• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.176-183
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• 2001

Loblolly pine (Pinus taeda L.) is the most economically important timber producing species in the southern United States. Much attention has been given to predicting diameter distributions for the solution of multiple-product yield estimates. The three-parameter Weibull diameter distribution yield prediction systems were developed for loblolly pine plantations. A parameter recovery procedure for the Weibull distribution function based on four percentile equations was applied to develop diameter distribution yield prediction models. Four percentiles (0th, 25th, 50th, 95th) of the cumulative diameter distribution were predicted as a function of quadratic mean diameter. Individual tree height prediction equations were developed for the calculation of yields by diameter class. By using individual tree content prediction equations, expected yield by diameter class can be computed. To reduce rounding-off errors, the Weibull cumulative upper bound limit difference procedure applied in this study shows slightly better results compared with upper and lower bound procedure applied in the past studies. To evaluate this system, the predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level to check if any significant differences existed. Statistically, no significant differences were detected based on the data from 516 evaluation data sets. This diameter distribution yield prediction system will be useful in loblolly pine stand structure modeling, in updating forest inventories, and in evaluating investment opportunities.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.335-346
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• 2016

This study produced the parameter maps of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall generation model across South Korea and developed and validated the web application that automates the process of rainfall generation based on the produced parameter maps. To achieve this purpose, three deferent sets of parameters of the MBLRP model were estimated at 62 ground gage locations in South Korea depending on the distinct purpose of the synthetic rainfall time series to be used in hydrologic modeling (i.e. flood modeling, runoff modeling, and general purpose). The estimated parameters were spatially interpolated using the Ordinary Kriging method to produce the parameter maps across South Korea. Then, a web application has been developed to automate the process of synthetic rainfall generation based on the parameter maps. For validation, the synthetic rainfall time series has been created using the web application and then various rainfall statistics including mean, variance, autocorrelation, probability of zero rainfall, extreme rainfall, extreme flood, and runoff depth were calculated, then these values were compared to the ones based on the observed rainfall time series. The mean, variance, autocorrelation, and probability of zero rainfall of the synthetic rainfall were similar to the ones of the observed rainfall while the extreme rainfall and extreme flood value were smaller than the ones derived from the observed rainfall by the degree of 16%-40%. Lastly, the web application developed in this study automates the entire process of synthetic rainfall generation, so we expect the application to be used in a variety of hydrologic analysis needing rainfall data.

• Journal of Korea Water Resources Association
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• v.53 no.5
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• pp.383-393
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• 2020

The main objective of this study is to provide a robust model for estimating parameters of the Clark unit hydrograph (UH) using the observed rainfall-runoff data in the Soyangang dam basin. In general, HEC-1 and HEC-HMS models, developed by the Hydrologic Engineering Center, have been widely used to optimize the parameters in Korea. However, these models are heavily reliant on the objective function and sample size during the optimization process. Moreover, the optimization process is carried out on the basis of single rainfall-runoff data, and the process is repeated for other events. Their averaged values over different parameter sets are usually used for practical purposes, leading to difficulties in the accurate simulation of discharge. In this sense, this paper proposed a hierarchical Bayesian model for estimating parameters of the Clark UH model. The proposed model clearly showed better performance in terms of Bayesian inference criterion (BIC). Furthermore, the result of this study reveals that the proposed model can also be applied to different hydrologic fields such as dam design and design flood estimation, including parameter estimation for the probable maximum flood (PMF).

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.690-693
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• 2002

According to the growth of communication biz, embedded market rapidly developing in domestic and overseas. Embedded system can be used in various way such as wire and wireless communication equipment or information products. There are lots of developing performance applying speech recognition to embedded system, for instance, PDA, PCS, CDMA-2000 or IMT-2000. This study implement minimum memory of speech recognition engine and DB for apply real time embedded system. The implement measure of speech recognition equipment to fit on embedded system is like following. At first, DC element is removed from Input voice and then a compensation of high frequency was achieved by pre-emphasis with coefficients value, 0.97 and constitute division data as same size as 256 sample by lapped shift method. Through by Levinson - Durbin Algorithm, these data can get linear predictive coefficient and again, using Cepstrum - Transformer attain feature vectors. During HMM training, We used Baum-Welch reestimation Algorithm for each words training and can get the recognition result from executed likelihood method on each words. The used speech data is using 40 speech command data and 10 digits extracted form each 15 of male and female speaker spoken menu control command of Embedded system. Since, in many times, ARM CPU is adopted in embedded system, it's peformed porting the speech recognition engine on ARM core evaluation board. And do the recognition test with select set 1 and set 3 parameter that has good recognition rate on commander and no digit after the several tests using by 5 proposal recognition parameter sets. The recognition engine of recognition rate shows 95%, speech commander recognizer shows 96% and digits recognizer shows 94%.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.333-342
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• 2005

This paper proposes a method, which recognizes student's identification card by using image processing and recognition technology and can manage student information on the web. The presented scheme sets up an average brightness as a threshold, based on the brightest Pixel and the least bright one for the source image of the ID card. It is converting to binary image, applies a horizontal histogram, and extracts student number through its location. And, it removes the noise of the student number region by the mode smoothing with 3$\times$3 mask. After removing noise from the student number region, each number is extracted using vertical histogram and normalized. Using the enhanced ART1 algorithm recognized the extracted student number region. In this study, we propose the enhanced ART1 algorithm different from the conventional ART1 algorithm by the dynamical establishment of the vigilance parameter. which shows a tolerance limit of unbalance between voluntary and stored patterns for clustering. The Experiment results showed that the recognition rate of the proposed ART1 algorithm was improved much more than that of the conventional ART1 algorithm. So, we develop an educational matters administration system by using the proposed recognition method of the student's identification card.

