• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.515-522
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• 2015

Through the correspondence works with IEC in the smart grid fields and power IT fields, we set up the interpretation work procedure and defined the work rule for correspondence by analyzing the work results. In addition, we suggest cases for discussion of terms and definitions in the IEC and analyze them and then propose a matrix classification system for standardization to solve the cases for discussion. The matrix classification system with 3-axes of classification has been applied to newly emerging terminologies followed by smart gird. We drew the usefulness in search of terms in application fields and showed the cases of applying the matrix classification. The IEC Electropedia classification standard is unclear and the classification is mixed with principle, application and product areas. We proposed a new working group in IEC TC1 for research on the matrix classification system and then TC 1 decided to organize a new WG titled in the "IEV structure and supporting tools".

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.157-168
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• 2009

Geospatial information, which deeply has an effect on our life, have been evolved as intelligent geospatial information in Ubiquitous era. Also, Various services are introduced using the intelligent geospatial information. However, there is no classification system, for understanding the intelligent geospatial information services, considering any developers and users. It needs to be classification system to classify these services. In this paper, we introduced a concept of intelligent geospatial information and developed a service classification matrix regarding to the features of the services. This service classification matrix has three scales; service domain, service intelligent level, and geo-location accuracy. The propose of this matrix can be utilized in two aspects. First, the matrix can improve the reality that doesn't reflect actual demands for the services. Second, the matrix can present the goal of the new services or the development direction. The matrix can be utilized to the geospatial industry as creating the new blue ocean services. However, the service classification matrix needs to modify and complement to have no anything wrong when the various services are applied to the matrix. In the long run, the matrix has to be utilized as a material to make out a service roadmap or TRM(Technical Reference Model).

• Journal of Korean Library and Information Science Society
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• v.32 no.4
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• pp.99-117
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• 2001

This paper reports on the development of an automatic book classification system using the faced classification principles of CC(Colon Classification). To conduct this study, some 670 words in the botanical field were selected, analyzed in terms [P], [M], [E], [S], [T] employed in CC 7, and included in a database for classification. The principle of an automatic classification system is to create classification numbers automatically through automatic subject recognition and processing of key words in titles through the facet combination method of CC. Particularly, a classification database was designed along with a matrix-principle specifying the subject field for each word, which can allow automatic subject recognition possible.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.360-362
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• 2008

Based on classification systems of power and IT standard dictionaries, scientific and technological standard, SPARK, power IT fields of IEC and organization units of corporations, we propose a new classification system for the standardization of power of terminologies. The classification system consists of a hierarchical structure with general classification, application fields and specific technologies while keeping the conventional matrix-type classification system. Interpretation work of the power of terminologies confirms that the proposed classification system is efficient.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.277-284
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• 2010

As technology is developed, the quantity of new vocabularies is increasing more rapidly. So many vocabularies of technology have various meanings for each part and are used diversely according to circumstances. Therefore, the necessity of reasonable methods of standardization and purification is increasing and it is necessary to establish a classification system of terminology for the first phase of the standardization. Firstly, based on classification systems of power and IT standard dictionaries, scientific and technological standard, SPARK, power IT fields of IEC and organization units of corporations, we propose a new classification system for the standardization of power IT terminologies. The classification system consists of a hierarchical structure with general classification, application fields and specific technologies while keeping the conventional matrix-type classification system. And interpretation methods of power IT terminologies, which are classified according to the new classification system for the standardization of power IT terminologies, is proposed. The interpretation works of the power IT terminologies confirm that the classification system is systematic and the interpretation process is efficient.

• Journal for History of Mathematics
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• v.18 no.1
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• pp.103-110
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• 2005

This paper is aimed at studying a historical background of graph theory and we deal with the computer representation of graph through a simple example. Graph is represented by adjacency matrix, edge table, adjacency lists and we study the matrix representation by Euler circuit. The effect of the matrix representation by Euler circuit economize the storage capacity of computer. The economy of a storage capacity has meaning on a mobile system.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.1-9
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• 2019

Various probabilistic methods have been proposed for using interpopulation allele frequency differences to infer the ethnic group of a DNA specimen. The selection of the statistical method is critical because the accuracy of the statistical classification results vary. For the ancestry classification, we proposed a new ancestry evaluation method that estimate the combined ethnicity index as well as compared its performance with various classical classification methods using two real data sets. We selected 13 SNPs that are useful for the inference of ethnic origin. These single nucleotide polymorphisms (SNPs) were analyzed by restriction fragment mass polymorphism assay and followed by classification among ethnic groups. We genotyped 400 individuals from four ethnic groups (100 African-American, 100 Caucasian, 100 Korean, and 100 Mexican-American) for 13 SNPs and allele frequencies that differed among the four ethnic groups. Additionally, we applied our new method to HapMap SNP genotypes for 1,011 samples from 4 populations (African, European, East Asian, and Central-South Asian). Our proposed method yielded the highest accuracy among statistical classification methods. Our ethnic group classification system based on the analysis of ancestry informative SNP markers can provide a useful statistical tool to identify ethnic groups.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.177-181
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• 1996

Systematic classification system for standardization in telecommunication is essential to the standardization R&D strategy. This paper suggests a new reference model for development of work area and classification scheme related to the telecommunications standardization : Cubic and matrix approach. Standardization Work Areas(SWAs) that are upper level of the reference model are classified by its main role and function reflecting the market trends and user needs. Standardization expertise is lower level scheme, which can be regarded as the different possible layers of standardization to be applied to each one of the SWAs grouped under upper level scheme. A new reference model consists of two planes that are SWAs plane and Standardization layer plane. Finally the reference model for classification of SWAs in telecommunication mapping onto matrix table that row and column are defined by SWAs and standardization layer respectively.

• Tunnel and Underground Space
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• v.18 no.6
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• pp.408-417
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• 2008

Rock mass classification methods such as RMR and Q system have different characteristics each other in parameters considered and applications, and so it is very important to prescribe the relationship between parameters for the analysis of correlativity of these methods. With the Held data of RMR and Q estimation in road construction sites, the acquaintance relations between RMR and Q of rock mass classifications are analyzed. The correlation equations between parameters of RMR and Q, matrix of correlation coefficients and the generalized form of acquaintance relation matrix are derived. This acquaintance relation matrix can be further extended to the form of generalized acquaintance relation network, and could be used to analyze the correlativity and to enhance the utility of common rock mass classification methods.

• ETRI Journal
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• v.39 no.6
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• pp.841-850
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• 2017

We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.