• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.313-329
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• 2014

This study aims to provide intellectual access to TV content using faceted classification. In order to describe the content of news and current affairs programs, a faceted approach was explored. Based on the Ranganathan's PMEST formula, the basic facets - 'who', 'what', 'how', 'where', 'when' - and their sub-facets were created, specifically for describing the news genre. Additionally, the formal structure and the contextual features of the news genre were mainly considered for creating sub-facets. These created facets were applied to a news genre program. The result shows that these suggested facets are useful for representing well the contextual components of the news genre. The application of faceted classification is expected to improve the identification of the specific TV content.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.290-294
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• 1997

Chromosomes, as the genetic vehicles, provide the basic material for a large proportion of genetic investigations. The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, we propose an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We are employed three morphological feature parameters ; centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.), as input in neural network by preprocessing twenty human chromosome images. The results of our experiments show that our TMANN classifier is much more useful in neural network learning and successful in chromosome classification than the other classification methods.

• Fashion & Textile Research Journal
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• v.13 no.5
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• pp.734-742
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• 2011

This study has been undertaken as a basic research for automatic pattern design for baseball uniforms manufactured under custom-MTM system, propose building up of a system whereby various partial patterns are combined under an automatic design system and develop a multi-combination type pattern searching algorithm which allows development of a various designs. As a result of this, type classification based on pattern design elements includes side, open, collar, facing and panel type. Design have been divided into coarse classification ranging from level 1 to 7 according to pattern design elements, based on a design distribution chart. Out of 7 such levels, 3 major types determining design which are, more specifically, level 1 sleeve type, level 2 open type and level 3 collar type, have been taken and combined to determine a total of 12 types to be used for design classification codes. Respective name of style and patterns have been coded using alphabet and numerals. Totally, pattern searching algorithm of multi-combination type has been developed whereby combination of patterns belonging to a specific style can be retrieved automatically once that style name is designated on the automatic pattern design system.

• Journal of Soil and Groundwater Environment
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• v.15 no.6
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• pp.64-71
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• 2010

National inventory of soil and groundwater contamination is an efficient decision-making tool to identify and manage existing or potential contaminated sources and contaminants. It has been used as basic data for establishing the scheme of regulations and remediation plans of soil and groundwater contamination in developed countries. This study examined classification of existing or potential sources of soil and groundwater contamination from various countries to suggest implications that required for development of classification of soil and groundwater contamination sources in Korea. Each country has provided a list of currently or potentially contaminating activities or landuses and identified some of the potential contaminants related to those contamination sources. Consideration of sources which had not been mentioned or regarded as contamination sources before was suggested for Korea situation. In addition, it is necessary to compile a list of existing data and information as much as possible to develop a detailed and practical list of various contamination sources.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.382-394
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• 2007

Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

• Journal of the Korean Society for Library and Information Science
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• v.5
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• pp.152-178
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• 1978

This has been designed for an attempt to survey a library use competency in order to provide basic information to plan more effective library use instruction for high school students. To get necessary data, a questionnaire was sent to 450 students in the 7 sample high schools in Seoul, and $80\%$ of them responded. The followings are the analysed results. 1. $42\%$ of them responded that they have heard about the decimal classification and $15\%$ of all the students have ever used decimal classification to search for the materials. 2. $3.6\%$ responded that they can understand the decimal classification and $66\%$ of all the students want to know about decimal classification. 3. $94\%$ responded that they have heard about the catalog cards and $41\%$ of all the students used catalog cards to search for the materials. 4. $29\%$ responded that they can understand the catalog cards and $68\%$ of all the students want to know about the catalog cards. 5. $61\%$ responded that they can use reference books. 6. $55.6\%$ responded that they know about the parts of a book. 7. $11\%$ responded that they can footnote. Reviewing the results of this study, library use competency of high school students can be said to be below level. And more effective approach is expected.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.113-131
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• 2002