• Health Policy and Management
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• v.19 no.4
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• pp.98-120
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• 2009

The purpose of this study is to elicit preference for drug listing decision criteria and to estimate the ICER threshold in South Korea using the discrete choice experiment (DCE) method. To collect the data, a DCE survey was administered to a subject sample either educated in the principle concepts of pharmacoeconomics or were decision makers within that field. Subjects chose between alternative drug profiles differing in four attributes: ICER, uncertainty, budget impact and severity of disease. The orthogonal and balanced designs were determined through computer algorithm to take the optimal set of drug profiles. The survey employed 15 hypothetical choice sets. A random effect probit model was used to analyze the relative importance of attributes and the probabilities of a recommendation response. Parameter estimates from the models indicated that three attributes (ICER, Impact, Severity of disease) influenced respondents' choice significantly(p${\pm}$0.001). In addition, each parameter displayed an expected sign. The Lower the ICER, the higher the probability of choosing that alternative. Respondents also preferred low levels of uncertainty and smaller impact on health service budget. They were also more likely to choose drugs for serious diseases rather than mild or moderate ones. Uncertainty however is not statistically significant. The ICER threshold, at which the probability of a recommendation was 0.5, was 29,000,000 KW/QALY in expert group and 46,500,000 KW/QALY in industry group. We also found that those in our sample were willing to accept high ICER to get medication for severe diseases. This study demonstrates that the cost-effectiveness, budget impact and severity of disease are the main reimbursement decision criteria in South Korea, and that DCE can be a useful tool in analyzing the decision making process where a variety of factors are considered and prioritized.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.2 s.7
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• pp.53-66
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• 2005

Microscopic simulation models, which focus on individual vehicles, are used extensively in the transportation operations in order to capture vehicle to vehicle and vehicle to traffic controls. There are many important factors involved when a micro simulation model is applied as an evaluation tool for the traffic system. They typically include test bed, software, simulation time period, measure of effectiveness, parameter for a software, OD matrix, and random seed number. To evaluate the effects of those factors, sensitivity analysis was performed to identify the effects of those factors based on CORSIM and TRANSIMS results. Three freeway corridors, two in Houston (I-10 and US 290) and one in Sin Antonio (I-37), were chosen as test beds. Three time periods (AM, PM, off-peak) and three OD matrix estimates were used for the analysis. It was found that the micro-simulation results were highly sensitive to the model Parameter sets and the OD information. The degree of sensitivity was a function of the test bed and time period.

• Korean Journal of Human Ecology
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• v.15 no.3
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• pp.491-499
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• 2006

The purpose of this study is to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on choice of pizza restaurant, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurants based on seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 university students as respondents. Twenty one students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results were as followed: Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by purchase frequency. Based on the estimated models developed for the two purchase frequency groups, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with frequently purchase frequency group was highest, and the parameter estimate for price with frequently purchase frequency group was highest. The pizza restaurants that charged 20,000 won, offered 100% discount on eleventh pizza, promised to deliver pizza in 20 min, usually delivered the pizza as promised, offered 2 or more types of pizza crust, delivered steaming hot pizza, and did not offer a money-back guarantee which was favored by each of the two purchase frequency groups. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers can receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.363-374
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• 2009

The 2D flow around 13 similar stay-vane profiles with different trailing edge geometries is investigated to determinate the main characteristics of the excitation forces for each one of them and their respective dynamic behaviors when modeled as a free-oscillating system. The main goal is avoid problems with cracks of hydraulic turbines components. A stay vane profile with a history of cracks was selected as the basis for this work. The commercial finite-volume code $FLUENT^{(R)}$ was employed in the simulations of the stationary profiles and, then, modified to take into account the transversal motion of elastically mounted profiles with equivalent structural stiffness and damping. The k-$\omega$ SST turbulence model is employed in all simulations and a deforming mesh technique used for models with profile motion. The static-model simulations were carried out for each one of the 13 geometries using a constant far field flow velocity value in order to determine the lift force oscillating frequency and amplitude as a function of the geometry. The free-oscillating stay-vane simulations were run with a low mass-damping parameter ($m^*{\xi}=0.0072$) and a single mean flow velocity value (5m/s). The structural bending stiffness of the stay-vane is defined by the Reduced Velocity parameter (Vr). The dynamic analyses were divided into two sets. The first set of simulations was carried out only for one profile with $2{\leq}Vr{\leq}12$. The second set of simulations focused on determining the behavior of each one of the 13 profiles in resonance.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.511-518
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• 2009

A lot of methods are proposed to provide services for object informations in distributed domain to satisfy the recent increase of user-centered services. This paper proposed a method called fuzzy drop manager for the service of reliable distribution application domain objects. The proposed system accesses the domain using replica parameter ci,j and access matrix Z, and evaluates the reference relatedness inside the domain using the relatedness, given by the mapping of intra-domain fuzzy relevance, between fuzzy sets. Objects in the domain generated an $\alpha$-level set according to the reference relatedness obtained by applying $\alpha$-level to extend queries. Simulation results showed that the proposed method has better performance than the other methods.