• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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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.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.235-238
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• 2004

In this paper, we will present the implementation method of telemetry trend analysis in KOMPSAT-2 (KOrea Multi Purpose SATellite II), and then we will show the test result of trend analysis with telemetry data. Trend Analysis function is one of the module of Satellite Operations Subsystem and that analyzes the telemetry data of satellite state of health and telemetry trend for operation support. With this system many clients can analyze telemetry data simultaneously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3221-3242
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• 2021

The purpose of the study is to examine the current study trend of 'QR code' and suggest a direction for the future study of big data analysis: (1) Background: study trend of 'QR code' and analysis of the text by subject field and year; (2) Methodology: data scraping and collection, EXCEL summary, and preprocess and big data analysis by R x 64 4.0.2 program package; (3) the findings: first, the trend showed a continuous increase in 'QR code' studies in general and the findings were applied in various fields. Second, the analysis of frequent keywords showed somewhat different results by subject field and year, but the overall results were similar. Third, the visualization of the frequent keywords also showed similar results as that of frequent keyword analysis; and (4) the conclusions: in general, 'QR code' studies are used in various fields, and the trend is likely to increase in the future as well. And the findings of this study are a reflection that 'QR code' is an aspect of our social and cultural phenomena, so that it is necessary to think that 'QR code' is a tool and an application of information. An expansion of the scope of the analysis is expected to show us more meaningful indications on 'QR code' study trends and development potential.

• Journal of Environmental Impact Assessment
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• v.4 no.2
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• pp.93-103
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• 1995

This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.65-73
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• 2013

In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

• Fashion & Textile Research Journal
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• v.22 no.5
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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.

• Design & Manufacturing
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• v.15 no.4
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• pp.14-23
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• 2021

In this study, we have analyzed the access status and the data usage trend of the public Wi-Fi on the bus, which has not been carried out in the previous studies. The analysis period of this study is 5 months from Nov. 2020 to Mar. 2021. When we compared the access status of Seoul metropolitan and the non-metropolitan region against each region's deployment status ratio, the access ratio of the metropolitan region was higher than the non-metropolitan region, of which the gap was 4.53%. The access for each region showed the growing trend, which was 43.5% on average. The data usage also showed the growing trend, 2.7% on average. Weekly data usage showed the growing trend irrespective of weekdays or weekends. The data usage of the weekdays was 695GB higher than weekends. The data usage during commuting hours including school (7:00~9:00 a.m. and 4:00~6:00 p.m.) was higher than 3,000GB. We can conclude that bus public Wi-Fi was used more actively in non-metropolitan region than Seoul metropolitan region by the office workers and students. The secure access also showed the growing trend. And the secure data usage also showed the growing trend.

• Journal of Korean Society on Water Environment
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• v.26 no.6
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• pp.895-902
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• 2010

The effect of seasonality on water quality variation is very significant. Generally, it reduce the power of the trend extraction. A parametric time-series model was used for detecting trends in historic constituent concentration data. The effect of seasonality is able to remove from time series decomposition technique. According to such statistic methode, long-term water quality trend analysis system (NTrend 1.0) was developed by Nakdong River Water Environmental Research Center. The trend analysis of BOD variation was conducted with NTrend 1.0 at Goreong and Moolkum site in Nakdong river to show the effect of water quality management action plan. Power test of trend extraction was tried each case of 'deseasonalized and deannulized' data and 'deseasonalized' data. Analysis period was from 1989 to 2006, and it's period was divided again three times, 1989~1993, 1994~1999 and 2000~2006 according to action plan period. The BOD trend was downward in Goreong site during three times and it's trend slope was very steep, and upward in Moolkum during 1989~1993, but it was turned downward during 1994~1999 and 2000~2006. It was revealed that it's very effective to reduce the concentration of BOD by water quality management action plan in that watershed. The result of power test was shown that it is high for trend extraction power in case of 'deseasonalized' data.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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• pp.33-37
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• 2022

Purpose: This study aims to understand the trend and central concept of domestic researches on laughter therapy. For the analysis, this study used total 72 theses verified by inputting the keyword 'laughter therapy' from 2007 to 2021. Research design, data and methodology: This study performed the development and analysis of keyword co-occurrence network, analyzed the types of researches through topic modeling, and verified the visualized word cloud and sociogram. The keyword data that was cleaned through preprocessing, was analyzed in the method of centrality analysis and topic modeling through the 1-mode matrix conversion process by using the NetMiner (version 4.4) Program. Results: The keywords that most appeared for last 14 years were laughter therapy, depression, the elderly, and stress. The five topics analyzed in thesis data from 2007 to 2021 were therapy, cognitive behavior, quality of life, stress, and the elderly. Conclusions: This study understood the flow and trend of research topics of domestic laughter therapy for last 14 years, and there should be continuous researches on laughter therapy, which reflects the flow of time in the future.

• Journal of Korea Water Resources Association
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• v.47 no.3
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• pp.223-235
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• 2014

In recent, the various methods to predict the hydrological impacts due to climate change have been developed and applied. Especially the trend analysis using observed and future hydrological data has been performed than ever. Parametric or non-parametric tests can be applied for a trend analysis. However, the non-parametric tests have been commonly used in the case of trend analysis using hydrological data. Therefore, the two types of non-parametric tests, Mann-Kendall (MK) test and Spearman Rho (SR) test, were used to detect the trend in the observed and future rainfall data that were collected from the Nakdong River basin. Also, the Pre-Whitening (PW) and the Trend Free Pre-Whitening (TFPW) as the pre-process of the trend analysis were performed. Also, the result of trend analysis suggest that those pre-processes have a statistically significant effect. Additionally, the Sequential Mann-Kendall (SMK) was used to reveal the beginning point of a trend in the observed and future rainfall data in the Nakdong River basin. The rainfall patterns in most rainfall gauges using the observed rainfall show the increasing trend and the abrupt changes in the specific months (from April to May and September to October). Also, the beginning point of the trend is brought forward by several months when climate change is accelerated. Finally, the results of this study can provide the useful background for the research related to climate change and water resources planning in the Nakdong River basin.