• Fashion & Textile Research Journal
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• v.9 no.6
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• pp.613-625
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• 2007

Globalizing the Japanese fashion successfully, Hanae Mori's work awoke the western fashion world's nostalgia towards the East. Analyzing the aesthetic characteristics of Hanae Mori's clothes what kinds of aesthetic characteristic that her work had and what kinds of influences that she made in the modern fashion would provide substantial contribution of the world's modern fashion. This study provided forms and remarkable features of Japanese traditional custom, revealed Hanae Mori's life and her philosophies of fashion, and defined Hanae Mori's aesthetic characteristics by analyzing her work from 1970's until the retirement, July 2004. Methods of this study are completed by documentary records of Hanae Mori, research papers and fashion magazines that are published domestically and internationally, and collected materials from internet. The results of analysis are epitomized as below. Hanae Mori was the first Japanese fashion designer who expressed the characteristics of traditional Japanese custom with modernity sprit. In the 60's and 70's, especially in the U.S. and European fashion market, she inspired western fashion designers by her original sprit of art: combining Japanese tradition which showed distinctive color and spirit of nature and the western beauty. Hanae Mori created new dress molding from the Kimono's unstructured feature. Her layered look dressing, oblique adjustment and Obi, and others all enabled Mori to express Japanese image into modern fashion. Additionally, in terms of traditional Japanese image being acknowledged world-widely, she played a major contribution in world fashion by suggesting a new vision and raised several sensations in fashion artistry and modeling. Amongst her various patterns, Hanae Mori had butterfly patterns in most of her works, which was her representative symbol. This spoke for her strong will and senses of duty that wanting to inform beauty of Japanese women who were reflected in modern and graceful butterfly patterns. Flowers were another element that symbolized Mori. Using various flower motifs that bloomed in every different four seasons, she connected two images into her fashion; beauty of the nature and enlightening image of vibrating life. The aesthetic characteristics of Hanae Mori's clothes were defined as five: Japonism, naturalism, feminism, eroticism, and modernism. Japonism which is the spirit of Japanese, Mori used the concept to connect the East and the West. Naturalism represented harmony of the nature and the human. Feminism highlighted Eastern women's beauty. Eroticism emitted feminine attraction. Modernism represented simplicity and sophistication. Such aesthetic character illustrated Mori's original emotion that was based on Japanese spirit and she combined it with values of the East and the West. From the analysis of Mori's aesthetic characteristics, it is clearly recognizable her feministic beauty is emanated by her original emotion and sensibility.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.4
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• pp.51-62
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• 2012

According to the Lighthill and Whitham's shock wave model, a shock wave exists even in a homogeneous speed condition. They referred this wave as unobservable- analogous to a radio wave that cannot be seen. Recent research has attempted to identify how such a counterintuitive conclusion results from the Lighthill and Whitham's shock wave model, and derive a new asymptotical shock wave model. The asymptotical model showed that the shock wave in a homogenous speed traffic stream is identical to the ambient vehicle speed. Thus, no radio wave-like shock wave exists. However, performance tests of the asymptotical model using numerical values have not yet been performed. We investigated the new asymptotical model by examining the implications of the new model, and tested it using numerical values based on a test scenario. Our investigation showed that the only difference between both models is in the third term of the equations, and that this difference has a crucial role in the model output. Incorporation of model parameter${\alpha}$ is another distinctive feature of the asymptotical model. This parameter makes the asymptotical model more flexible. In addition, due to various choices of ${\alpha}$ values, model calibration to accommodate various traffic flow situations is achievable. In Lighthill and Whitham's model, this is not possible. Our numerical test results showed that the new model yields significantly different outputs: the predicted shock wave speeds of the asymptotical model tend to lean toward the downstream direction in most cases compared to the shock wave speeds of Lighthill and Whitham's model for the same test environment. Statistical tests of significance also indicate that the outputs of the new model are significantly different than the corresponding outputs of Lighthill and Whitham's model.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.