• Fire Protection Technology
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• s.15
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• pp.22-27
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• 1993

The classification of hazardous area is a method of analysing and classifying the environment where explosive gas or vapour atmosphere may be expected to be present. The object of area classification is to enable the proper selection and installation of electical apparatus and other equipments. This report is intended to serve a general reference about the classification procedure of hazardous area with explanations of related Korean Standard.

• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.2
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• pp.209-214
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• 2002

At this paper, I classified ‘tetanus’ in 『DongEuiBoGam』 and studied the concept, causes, symptoms, pathological mechanisms of that disease and then I had a new understanding that concept of tetanus in 『DongEuiBoGam』 is different with concept of tetanus in Western Medicine. In the mean time, I investigated the classification in 「Classification of Korean Standard Cause of Death(Oriental Medicine)」 (1995, The Korean Economic Planning Board), and concluded the concept of tetanus in "DongEuiBoGam".

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2846-2848
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• 2005

This paper proposes a pattern classification algorithm for the defect distribution of Hard Disk Drive (HDD). In the HDD productions, the defect pattern of defective HDD set is important information to diagnosis of defective HDD set. In this paper, 5 characteristics are determined for the classification to six standard defect pattern classes. A fuzzy inference system is proposed, the inputs of which are 5 characteristic values and the outputs are the possibilities that the input pattern is classified to the standard patterns. Classification result is the pattern with maximum possibility. The proposed algorithm is implemented with a PC system for defective HDD sets and shows its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.15-26
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• 2013

This paper proposes a classification method of parallel, vertical parking states and pillars for parking assist system using ultrasonic sensors. Since, in general parking space detection module, the compressed amplitude of ultrasonic data are received, the analysis of them is difficult. To solve these problems, in preprocessing state, symmetric transform and noise removal are performed. In feature extraction process, four features, standard deviation of distance, reconstructed peak, standard deviation of reconstructed signal and sum of width, are proposed. Gaussian fitting model is used to reconstruct saturated peak signal and discriminability of each feature is measured. To find the best combination among these features, multi-class SVM and subset generator are used for more accurate and robust classification. The proposed method shows 92 % classification rate and proves the applicability to parking space detection modules.

• Proceedings of the KSRS Conference
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• v.2
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• pp.525-528
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• 2006

The remote sensing data can be used to calculate the water depth especially in the clear and shallow water area. In this study, the SPOT data was used for bathymetric mapping in Dong-Sha atoll, located in northern South China Sea. The in situ sea depth was collected by echo sounder as well. A global positioning system was employed to locate the accurate sampling points for sea depth. An empirical model between measurement sea depth and band digital count was determined and based on least squares regression analysis. Both non-classification and unsupervised classification were used in this study. The results show that the standard error is less than 0.9m for non-classification. Besides, the 10% error related to the measurement water depth can be satisfied for more than 85% in situ data points. Otherwise, the 10% relative error can reach more than 97%, 69%, and 51% data points at class 4, 5, and 6 respectively if supervised classification is applied. Meanwhile, we also find that the unsupervised classification can get more accuracy to estimate water depth with standard error less than 0.63, 0.93, and 0.68m at class 4, 5, and 6 respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.253-265
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• 2016

We propose an obstacle classification method using multi-decision factors and decision sections based on Single 2D LiDAR. The existing obstacle classification method based on single 2D LiDAR has two specific advantages: accuracy and decreased calculation time. However, it was difficult to classify obstacle type, and therefore accurate path planning was not possible. To overcome this problem, a method of classifying obstacle type based on width data was proposed. However, width data was not sufficient to enable accurate obstacle classification. The proposed algorithm of this paper involves the comparison between decision factor and decision section to classify obstacle type. Decision factor and decision section was determined using width, standard deviation of distance, average normalized intensity, and standard deviation of normalized intensity data. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 2D LiDAR-based method, thus demonstrating the possibility of obstacle type classification using single 2D LiDAR.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.977-985
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• 2013

Many situations are classified into more than two categories in real world. In this work, we consider ROC surface and VUS, which are graphical representation methods for classification models with three categories. The standard criteria of AUC for the probability of default based on Basel II is extended to the VUS for ROC surface; therefore, the standardized criteria of VUS for the classification model is proposed. The ranges of AUC, K-S and mean difference statistics corresponding to VUS values for each class of the standard criteria are obtained. The standard criteria of VUS for ROC surface can be established by exploring the relationships of these statistics.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.241-243
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• 2006

To supply the materials the right time, and the right place, it is required some information maintenance system to manage this procedure effectively. In this paper, we represent the standard products classification for EMU and the materials maintenance information system to manage the parts used EMU maintenance efficiently. The standard material classification is matched to G2B code made by the Supply Administration. The implemented material information system can perform various functions such as the inquiry of the number of stocks, the demand of the materials, and etc.

• Journal of the Korean Society for information Management
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• v.18 no.3
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• pp.285-309
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• 2001

The industry information grows faster than any other information resources in the Internet age. Unfortunately, however, there is no consensus on the standard of the classification among the information providers of the industry fields. This may a problematic issue not only in building a continuous and systematic development of the industry information, but also in the use of the information among the users. This study aims to propose a well-structured and/or an efficient classification scheme for the industry information to help the users with easy to retrieve the Internet resources. To do this, we analyzed the subject classification scheme of the domestic industry information on the web sites, which is largely adopted the \"Korean Standard for the Industry Classification\". In addition, we suggested the principle of the subject classification and their hierarchial structure derived from the analysis of the knowledge and document classification scheme. As a result, it was suggested an optimized industry classification scheme based on the analysis of the validity test of classification item measured by the quantitative analysis of the industry information, which it currently accessible through the Internet. Internet.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.225-233
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• 2012

A comprehensive research effort in order to develop and disseminate modernized Korean housing (Hanok) has recently been initiated by Korean government. This large scale research project encompasses a wide spectrum of housing development including public policy, architectural plans, modules, construction materials and methods, prefabricated assemblies, automated production, construction management, and advanced information systems. For the purpose of integrating and automating the whole processes from an industry perspective, it is of great importance to develop a standard classification system and project numbering system (PNS) for the modernized Korean housing. This paper focuses on the standard classification systems and PNS for cost and schedule control. The distinct characteristics and managerial requirements were explored and embedded into the proposed classifications for modernized Hanok.