• Journal of the Korean Society of Costume
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• v.66 no.4
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• pp.128-145
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• 2016

Unlike the past, when fashion brands adopted unilateral communication with their consumers, the brands today have recognized the importance of bi-lateral communication. This has led to the companies producing fashion films as a means to elicit a consensus in opinion between the brands and the consumers. Such fashion films should be understood as films using fashion that transcends time, and also as a type of fashion media. This study, which is based upon the understanding that fashion films are a part of strategic marketing for enhancing the value of brands, used domestic and international literature in order to define fashion films, and establish a theoretical basis for these films. Corroborative study was also conducted for the purpose of practical categorization. This study aims to investigate the characteristics of fashion films, and to suggest a new approach to the study of fashion films. The study adopted the research methodology used in Dudley Andrew's film theory in order to create a theoretical frame that can be used to categorize fashion films. The theory is of significance because it is the basis for the category of motion picture fashion film and media technology fashion film. The study on the categorization and the characteristics of fashion films based upon 6 sub-categories shows a consistent trend of fashion films. From the results, it can be inferred that the films contribute, in part, to the enhancement of brand value. Fashion films have shown rapid growth with the mixture of other media, and with the introduction of cutting-edge technology. Fashion films can be used as new marketing methods for the fashion brands in this digital age.

• Journal of Information Management
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• v.35 no.4
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• pp.81-105
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• 2004

In this study, the way of the automatic text categorization on web-based query was implemented. X2 methods based on the Supported Vector Machine were used to test the efficiency of text categorization on queries. This test is carried out by the model using the Synonymy List. 713 synonyms were extracted manually from the tested documents. As the result of this test, the precision ratio and the recall ratio were decreased by -0.01% and by 8.53%, respectively whether the synonyms were assigned or not. It also shows that the Value of F1 Measure was increased by 4.58%. The standard deviation between the recall and precision ratio was improve by 18.39%.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2016.05a
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• pp.23-24
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• 2016

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.15-40
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• 2020

Due to the explosive growth of mobile application services, categorizing mobile application services is in need in practice from both customers' and developers' perspectives. Despite the fact, however, there have been limited studies regarding systematic categorization of mobile application services. In response, this study proposed a method for categorizing mobile application services, and suggested a service taxonomy based on the network clustering results. Total of 1,607 mobile healthcare services are collected through the Google Play store. The network analysis is conducted based on the similarity of descriptions in each application service. Modularity detection analysis is conducted to detects communities in the network, and service taxonomy is derived based on each cluster. This study is expected to provide a systematic approach to the service categorization, which is helpful to both customers who want to navigate mobile application service in a systematic manner and developers who desire to analyze the trend of mobile application services.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.4
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• pp.11-22
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• 2009

This was a 2nd-year study aiming at developing the procedure of alternative system that was intended to restore not only biophysically disturbed areas but also psychologically and socially damaged community. It was suggested that this participatory restoration system could be constructed based on integrative categorization processes consisting of damage types and readiness of local residents for participation. Three case study sites-High-One resort, Lafarge-Halla cement, and high-altitude farmland near Gangneung city, were selected to apply the theoretical framework proposed as a result of 1st-year work. In order to develop introductory programs, key concepts such as forest for future, carbon offset forest, and healing forest, have been suggested based on analysis of 6 system components including human resources, communication, legal and institutional support, financial sources, restoration methods, and activity programs for each site. More detailed processes and procedures can be identified, defined, and refined after the end of final, 3rd-stage of the study in April of 2010.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.991-997
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• 2009

Recently, many countries are developing and investing in various homeland security technologies against terrorism. The importance of homeland security has been growing because of nuclear weapon threat from North Korea, the burning of cultural assets, and violence crimes. Therefore, in this paper, we have described and analyzed the trends related to homeland security technology. The main techniques toward homeland security are aggregation technology, integration technology, collaboration technology, categorization technology, intelligence technology, and mining technology. Those are likely to become the growth potentials until fade out of threat. Therefore, we require more government policies to support a budget enlargement.

