• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.184-190
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• 2006

Recently, Lee et al. have proposed an algorithm utilizing the signals from different paths by using bottom mounted simple linear array to estimate 3-D location of oceanic target. But this algorithm assumes that sound velocity is constant along depth of sea. Consequently, serious performance loss is appeared in real oceanic environment that sound speed is changed variously. In this paper, we present a 3-D near field localization algorithm for inhomogeneous sound speed. The proposed algorithm adopt localization function that utilize ray propagation model for multipath environment with linear sound speed profile(SSP), after that, the proposed algorithm searches for the instantaneous azimuth angle, range and depth from the localization cost function. Several simulations using linear SSP and non linear SSP similar to that of real oceans are used to demonstrate the performance of the proposed algorithm. The estimation error in range and depth is decreased by 100m and 50m respectively.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.1-8
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• 2024

Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which makes it possible to simultaneously evaluate both physiological and morphological parameters. Among the physiological and morphological parameters are classifying healthy and diseased plants, assessing the severity of the disease, differentiating the types of pathogens, and identifying the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. Plant diseases cause significant economic losses in agriculture around the world as the symptoms of diseases usually appear when the plants are infected severely. Early detection, quantification, and identification of plant diseases are crucial for the targeted application of plant protection measures in crop production. Hence, this can be done by possible applications of hyperspectral sensors and platforms on different scales for disease diagnosis. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation, and identification of diseases, estimation of disease severity, and phenotyping of disease resistance of genotypes. This review provides a deeper understanding, of basic principles and implementation of hyperspectral sensors that can measure pathogen-induced changes in plant physiology. Hence, it brings together critically assessed reports and evaluations of researchers who have adopted the use of this application. This review concluded with an overview that hyperspectral sensors, as a non-invasive system of measurement can be adopted in early detection, identification, and possible solutions to farmers as it would empower prior intervention to help moderate against decrease in yield and/or total crop loss.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.98-106
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• 2019

The coefficient and exponent of the MUSLE(Modified Universal Soil Loss Equation) runoff factor in the SWAT(Soil and Water Assessment Tool) model are 11.8 and 0.56 respectively, which are equally applied to the estimation of soil erosion regardless of land use. they could derive overestimation or underestimation of soil erosion, which can cause problems in the selection of soil erosion-vulnerable area and evaluation of reduction management. However, there are no studies about the estimation of coefficients and exponent for the MUSLE runoff factor by land use and their applicability to the SWAT model. Thus, in order to predict soil erosion and sediment behavior accurately through SWAT model, it is necessary to estimate the coefficient and exponent of the MUSLE runoff factor by land use and evaluate its applicability. In this study, the coefficient and exponent of MUSLE runoff factor by land use were estimated for Gaa-cheon Watershed, and the differences in soil erosion and sediment from SWAT model were analyzed. The coefficient and exponent of runoff factor estimated by this study well reflected the characteristics of soil erosion in domestic highland watershed. Therefore, in order to apply the MUSLE which developed based on observed data of US agricultural basin to the domestic watershed, it is considered that a sufficient modification and supplementation process for the coefficient and exponent of the MUSLE runoff factor depending on land use is necessary. The results of this study can be used as a basic data for selecting soil erosion vulnerable area in the non-point source management areas and establishing and evaluating soil erosion reduction management.

• Journal of The Korean Society of Grassland and Forage Science
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• v.18 no.4
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• pp.323-328
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• 1998

A field experiment was carried out to determine the effects of chemical and mechanical treatment at mowing on the field drying rate and hay quality of autumn oat (Avena sativa L.). The chemical drying agent/mower conditioner ($K_2CO_3$ 2%, conditioning, $K_2CO_3$ 2% + conditioning and control) were treated at different harvest stages (late boot, heading and bloom stage) for hastening hay manufacture in the autumn of 1996. After field dry, square bales were made by hay baler, and the dry matter(DM) loss and visual estimation of oat hay were evaluated after storing two months. In general, the field drying rate of oat was slow, regardless of harvest stage. Mechanical and chemical + mechanical treatment were effective, but the effectiveness of chemical alone was very low. With mower conditioning, the duration of field dry was shortened by 2 days compared with control. The DM loss of hay was higher at boot stage(51.4%) than at heading stage (21.1%), and the DM loss was reduced by mechanical and chemical + mechanical combined treatment. The visual score (leafiness, green color, odor and softness) of hay after storing was high in mechanical and chemical + mechanical, but the score by chemical alone was very low. The nutritive value (ADF, NDF, digestibility, and relative feed value) of hay was also high with treatment of mechanical and chemical + mechanical, but the quality by chemical alone was similar compared with control. In conclusion, mower conditioning can enhance the field drying rate of autumn oat, but the drying efficiency of the chemical drying agent was very low. However, it is suggested that hay-making of oat in autumn is very hard though using mower conditioner.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.106-120
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• 2006

Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.

