• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.132-140
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• 2005

This study was conducted to develop regional site index equations for main tree species in Gangwon, Gyunggi-Chungcheong, Gyungsang, and Jeolla area of Korea, using environmental and soil factors obtained from a digital forest site map. Using the large data set obtained from the digital forest map, a total of 28 environmental and soil factors were regressed on site index by tree species for developing the best site index equations for each of the regions. The selected main tree species were Larix 1eptolepis, Pinus koraiensis, Pinus densiflora, Pinus thunbergii, and Quercus acutissima. Finally, four to five environmental and soil factors by species were chosen as independent variables in defining the best regional site index equations with the highest coefficients of determination $(R^2)$. For those site index equations, three evaluation statistics such as mean difference, standard deviation of difference and standard error of difference were applied to the data sets independently collected from fields within the region. According to the evaluation statistics, it was found that the regional site index equations by species developed in this study conformed well to the independent data set, having relatively low bias and variation. It was concluded that the regional site index equations by species had sufficient capability for the estimation of site productivity.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.3
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• pp.301-307
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• 2013

This study was evaluated high end research grade Near Infrared Reflectance Spectrophotometer (NIRS) to field grade multiple Near Infrared Reflectance Spectrophotometer (NIRS) for rapid analysis at fresh rice leaf at sight with 238 samples of fresh rice leaf during year 2012, collected Jeollabuk-do for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with 400 nm ~ 2500 nm during from year 2003 to year 2009, seven years collected fresh rice leaf database then trim and fit to field grade NIRS with 1200 nm ~ 2400 nm then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.005% differences, rapidly analysis for chemical constituents, Total nitrogen in fresh rice leaf within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless last during more than 8 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of fresh rice leaf analysis with NIRS at sight. Especially the agriculture products such as rice will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods global distance (GD) and neighbour distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Korean Journal of Microbiology
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• v.41 no.1
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• pp.24-37
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• 2005

This study was conducted to analyze the molecular epidemiological properties and to select the most efficient and reliable PCR method on 116 of Staphylococcus aureus (S. aureus) isolates from Korean cattle, black goat, pig, dog, chicken, mouse and also human clinical cases from hospital. The distribution patterns of SSG [species specific genes; coagulase (coa), protein A (spa), nuclease (nuc) and aroA (RsaI) gene] were analyzed by PCR method. Among the SSGs, the nuc-gene was found in all strains $(100\%)$ tested and followed by coa-gene $(87.9\%)$, spa-gene $(91.4\%)$ and aroA-gene $(26.7\%)$, in order. The genetic subtyping by RFLP method was performed on the coa [AluI] and aroA-gene [RsaI] PCR products. The mecA-gene PCR and PCR-RFLP techniques were chosen to detect and verify of MRSA strains. Only the human strains $(12.1\%)$ were detected the positive mecA-gene products (533 bp), which were divided into two specific bands [201 & 332 bp] by HhaI enzyme digestion. On coa-gene and spa-gene typing, coa-gene was typed with ten kinds of genotype and coa-3 type were determined as the most predominant genotype, while spa-gene was divided into eleven kinds of genotype and also spa-7 type were selected the most prevalent genotype based on their genetic variations. On the aroA and coa-gene subtyping by PCR-RFLP, aroA-gene products were discriminated with only seven types of genotype, while coa-gene products were further divided into an eleven genotype, respectively. In comparison of SID values of five PCR based typing methods, the coa-PCR-RFLP (SID0.894) was evaluated the most efficient and reliable tools and followed by coa-PCR (SID0.883) and aroA-PCR-RFLP (SID0.462), in order. In conclusion, we could determined that the coa-PCR-RFLP method was the most suitable genetic analysis tool for S. aureus and MRSA strains from domestic animals and humans.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.861-874
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• 2012

To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 $km^2$) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.4
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• pp.25-34
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• 2010

