• Journal of KIBIM
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• v.4 no.2
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• pp.25-32
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• 2014

Today, there is a growing need of environment-friendly buildings, so-called 'green', facilities, and energy saving buildings to decrease environmental pollutants released into cities by construction activities. Green-Building Information Modeling (Green-BIM) is a purpose-built solution which supports to forecast energy consumption of 3-D model of a building by augmenting its primary 3-D measurements (width, height and depth) with many more dimensions (e.g. time, costs, social impacts and environmental consequences) throughout a series of sequential phases in the lifecycle of a building. The current study was carried out in order to integrate vegetation systems (particularly green roof and green wall systems) and investigate thermal performance of the new Sainsbury's building which will be built on Melton road, Leicester, United Kingdom. Within this scope, a 3-D building model of the news Sainsbury's building was first developed in $Autodesk^{(R)}$ $Revit^{(R)}$ and this model was then simulated in $Autodesk^{(R)}$ $Ecotect^{(R)}$once weather data of the construction site was obtained from $Autodesk^{(R)}$ Green Building $Studio^{(R)}$. This study primarily analyzed data from (1) solar radiation, (2) heat gains and losses, and (3) heating and cooling loads simulation to evaluate thermal performance of the building integrated with vegetation system or conventionally available envelops. The results showed that building integrated vegetation system can potentially reduce internal solar gains on the building rooftops by creating a 'bioshade'. Heat gains and losses through roofs and walls were markedly diminished by offering greater insulation on the building. Annual energy loads for heating and cooling were significantly reduced by vegetation more significantly through the green roof system in comparison to green wall system.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.3
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• pp.342-352
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• 2014

Purpose: The purpose of this study was to identify how political interest, efficacy and media usage influence political participation in hospital nurses. Methods: Participants were 286 nurses, who were informed of the study purpose and agreed to participate. Data were collected during November and December, 2012 using a questionnaire on political interest, political efficacy, media usage and political participation. Data were analyzed using t-test, ANOVA, Scheff$\acute{e}$'s test, Pearson Correlation Coefficients, and Multiple Stepwise Regression. Results: Scores for political participation and political interest was average. The score for political efficacy was higher than average. Political participation was significantly different by education level, job career, position, and intention to vote in the election for the 18th President. Political participation had a moderate positive correlation with political interest (r=.50, p<.001), political efficacy (r=.32, p<.001) and media usage (r=.14, p=.022). Political interest (${\beta}$=.43) was the factor most influential on political participation, explaining 25% of the variance. A total of 32% of political participation was explained by political interest, political efficacy, and TV news or SNS for media use. Conclusion: The results suggest that it is necessary to develop strategies to promote political interest and political efficacy for hospital nurses to improve political participation.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.845-850
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• 2009

Use of XML data has been increased with growth of Web 2.0 environment. XML is recognized its advantages by using based technology of RSS or ATOM for transferring information from blogs and news feed. Bitmap clustering is a method to keep index in main memory based on Relational DBMS, and which performed better than the other XML indexing methods during the evaluation. Existing method generates too many clusters, and it causes deterioration of result of searching quality. This paper proposes k-Bitmap clustering method that can generate user defined k clusters to solve above-mentioned problem. The proposed method also keeps additional inverted index for searching excluded terms from representative bits of k-Bitmap. We performed evaluation and the result shows that the users can control the number of clusters. Also our method has high recall value in single term search, and it guarantees the searching result includes all related documents for its query with keeping two indices.

• The Research Journal of the Costume Culture
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• v.20 no.1
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• pp.36-48
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• 2012

This study intends to provide fundamental data to develop creative high-value designs, proving that the cut-out technique, a decorative element of fashion design, can be used to express various visual effects. The author performed a literature review of such publications as Gap Press, Fashion News, and Mode & Mode from 2001S/S to 2010S/S, referring to Internet data to empirically analyze the cut-out technique in contemporary fashion. The study found that the cut-out design is effective overall, but is best suited for one-piece designs and for partial rather than whole items of clothing. The basic motif of the cut-out is a geometrical pattern based on a line, a tear, or is shapeless. The cut-out design is mostly shown as an overall pattern or as a symmetrical shape. Analysis shows that the characteristics of the contemporary fashion utilizing the cut-out technique are as follow: First, the cut-out technique exposes the curves of a woman's body in a direct or indirect way, thereby emphasizing her sexuality and maximizing the value of female beauty. Second, through the cut-out technique, we can highlight the various types of space formed by the technique and repeated patterns; we may also elaborate on single-patterned laser-cut designs, which will show that the particular surface effect of the material can strongly impact the attractiveness of the design through emphasis and decoration. Third, damaging or destroying clothes on purpose, showing surprising concepts through optical illusions, and expressing humor by ignoring existing clothing styles show our willingness to escape from traditional or obvious design ideas, as well as demonstrating individuality and playfulness.

