• 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.

• The Korean Journal of Archival Studies
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• no.53
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• pp.229-259
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• 2017

The purpose of this study is to find out the level of the classification system of the government-funded research institutes and to search the future direction of the classification scheme of these research institutes. As a result of analyzing the classification system and regulations of the 23 government-funded research institutes, it is found that the regulations of the records management of most institutions are basically based on other regulations before Public Records Act. In addition, there are not many institutions in which the record production system that reflects the Public Records Act is introduced, and the production and classification of the records are performed separately, and the classification scheme in which the organization classification and the functional classification are mixed is often used only as a reference tool for setting retention period. To overcome this situation, it is necessary to improve the regulation, classification scheme and system. The revision of the law at the national level and establishment of records management regulations at the institutional level should be made. A special classification scheme for 'research' which is a core function of the research institute should be designed and this classification scheme must be applied from the registration stage of records. The fact that the record management obligation is ignored and the production records are not properly managed is to deny the value of the research field records by themselves. I hope that the records management of government-funded research institutes will be moved in place as soon as possible and practical issues will be communicated to academia and good ideas for better development will be returned to the field of practice.

• Ecology and Resilient Infrastructure
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• v.7 no.3
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• pp.199-207
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• 2020

Against the backdrop of frequent weather disasters such as floods, droughts, and heat waves worldwide, urban parks should provide functions for the safety of urban residents as well as rest, culture, and ecological functions. In this study, a classification system for urban disaster prevention parks is proposed for the safety of the urbanites with the aim of securing a complex function in a green space in response to climate changes in the city. Analytical indicators were extracted through literature research, and the classification system was verified through on-site surveys of the target sites and interviews with those involved. The large class for evaluation was divided into three types: location, spatial composition, and disaster prevention complex facilities of urban parks; the direction of improvement was proposed for problems identified through empirical analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.32-38
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• 2018

Studies on classification of national roads have been continued, but there is little research on the classification of urban arterial roads. Due to the increase of traffic volume, urban arterial roads do not perform well as main roads. In this paper, the function of urban arterial road was established by using cluster analysis using traffic characteristics. Traffic characteristics such as traffic volume, weekend coefficient and speed coefficient were used to establish the functions of 55 main arterial roads in Seoul. The results of this paper are compared with those of the method using AADT. The method using AADT classifies the characteristics according to the traffic volume of the whole lane. In this paper, however, the results are derived using the traffic volume per lane reflecting the actual traffic volume. In addition, the functional classification of the arterial roads in Seoul was compared with the results of this paper to verify that the traffic characteristics were reflected. As a result, the method presented in this paper is more effective in showing traffic characteristics than the current highway functional classification method, and the functional classification system will be helpful for road extension and planning design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.201-204
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• 2007

In this paper, we research the content-based analysis and classification according to the composition of the feature parameters pool for the auditory signals to implement the auditory indexing and searching system. Auditory data is classified to the primitive various auditory types. we described the analysis and feature extraction method for the feature parameters available to the auditory data classification. And we compose the feature parameters pool in the indexing group unit, then compare and analysis the auditory data centering around the including level and indexing criterion into the audio categories. Based on this result, we composit feature vectors of audio data according to the classification categories, then experiment the classification using discrimination function.

• The Korean Journal of Ecology
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• v.19 no.5
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• Journal of Korean Society of Archives and Records Management
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• v.7 no.2
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• pp.43-71
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• 2007

The Records and Archival Management System of Korean Government was founded in the early 1960s after the overall national structure reform and the implementation of the new administrative management technique, which boosted the efficiency of the way of conducting business, into the public administration, and Promoted in 1962, the records appraisal and destruction works included not only retention and destruction of official documents but also the development of efficient management and elimination systems for official documents to be produced in the future. and Korean government elaborated the appraisal system to stipulate the retention period on the basis of functional classification and documentary function.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.71-89
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• 2003

Although many studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective in the classification problems. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques. This study proposes the linearly combining methodology of different classification techniques. The methodology is developed to find the optimal combining weight and compute the weighted-average of different techniques' outputs. The proposed methodology is represented as the form of mixed integer programming. The objective function of proposed combining methodology is to minimize total misclassification cost which is the weighted-sum of two types of misclassification. To simplify the problem solving process, cutoff value is fixed and threshold function is removed. The form of mixed integer programming is solved with the branch and bound methods. The result showed that proposed methodology classified more accurately than any of techniques individually did. It is confirmed that Proposed methodology Predicts significantly better than individual techniques and the other combining methods.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.439-442
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• 1997

In our research, we will extract diagnostic parameters by LPC method and wavelet transform. Then, we will design artificial neural network which is based on RBF that can express input features in terms of fuzzy. Because PVC(Premature Ventricular Contraction) has possibility to cause heart attack, the detection of PVC is a very significant problem. To deal with this problem, LPC method which gives different coefficients or different morphologies and wavelet transform which has superior localization nature of time-frequency, are used to extract effective parameters or classification of normal and PVC. Because RBF network can allocate an input feature to the membership degree of each category, total system will be more flexible.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.667-680
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• 2007

The bio-data processing is used for a suitable purpose with bio-signals, which are obtained from human individuals. Recently, there is increasing demand that the bio-data has been widely applied to various applications. However, it is often that the number of data within each class is limited and the number of classes is large due to the property of problem domain. Therefore, the conventional pattern recognition systems and classification methods are suffering form low generalization performance because the system using the lack of data is influenced by noises of that. To solve this problem, we propose a modified additive factor model for bio-data generation, with two factors; the class factor which affects properties of each individuals and the environment factor such as noises which affects all classes. We then develop a classification system through defining a new similarity function using the proposed model. The proposed method maximizes to use an information of the class classification. So, we can expect to obtain good generalization performances with robust noises from small number of datas for bio-data. Experimental results show that proposed method outperforms significantly conventional method with real bio-data.