• Journal of Bio-Environment Control
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• v.11 no.4
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• pp.151-156
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• 2002

Root zone cooling, such as soil or nutrient solution cooling, is less expensive than air cooling in the whole greenhouse and is effective in promoting root activity, improving water absorption rate, decreasing plant temperature, and reducing high temperature stress. The heat transfer of a soil cooling system in a plastic greenhouse was analyzed to estimate cooling loads. The thermal conductivity of soil, calculated by measured heat fluxes in the soil, showed the positive correlation with the soil water content. It ranged from 0.83 to 0.96 W.m$^{[-10]}$ .$^{\circ}C$$^{[-10]}$ at 19 to 36％ of soil water contents. As the indoor solar radiation increased, the temperature difference between soil surface and indoor air linearly increased. At 300 to 800 W.m$^{-2}$ of indoor solar radiations, the soil surface temperature rose from 3.5 to 7.$0^{\circ}C$ in bare ground and 1.0 to 2.5$^{\circ}C$ under the canopy. Cooling loads in the root zone soil were estimated with solar radiation, soil water content, and temperature difference between air and soil. At 300 to 600 W.m$^{-2}$ of indoor solar radiations and 20 to 40％ of soil water contents,46 to 59 W.m$^{-2}$ of soil cooling loads are required to maintain the temperature difference of 1$0^{\circ}C$ between indoor air and root zone soil.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.68-76
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• 2021

Foodborne outbreaks frequently occur worldwide and result in huge economic losses. It is the therefore important to estimate the costs associated with foodborne diseases to minimize the economic damage. At the same time, it is difficult to accurately estimate the economic loss from foodborne disease due to a wide variety of cost components. In Korea, there are a limited number of analytical studies attempting to estimate such costs. In this study we investigated the components of economic cost used in foreign countries to better estimate the cost of foodborne disease in Korea. Seven recent studies investigated the cost components used to estimate the cost of foodborne disease in humans. This study categorized the economic loss into four types of cost: direct costs, indirect costs, food business costs, and government administration costs. The healthcare costs most often included were medical (outpatient) and hospital costs (inpatient). However, these cost components should be selected according to the systems and budgets of medical services by country. For non-healthcare costs, several other studies considered transportation costs to the hospital as an exception to the cost of inpatient care. So, further discussion is needed on whether to consider inpatient care costs. Among the indirect costs, premature mortality, lost productivity, lost leisure time, and lost quality of life/pain, grief and suffering costs were considered, but the opportunity costs for hospital visits were not considered in any of the above studies. As with healthcare costs, government administration costs should also be considered appropriate cost components due to the difference in government budget systems, for example. Our findings will provide fundamental information for economic analysis associated with foodborne diseases to improve food safety policy in Korea.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.4
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• pp.255-263
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• 2009

This study assessed the facility volume distribution for artificial reefs (ARs) deployed at the sea bottom in fishing grounds in the Busan Sea region, and estimated the efficient use of volume in the initial AR group. Analysis of the volume of AR facilities in the Busan Sea region indicated that the quantity and surface areas of deployed facilities varied greatly between 1997 and 2004. However, a rapid decrease in AR facility volume after 2003 indicated an increased use of different kinds of ARs, such as steel or ceramic ARs. And the results revealed that a total of 2,777 AR facilities were deployed in the Gijang sea region with a founding ratio of 89%; corresponding numbers for the Heaundae and Namgu sea region were 7,691 and 84.9%, and 905 and 96% for the cubic type of AR in the Saha and Gangseo sea regions. The analysis indicated that ARs deployed in the Busan sea region maintained a good conservation ratio of more than 85%. The loss in AR volume (approximately 15%) was due to subsidence, breakaway, and incomplete deployment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5452-5457
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• 2012

It is saving material cost and construction cost by replacing conventional building materials, and It has advantages for aesthetic value. In the Europe, the United States, Japan and other country research about BIPV is actively being carried out and marketability is also being infinity expanding. Arch type PV systems efficiency characteristics is different depending on PV array's directly connection, parallel connection and arches angle, but is a lack of analysis on this nowadays. When the arch type PV system design up, they consider about aesthetic value and they didn't consider about generation efficiency. In this paper, we try to improve the efficiency through optimization of arch type PV system and estimation of the efficiency parameters of the arch type PV system, such as latitude, longitude, temperature, insolation, arch angle and each kind loss from system organization. For improving Arched PV system efficiency, proposed multiple control inverter system, and using simulation tool of Arched PV system "Solar pro", flat-plate type and many arch type PV system configuration the driving characteristics were compared and analyzed.