• Imaging Science in Dentistry
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• v.45 no.2
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• pp.123-131
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• 2015

Throughout the years, various classifications have evolved for the diagnosis of vascular anomalies. However, it remains difficult to classify a number of such lesions. Because all hemangiomas were previously considered to involute, if a lesion with imaging and clinical characteristics of hemangioma does not involute, then there is no subclass in which to classify such a lesion, as reported in one of our cases. The recent classification proposed by the International Society for the Study of Vascular Anomalies (ISSVA, 2014) has solved this problem by including non-involuting and partially involuting hemangioma in the classification. We present here five cases of vascular anomalies and discuss their diagnosis in accordance with the ISSVA (2014) classification. A non-involuting lesion should not always be diagnosed as a vascular malformation. A non-involuting lesion can be either a hemangioma or a vascular malformation depending upon its clinicopathologic and imaging characteristics.

• Journal of Korean Library and Information Science Society
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• v.44 no.2
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• pp.399-422
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• 2013

This study suggests some ideas for improvement of mixing classification and illogical subdivisions arrangement of Statistics in Social Science and Mathematical Statistics in Natural Science on KDC. We investigate the characteristics, educational system, and curriculum of Statistics in Korea. Besides, we compare and analyze classification systems such as KDC, DDC, LCC, NDC and Research Fields Code by National Research Foundation of Korea. As a result, Statistics in Social Science is relocated and integrated with the subfield of Natural Science according to the academic background. Existing social statistics topics are subdivided into statistical research methods complementing social science research methods. The heading 'Probabilities, Statistical mathematics' in Natural Science is changed to 'Statistics', and the subdivisions are expanded and revised.

• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.191-197
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• 2003

Accurate detection and classification of faults on transmission lines is vitally important. In this respect, many different types of faults occur, such as inter alia low impedance faults (LIF) and high impedance faults (HIF). The latter in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if undetected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. Because of the randomness and asymmetric characteristics of HIFs, their modeling is difficult and numerous papers relating to various HIF models have been published. In this paper, the model of HIFs in transmission lines is accomplished using the characteristics of a ZnO arrester, which is then implemented within the overall transmission system model based on the electromagnetic transients program (EMTP). This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System (ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square (RMS) values of 3-phase currents and zero sequence current. The performance of the proposed algorithm is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results demonstrate that the ANFIS can detect and classify faults including LIFs and HIFs accurately within half a cycle.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.1-6
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• 2020

In this paper, a method for improving the defect classification performance in steel plate surface has been studied, based on DWT(discrete wavelet transform) and SVM(support vector machine). Surface images of the steel plate have low contrast, uneven, and featureless, so that the contrast between defect and defect-free regions is not discriminated. These characteristics make it difficult to extract the feature of the surface defect image. In order to improve the characteristics of these images, a synthetic images based on discrete wavelet transform are modeled. Using the synthetic images, edge-based features are extracted and also geometrical features are computed. SVM was configured in order to classify defect images using extracted features. As results of the experiment, the support vector machine based classifier showed good classification performance of 94.3%. The proposed classifier is expected to contribute to the key element of inspection process in smart factory.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.1
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• pp.93-114
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• 2016

As a means of improving Korean Soil Classification System, we have reviewed Australian Soil Classification System by comparing Soil Taxonomy and FAO/WRB Classification System. Australian Soil Classification System is composed of 14 of Order, 87 of Sub-order, 556 of Great-group, 2,451 of Sub-group, and 7,276 of Family. Interestingly, soil order has the Anthroposols which is not classified with Soil Taxonomy, and the classification for some of soils is based on soil texture abruption horizon and soil structure. Seven of 14 soil orders are classified with an old version based on soil color rather than morphological characteristics. The distribution scale of Australian soil order is the largest in Tenosols, and followed by Kandosols, Rudosols, Sodosols and Vertisols in Australia.

