• Speech Sciences
• /
• 제14권1호
• /
• pp.151-162
• /
• 2007

This study focuses on the classification of pathological voice using GMM (Gaussian Mixture Model) and compares the results to the previous work which was done by ANN (Artificial Neural Network). Speech data from normal people and patients were collected, then diagnosed and classified into two different categories. Six characteristic parameters (Jitter, Shimmer, NHR, SPI, APQ and RAP) were chosen. Then the classification method based on the artificial neural network and Gaussian mixture method was employed to discriminate the data into normal and pathological speech. The GMM method attained 98.4% average correct classification rate with training data and 95.2% average correct classification rate with test data. The different mixture number (3 to 15) of GMM was used in order to obtain an optimal condition for classification. We also compared the average classification rate based on GMM, ANN and HMM. The proper number of mixtures on Gaussian model needs to be investigated in our future work.

• Journal of the Ergonomics Society of Korea
• /
• 제23권3호
• /
• pp.13-24
• /
• 2004

Anthropometric data is a fundamental resource in developing ergonomic products and workplaces. However, designers often experience difficulty in searching anthropometric data relevant to the design due to the technicality of anthropometric terminologies, ambiguity in the description of measurement method for some anthropometric variables, and inefficiency of existing search methods for anthropometric data. The present study suggests a method to develop a classification system of anthropometric variables for systematic, efficient search of anthropometric data. The proposed method first classifies anthropometric variables according to body segment and type of variable, and then arranges anthropometric variables of the same body segment and variable type by comparing the heights of their reference points. The proposed classification method was applied to establish a classification system of 66 anthropometric variables that were selected for an automotive interior design. Then the established anthropometric classification system was utilized to design a search interface of a web-based anthropometric data retrieval system.

• Proceedings of the KSRS Conference
• /
• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.48-53
• /
• 1999

The paper presents an automated method for generating fuzzy rules and fuzzy membership functions for pattern classification from training sets of examples and an application to the land-cover classification. Initially, fuzzy subspaces are created from the partitions formed by the minimum and maximum of individual feature values of each class. The initial membership functions are determined according to the generated fuzzy partitions. The fuzzy subspaces are further iteratively partitioned if the user-specified classification performance has not been archived on the training set. Our classifier was trained and tested on patterns consisting of the DN of each band, (XS1, XS2, XS3), extracted from KITSAT-3 multispectral scene. The result represents that our classification method has higher generalization power.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• 제58권7호
• /
• pp.1424-1434
• /
• 2009

DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.

• Journal of Korea Multimedia Society
• /
• 제18권11호
• /
• pp.1261-1267
• /
• 2015

The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.

• Journal of Korea Multimedia Society
• /
• 제20권3호
• /
• pp.571-580
• /
• 2017

Recently, there are many communication softwares based on text on various smart devices. Unlike traditional print publishing, mobile publishing and SNS tools tends to utilize more decorative or more emotional fonts so that users can pass some feelings from contents. So font providers have released new fonts which deal with the requirements of the market. Nevertheless being released lots of new fonts, general users have not used them because they searched only by font name or font provider's name. It means that there is no way for users to know and find new things. In this study, we suggest font shape classification rules for font registration system based on font design features. We proved the validity of classification standard study through some experiments with 50 commercial fonts. Also the result of this study was provided for Korea Telecommunication Technology Association and adopted by the Korea industrial standard.

• Journal of Korean Library and Information Science Society
• /
• 제21권
• /
• pp.195-229
• /
• 1994

This article investigates the normative principles suggested by Rangannathan as the guiding principles for his theories, consisting of basic laws, fundamental laws, canons, principles and postulates. His five basic laws and five laws of library science are re-interpreted from the view point of library classification. And three planes of idea plane, verbal plane and notational plane, one of the core ideas in his analytico-synthetic theory of library classification, are analyzed. This article also suggests the demonstration model for this three planes using the ideas from chemistry ad chemical equation. In the last part, it analyzes the canons for library classification of three planes. These normative principles are basically guiding principles for so-called analytico-synthetic or faceted classification. But they can be a n.0, pplied to most of modern classification. But they can be a n.0, pplied to most of modern classification schemes, especially to semi-enumerative schemes including DDC, KDC, etc. so that they can improve the schemes. From this regard, these principles can also be helpful to the KDC, on the verge of the revision of its fourth edition.

• International Journal of Safety
• /
• 제1권1호
• /
• pp.28-35
• /
• 2002

Kullback Discrimination Information (KDI) is one of the pattern recognition methods. KDI defined as a measure of the mutual dissimilarity computed between two time series was studied for detection and classification of bearing flaking on outer-race and inner-races. To model the damages, the bearings in normal condition, outer-race flaking condition and inner-races flaking condition were provided. The vibration sensor was attached by the bearing housing. This produced the total 25 pieces of data each condition, and we chose the standard data and measure of distance between standard and tested data. It is difficult to detect the flaking because similar pulses come out when balls pass the defection point. The detection and classification method for inner and outer races are defected by KDI and nearest neighbor classification rule is proposed and its high performance is also shown.

• Journal of the Korean Society for information Management
• /
• 제15권3호
• /
• pp.45-71
• /
• 1998

There is increasing importance of a system to reorganize explosive expansion of internet information resources efficiently; therefore, an increasing concern about classification system as an instrument for facilitating an access to a specific subject and improving efficiency in information retrieval. Comparing the hierarchical structure and access methodology of internet-based classification system with those of library classification such as Dewey Decimal Classification through their structural aspects and retrival process, this paper proposes the proper classification system in internet environment.

• International Journal of Contents
• /
• 제13권2호
• /
• pp.66-74
• /
• 2017

Patent classification is becoming more critical as patent filings have been increasing over the years. Despite comprehensive studies in the area, there remain several issues in classifying patents on IPC hierarchical levels. Not only structural complexity but also shortage of patents in the lower level of the hierarchy causes the decline in classification performance. Therefore, we propose a new method of classification based on different criteria that are categories defined by the domain's experts mentioned in trend analysis reports, i.e. Patent Landscape Report (PLR). Several experiments were conducted with the purpose of identifying type of features and weighting methods that lead to the best classification performance using Support Vector Machine (SVM). Two types of features (noun and noun phrases) and five different weighting schemes (TF-idf, TF-rf, TF-icf, TF-icf-based, and TF-idcef-based) were experimented on.