• 한국의류산업학회지
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• 제10권6호
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• pp.926-935
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• 2008

The field of textile and fashion is regard to be sensitive to trend, however, the professional fashion information planning company for trend forecasting has not settled down in Korea. This study was designed to propose systemizing for fashion trend information planning in domestic fashion information service market. The empirical research was conducted by analysing in-depth interview data and news-scrap contents about each fashion information planning company. The result are as follows; First, fashion information service showed a little difference according to the type of fashion information companies, but they provided not only general fashion trends but also external market environmental information, survey-based consumer information and various segmented market research reports including academic information. Second, the fashion information planning process is largely divided into 3 stages; trend analysis, trend forecasting, trend application. The trend application step is the stage which connects the fashion information service industry to the fashion business. Thirdly, as a result of the competitive power evaluation for fashion information planning, the domestic fashion information planning companies came to reveal the fact that the possibility of carrying out and information analysis power were weak, however, how to present trend information had a relatively competitive. Consequently, this study is expected to play a role in understanding the importance of fashion trend information, and further ahead it would be helpful to organize the curriculum of fashion information planning subject in order to educate the future fashion executives.

• 센서학회지
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• 제33권5호
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• pp.248-254
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• 2024

Artificial intelligence techniques have improved fire-detection methods; however, false alarms still occur. Conventional methods detect fires using current sensors, which can lead to detection errors due to temporary environmental changes or noise. Thus, fire-detection methods must include a trend analysis of past information. We propose a deep-learning-based fire detection method using multi-sensor data and Kendall's tau. The proposed system used a BiLSTM model to predict fires using pre-processed multi-sensor data and extracted trend information. Kendall's tau indicates the trend of a time-series data as a score; therefore, it is easy to obtain a target pattern. The experimental results showed that the proposed system with trend values recorded an accuracy of 99.93% for BiLSTM and GRU models in a 20-tap moving average filter and 40% fire threshold. Thus, the proposed trend approach is more accurate than that of conventional approaches.

• 산업경영시스템학회지
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• 제40권4호
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• pp.237-245
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• 2017

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

• 한국의류산업학회지
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• 제22권5호
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• pp.551-560
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• 2020

Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

• 한국생활과학회지
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• 제18권2호
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• pp.465-476
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• 2009

The purpose of this study is to investigate recognition degree and acceptability of fashion trends of new consumers who live in digital era, and to determine how these factors have influence on their use of fashion trend information. The study was conducted with 696 people from 15 to 34 years old. A self-administrated questionnaire based on the results of previous researches was developed. The data were analyzed with statistical analyses such as frequency analysis, mean, factor analysis, t-test, ANOVA, correlation and regression analysis. The results are as follows: first, new digital consumer's recognition degree (RD) of fashion trends is 7.85 on the average, given that the top of scale is 20.0, it is quite low. Of fashion trend RD, fashion item RD is the highest. The female subjects recognize fashion trends better than the male subjects. Second, fashion trend acceptance of new digital generation is classified into 5 factors: 'search acceptance', 'lead acceptance', 'follow acceptance', 'non-acceptance', and 'delay acceptance'. The female subjects show higher degree in the factors of 'search acceptance', 'lead acceptance' and 'follow acceptance' of fashion trend than the males; hence it means that the females have more positive attitudes in fashion trend acceptance than the males. Third, there are significant differences between genders in the fashion information utilization. Compared to the males, the females more use fashion information on style, fabrics and color. Concludingly, their fashion trend recognition degree and acceptance made an influence in part on their utilization of fashion information.

• 대한가정학회지
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• 제41권10호
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• pp.185-198
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• 2003

Fashion is a field that responds sensitively to social and cultural atmospheres, brings about constant change due to consumer demand for new items in new fashion trends and in the latest design. The fashion industry tries to predict what kind of clothing the customers desires and produces fashion products according to trend information stated by fashion information services. This research analyses the relativity between the trends stated in the fashion information books and what consumer accept, and with this information find the application of trend information books in the planning of domestic woman's clothing. The used information books were based on Samsung Fashion Institute and Interfashion Planning, Inc. The 02/03 F/W season emphasized restoration-romantic, nostalgic mood themes. Fashion trend information and consumer acceptance condition tend to concentrate on trend themes given tv fashion information companies. In other words, $Sincere\;girl(39.04\%){\to}Frontier\;girl(34.92\%){\to}Dark\;lady(18.43\%){\to}Lady\;belle(7.59\%)$ in this order Also when looking into the consumer's wearing, no one theme appears by itself and the themes are mixed accordingly to one's lifestyle and sensibility. Accordingly fashion information organizations must provide precise fashion trends according to consumer sensibility & consumption and also compare trend information to consumer fashion trends each season. With this precise information the planned design plans will help the domestic fashion markets, which are gradually overrun by foreign brands, develop a unique and original fashion product that meets consumer sensitivity needs, and develop a new stepping stone for fashion companies and the relative fashion industry and furthermore contribute to the advancement of overseas markets.