• Asian Journal of Innovation and Policy
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• v.5 no.3
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• pp.251-274
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• 2016

Practical methodology for categorizing collaborative disciplines or research in a quantitative manner is presented by developing a Correlation Matrix of Major Disciplines (CMMD) using bibliometric data collected between 2009 and 2014. First, 21 major disciplines in science and engineering are defined based on journal publication frequency. Second, major disciplines using a comparing discipline correlation matrix is created and correlation score using CMMD is calculated based on an analyzer function that is given to the matrix elements. Third, a correlation between the major disciplines and 14 research fields using CMMD is calculated for validation. Collaborative researches are classified into three groups by partially accepting the definition of pluri-discipline from peer review manual, European Science Foundation, inner-discipline, inter-discipline and cross-discipline. Applying simple categorization criteria identifies three groups of collaborative research and also those results can be visualized. Overall, the proposed methodology supports the categorization for each research field.

• Asia pacific journal of information systems
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• v.14 no.2
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• pp.115-130
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• 2004

This paper proposes how to build an expert profile database in KMS, which provides the information of expertise that each expert possesses in the organization. To manage tacit knowledge in a knowledge management system, recent researches in this field have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise so that users can contact them for help. In this paper, we develop a framework to automate expert classification using a text categorization technique called Vector Space Model, through which an expert database composed of all the compiled profile information is built. This approach minimizes the maintenance cost of manual expert profiling while eliminating the possibility of incorrectness and obsolescence resulted from subjective manual processing. Also, we define the structure of expertise so that we can implement the expert classification framework to build an expert database in KMS. The developed prototype system, "Knowledge Portal for Researchers in Science and Technology," is introduced to show the applicability of the proposed framework.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3336-3346
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• 2022

In general, a number of severe accident scenarios derived from Level 2 probabilistic safety assessment (PSA) are typically grouped into several categories to efficiently evaluate their potential impacts on the public with the assumption that scenarios within the same group have similar source term characteristics. To date, however, grouping by similar source terms has been completely reliant on qualitative methods such as logical trees or expert judgements. Recently, an exhaustive simulation approach has been developed to provide quantitative information on the source terms of a large number of severe accident scenarios. With this motivation, this paper proposes a machine learning-based categorization method based on exhaustive simulation for grouping scenarios with similar accident consequences. The proposed method employs clustering with an autoencoder for grouping unlabeled scenarios after dimensionality reductions and feature extractions from the source term data. To validate the suggested method, source term data for 658 severe accident scenarios were used. Results confirmed that the proposed method successfully characterized the severe accident scenarios with similar behavior more precisely than the conventional grouping method.

• Ecology and Resilient Infrastructure
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• v.3 no.3
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• pp.207-211
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• 2016

This study focuses on the categorization of the phenomenon of vegetative recruitment on riparian channels, so called, the phenomenon from "white river" to "green river", and proposes for the corresponding research direction. According to the literature review and research outputs obtained from the authors' previous research performed in Korea within a limited scope, the necessary and sufficient conditions for the recruitment and retrogression of riparian vegetation may be the mechanical disturbance (riverbed tractive stress), soil moisture (groundwater level, topography, composition of riverbed material, precipitation etc.), period of submergence, extreme weather, and nutrient inflow. In this study, two categories, one for the reduction in spring flood due to the change in spring precipitation pattern in unregulated rivers and the other for the increase in nutrient inflow into streams, both of which were partially proved, have been added in the categorization of the vegetative recruitment and retrogression on the riparian channels. In order to scientifically investigate further the phenomenon of the riparian vegetative recruitment and retrogression and develop the working riparian vegetative models, it is necessary to conduct a systematic nationwide survey on the "white to green" rivers, establishment of the categorization of the vegetation recruitment and retrogression based on the proof of those hypotheses and detailed categorization, development of the working mathematical models for the dynamic riparian vegetative recruitment and retrogression, and adaptive management for the river changes.