• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.6
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• pp.152-161
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• 2006

This study is the primary study for analyzing the classifying characteristics of river wetlands in Korea and China. It is the first step for constructing the wetlands inventories and establishing the wetland conservation strategies in North-Eastern Asia. The case study sites are Han-river which is the representative river of Korea and Tu-men river which is flowing on the borderline of 3 nations, China, North Korea and Russia. The results are as follows : 1. The types of wetlands of Han-river in Korea and Tumen-river in China were classified by the methods of Koo(2002) which is focused on the topography and hydrology and Zhu(2002) which is emphasized the vegetation and habitats. 2. There are three features which are hydrology, topography and soil cover, and vegetation to classify the wetlands into each types. 3. According to the two wetland types by Koo and Zhu, classification system, wetlands in the case study area(Han river and Duman river) were classified by types. 4. In Koo's classifying system(2002), lots of Riverine, Lacustrins and Flat wetlands are found because the topographical and hydrological features are emphasized. On the contrary in Zhu's system(2002), there are lots of Palustrine wetlands because of emphasizing the vegetation. 5. By the topographic and geological characteristics of each sites, there are more wetland types in the lower Tumen river.

• Journal of the Korea Fashion and Costume Design Association
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• v.11 no.3
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• pp.87-99
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• 2009

The purpose of this study was to find out criteria for classifying fashion brand from the consumer point of view. This was compared with the viewpoint of fashion business practice in order to develop strategy of fashion brands and to manage brand effectively and systematically, and to suggest theoretical frame for application of these criteria. This study was researched as the succeeding study of a model of criteria for classifying fashion brands from the viewpoint of fashion business practice. Survey was used as a research method. The subjects were 422 women who were 20-30 years old and living in and near Seoul. Questionnaires were developed based on 37 fashion brands' classification criteria by means of pre-survey, and SPSS package and LISREL program were used to analyze the data. As a result of factor analysis considering 37 classification criteria, 8 factors were identified as classification criteria. They were as follows; the level of brand form, the level of product concept, the level of management item, the level of brand sales ability, the level of customer management, the level of brand advertising and awareness, the level of brand value, and the level of product lead ability. All of criteria were correlated to each other. The effective method to classify fashion brands was proposed by establishing the model of the relationship of the values of 7 criteria and by proving it with the structure equation model analysis. The model of criteria for classifying fashion brands that was suggested on this study was proved by the structure equation model analysis. In this study, from a consumer's point of view we suggested a theoretical framework describing which criteria would be selected to classify and utilize fashion brand market. This model can be used to select the most efficient classification criteria and classify them hierarchically instead of selecting only one among some factors that complex and interactional and classifying.

• Journal of the Korean Mathematical Society
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• v.32 no.3
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• pp.563-571
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• 1995

The recent work of Hopkins, Kuhn and Ravenel [H-K-R] indicates the Morava K-theory, $K(n)^*(-)$, occupy an important and fundamental place in homology theory. In particular $K(n)^*(BG)$ for classifying spaces of finite groups are studied by many authors [H-K-R], [R], [T-Y 1, 2] and [Hu].

• Journal of the Korea Fashion and Costume Design Association
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• v.4 no.3
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• pp.33-42
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• 2002

The purpose of this study was to find out criteria for classifying fashion brand from consumer point of view in order to develop strategy of fashion brands and to manage brand effectively and systematically, and to suggest theoretical frame for application of these criteria. Survey was used as a research method. Subject were 422 age of 20-30 women living in and near Seoul. Questionnaires was developed to based on 37 classification criteria, and SPSS package program were used to analyze data. The results of this study were as follows: First, factor analysis considering 37 classification criteria identified 8 factors as classification criteria. They were the level of brand form, the level of product concept, the level of management item, the level of brand sales ability, the level of customer management, the level of brand advertizing and awareness, the level of brand value, the level of product lead ability. Second, the most important factor was the level of customer management, but comparatively factor of the level of brand sales ability the level of brand value was less important. Third, consumer cognized difference of criteria for classifying fashion brands. And the level of product lead ability was the most important factor in women's wear category and the level of brand form was in general casual wear category.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.127-135
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• 2011

