• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.21-29
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• 2019

This study analyzed the variability of drought risk based on trend analysis of dry-seasonal dam inflow located in upper river basins. To this, we used areal averaged precipitation and dam inflow of three upper river dams such as Soyang dam, Chungju dam, and Andong dam. We employed Mann-Kendall trend analysis and change point detection method to identify the significant trends and changing point in time series. Our results showed that significant decreasing trends (95% confidence interval) in dry-seasonal runoff rates (= dam inflow/precipitation) in three-dam basins. We investigated potential causes of decreasing runoff rates trends using changes in potential evapotranspiration (PET) and precipitation indices. However, there were no clear relation among changes in runoff rates, PET, and precipitation indices. Runoff rate reduction in the three dams may increase the risk of dam operational management and long-term water resource planning. Therefore, it will be necessary to perform a multilateral analysis to better understand decreasing runoff rates.

• 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.

• 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 Digital Convergence
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• v.20 no.3
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• pp.275-281
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• 2022

This paper intends to provide a more effective understanding of the management performance (survival and growth) of startups and to suggest methods that can be applied to empirical research related to startups in the future. Therefore, in this study, the effect of entrepreneurship, trend analysis, and government support on business performance (non-financial and financial) is studied. A total of 220 questionnaires were received, and 215 were adopted except for 5 insincere questionnaires. Therefore, it was evaluated based on statistical data of 215 companies surveyed by startup officials. The questionnaire was analyzed using the SPSS 28.0 statistical program. The results of the study confirmed that all three items of the hypothesis, government support, entrepreneurship, and trend analysis of start-ups all play a positive role regardless of the difference in financial and non-financial management performance.

• (The) Research of the performance art and culture
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• no.37
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• pp.437-464
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• 2018

This study used semantic network analysis to understand the academic identity and characteristics of the society of korean performance art and culture and to grasp the trend of the research. For this purpose, this study analyze the research trend of korean performance art and culture related papers based on 455 whole articles in the Journal of The Society of Korean Performance Art and Culture by the Korean Performance Art and Culture Association from 2000 to 2017. Through this research, the trends of The Society of Korean Performance Art and Culture in the period of time were identified, and the phenomenon of the performance culture field and the future development direction were suggested.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.456-459
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• 2002

It is lately issued studies on EVMS(Earned Value Management System) throughout construction industry, which is management system integrating cost and schedule effectively. So identifying importance and circumstance of introducing EVMS, CPI(Cost Performance Index) and SPI(Schedule Performance Index), which are critical components on schedule introducing EVMS, calculate and it intends to analyze the trend and problem of cost and time throughout project management, applying various statistical data analysis method.

• 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.

• Earthquakes and Structures
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• v.25 no.5
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• pp.369-383
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• 2023

Seismic resilience (SR) plays a vital role in evaluating and improving performance losses along with saving repair costs of structures from potential earthquakes. To further explore the developments, hotspots, and trend directions of SR, a total of 901 articles are obtained from the Web of Science (WoS) database. CiteSpace software is used to conduct a bibliometric analysis, which indicates an upward trend of publications in SR and explores the relationship of countries, journals, cited references, and keywords based on visual maps and detailed tables. Then, based on the results of the bibliometric analysis, a state-of-the-art review is conducted to further explore the current challenges and trend directions of SR. The trend directions can be divided into five categories: (a) SR assessments of infrastructure structures, (b) multi-hazard quantifications of SR, (c) seismic resilient structures, (d) refining and calibrating analytical models, and (e) multi-criteria decision-making frameworks for sustainability and SR.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.216-222
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• 2020

The purpose of this study was to predict the performance of female weightlifters using time series analysis. Based on this purpose, a time series analysis was used to calculate the performance prediction model for women(58kg) among the domestic women weightlifters who participated in the Olympics. As a result of creating time series data based on 10 years of record and then evaluating the sequential charts of each athlete group, the female athletes' records did not show any seasonality or difference. In addition, after examining the independence of the data through the creation of a time series model, it was shown that the models produced conformed to the criteria for compliance and that there was no difference in the data, but there was a trend. Accordingly, Holt linear trend analysis of the exponential smoothing model was applied. As a result of deriving the prediction model of the athletes through this process, it was found that the women (58kg) who participated in the Olympics continued to improve within the range of 166.11kg to 184.1kg.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.105-112
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• 2020

The study investigates and measures the impact of capital structure, profitability and financial performance on the success of the business organization. Capital structure of the business organization refers to the proportion of external funds and internal funds, i.e., debt and equity. In Saudi Arabia, petrochemicals companies are working on equity, but financial performance reflects negative trend for the period 2004 to 2016. The research is based upon secondary data available on the websites of petrochemicals companies of Saudi Arabia. Financial Ratio variability analysis and Trend Indices of financial ratios (TI_CBI) measure and compare the financial variability and sensitivity of financial ratios of the business organization. Correlation between Trend Indices (TI_CBI) of independent variable and dependent variables are to be calculated to know the impact of changes in debt equity on other dependent variables. The results reveal the unexpected performance of petrochemicals companies due to under-utilization of the resources caused by low demand and lower prices of the products governed by some internal and external factors. The study finds that size, demand, cost of production, profitable streams of products, and low cost capital in external funds are the factors responsible for overall growth development of the petrochemicals industry of Saudi Arabia.