• Trans-
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• v.8
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• pp.1-28
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• 2020

This study examines musical characteristics of so-called 'Hongdae Sound' as a historic musical trend by comparing with 'US 8^th Army Sound' and British 'London Punk'. Hongdae Sound refers to the musical trend that was formed with independent bands and musicians who mostly performed live in the club called 'Drug' in Hongdae area, and voluntarily adopted minor musical sensitivity and indie spirit of 'post-punk rock' genre. But as an industrial standpoint the superficial identity of 'indie' interferes with academic approach when analysing musical aspects of Hongdae Sound. Therefore it is necessary to rearrange its characteristics as the musical trend based on regional classification in order to fully appreciate its status in history of Korean popular music. US 8^th Army Sound refers to the musical trend that was played within the live stages in US military bases in Korea. Many hired Korean musicians for those shows were able to learn the current popular musical trend in the States, and to spread those to the general public outside the bases. The industrial system of the Army Sound was very similar to that of K-Pop, but when it comes to leading the newest musical trend of 'rock-n-roll', it had more resemblance to that of Hongdae Sound. London punk was the back-to-basic form of pure rock that was armed with social angst and rebel, indie spirit. Its primal motto was 'do-it-yourself', and Hongdae Sound mostly followed its industrial, musical and spiritual paths. London punk was short-lived because it abandoned its indie spirits and became absorbed to the mainstream. But Hongdae sound maintain its longevity by maintaining the spirit and truthfulness of indie, while endlessly experimenting with new trends.

• Knowledge Management Research
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• v.20 no.3
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• pp.139-154
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• 2019

With the increasing use of smartphone apps, many apps are coming out in various fields. In order to analyze the current status and trends of apps in a specific field, it is necessary to establish a classification scheme. Various schemes considering users' behavior and characteristics of apps have been proposed, but there is a problem in that many apps are released and a fixed classification scheme must be updated according to the passage of time. Although it is necessary to consider many aspects in establishing classification scheme, it is possible to grasp the trend of the app through the proposal of a classification scheme according to the characteristic of the app. This research proposes a method of establishing an app classification scheme through the description of the app written by the app developers. For this purpose, we collected explanations about apps in the tourism field and identified major categories through topic modeling. Using only the apps corresponding to the topic, we construct a network of words contained in the explanatory text and identify subcategories based on the networks of words. Six topics were selected, and Clauset Newman Moore algorithm was applied to each topic to identify subcategories. Four or five subcategories were identified for each topic.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.184-191
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• 2020

With the emergence of the 4th Industrial Revolution, core technologies that will lead the 4th Industrial Revolution such as AI (artificial intelligence), big data, and Internet of Things (IOT) are also at the center of the topic of the general public. In particular, there is a growing trend of attempts to present future visions by discovering new models by using them for big data analysis based on data collected in a specific field, and inferring and predicting new values with the models. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable, the correlation between the variables, and multicollinearity. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified according to the purpose of analysis. Therefore, in this study, data is classified using a decision tree technique and a random forest technique among classification analysis, which is a machine learning technique that implements AI technology. And by evaluating the degree of classification of the data, we try to find a way to improve the classification and analysis rate of the data.

• Journal of Fashion Business
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• v.4 no.3
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• pp.103-114
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• 2000

The purpose of this study was to test the discriminant analysis model of Quick Response system and to examine the detailed relationship between each discriminant factor and Quick Response adoption. In this discriminant analysis model of Quick Response system, firm size, strategic type, product category, fashion trend, selling time and the Quick Response benefits were included as discriminant factors. Onehundred and two subjects were randomly selected for the survey study and discriminant analysis, descriptive analysis, t-test, and x square test were used for the data analysis. The results of this study were: 1. Wilks Lambda and F value support the discriminant analysis model that, taken together firm size, strategic type, product category, fashion trend, selling time and the Quick Response benefits significantly help to explain Quick Response adoption. 2. The importance of discriminant ability was, in order, firm size, the Quick Response benefits, women's wear, fashion trend, analyzer, selling time, reactor, defender and men's wear. 3. The discriminant function had the high hit ratio, so this can be well used for the classification of Quick Response adoption/nonadoption.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.2 s.191
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• pp.7-12
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• 2007

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.59-71
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• 2019

In the rapidly changing industrial environment, the continuous increase in demand for entrepreneurship emphasizes the effective support of the government for the survival and growth of entrepreneurs and the necessity of establishing systematic initiative promotion policies. To this end, Of the total number of enterprises. The purpose of this study is to establish a new classification system for entrepreneurial industry that reflects the trend of entrepreneurship based on convergence technology that emerged during the 4th Industrial Revolution era in order to establish a systematic initiative upbringing policy. In this paper, we propose a new classification system for entrepreneurial ecosystem by using Delphi technique. As a result of the study, the categories of entrepreneurial industry are classified into technology entrepreneurship and general entrepreneurship. Technology entrepreneurship is divided into ICT services, ICT manufacturing, general manufacturing, cultural contents and biotechnology. The results of this study suggest a meaningful implication in the establishment of effective policies to support entrepreneurship in the future by establishing new standards of industry classification system of entrepreneurs.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.3
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• pp.231-245
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• 2002

A better knowledge of emission inventories can serve several important functions such as provision of public information, identification of primary sources, assessment of temporal and spatial trend, and analysis for national modelling studies. The purpose of this paper is to propose the new air emission source categories on the basis of the Korea Standard Industrial Classification. Hence, the paper focuses on reviewing and comparing the air emission sources categories of USEPA, and EU. The new emission source categories compose Tiers 1, 2, and 3. For Tier 1, there are 14 categories; fuel combustion-utilities, industries, and heating and others, chemical and allied product manufacturing, metals processing, and petroleum and related industries, etc. Tier 2 consists of small categories classified minutely in Tier 1. Tier 3 connects the categories of Tier 2 with the Korea Standard Industrial Classification.

• Journal of the Korean Society for information Management
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• v.22 no.4 s.58
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• pp.5-22
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• 2005

As the development of advertising industry and media the research about an advertisement get accomplished. As the result information resources called on the advertising materials are on an Increasing trend. However, it looks into the classification system In advertising field of KDC, the problems are as the follows : (1) the classification items are too incomplete, (2) the main class is badly arranged. The reason have no regard for the correlation with a science. So, it gives rise to confusion to the librarian and user. The purpose of the study is to present the improvement plan on the classification system in advertising field of KDC. In order to build the improvement plan, the four steps are utilized. The first step Is to investigate the characteristic of sciences on advertising and a type. The second one is to survey the current status of the library classification as KDC, NDC, DDC, and LCC. The third one is to analyse the classification system of library and web site on the advertising. The forth one is to grasp the problems on the classification system In advertising field of KDC.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.637-651
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• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.1
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• pp.25-44
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• 2013

The purpose of this study was to analyze the trends of Classification Studies in Korea from 205 research articles in five scholarly journals in Library and Information Science during the period 1986-2011. Individual article was analyzed in the aspects of specific research topics, research methodologies, data collection & analysis, and the characteristics of classification research was suggested. The amount of research paper has increased during the period and the focus of the study was on practical use and most of the papers were about new classification schedules or modification of current classification systems. Most of the papers were literature research and comparative research on classification systems by professors or graduate students. Top 9 authors in classification research were professors or lecturers and a few authors were computer science major. Therefore, various research topics, research methodologies and collaborations with other disciplines are necessary for future classification research.