• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.06a
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• pp.53-80
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• 1999

Productivity and environmental conservation in nowadays trade-off and serious problem in agriculture. Precision farming is developing for solving the trade-off problem using systems approach and variable management. The systems approach is attributed to aiming at information-oriented agriculture, environmental-friendly sustainable agriculture, and complex system optimization . The variable management is composed of describing variability , variable-rate technology and decision support system. Three levels of technology development and three farming strategies are introduced for having a prospect. Describing the variability is the first step to promote it. Precision farming could be available for small scale farming as well as big scale farming. Paddy field precision farming will undergo in its distinctive way.

• School Mathematics
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• v.16 no.4
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• pp.727-743
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• 2014

The concepts of sample and sampling are central to the statistical thinking and foundations of the statistical literacy, so we need to be emphasized their importance in the statistics education. However, many researches which dealt with samples only analyze textbooks or students' responses. In this study, the concept of sample is addressed by a historical consideration which is one aspect of the didactical analysis. Moreover, developing concept of sample is analyzed from the preceding studies about the statistical literacy, considering the sample representativeness and the sampling variability. The results say that the historical process of developing the concept of sample can be divided into three step: understanding the sample representativeness; appearing the sample variance; recognizing the sampling variability. Above all, it is important to aware and control the sampling variability, but many related researches might not consider sample variability. Therefore, it implies that the awareness and control of sampling variability are needed to reflect to the teaching-learing of sample for developing the students' statistical literacy.

• 한국체육학회지인문사회과학편
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• v.57 no.6
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• pp.263-272
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• 2018

This study examined the association of gait variability and physical fitness with frailty status in older women. In a cross-sectional design, 168 elderly women, aged 65 years and older (75.07±5.40 years), measured body composition, gait parameters gait variability, physical fitness variables, MMSE-DS and CES-D. Subjects were classified as robust, pre-frail, and frailty based on the Fried et al.(2001) criteria for frailty weight loss, exhaustion, low hand-grip strength, low gait speed, and physical inactivity. Logistic regression analyses were used to determine the odds ratio (ORs) and 95% confidence interval (CI) of frailty status for having gait variability and physical fitness levels. Compared to the robust group (OR=1), the frailty group had significantly higher ORs of having terminal double limb stance (OR=1.48, 95% CI=0.10-2.21, p=.049), step cadence (OR=2.06, 95%CI=1.20-3.43, p=.009) variability, and significantly lower ORs of having upper-strength (OR=0.49, 95%CI=0.31-0.77, p=.002) even after adjusting for age, education, comorbidity, K-IADL, MMSE-KC and CES-D score. The finding of this study suggested that terminal double limb stance, step cadence and upper body muscular strength were independent predictors of frailty.

• Physical Therapy Korea
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• v.30 no.4
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• pp.268-274
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• 2023

Background: Ankle sprains occur frequently among humans who undertake various body movements. Diverse walking environments and dual tasks, that can affect ankle sprains, have been studied. However, there is a lack of research on inter-trial variability according to the changes in gait speed. Objects: The purpose of this study was to compare the adaptive ability of walking between the subjects with chronic ankle instability and healthy adults while performing a walking task with different walking speeds. Methods: In this study, 24 people in the chronic ankle instability group and 24 people in the healthy ankle group were selected as subjects. The length of the pre-measurement and the actual walking measurement were both set to 4.6 m. Once the subjects entered the measurement section, they changed their gait speed according to the randomly assigned speed change. Gait was measured twice and the average value was used for the analysis. Results: The coefficient of variation (CV) of cycle time in subjects with chronic ankle instability showed a significant difference in all cases except when the subjects changed their speed from preferred to slow and from slow to preferred. The CV of step length demonstrated a significant difference in all cases except for the change from slow to preferred and from preferred to fast. The cycle time and step length differential showed a significant difference only when the subjects changed the speed from slow to fast. Conclusion: The subjects with chronic ankle instability were found to have significantly reduced walking adaptability while performing inter-trial variability tasks with different gait speeds compared to healthy subjects.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.707-723
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• 2020

