• The Korean Journal of Ecology
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• v.1 no.1
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• pp.17-23
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• 1977

Flowering dates of 389 plant species in the Hongneung Arboretum, Seoul, had been recorded from 1968 through 1975. The thermal analysis on the air temperature as the key factor determining the first flowering date, with climatological data obtained in the Arboretum, were undertaken by Nuttonson's Index (1948) and Lindsey & Newman's Index (1956). The results and conclusion in this study are as follow; Peak in the bell shape distribution curve of the species and first flowering dates, largely, was early May. Flower spans of most species were 10 to 20 days, neverthless, some species flower only a few days while others may stay flowering a hundred days even more. Increase-curves of summation temperature from early spring through late-summer showed almost the same mode in both Nuttonson;s Index (Tn) and Lindsey & Newman's Index (T1). These Indices manifested the exponential curve, increasing slowly at the beginning of spring chiefly but rapidly from the middle part of April. The equation of the linear relationahip between Tn and Tl as far as in thisstudy is as follow. Tl=230Tn It appears that the distribution of summation temperature, below Tn=400°C·day, affects the first flowering, even though it could be modified somehow by the distribution of precipitation, day length and others. Nuttonson's Index (Tn.f) and Lindsey & Newman's Index (Tl.f) upon the thermal amount first flowering dates have been respectively simulated as follow. Tn.f=θa + C Tl.f=230θa + 230C where θ is air temperature 10°C, a and C are a constant.

• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.100-106
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• 2022

The relationships between river length and weir density versus fish species observed were analyzed for 210 local rivers in the Seomjin River system (SJR). A nonlinear exponential relationship between river length and number of fish species were observed. Model coefficient was 0.03 and coefficient of determinant (R²) was 0.59, meaning that about 59.0% of total variance was explained by river length variable. Predicted value by model and observed number of species showed a difference. About 110 local rivers (about 52.4%) showed lower value than predictive value. The average index of weir's density (IWD) in the SJR was about 2.7/km, which was significantly higher than that of other river basins. As a result of nonparametric 2-Kimensional Kolmogorov-Smirnov (2-DKS) analysis based on the IWD, the threshold value affecting fish diversity was about 2.5/km (D_max=0.048, p<0.05). Above the threshold value, it means that the number of fish species would be decreased. In fact, the ratio of the expected species to the observed species was lowered to less than 70%, when the IWD is higher than the threshold value. To maintain aquatic ecological connectivity in future, it is necessary to manage IWD below the threshold value.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.597-604
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• 2020

Muskingum, a hydrologic channel flood routing, is a method of predicting outflow by using the relationship between inflow, outflow, and storage. As many studies for Muskingum model were suggested, parameters were gradually increased and the calculation process was complicated by many parameters. To solve this problem, an optimization algorithm was applied to the parameter estimation of Muskingum model. This study applied the Advanced Nonlinear Muskingum Model considering continuous flow (ANLMM-L) to Wilson flood data and Sutculer flood data and compared results of the Linear Nonsingum Model incorporating Lateral flow (LMM-L), and Kinematic Wave Model (KWM). The Sum of Squares (SSQ) was used as an index for comparing simulated and observed results. Exponential Bandwidth Harmony Search with Centralized Global Search (EBHS-CGS) was applied to the parameter estimation of ANLMM-L. In Wilson flood data, ANLMM-L showed more accurate results than LMM-L. In the Sutculer flood data, ANLMM-L showed better results than KWM, but SSQ was larger than in the case of Wilson flood data because the flow rate of Sutculer flood data is large. EBHS-CGS could be appplied to be appplicable to various water resources engineering problems as well as Muskingum flood routing in this study.

• Journal of radiological science and technology
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• v.41 no.6
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• pp.533-538
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• 2018

As the use of digital radiographic system has been expanded, there are some concerns an increase about in patient of radiation dose. Therefore, International Electro-technical Commission (IEC) has been proposed a standard foe exposure index (EI). In this study, the EI was measured on human chest model using computed radiography (CR). Radiation quality used RQA5 of IEC62494-1. After acquiring the chest anterior posterior image (Chest AP) by using the phantom, the EI was obtained by applying the system response. In this study, we have analyzed the images with the detector size (Full filed ROI) and the optimized image (Fit filed ROI). The EI increased proportionally with radiation dose increase. Due to the discrete increase in pixel value, the EI showed an exponential increase. The discrete increase in noise equivalent quanta (NEQ) resulted in a discrete increase in the EI. The EI of the two images used in this study increased with increasing NEQ but showed different increments. For the measurement of the EI, IEC standards must be followed. The EI should be used as an index to evaluate the image quality for quality control of X-ray image rather than as an indicator of exposure dose. When calculating the EI, the system response should be applied depending on whether or not the grid is used. The size of the field should be obtained by including only the necessary parts.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1078-1086
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• 2009