• 복식문화연구
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• 제15권4호
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• pp.634-646
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• 2007

The aim of his study is to understand the developed aspect and proportions of the exotic images. Thus, this analyzed the exotic images in domestic fashion brand items as an relevance with fashion trend information. The exotic images are in the order of 'ethnic', 'retro', artistic', 'elegance', 'primitive', 'seductive', 'folklore', 'extreme hybrid', 'romantic', 'natural', 'splendid', 'bohemian', 'classical', 'kidult', 'modern', 'traditional', 'vintage' expressed in domestic fashion goods by the categories of its key-words expressed fashion trend information, and suitable for the fashion trend in 21C and fashionable for goods in the domestic fashion market by expressing the racial costume images and retro look, the maximized women's elegance, the difference images with an humor and unfamiliarity.

• The International Journal of Costume Culture
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• 제4권3호
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• pp.229-240
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• 2001

The purpose of the present study was to analyze the acceptance level of forecasted information of casual wear in tate 1990s in Korea and the way of utilizing fashion trends information by casual wear industries. The Present study was implemented by content analysis and descriptive survey using questionnaire and interview. Trends information in fashion journals published by fashion institute and articles in daily newspapers were analyzed in terms of fashion image, color, fabric, and silhouette. The data collected from questionnaire and interview with 113 fashion specialists were analyzed through frequency, percentage. The results indicated that among the forecasted information regarding fashion image, romantic and feminine images showed a high level of acceptance to national brand women's casual wear in the late 1990s, while mannish image showed a low level of acceptance. For men's casual wear in the same time period, androgynous trends appeared most frequently, not only in forecasted information, but also in actual trend. it was forecasted that yellow, white, and gray would be in trend and those colors appeared frequently in actual trend. On the other hand pastel tone appeared much more frequently than forecasted. Natural, thin - transparent (S/S) and stretch fabrics (F/W) were in actual trend as it was forecasted. Fit and Pare (woman), and long and slim (man) silhouettes were in actual trend as if was forecasted, but barrel silhouette appeared only in forecasted information. Most of the information forecasting fashion trends for next season were applied to the product planning of the season, right after the information comes out.

• 한국컴퓨터정보학회논문지
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• 제25권12호
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• pp.35-44
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• 2020

본 연구에서는 주가 결정 방법이 주가 경향 예측에 미치는 영향을 확인하기 위한 분석을 수행한다. 주식시장에서 성공적인 투자를 위해서는 주가의 상승과 하락을 정확하게 예측하는 것이 큰 도움이 되므로 주가 경향 예측에 관해 많은 연구가 진행되고 있다. 예를 들어 근래에는 SNS나 뉴스의 내용을 텍스트 마이닝을 이용하여 분석하고, 이를 이용한 주가 등락의 예측 방법이 제안되었으며 다양한 기계학습 기법들이 활용되고 있다. 그러나 주가의 경향을 '상승' 또는 '하락'으로 결정하는 방법은 제대로 분석된 적 없으며 일반적으로 쓰던 방법을 답습하고 있다. 이에 본 논문에서는 주가 경향 결정 방법을 이동평균을 이용해 일반화하고 주가 경향 결정 방법이 예측 정확도에 미치는 영향을 분석한다. 분석 결과, 다음 날의 주가 경향을 예측하는 경우, 주가 경향 결정방법에 따라 예측 정확도가 47%까지 차이가 남을 발견하였다. 또한 경향 결정에 사용되는 기준값 윈도우의 크기와 예측의 정확도는 비례 관계이며, 대상값 윈도우의 크기와 정확도는 반비례 관례임을 알 수 있었다.

• 한국정보통신학회논문지
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• 제19권8호
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• pp.1811-1817
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• 2015

본 논문은 국내에서 수행된 정보보안에 연구 트렌드를 분석하고, 국제적 연구 트렌드와 비교함으로써 향후 국가차원에서 나아가야할 방향에 대해 고찰해보고자 한다. 이는 기존에 수행된 정보보안의 국제 연구 트렌드 분석에 대한 후속작으로, 기존 연구의 결과와 정확한 비교를 위해 동일한 분석 방법을 이용한다. 이를 위해 2001년부터 2014년까지 발표 및 게재된 국내 논문을 활용하며, 보안과 깊이 관련된 기술들 사이의 시간별 연관성을 측정하여 국내 연구 트렌드를 분석하고, 그 결과를 비교한다. 또한 국내외의 미래 기술 시장을 함께 고려함으로써 향후 우리가 나아가야 할 발향을 살펴보고자 한다.