In this study, a decision tree type of quality control (QC) method was developed to improve the temporal-spatial representation and accuracy of the visibility data being operated by the Korea Meteorological Administration (KMA). The quality of the developed QC method was evaluated through the application to the 3 years (2016.03-2019.02) of 290 stations visibility data. For qualitative and quantitative verification of the developed QC method, visibility and naked-eye data provided by the KMA and QC method of the Norwegian Meteorological Institute (NMI) were used. Firstly, if the sum of missing and abnormal data exceeds 10% of the total data, the corresponding point was removed. In the 2nd step, a temporal continuity test was performed under the assumption that the visibility changes continuously in time. In this process, the threshold was dynamically set considering the different temporal variability depending on the visibility. In the 3rd step, the spatial continuity test was performed under the assumption of spatial continuity for visibility. Finally, the 10-minute visibility data was calculated using weighted average method, considering that the accuracy of the visibility meter was inversely proportional to the visibility. As results, about 10% of the data were removed in the first step due to the large temporal-spatial variability of visibility. In addition, because the spatial variability was significant, especially around the fog area, the 3rd step was not applied. Through the quantitative verification results, it suggested that the QC method developed in this study can be used as a QC tool for visibility data.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.139-145
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• 2019

This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.377-382
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• 2016

In 2013, a total capacity of 591.3 MW of installed wind power generation was achieved in Korea, with a total of 1,139 MWh of wind energy generated that year. More wind power plants will be installed in the coming years, and it is important to develop methods to reduce the output variability of these resources so as to provide stable power to the power grid of Korea. In this regard, this paper proposes the use of energy storage system (ESS) as a means to stabilize the output variability of wind power plants. Presented in this paper is a method that uses Discrete Fourier Transform (DFT) to determine the ESS capacity needed to provide a stable power output for ancillary services such as frequency regulation, economic dispatch, and emergency reserves. In the first step of the proposed method, four regions (namely, Samdal, Yeongdeok, Yeongyang, and Gangwon) in Korea that had the most wind power generation capacity were selected for analysis. In the second step, the individual and aggregated wind power outputs of the selected regions in 2013 were obtained This information was then used in the third step, where DFT analysis of the power outputs was used to drive the magnitudes of the output variation. And finally, the ESS capacity requirements needed to provide different ancillary services were determined based on the magnitudes of the output variation.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.435-446
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• 2000

Statistical process control(SPC) and engineering process control(EPC) are two strategies for quality improvement that have been developed independently. EPC seeks to minimize variability by adjusting compensatory variables in order to make the process level close to the target, while SPC seeks to reduce variability by monitoring and eliminating causes of variation. One purpose of this paper is to propose the IMA(0,1,1) model as the in-control process model. For the out-of-control process model we consider two cases; one is the case with a step shift in the level, and the other is the case with a change in the nonstationarity. Another purpose is to suggest the use of an integrated process control procedure with adjustment and monitoring, which can consider the proposed process model effectively. An integrated control procedure will improve the process control activity significantly for cases of the proposed model, when compared to the procedure of using either EPC or SPC, since EPC will keep the process close to the target and SPC will eliminate special causes.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.773-788
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• 2000

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for processes quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation. while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been needs for a process control proceduce which combines the tow strategies. This paper considers a combined scheme which simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an integrated moving average(IMA) process with a step shift. The EPC part of the scheme adjusts the process back to target at every fixed monitoring intervals, which is referred to a repeated adjustment scheme. The SPC part of the scheme uses an exponentially weighted moving average(EWMA) of observed deviation from target to detect special causes. A Markov chain model is developed to relate the scheme's expected cost per unit time to the design parameters of he combined control scheme. The expected cost per unit time is composed of off-target cost, adjustment cost, monitoring cost, and false alarm cost.

• Journal of Biosystems Engineering
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• v.39 no.1
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• pp.39-46
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• 2014

Purpose: Monitoring and control of environmental condition is highly important for optimum control of the conditions, especially in greenhouses and plant factories, and the condition is not uniform within the facility. Objectives of the study were to investigate variability in soil water content and to provide information useful for better irrigation control. Methods: Experiments were conducted in a strawberry-growing greenhouse (greenhouse 1) and a cherry tomato-growing greenhouse (greenhouse 2) in winter. Soil water content, electrical conductivity (EC), and temperature were measured over the entire area, at different distances from an irrigation pump, and on ridge and furrow areas. Results: When measured over the entire greenhouse area, soil water content decreased and temperature and electrical conductivity increased over time from morning to afternoon after irrigation. Water content decreased by distance from the irrigation pump up to 70 m and increased after that, and temperature showed an inverse pattern. Soil water contents on the ridge were lower than those on the furrow, and the differences were 10.2~18.4%, indicating considerable variability. The lowest EC were observed on the furrow and highest values were observed on the ridge. Soil water contents were less and temperature levels were greater at the window side than in the center locations. Conclusions: Selection of number and location of soil water content sensor would be the first step for better water content monitoring and irrigation control. Results of the study would provide basic data useful for optimum sensor location and control for underground greenhouse environment.