• Journal of Korean Library and Information Science Society
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• v.38 no.2
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• pp.315-335
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• 2007

This study suggests basic principals and requirements for future development of children's library classification scheme Until now there is no standardized children's library classification system, thereby librarians as well as library users have to go through many troubles. Therefore this study researched current conditions of children's libraries In Korea and analyzed the types and characteristics of children's books. This study reviewed children's book classification systems and how these systems are being used in three different library system: public and Inpyo Children's Library, Miracle Library, and private children's libraries. This study conducted in-depth research on two notable children's book classification systems of Neutinamu Children's Library and Parangsae Children's Library. This study suggests basic principals and requirements for children's library classification scheme, based on researches described above.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.271-281
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• 2013

This paper considers a problem of classification of variable stars based on functional data analysis. For a better understanding of galaxy structure and stellar evolution, various approaches for classification of variable stars have been studied. Several features that explain the characteristics of variable stars (such as color index, amplitude, period, and Fourier coefficients) were usually used to classify variable stars. Excluding other factors but focusing only on the curve shapes of variable stars, Deb and Singh (2009) proposed a classification procedure using multivariate principal component analysis. However, this approach is limited to accommodate some features of the light curve data that are unequally spaced in the phase domain and have some functional properties. In this paper, we propose a light curve estimation method that is suitable for functional data analysis, and provide a classification procedure for variable stars that combined the features of a light curve with existing functional data analysis methods. To evaluate its practical applicability, we apply the proposed classification procedure to the data sets of variable stars from the project STellar Astrophysics and Research on Exoplanets (STARE).

• Journal of the Korean housing association
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• v.24 no.1
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• pp.11-20
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• 2013

The purpose of the study was to develop a classification of management for the qualitative improvement of the management of multi-family housing. The date were analyzed using the Excel program in terms of frequency and, criticality analysis in order to draw items stage by stage. The process of research was as follows: The first process drew classification of types using the content analysis of the documented studies. The second process examined subcategories according to classification of types via interviews of supervisors. Further, the criticality analysis between the two items was examined. Additionally, when this study surveys and analyzes the satisfactions and importance of management on the basis of the classification, it can have an effect on management by reflecting the result. In conclusion, the classification of the management of multi-family housing will make up the improvement scheme of supplement education, certification related management and management regulations on the characteristics of multi-family housing by types of houses in the future.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1584-1595
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• 2017

Each cultural community has developed a variety of fonts to express their own language and characters. Hangul has also diversified its font shapes through changing the composition ratio and look of the consonants and vowels. Rather, thanks to the variety of these fonts, a considerable amount of time and effort must be devoted to the selection of a specific font shape. This is related to the fact that the current Hangul service and classification system process the font only with its name or the name of the manufacturer. It means that there is no consensus about the font shape classification system for Hangul. In this study, we propose a shape property set that can be a basis for classifying Hangul fonts. The font shape property set was generated by performing statistical analysis with features which have been studied by the font design experts and was verified through questionnaire using representative fonts based on the classification scheme defined by the Hangul font design classification system standard. This study is meaningful in that it is a study on shape classification properties of K-means and PCA statistical techniques based on font data rather than design field study.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1409-1411
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• 2003

The application of simulated KOMPSAT-2 imagery to monitor graveyards is to be developed. Positions calculated from image were compared with those obtained from Geographic Positioning System. With 24 checkpoints, the position of graveyards showed within 5-meter range. Unsupervised classification, supervised classification, and objected-orientation classification algorithms were used to extract the graveyard. Unsupervised classification with masking processes based on National topographic data gives the best result. The graveyards were categorized with four types in field studies while the two types of graveyards were shown in descriptive statistics. Cluster Analysis and discriminant analysis showed the consistency with two types of tombs. It was hard to get a specific spectral signature of graveyards, as they are covered with grasses at different levels and shaded from the surrounding trees. The slopes and aspects of location of graveyards did not make any difference in the spectral signatures. This study gives the basic spectral characteristics for further development of objected-oriented classification algorithms and plausibility of KOMPSAT-2 images for management of mountainous areas in the aspect of position accuracy and classification accuracy.