The relationships among multi-dimensional data (such as medical examination data) with ambiguity and variation are difficult to explore. The traditional approach to building a data classification system requires the formulation of rules by which the input data can be analyzed. The formulation of such rules is very difficult with large sets of input data. This paper first describes two classification approaches using back-propagation (BP) neural network and Mahalanobis distance (MD) classifier, and then proposes two classification approaches for multi-dimensional feature selection. The first one proposed is a feature selection procedure from the trained back-propagation (BP) neural network. The basic idea of this procedure is to compare the multiplication weights between input and hidden layer and hidden and output layer. In order to simplify the structure, only the multiplication weights of large absolute values are used. The second approach is Mahalanobis-Taguchi system (MTS) originally suggested by Dr. Taguchi. The MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric. We combine the automatic thresholding with MD: it can deal with a reduced model, which is the focus of this paper In this work, two case studies will be used as examples to compare and discuss the complete and reduced models employing BP neural network and MD classifier. The implementation results show that proposed approaches are effective and powerful for the classification.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.311-318
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• 1997

On April 27,1993, a forest fire occurred in Morito-area, Manba-city, Gunma-prefecture Japan. Under the prevailing strong winds, the fire spread and extended to the largest scale ever in Gunma-prefecture. The author chartered a helicopter on May 5, one week after the fire was extinguished, and took aerial photos of tile damaged area, and investigated the condition. of the fire through field survey and data collection. The burnt area extended. over about 100 hectares, and the damage amounted to about 190 million yen (about two million dollar). The fire occurred at a steep mountainous area and under strong winds, therefore, md and topography strongly facilitated the spreading, It is the purpose of this paper to report a damage investigation of the fire and to develop the forecasting method of forest fires based on the topographical analysis and spreading speed of fire. In the first place, I analyze the topographical structure of the regions which became the bject of this study with some topographical factors, and construct a land form classification ap. Secondly, I decide the dangerous condition of each region in the land form classification map according to the direction of the wind and spreading speed of f'kre. In the present paper, I try to forecast forest fires in Morito area, and the basic results for the forecasting method of forest fires were obtained with the topographical classification system and spreading speed of fire.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.63-74
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• 2024

The objectives of this study is to classify evacuation types, derive the characteristics of 4 types, develop and discover evacuation routes within the performance hall space, and present the statistical classification results of the evacuation classification model by classification type. To achieve this purpose, the characteristics of each evacuation type's four types are applied through a network reliability analysis method and utilized for institutional improvement and policy. This study applies for the building law, evacuation and relief safety standards when establishing a performance hall safety management plan, and reflects it in safety-related laws, safety standards, and policy systems. Statistical data by evacuation type were analyzed, and measurement characteristics were compared and analyzed by evacuation types. Evaluate the morphological similarity and reliability of evacuation types according to door width and passage length and propose the install position of evacuation guidance sign boards. The results of this study are expected to be used as basic data to provide operation strategies for safety facility evacuation information sign boards according to evacuation route classification types when taking a safety management plan. The operation strategy for the evacuation sign boards installation that integrates employee guidance and safety training is applied to the performance hall safety management plan. It will contribute to establishing an operational strategy for performance space safety when constructing performance facilities in the future.

• Journal of Wind Energy
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• v.13 no.4
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• pp.58-69
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• 2022

This study reviews previous studies on the scale of offshore wind power industry ecosystems to provide basic data for a revitalization strategy for the offshore wind power industry and proposes an analysis of transaction networks based on the special classification of the renewable energy industry. First, we examine the localization rate, technology level, and price level of the offshore wind industry. Second, this research compares the methodology and estimation results of previous studies estimating the scale of the wind power industry. Third, we examine the details related to the enactment of a special classification of the renewable energy industry statistics and review the Korea Energy Agency's renewable energy industry statistics (focusing on 2019 and 2020). Finally, this study suggests the necessity of analyzing an inter-company transaction network based on special classifications of the renewable energy industry to grasp the status of each region and value chain of the offshore wind industry.