• IEIE Transactions on Smart Processing and Computing
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• v.5 no.1
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• pp.43-48
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• 2016

We propose plain fingerprint classification based on a core stochastic algorithm that effectively uses a core stochastic model, acquiring more fingerprint minutiae and direction, in order to increase matching performance. The proposed core stochastic algorithm uses core presence/absence and contains a ridge direction and distribution map. Simulations show that the fingerprint classification accuracy is improved by more than 14%, on average, compared to other algorithms.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.3
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• pp.53-72
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• 2013

For the purpose of improving the Korean Decimal Classification (KDC) in the design field, this study investigated the classification systems of design research suggested in previous studies and compared KDC, DDC, LCC, and NDC. The problems identified from the current KDC include lack of subdivisions regarding basic design theories and major design application fields and the absence of notes for explaining the scope of each design field. To solve these problems, this study suggested improvements for design theories, graphic design, industrial design, and environmental design.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.367-373
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• 2000

Natural and artificial land features are very dynamic, changing somewhat repidly in our lifetime. It is important that such changes are inventoried accurately so that the physical and human processes at work can be more fully understood. Change detection is a technique used to determine the change between two or more time periods of a particular object of study. Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution in the population of interest. The purpose of this research is to detect environmental changes surrounding an area of Mountain Moscow, Idaho using Landsat Thematic Maper (TM) images of (July 8, 1990 and July 20, 1991). For accurate classification, the Image enhancement process was performed for improving the image quality of each image. A SPOT image (Aug. 14, 1992) was used for image merging in this research. Supervised classification was performed using the maximum likelihood method. Accuracy assessments were done for each classification. Two images were compared on a pixel-by-pixel basis using the post-classification comparison method that is used for detecting the changes of the study area in this research. The 'from-to' change class information can be detected by post classification comparison using this method and we could find which class change to another.

• Journal of Soil and Groundwater Environment
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• v.15 no.6
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• pp.122-127
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• 2010

Constructing the national inventory that can be used as a tool to identify and assess existing or potential contamination is necessary for efficiently managing the soil and groundwater contamination. In order to start this construction, the first step is how we define and classify potential contamination sources of soil and groundwater. After selecting the basic classification model of contamination sources from developed countries, we suggested the classification and list of the potential contamination sources of soil and groundwater which are appropriate for specific conditions of South Korea. In addition, we investigated several databases to confirm the existence of available data sources and then examined established attribute data through chemical accident response information system (CARIS) and water information system (WIS) in National Institute of Environmental Research and mine geographic information system (MGIS) in Mine Reclamation Corporation. All sorts of attribute data in the existing databases can be utilized as significant assessment factors for determining the management priority of potential contamination sources in the future. Therefore, it is required the expanded investigation of additional database sources and the continual modification so that the classification system of potential contamination sources can be improved.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.2
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• pp.85-105
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• 2017

Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter's Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider's International Classification, Bibliothecal Bibliographic Klassification (BBK), and Broad System of Ordering (BSO). We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design.

• Journal of Korean Society on Water Environment
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• v.29 no.4
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• pp.504-513
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• 2013

Water quality trends for major tributaries (66 sites) in the Yeongsan River basin of Korea were examined for 12 parameters based on water quality data collected every month over a period of 12 months. The complex data matrix was treated with multivariate analysis such as PCA, FA and CA. PCA/FA identified four factors, which are responsible for the structure explaining 78.2% of the total variance. The first factor accounting 27.3% of the total variance was correlated with BOD, TN, TP, and TOC, and weighting values were allowed to these parameters for grade classification. CA rendered a dendrogram, where monitoring sites were grouped into 5 clusters. Cluster 2 corresponds to high pollution from domestic wastewater, wastewater treatment and run-off from livestock farms. For grade classification of tributaries, scores to 10 indexes were calculated considering the weighting values to 3 parameters as BOD, TN and TP which were categorized as the first factor after FA. The highest-polluted group included 10 tributaries such as Gwangjucheon, Jangsucheon, Daejeoncheon, Gamjungcheon, Yeongsancheon. The results indicate that grade classification method suggested in this study is useful in reliable classification of tributaries in the study area.

• Journal of Environmental Science International
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• v.12 no.12
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• pp.1215-1225
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• 2003

The purpose of this research was to investigate the characteristics of urban ecotopes and to classify ecotopes systematically from them. Total of 15 characteristics for classification of ecotopes were selected, and there were categorized 3 factors, that is abiotic, biotic and anthropological factors. The ecotope types in the study area were classified into 67. The classification of ecotope was made with SPSS for Windows Version 10.0 on the basis of the 15 characteristics. As the results of cluster analysis using the average linkage method between groups, groups of ecotope type were divided into 15 clusters. It was known that there was not a great difference in an affinity as the result of overlapping the maps of ecotope type and land use type. This research suggested characteristics for classification of ecotopes, but there was a limit to Set the objective method for grade classification because of lacking in the basic data, the research of characteristics will be accomplished continuously.

• Journal of the Korea Convergence Society
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• v.5 no.1
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• pp.35-41
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• 2014

An automatic speech recognition system is one of the popular research problems. There are many research groups working in this field for different language including Japanese. Japanese vowel recognition is one of important parts in the Japanese speech recognition system. The vowel classification system with the Mamdani fuzzy inference system was developed in this research. We tested our system on the blind test data set collected from one male native Japanese speaker and four male non-native Japanese speakers. All subjects in the blind test data set were not the same subjects in the training data set. We found out that the classification rate from the training data set is 95.0 %. In the speaker-independent experiments, the classification rate from the native speaker is around 70.0 %, whereas that from the non-native speakers is around 80.5 %.

• Journal of the Korean Institute of Rural Architecture
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• v.1 no.3
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• pp.3-12
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• 1999

This research studies into the plane type classification and reviews its transition which has been used in the basic research of the traditional houses on the korean peninsula. The conclusions are as follows. Until now, plane type classification of traditional houses on the Korean peninsula were used to explain the characteristics of the region, or social class of the time. This classification was not used as a research tool to discover the hidden principals of the development process of traditional houses nor to attempt to restore the traditional habitation culture of the Korean peninsula.

• ETRI Journal
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• v.35 no.6
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• pp.1105-1114
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• 2013

Owing to the large number of video programs available, a method for accessing preferred videos efficiently through personalized video summaries and clips is needed. The automatic recognition of user states when viewing a video is essential for extracting meaningful video segments. Although there have been many studies on emotion recognition using various user responses, electroencephalogram (EEG)-based research on preference recognition of videos is at its very early stages. This paper proposes classification models based on linear and nonlinear classifiers using EEG features of band power (BP) values and asymmetry scores for four preference classes. As a result, the quadratic-discriminant-analysis-based model using BP features achieves a classification accuracy of 97.39% (${\pm}0.73%$), and the models based on the other nonlinear classifiers using the BP features achieve an accuracy of over 96%, which is superior to that of previous work only for binary preference classification. The result proves that the proposed approach is sufficient for employment in personalized video segmentation with high accuracy and classification power.