Effect of Total Leaf Numbers on the Growth and Fruit Quality in Muskmelon Plants Showing Leaf Yellowing Symptoms

This study was conducted to evaluate the influence of total leaf numbers on the growth, net formation of fruits, and occurrence of leaf yellowing symptoms (LYS) in muskmelon plants. The growth and development of LYS on muskmelon plants having 25, 30, and 35 fully expanded leaves on the vine were compared to those of the control plant having 20 leaves. Plant height, leaf area, root fresh weight, and root dry weight increased as the number of leaves increased. Plants with 35 leaves showed the greatest plant growth. Net photosynthetic rate was positively related to increasing leaf numbers with plants having over 25 leaves showing the greatest photosynthetic rates. On the other hand, there were no significant differences in chlorophyll content and root activity among treatments with different leaf numbers. The ratio of LYS infection was also greater in plants having 25-30 leaves, than in those having leaf numbers. Plants with different leaf numbers and LYS infection showed a variation in fruit quality, although LYS did not significantly affect fruit quality except net index. The plants having 20 leaves that showed LYS developed fruits that had significantly smaller flesh (mesocarp) thickness than, the plants having greater numbers of leaves. The higher sugar contents of fruits were found in the plants having 35 leaves whether they showed LYS (12.1°Bx) or not (12.5°Bx). Therefore, leaving more than 25 healthy leaves per plant was recommended for minimizing damage from LYS.OAIID:oai:osos.snu.ac.kr:snu2015-01/104/0000027607/11ADJUST_YN:NEMP_ID:A075898DEPT_CD:517CITE_RATE:0FILENAME:(이희주)effect_of_total_leaf_numbers_on_the_growth_and_fruit_quality_in_muskmelon_plants_showing_leaf_yell··.pdfDEPT_NM:식물생산과학부CONFIRM:

Flexibility-Based Evaluation of Variable Generation Acceptability in Korean Power System

This study proposes an evaluation method for variable generation (VG) acceptability with an adequate level of power system flexibility. In this method, a risk index referred to as the ramping capability shortage expectation (RSE) is used to quantify flexibility. The RSE value of the current power system is selected as the adequate level of flexibility (i.e., RSE criterion). VG acceptability is represented by the VG penetration level for the RSE criterion. The proposed evaluation method was applied to the generation expansion plan in Korea for 2029 in order to examine the validity of the existing plan for VG penetration. Sensitivity analysis was also performed to analyze the effects of changes in system uncertainty on VG acceptability. The results show that the planned VG penetration level for 2029 can improve by approximately 12% while securing flexibility

Monitoring Volatility Change for Time Series Based on Support Vector Regression

This paper considers monitoring an anomaly from sequentially observed time series with heteroscedastic conditional volatilities based on the cumulative sum (CUSUM) method combined with support vector regression (SVR). The proposed online monitoring process is designed to detect a significant change in volatility of financial time series. The tuning parameters are optimally chosen using particle swarm optimization (PSO). We conduct Monte Carlo simulation experiments to illustrate the validity of the proposed method. A real data analysis with the S&P 500 index, Korea Composite Stock Price Index (KOSPI), and the stock price of Microsoft Corporation is presented to demonstrate the versatility of our model

Net Load Carrying Capability of Generating Units in Power Systems

This paper proposes an index called net load carrying capability (NLCC) to evaluate the contribution of a generating unit to the flexibility of a power system. NLCC is defined as the amount by which the load can be increased when a generating unit is added to the system, while still maintaining the flexibility of the system. This index is based on the flexibility index termed ramping capability shortage expectation (RSE), which has been used to quantify the risk associated with system flexibility. This paper argues that NLCC is more effective than effective load carrying capability (ELCC) in quantifying the contribution of the generating unit to flexibility. This is explained using an illustrative example. A case study has been performed with a modified IEEE-RTS-96 to confirm the applicability of the NLCC index. The simulation results demonstrate the effect of operating conditions such as operating point and ramp rate on NLCC, and show which kind of unit is more helpful in terms of flexibility

Impact of the Complementarity between Variable Generation Resources and Load on the Flexibility of the Korean Power System

This study examines the effect of the complementarity between the variable generation resources (VGRs) and the load on the flexibility of the power system. The complementarity may change the ramping capability requirement, and thereby, the flexibility. This effect is quantified using a flexibility index called the ramping capability shortage expectation (RSE). The flexibility is evaluated for different VGR mix scenarios under the same VGR penetration level, and an optimal VGR mix (i.e., one that maximizes flexibility) is obtained. The effect of the complementarity of the wind and PV outputs on the flexibility is investigated for the peak-load day of 2016 for the Korean power system. The result shows that the RSE value for the optimal VGR mix scenario is 6.95% larger than that for the original mix scenario

Flexibility-Based Reserve Scheduling of Pumped Hydroelectric Energy Storage in Korea

The high penetration of renewable energy resources has made it harder to secure a flexible power system. Accordingly, this has become an issue in operating power systems. As a possible solution, pumped hydroelectric energy storage (PHES) has received much attention because of its fast start-up and ramp characteristics. This study proposes a flexibility-based reserve scheduling method for PHES. In this method, the reserve scheduling of PHES was conducted to improve flexibility; the associated risk index was termed the ramping capability shortage expectation (RSE). The peak-load days in 2016 and 2029 were selected to examine the applicability and performance of the proposed method. Results indicate that the proposed method can improve the flexibility by 4.45% for 2016 and 0.9% for 2029, respectively

One-class classification-based monitoring for the mean and variance of time series

© 2022 John Wiley & Sons Ltd.This study develops a statistical process control (SPC) chart that simultaneously monitors the mean and variance of general location-scale time series models. Integrating the one-class classification (OCC) technique (the support vector data description (SVDD) particularly), we formulate a nonlinear boundary to enclose in-control observations for detecting structural anomalies. The control limits obtained from SVDD can capture a more sophisticated structural change and are also controllable. We particularly propose a control chart formulated using location-scale residuals. This further enhances our ability to detect shifts in the mean, variance, and various model parameters. The proposed OCC control chart is compared with some traditional charts and is validated by conducting simulations under various circumstances. Moreover, we consolidate applicability in a real data analysis by demonstrating its functionality with the S&P 500 index.N

Robust control chart for nonlinear conditionally heteroscedastic time series based on Huber support vector regression.

This study proposes a control chart that monitors conditionally heteroscedastic time series by integrating the Huber support vector regression (HSVR) and the one-class classification (OCC) method. For this task, we consider the model that incorporates nonlinearity to the generalized autoregressive conditionally heteroscedastic (GARCH) time series, named HSVR-GARCH, to robustly estimate the conditional volatility when the structure of time series is not specified with parameters. Using the squared residuals, we construct the OCC-based control chart that does not require any posterior modifications of residuals unlike previous studies. Monte Carlo simulations reveal that deploying squared residuals from the HSVR-GARCH model to control charts can be immensely beneficial when the underlying model becomes more complicated and contaminated with noises. Moreover, a real data analysis with the Nasdaq composite index and Korea Composite Stock Price Index (KOSPI) datasets further disclose the validity of using the bootstrap method in constructing control charts