• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.263-269
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• 2010

This study examined the relative effect of participative and assigned goal-setting on team performance quantity and trend. Participants were 30 college students. They were divided into 15 pairs considering individual typing speed. Members in each pair were randomly assigned to the two experimental conditions. Participants were asked to type materials for 19 days. The dependent variable was the number of words typed. The results indicated that there was no significant difference in performance quantity between the two conditions. However, the average percentage of goal accomplishment under participative goal-setting condition was higher than that under assigned goal-setting condition. Also, the results showed that the difference in trend between two conditions was statistically significant.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.269-282
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• 2011

The purpose of this study was to compare consumer satisfaction by analyzing importance on characteristics of clothing, performance, and their inconsistency between Korea and the United States. The data was collected by using a survey based on three sages of pre-tests, and main survey conducted in The U.S and Korea. Data of 520 participants from each country (260 males and 260 females) was used. The results of this study is as follows: First, both consumers in Korea and U.S. showed five factors such as aesthetics/trend, body shape, practical use/wearing, care, and distorted. In performance factor of Korean students was consisted of wearing/care, aesthetics, body shape, distorted, and trend/symbolism while that of American students was consisted of wearing, aesthetics, body shape, trend/image factor, and distorted. Second, regarding importance rate, aesthetics/trend, practical use/wearing, care, and distorted affected satisfaction of Korean students whereas aesthetics/trend factor affected satisfaction of American students. Regarding performance, body shape factor, distorted, trend/symbolic affected satisfaction of Korean students whereas trend/image affected satisfaction of American students. Third, satisfaction of Korean and American students influenced re-purchase intention and positive word-of-mouth, so proved to be the result variable of satisfaction. By understanding the differences between consumers in Korea and U.S., apparel importers and exporters may develop effective business strategies to better fulfill their customers' needs and desires, and therefore, increase their profit.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.136-148
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• 2013

I would like to trace back periodic social trend by searching if regular performance might have reflected on social trend on its theme by analyzing theme trend of The National Dance Company of Korea, Dance Company of Seoul city, Dance Company of KyungKi-Do and to provide the meaningful results for further study by checking if the theme of dancing performance is in relation with social structure. To perform this research, I had studied on previous thesis and reference books. For example, I selected three groups, of The National Dance Company of Korea, Dance Company of Seoul city, Dance Company of KyungKi-Do, to research their theme of regular performance through checking previous thesis related to, performance material, news articles, pamphlets from beginning to present. How to analyze is being proceeded from foundation of dancing company to present according to Kim Byungseok's classification method, which was consistently used for searching theme trend from previous study as below; 1) Theme based on traditional conscious,2) Theme based on Literature, 3) Theme based on Historic issues, 4) Theme based on abstract, 5) Theme based on reality, 6)Theme based on social issues.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.183-189
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• 2024

In order to effectively predict time series data, this study proposed a hybrid prediction model that decomposes the data into trend, seasonality, and residual components using Seasonal-Trend Decomposition on Loess, and then applies ARIMA to the trend component, Fourier Series Regression to the seasonality component, and XGBoost to the remaining components. In addition, performance comparison experiments including ARIMA, XGBoost, LSTM, EMD-ARIMA, and CEEMDAN-LSTM models were conducted to evaluate the prediction performance of each model. The experimental results show that the proposed hybrid model outperforms the existing single models with the best performance indicator values in MAPE(3.8%), MAAPE(3.5%), and RMSE(0.35) metrics.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.997-1004
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• 2012

In enterprise software projects, performance issues have become more critical during recent decades. While developing software products, many performance tests are executed in the earlier development phase against the newly added code pieces to detect possible performance regressions. In our previous research, we introduced the framework to enable automated performance anomaly detection and reduce the analysis overhead for identifying the root causes, and showed Statistical Process Control (SPC) can be successfully applied to anomaly detection. In this paper, we explain the special performance trend in which the existing anomaly detection system can hardly detect the noticeable performance change especially when a performance regression is introduced and recovered again a while later. Within the fixed number of sampling period, the fluctuation gets aggravated and the lower and upper control limit get relaxed so that sometimes the existing system hardly detect the noticeable performance change. To resolve the issue, we apply dynamically tuned sampling window size based on the performance trend, and Fuzzy theory to find an appropriate size of the moving window.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.73-74
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• 2005

Shipping company and operators have to manage well to keep shipping schedules without problems in main engine. Specially operators have to operate main engine within the limit of operation point, and adjust related parameters to be operated safely and continuously. Also operators have ability to analyze fouling condition of hull through comparing data gotten from P-V curve and performance results of new building ships in trial with service ships. In this study, not only compared main engine performance results in shop trial and sea trial, but also investigated performance trend in accordance with the time elapsed for the service ship's diesel engine. They were confirmed as follows. First, shop trial load is higher than sea trial load but ship's speed is satisfied with owner's contract speed. Second as time goes by, load of service ship increases steadily and other parameters related with main engine shows variable change depend on main engine load increasing.

• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.11-16
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• 2010

This study examined the relative effect of participative and assigned goal setting on team performance. Participants were 30 college students and their typing speed was tested. They were ordered on the basis of the typing speed and were divided into 15 pairs, with the members of each pair having similar typing speed. Members in each pair were randomly assigned to the two experimental conditions. Participants were asked to type materials provided by the experimenter for 20 days. The dependent variable was the number of words typed. The results showed that there was no significant difference in performance between the two conditions. The results also showed that the difference in trend between two conditions was not statistically significant.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.789-798
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• 2000

The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.702-714
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• 2020

Stock investment is a personal investment technique that has gathered tremendous interest since the reduction in interest rates and tax exemption. However, it is risky especially for those who do not have expert knowledge on stock volatility. Therefore, it is well understood that accurate stock trend prediction can greatly help stock investment, giving birth to a volume of research work in the field. In order to compare different research works and to optimize hyper-parameters for prediction models, it is required to have an evaluation standard that can accurately assess performances of prediction models. However, little research has been done in the area, and conventionally used methods have been employed repeatedly without being rigorously validated. For this reason, we first analyze performance evaluation of stock trend prediction with respect to performance metrics and data composition, and propose a fair evaluation method based on prediction disparity ratio.