prepared.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.189-214
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• 2008

Objective of this research is to point out problems of geographic division structure in current Korean Decimal Classification System and provide solutions. For this purpose key classification methods were divided to decimal and non-decimal classification methods and analyzed for geographical division principles. In addition, national institutes regional division standards from Korea, USA and Japan were researched. Through these analysis, we provided suggestions to improve the table of geographical division in KDC4 including public institutions administrative district classification structure relations and consistency, and other regional divisional standards (proposal) instead of typical administrative district reflecting various geographical conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.2
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• pp.163-172
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• 2001

This study present the quadratic programming as the classification method of remote sensed data applying to the extraction of landcover and examine it's applicable capability by comparing the classification accuracy of quadratic programming with that of neural network and maximum likelihood method which are used in the extraction of thematic layer. As the results, as drawing the more improved classification results by 6% than maximum likelihood method, we could discern that the method of quadratic programming is appliable to classifying the remote sensed data. Also, in the classification of quadratic programming method, we could definitely indicate the results which was ignored in the previous extreme(binary) classification method by affecting the class decision with the class composition proportion.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.108-115
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• 2001

In this paper we are attempted to quantitative classification of the three object color regions on a RGB image using of an improved ML(Maximum Likelihood) classification method. A RGB color image consists of three bands i.e., red, green and blue. Therefore it has a 3 dimensional structure in view of the spectral and spatial elements. The 3D structural yokels were projected in RGB cube wherefrom the ML method applied. Between the conventionally and easily usable Box classification and the statistical ML classification based on Bayesian decision theory, we compared and reviewed. Using the ML method we obtained a good segmentation result to classify positive cell nucleus, negative cell Nucleus and background un a immuno-histological breast carcinoma image. Hopefully it is available to diagnosis and prognosis for cancer patients.

• Journal of Korean Library and Information Science Society
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• v.34 no.1
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• pp.43-65
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• 2003

Libraries have long experience of applying classification schemes to resources - chiefly books. The ultimate goals of classification are systematic shelving of books and ease of user's access. In order to achieve these goals, books about a particular field of knowledge should be shelved together and near each other. If not so, it is classification error. The focus of this study is, therefore, on analysing the classification error in Korea public libraries and suggesting some alternatives.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.11a
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• pp.247-251
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• 2008

GHS는 위험물 분류와 운송부문에 관하여 물리 화학적 위험성과 급성독성의 분류와 표시사항을 기본으로 하여 기존의 UN시험방법과 큰 차이가 없으나 국내 기준인 위험물안전관리법의 위험물 판정 시험방법 및 분류체계와 달라 검토가 필요하다. 본 연구에서는 위험물안전관리법에 의해 분류된 제2류 가연성고체 물질과 제3류 자연발화성 물질 및 금수성물질을 대상으로 각각의 위험물 판정시험을 실행하였다. 시험 결과 GHS를 국내 실정에 맞게 적용하기 위해서는 각각의 판정 시험 결과를 통해 정확한 데이터를 확보하고 이를 통해 위험물안전관리법의 분류기준과 GHS에 따른 대응 분류기준을 제시함으로써 국제무역시 제도간의 규제 및 표지의 상이함을 통해 나타나는 문제점들을 예방할 수 있을 것이다.

• Journal of Gastric Cancer
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• v.9 no.4
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• pp.159-166
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• 2009

Purpose: We evaluated the efficacy and prognostic predictability of the $7^{th}$ UICC TNM classification compared to $6^{th}$ UICC TNM classification in patients with gastric cancer. Materials and Methods: Between June 1992 and December 2006, 1,633 patients with gastric cancer who had undergone gastric surgery and who had been analyzed by the $6^{th}$ UICC method were analyzed using the new $7^{th}$ UICC system. Results: Significant differences in 5-year survival rates were observed for $7^{th}$ UICC N0, N1, N2, N3a, and N3b compared to $6^{th}$ UICC. There were no significant differences in 5-year survival rates between T2 and T3. Distinct survival differences were present between stage III (IIIa, IIIb, and IIIc) and stage IV in $7^{th}$ UICC. Significant differences in 5-year survival rates were not expected for Ia versus Ib, Ib versus IIa, and IIb versus IIIa. The survival rates for the same stages were not homogeneously differentiated by $7^{th}$ UICC except for stage IV. Conclusion: The $7^{th}$ UICC classification system is not better able to predict patient survival compared to 6th UICC in patients with gastric cancer, but is better for accurate prognosis of patients with stage IV gastric cancer.

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.63-81
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• 2017

This study investigated general problems concerning the social welfare field in the KDC 6th edition based comparative analysis academic characteristics and classification system, and suggested on some ideas for the improvements of them. Results of the study are summarized as follows. First, a main field of the social welfare is generally divided into a general social welfare, social works, and social welfare services to special classes and groups including people with disabilities, young people, aged, women, and families. Second, I analyzed on social welfare from the collection database at the National Library of Korea. Based on analysis of the data. the keyword frequency of social welfare policy and management, pensions, care services, and support works for the underprivileged was relatively high. Third, modified classification of items was basically performed through the academic characteristics of the social welfare and the keyword analysis, and maintaining the existing KDC classification system caused less confusion as much as possible.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.931-940
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• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.