Efficient ordering of decision variables is one of the methods that find solutions quickly in the depth first search using backtracking. At this time, development of variables ordering algorithms considering dynamic and static properties of the problems is very important. However, to exploit optimal variable ordering algorithms appropriate to the problems. In this paper, we propose a problem classifying rule which provides problem type based on variables' properties, and use this rule to predict optimal type of variable ordering algorithms. We choose frequency allocation problem as a DS-type whose decision variables have dynamic and static properties, and estimate optimal variable ordering algorithm. We also show the usefulness of problem classifying rule by applying base station problem as a special case whose problem type is not generated from the presented rule.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.4 no.2
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• pp.11-25
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• 2001

A wetland is an ecosystem which is the most useful and highly-energetic transition area. This study has been carried out to classify and identify the various types of wetlands in Korea. The main objective of this study are 1) defining and classifying of wetlands, and 2) identifying the wetlands characteristics, and 3) studying cases on the natural wetlands such as Han river, DMZ(Demillitarized Zone), Upo wetland and Yong(Dragon) wetland. The results as follows： 1) Development of the indices for identifying and classifying wetlands in encompassing in such as Ramsar Conference, US NWI(National Wetlands Inventory), Hydrogeomorphic system. 2) Development on the classifying method on the wetlands in the level of supersystem, system, subsystem, class and subclass. The systems include Palustrine and Riverine, and the subsystems are Seasonal, Permanent(Palustrine) and Impersistent, Lower perennial, Impersistent (Riverine). 3) Finally, we find out Young wetland is Palustrine/Permanent/Slope/Persistent, and Upo wetland consists of various types of wetlands, those are, Palustrine/Permanent/Depression/Forest Deciduous, Palustrine/Permanent/Depression/Shrub Deciduous, Palustrine/Permanent/Depression/Persistent, Palustrine /Permanent/Depression/Hydrophytes, and Lacustrine/Permanent/Openwater/Hydrophytes. The taxonomy of this study stems from identifying and classifying wetlands with indices mainly based on hydrologic features and substrates. So, it is needed that consequent studies are to be performed with various viewpoints. And the studying cases were limited because of the restricted entrance into the DMZ, And, we selected only 10 crucial sites in Han river as the subject for wetlands regulation and creation. And, for advanced studies, drawing up inventory and mapping are necessary.

• Journal of Elementary Mathematics Education in Korea
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• v.22 no.3
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• pp.221-240
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• 2018

In this study, we focus on the classifying and representing data in the elementary mathematics curriculum for 1st and 2nd grades which have been rarely addressed in the previous studies. We analyze the significance of classifying and representing sata in terms of statistical problem solving and variability as the core of statistical literacy. As a result, the classifying and representing data are important for students to recognize the variability which is ubiquitous in the data and to construct distribution of data, respectively. They are reflected in the 2015 revised mathematics curriculum as the statistical literacy for addressing data. We suggest some implications to teach the classifying and representing data as the practice of statistical literacy education in their statistics classes for 1st and 2nd grades.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Journal of Digital Convergence
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• v.6 no.4
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• pp.177-183
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• 2008

This paper aims to offer a solution based on intelligent document classification to create a user-centric information retrieval system allowing user-centric linguistic expression. So, structures expressing user intention and fine document classifying process using EBL, similarity, knowledge base, user intention, are proposed. To overcome the problem requiring huge and exact semantic information, a hybrid process is designed integrating keyword, thesaurus, probability and user intention information. User intention tree hierarchy is build and a method of extracting group intention between key words and user intentions is proposed. These structures and processes are implemented in HDCI(Hybrid Document Classification with Intention) system. HDCI consists of analyzing user intention and classifying web documents stages. Classifying stage is composed of knowledge base process, similarity process and hybrid coordinating process. With the help of user intention related structures and hybrid coordinating process, HDCI can efficiently categorize web documents in according to user's complex linguistic expression with small priori information.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.651-657
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• 2005

This study figures out the objectives of supply chain integration and proposes a conceptual framework for classifying the type of supply chain integration in order to help developing supply chain integration strategy. We figure out the objectives of supply chain integration by structural integration and functional integration and then develop a conceptual framework for classifying the type of supply chain integration by combining the clusters of structural integration factors and functional integration factors. Using the framework, a firm would be able to figure out which type of supply chain it belongs to and develop appropriate supply chain integration strategy.