• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.2
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• pp.129-144
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• 2017

Throughout the rich human history, patterns have developed as a symbolic sign and representation of the inner psychology of human beings. Thanks to its intrinsic beauty and emotional richness, the flower has been utilized as a one of the major materials for patterns used in everyday life and art. As a product of nature, floral patterns have played a key role in fashion trends as a Surface Design with other elements of fashion design such as silhouette, fabric and color. Therefore, this research sought to identify the trends of floral patterns of women's garments that appeared at the four major global fashion collections (Paris, Milano, New York and London), and to analyze how importantly the fashion magazines' prediction were applied in the actual collections. Furthermore, the research aimed to suggest possible methods to utilize trend magazines for collections in the future. As a main research method, the authors investigated professional fashion literature and internet websites to extract a total of 4,681 items presented by sixteen designers who participated in the four major global fashion collections each time during the period of the 2012 S/S~2017 S/S seasons. First View Korea and Samsung Design Net were used as major sources for the pattern extraction and analysis. According to the analysis, floral patterns account for 31%(1,454 items) among the total number of patterns appearing in the four major global fashion collections(4,681 items). For the reflection ratio, Samsung Design Net recorded a 4% higher ratio(52%) than First View Korea(48%). Based on the data and analysis of this research, the authors expect that floral patterns in various forms will be continuously presented in fashion collections, and conclude that utilizing fashion magazines is highly useful due to their appropriate predictions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.3
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• pp.235-245
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• 2002

The purpose of this study is to figure out the tendency of tunnel convergence during excavation and to present a methodology for the prediction of a fault zone ahead of a tunnel face by analyzing three dimensional displacements in various ways. 3-D numerical analysis was performed to investigate changes of tunnel convergence vectors near a fault zone and to propose a flow chart for predicting fault zones. Results of the site investigation and results of trend line analysis of in-situ data were compared to verify the usefulness of a trend line analysis. It is concluded that the orientation of faults can be predicted by using stereonets and the direction of initial stresses can be predicted from the arm length of a displacement vector as a tunnel approaches fault zones. The results of the trend line analysis coincided with those of the site investigation, and a methodology for the prediction of a fault zone was proposed.

• Journal of the Korea Fashion and Costume Design Association
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• v.6 no.3
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• pp.67-81
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• 2004

This research demonstrates clothing consumption values, fashion preferences of career women from the early 1920s to late 1930s. And having thorough understanding of values and preferences, allows us to establish marketing strategies for clothing companies. The main purpose of this study is (1) to formalize consumer group based upon the clothing consumption values, (2) to find for characteristics of consumer depending on classification of consumption value in clothing, (3) to understand the preferences of career women about fashion trends. Analyzing data was performed 292 copies, resulting factor analysis, Cluster analysis, X-test, Anova, Tukey test, t-test, frequency analysis, and reliability analysis. This paper showed 7 distinctive characteristics of career women about clothing consumption value. These characteristics can be listed as 1) value of brand image, 2) value of self-expression, 3) functional values, 4) epistemic values, 5) coordination values, 6) social values 7) psychological values. Importantly, brand image value became most significant aspects among 7 factors. Analyzing consumers based upon stated 7 factors, it was found that they are segregated into 4 groups; Self-expressive Group, Psychological Stability Group, Functional Group, Social Group. Secondly, for fashion trend preferences, self-expressive group, psychological stability group, and functional group favored Romantic Feminine Style respectively. Social Group showed preference in Nu-Basic'. The reason for such trend dealt with fabric materials and colors. Finally examining population statistics, younger generations showed more preferences in Nu-Basic', and consumers from ages of 26 to 28, 32 to 34 showed preferences in Romantic Feminine' regardless of their household income, clothing related expenditures, jobs, and education level. On the other hand, 'Modem Classic' was popular among college graduates and 'Paradise' was somewhat less popular among all ages except from ages of 32 to 34, consumers consumption 300,000Won to 400,000Won on clothing related expenditures. And 'Energy' seemed to attract more highly educated females, who had more than masters in degrees with over 300,000 to 400,000Won for clothing related expenditures.

• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.87-99
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• 2013

For analysis of climate change effects on agriculture, precise agricultural meteorological data are needed to target period and site. In this study, agricultural meteorological data under new climate change scenario (RCP 8.5) are constructed from 2011 to 2099 in 111 agriculture major station suggested by Rural Development Administration (RDA). For verifying constructed data, comparison with field survey data in Suwon shows same trend in maximum temperature, minimum temperature, average temperature, and precipitation in 2011. Also comparison with normals of daily data in 2025, 2055, and 2085 shows reliability of constructed data. In analysis of constructed data, we can calculate sum of days over temperature and under temperature. Results effectively show the change of average temperature in each region and odd days of precipitation which means flood and dry days in target region.