This study was conducted to develop evaluation indicators to improve athletic performance and operational management of golf courses and the results of the research are as follows. Through theoretical research and a preliminary professional survey, 15 on-going evaluations of golf course composition and operational management and 55 sub-evaluation indices were rejected while 10 on-going evaluations and 52 sub-evaluation indicators were reconfigured as final for environmental-friendliness, level of member services, level of human service of game personnel, difficulties of course, management level of the course, fairness of operational management, accessibility and location characteristic, traditions and ambiance of the golf club, quality of course, and course layout. When analyzing the important decision factors in golf course user preference evaluation indicators, the following contributed in the order of higher to lower contributions: the management level of the course, excellence of the course, level of human services for personnel, course layout and environmental-friendliness. When identifying the path coefficient of golf course evaluation indicators, the curvature of a hole and the length of the course had a causal effect on the 'course layout' section. Tournament facilities and various shot values had a causal relationship with 'excellence of the course', in the order of higher to lower, and convenience of waiting and fair allocation of reservations for 'fairness of operational management'. The history of the golf course and its environmental characteristics, history and culture of the region have relatively higher causal effects on 'traditions of the golf club' and geographical conditions on 'accessibility and location characteristics', pesticide and fertilizer usage and water pollution on 'environmental-friendliness', and member benefit and kindness of employees on 'level of member services'. The kindness and expertise of the game personnel had a relatively higher causal effect on the 'level of human services of game personnel', the location of tenning area, and location of OB and hazards on 'difficulties of course', and rough conditions and obstacles management on 'management level of the course'. There is a need to complete a systematic evaluation index system for golf course user preferences through future studies for a more detailed assessment, as well as a process to verify these evaluation indicators by application to domestic and international golf courses.

• 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.

• The KIPS Transactions:PartC
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• v.10C no.3
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• pp.377-386
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• 2003

This study suggested a technique to maintain an efficient core-based multicast tree using weighted clustering factors in mobile Ad-hoc networks. The biggest problem with the core-based multicast tree routing is to decide the position of core node. The distance of data transmission varies depending on the position of core node. The overhead's effect on the entire network is great according to the recomposition of the multicast tree due to the movement of core node, clustering is used. A core node from cluster head nodes on the multicast tree within core area whose weighted factor is the least is chosen as the head core node. Way that compose multicast tree by weighted clustering factors thus and propose keeping could know that transmission distance and control overhead according to position andmobility of core node improve than existent multicast way, and when select core node, mobility is less, and is near in center of network multicast tree could verification by simulation stabilizing that transmission distance is short.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.301-307
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• 2015

A bond-based peridynamic model has been shown to be capable of analyzing many of dynamic brittle fracture phenomena. However, there have been issued limitations on handling constitutive models of various materials. Especially, it assumes bonds act independently of each other, so that Poisson's ratio for 3D model is fixed as 1/4 as well as taking only account the bond stretching results in a volume change not a shear change. In this paper a state-based peridynamic model of dynamic brittle fracture is presented. The state-based peridynamic model is a generalized peridynamic model that is able to directly use a constitutive model from the standard theory. It permits the response of a material at a point to depend collectively on the deformation of all bonds connected to the point. Thus, the volume and shear changes of the material can be reproduced by the state-based peridynamic theory. For a linearly elastic solid, a plane stress model is introduced and the damage model suitable for the state-based peridynamic model is discussed. Through a convergence study under decreasing the peridynamic nonlocal region($\delta$-convergence), the dynamic fracture model is verified. It is also shown that the state-based peridynamic model is reliable for modeling dynamic crack propagatoin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1A
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• pp.19-30
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• 2012

Recently, vision-based dynamic deflection measurement techniques have significant interests and are getting more popular owing to development of the high-quality and low-price camcorder and also image processing algorithm. However, there are still several research issues to be improved including the self-vibration of vision device, i.e. camcorder, and the image processing algorithm in device aspect, and also the application area should be extended to measure three dimensional movement of floating structures in application aspect. In this study, vision-based dynamic motion measurement technique using multiple targets is proposed to measure three dimensional dynamic motion of floating structures. And also a new scheme to select threshold value to discriminate the background from the raw image containing targets. The proposed method is applied to measure the dynamic motion of large concrete floating quay in open sea area under several wave conditions, and the results are compared with the measurement results from conventional RTK-GPS(Real Time Kinematics-Global Positioning System) and MRU(Motion Reference Unit).

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.524-532
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• 2020

In this study, noise radiated from a high-speed fan-motor unit for a cordless vacuum cleaner is reduced by designing splitter blades on the existing impeller. First of all, in order to investigate the flow field through a fan-motor unit, especially impeller, the unsteady incompressible Reynolds-Averaged Navier-Stokes (RANS) equations are numerically solved by using computational fluid dynamic technique. With predicted flow field results as input, the Ffowcs Williams-Hawkings (FW-H) integral equation is solved to predict aerodynamic noise radiated from the impeller. The validity of the numerical methods is confirmed by comparing the predicted sound pressure spectrum with the measured one. Further analysis of the predicted flow field shows that the strong vortex is formed between the impeller blades. As the vortex induces the loss of the flow field and acts as an aerodynamic noise source, supplementary splitter blades are designed to the existing impeller to suppress the identified vortex. The length and position of splitter are selected as design factors and the effect of each design factor on aerodynamic noise is numerically analyzed by using the Taguchi method. From this results, the optimum location and length of splitter for minimum radiated noise is determined. The finally selected design shows lower noise than the existing one.