• Journal of the Korea Fashion and Costume Design Association
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• v.9 no.3
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• pp.59-73
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• 2007

The purpose of this study is to find out the promotion methods for successful management of 'the fashion saho internet shopping mall' with a small capital. This study analyze the research reports, the news items, the documents on the internet shopping mall and data on promotion method which are offered by the hosting companies of the internet shopping mall like 'Cafe 24', 'Make shop', 'Whoismall' and the promotion consulting companies like 'Whoisad', 'Naver keyword shop'. And also analyze the data that interviewed the administrator of internet shopping mall and directly observed the famous internet shopping mall sites. Generally speaking, the promotion mix, marketing communication program can classify 'advertisement', 'publicity', 'personal selling', and 'sales promotion'. This study analyze the research materials on the basis of advertisement, publicity, personal selling, and sales promotion. The result are as follows. 1. The promotion methods at the stage of information the shopping mall site to the consumer are advertisement, and publicity. ${\bigcirc}$ The methods of advertisement are 'searching engine registration', 'advertisement of key word', 'advertisement of overture', 'advertisement of banner', 'advertisement cooperation marketing', 'advertisement of e-mail'. ${\bigcirc}$ The methods of publicity are using 'cafe', 'blog', 'Naver information site', 'community bulletin board', 'the fashion magazine or a press report' and 'cosponsorship'. 2. The main promotion methods at the stage of inducing the purchase are 'personal selling', and various 'sales promotion'. ${\bigcirc}$ 'Personal selling' at the shopping mall have an effect on the communication at bulletin board over the internet and the telephone. ${\bigcirc}$ 'Sales promotion' are attempted by 'VMD', 'deposit system', 'sale', etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.836-845
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• 2002

Video summary is one of the tools which can provide the fast and effective browsing for a lengthy video. Video summary consists of many key-frames that could be defined differently depending on the video genre it belongs to. Consequently, the video summary constructed by the uniform manner might lead into inadequate result. Therefore, identifying the video genre is the important first step in generating the meaningful video summary. We propose a new method that can classify the genre of the video data in MPEC compressed bit-stream domain. Since the proposed method operates directly on the compressed bit-stream without decoding the frame, it has merits such as simple calculation and short processing time. In the proposed method, only the visual information is utilized through the spatial-temporal analysis to classify the video genre. Experiments are done for 6 genres of video: Cartoon, commercial, Music Video, News, Sports, and Talk Show. Experimental result shows more than 90% of accuracy in genre classification for the well -structured video data such as Talk Show and Sports.

• Knowledge Management Research
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• v.20 no.3
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• pp.155-171
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• 2019

In the entertainment industry which has great uncertainty, it is essential to predict public preference first. Thanks to various mass media channels such as cable TV and internet-based streaming services, the reality audition program has been getting big attention every day and it is being used as a new window to new entertainers' debut. This phenomenon means that it is changing from a closed selection process to an open selection process, which delegates selection rights to the public. This is characterized by the popularity of the public being reflected in the selection process. Therefore, this study aims to implement a machine learning model which predicts the winner of , which has recently been popular in South Korea. By doing so, this study is to extend the research method in the cultural industry and to suggest practical implications. We collected the data of winners from the 1st, 2nd, and 3rd seasons of the Produce 101 and implemented the predictive model through the machine learning method with the accumulated data. We tried to develop the best predictive model that can predict winners of by using four machine learning methods such as Random Forest, Decision Tree, Support Vector Machine (SVM), and Neural Network. This study found that the audience voting and the amount of internet news articles on each participant were the main variables for predicting the winner and extended the discussion by analyzing the precision of prediction.

• Database Research
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• v.34 no.3
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• pp.3-13
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• 2018

Text classification is one of the text mining technologies that classifies a given textual document into its appropriate categories and is used in various fields such as spam email detection, news classification, question answering, emotional analysis, and chat bot. In general, the text classification system utilizes machine learning algorithms, and among a number of algorithms, naïve Bayes and support vector machine, which are suitable for text data, are known to have reasonable performance. Recently, with the development of deep learning technology, several researches on applying deep neural networks such as recurrent neural networks (RNN) and convolutional neural networks (CNN) have been introduced to improve the performance of text classification system. However, the current text classification techniques have not yet reached the perfect level of text classification. This paper focuses on the fact that the text data is expressed as a vector only with the word dimensions, which impairs the semantic information inherent in the text, and proposes a neural network architecture based upon the semantic tensor space model.

• Fashion & Textile Research Journal
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• v.23 no.1
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• pp.31-43
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• 2021

This study analyzes the characteristics of fashion flex, which have recently spread on social media. The study was conducted with big data analysis that derived flex keywords from news articles and social media as well as case studies that collected 136 posted images on Instagram to analyze the content. The meaning of flex was positively accepted based on big data results. Flex was also a buzzword frequently used on social media as well as a symbolic meaning when discussing luxury goods or fashion brand experiences. The characteristics of fashion flex in social media were largely divided into three categories. First, conspicuous consumption is considered an active expression of individual fashion tastes or self-oriented consumption and emphasizes individuality through consumption. The second characteristic is that the public actively participates in events or fashion flex challenges. People use similar fashion styles or products to participate in playful social interactions with others using various Instagram functions. Finally, acts of pursuing psychological well-being in social media were used as the term flex in a broad sense and were shown to actively explore fashion-related materials and experiences for individual happiness. This study found that the meaning of existing conspicuous consumption is transforming into positive consumption, such as the expression of taste-based identity or the seeking of fun and psychological well-being. It is also meaningful that fashion has become an effective means to express individuality and taste in expressing flex.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.86-98
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• 2022

This study explored the agenda of conservative and liberal media in reporting COVID-19, and observed the effects of each media's partisan agenda-setting on the public with the same political orientation. To this end, researchers collected 5,286 articles on COVID-19 from five newspapers, and analyzed the survey data of 1,067 respondents. Next, the researchers extracted main agenda using LDA topic modeling and analyzed the correlation between newspapers' agenda and survey respondents' agenda. As results, 15 topics such as infection, vaccine, and economic crisis appeared as the media agenda, and the difference in major agenda between conservative and liberal media was found. On the other hand, the conservative media exerted an agenda-setting influence not only on the conservatives but also on the liberals, but the liberal media did not have a significant influence on the liberals. This study contributes to the methodological expansion of agenda-setting research by introducing a new way to confirm the effectiveness of agenda-setting by combining topic modeling and survey.