• Journal of Ecology and Environment
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• v.33 no.1
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• pp.37-45
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• 2010

I conducted extensive analyses of daily weather data of precipitation and temperature monitored from the Surface Synoptic Meteorological Station in Seoul from 1 October 1907 to 31 December 2009 to understand how the climate is changing and the ecological implications for Seoul, Korea. Statistical analyses of the data, including the lengths of seasons and growing degree-days (GDD), showed a clear warming trend in the Seoul area over the study period. The mean daily temperature in Seoul increased by $2.40^{\circ}C$ over the period of one hundred years, which was about three times faster than the global trend and it was striking to notice that mean daily temperature in Seoul in recent 30 years was increasing with the rate of $5.50^{\circ}C$ per hundred years, which is an extremely fast rate of increase in temperature. In the last 100 years, an increase in the number of summer days was apparent, coupled with a reduction in the average number of winter days for about 27 to 28 days based on the analysis of mean daily temperature. Although the lengths of spring and autumn have not changed significantly over the century, early initiations of spring and late onsets of autumn were quite apparent. Total annual precipitation significantly increased at the rate of 2.67 mm/year over the last 100 years, a trend not apparent if the analysis is confined to periods of 30 to 40 years. The information has the potential to be used not only for better understanding of ecological processes and hydrology in the area, but also for the sustainable management of ecosystems and environment in the region.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.4
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• pp.487-497
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• 2007

Increase of the greenhouse gases emissions during last century has led remarkable changes in our environment and climate system. Continuous monitoring of atmospheric constituents over the world is positively necessary to understand these changes around us. The concentrations of greenhouse gases ($CO_2,\;CH_4,\;N_2O,\;CFCs$) have been continuously measured at Global Climate Change Monitoring station in Gosan, Jeju since January, 2002. In this study, the variation characteristics of greenhouse gases as well as their annual, seasonal and diurnal trend using the data from January, 2002 to December, 2005 were analyzed. The raw data which was used in the analysis were validated with the methods recommended by WDCGG (World Data Center for Greenhouse Gases). The concentration of $CO_2$ was increasing continuously by 2.1 ppm/year, while $CH_4$ did not show any increasing or decreasing trend clearly for 4 years. The concentration of $N_2O$ was slightly increasing and CFCs were decreasing except CFC-12 which has longer lifetime compared with other CFCs. The variations of the greenhouse gases at Gosan were shown to be consistent with the global trend. But the concentration level of $CO_2$ in Korea was more or less higher than abroad.

• The Research Journal of the Costume Culture
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• v.18 no.6
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• pp.1274-1290
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• 2010

This study analyzed the design elements and fashion images of women's knitwear in collections of Paris, Milan, London and New York between 2003 and 2008, and examined knitwear trends in an effort to verify whether knitwear trends are repeated in certain cycles, whether they show complicated patterns in cycles and yet occur in quasi cycles, or whether they occur non-periodically in complicated forms of chaotic cycles. Trend cycle analysis results are deemed to identify the time series attribute of knit fashions. It also sought to categorize the attribute of various factors influencing knitwear trends with a view to determining relevancy between design elements, and to present the direction of predicting knitwear fashion trends and the progression of short-term knitwear trends. This study reached the following conclusion. According to design elements or fashion images, knitwear fashion trends occur in cycles, quasi cycles, non-periodical cycles. These cyclic characteristics can be used as scientific data for planning knitwear products. The study confirmed close relevancy between fashion images and fashion elements. It identified close relevancy between designs with similar fashion elements and images through coordinates by year and season, and it is possible to make short-term prediction of trend direction through the flow of coordinates. Time series data were insufficient, thereby making it difficult to perfectly verify chaos indices and giving limitations to this study. A study with more time series data will produce a more effective method of predicting and using knitwear fashion trends.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.493-500
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• 2011

The trends of technical terms express the changes of particular subjects in a specific research field over time. However, the amount of academic literature and patent data is too large to be analyzed by human resources. In this paper, we propose a method that can detect and analyze the trends of terms by modeling the life cycle of the terms. The proposed method is composed of the following steps. First, the technical terms are extracted from academic literature data, and the TDVs(Term Dominance Values) of terms are computed on a periodic basis. Based on the TDVs, the life cycles of terms are modeled, and technical terms with similar temporal patterns of the life cycles are classified into the same trends class. The experiments shown in this paper is performed by exploiting the NDSL academic literature data maintained by KISTI.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.141-146
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• 2018

The authors' author keywords are the most important elements that characterize the contents of the paper, By analyzing this in real time and providing it to users, It is possible to grasp research trends. Unstructured data of a journal created in a paper is constructed as a database, make use of this to make index data structure that can search in real time. In the index data structure, a thesis containing a specific keyword is searched, By extracting and clustering the author keywords, By presenting to the user a word cloud that can be displayed by size according to the weight, designed a method to visualize research trends. We also present the results of the research trend analysis of the keywords "virus" and "iris recognition" in the implemented system.