This paper presents a Fourier based algorithm for estimating the parameters of the low frequency oscillating modes. The proposed methods estimates various parameters(frequency, damping factor, mode magnitude, phase) by fitting Fourier spectrum and phase with a damped exponential cosine function. Dominant frequency is selected by taking frequency corresponding to the peak spectrum, and damping factor is estimated using the left/right spectra of Fourier spectrum. In addition, mode magnitude is calculated by the normalized peak spectrum, and phase is estimated from spectrum phase. Also, we introduce an accuracy index in order to determine the accuracy of the estimated parameters, and the index is calculated using the deviations of the peak spectrum and the left/right spectra. The parameter estimation methods proposed in this paper include very simple arithmetical processes, so the algorithms are simple and the calculation speed is very fast. The proposed methods are applied to test functions with two dominant modes. The results show that the proposed methods are highly applicable to low frequency parameter estimation.

• Textile Coloration and Finishing
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• v.21 no.1
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• pp.59-66
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• 2009

The seven kinds of polyester fabrics having different fabric characteristics were investigated in terms of their dyeing levelness under various liquor ratios. The levelness was evaluated statistically from color strength obtained at different sections of each piece of dyed fabrics. The color strength data were analyzed using a exponential decay function of 3 parameters, $y=y_0+ae^{-bx}$. The b value of the function was used as a index of sensitiveness of dependence on liquor ratio of levelness. The index, b value, showed a linear proportional relationship to thickness of fabrics. Average unlevelness of dyeings exhibited a inverse proportional relationship to both weight and thickness of fabrics.

• The Korean Journal of Ecology
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• v.7 no.2
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• pp.74-84
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• 1983

The dominant species of the sand vegetation in the western coast of Korea were Carex pumila, Ischaemum antheporoides, Calystegia soldanella, Carex kobomugi and Imperata cylindrica var. koenigii. The salt content of the sand dune soil and of the atmosphere of surveyed areas ranged from 3.93 to 13.86 mg% and from 25.81 to 168.86mg% respectively. Between the salt content of the atmosphere and that of the soil positive relationship was found. Species density and Simpson's index increased with the distance from the coast, the former was exponential, however, the latter was linear. The composition of biological types in the investigated stands were H-D4-R1-3-e or H-D4-R1-3-t. Relative numbers of psammophytes and rhizome psammophytes decreased with the distance from the coast, but those of other plants increased. The standing crop of the sand dune vegetation ranged from 0.04 to 491.64g/m2 and the average 27.77g/m2. This was varied as the stands and showed a linear increment as the distance from the coast was increased. The salt content of atmosphere significantly affected the density, T/R ratio in the standing crop and Simpson's index. The salt content of soil showed similar tendency on the density and the T/R ratio.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.10-12
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• 2003

This study was to monitor changes of leaf area index (LAI) and normalized difference vegetation index (NDVI), calculated from ground-based remotely sensed high resolution reflectance spectra, during rice (Oryza sativa L. cv. TNG 67) growth so as to determine their relationships and the optimum time period to use these parameters for yield prediction. Field experiments were conducted at the experimental farm of TARI to obtain various scales of grain yield and values of LAI and NDVI in the first and the second cropping seasons of 2001-2002. It was found that LAI and NDVI can be mutually estimated through an exponential relationship, and hence plant growth information and spectral remote sensing data become complementary counterparts through this linkage. Correlation between yield and LAI was best fitted to a nonlinear function since about 7 weeks after transplanting (WAT). The accumulated and the mean values of LAI from 15 days before heading (DBH) to 15 days after heading (DAH) were the optimum time period to predict rice yield for First Crops, while values calculated from 15 DBH to 10 DAH were the optimal timing for Second Crops.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.151-151
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• 2019

Because drought is a complex and stochastic phenomenon in nature, statistical approaches for drought assessment receive great attention for water resource planning and management. Generally drought characteristics such as severity, duration and intensity are modelled separately. This study aims to develop a relationship between drought characteristics using a bivariate copula model. To achieve the objective, we calculated the Standardized Precipitation Index (SPI) using rainfall data at 6 rain gauge stations for the period of 1961-1999 in Jehlum River Basin, Pakistan, and investigated the drought characteristics. Since there is a significant correlation between drought severity and duration, they are usually modeled using different marginal distributions and joint distribution function. Using exponential distribution for drought severity and log-logistic distribution for drought duration, the Galambos copula was recognized as best copula to model joint distribution of drought severity and duration based on the KS-statistic. Various return periods of drought were calculated to identify time interval of repeated drought events. The result of this study can provide useful information for effective water resource management and shows superiority against univariate drought analysis.