• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1161-1164
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• 1996

In this paper, a parameter optimization technique for a mobile robot navigation is discussed. Authors already have proposed a navigation algorithm for mobile robots with sonar sensors using fuzzy decision making theory. Fuzzy decision making selects the optimal via-point utilizing membership values of each via-point candidate for fuzzy navigation goals. However, to make a robot successfully navigate through an unknown and cluttered environment, one needs to adjust parameters of membership function, thus changing shape of MF, for each fuzzy goal. Furthermore, the change in robot configuration, like change in sensor arrangement or sensing range, invokes another adjusting of MFs. To accomplish an intelligent way to adjust these parameters, we adopted a genetic algorithm, which does not require any formulation of the problem, thus more appropriate for robot navigation. Genetic algorithm generates the fittest parameter set through crossover and mutation operation of its string representation. The fitness of a parameter set is assigned after a simulation run according to its time of travel, accumulated heading angle change and collision. A series of simulations for several different environments is carried out to verify the proposed method. The results show the optimal parameters can be acquired with this method.

• Journal of Environmental Science International
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• v.18 no.9
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• pp.983-992
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• 2009

The purpose of the present study is to analyze pollutant runoff characteristics from non-point sources in Joman River basin. The present study contains analyzed results of rainfall and SS, BOD, COD, TN, TP runoff from Joman River basin. This study contains a sensitivity analysis of parameters that affect the simulation results of rainfall and pollutants runoff. Result of the sensitivity analysis shows that proportion of watershed and impervious areas is the most sensitive to peak discharge and total flowrate for rainfall runoff and that WASHPO is the most sensitive parameter for pollutants runoff. For parameter estimation and verification, flowrate and water quality is measured at the Kangdong Bridge in Haeban stream. A single rainfall event is use to perform parameter estimation and verification. Results of the present study show that total pollutant loads of Joman River basin is 11,600 ton of SS, 452 ton of BOD, 1,084 ton of COD, 515 ton of TN, and 49 ton of TP, respectively. In addition, it is found that contribution ratio of non point source and total source is 89% of SS, 63% of BOD, 61% of COD, 21% of TN, and 32% of TP, respectively.

• Geotechnical Engineering
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• v.12 no.2
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• pp.43-58
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• 1996

In spite of drastic development of underground technology too many uncertainties still exist in design and construction of underground structures. Estimation of ground parameters might be one of those uncertainties in design of underground structures. It is not an easy task to estimate the parameters reasonably well in advance in the design stage. The main purpose of this paper is the best parameter estimation in the underground structures. In order to estimate unknown model parameters from the in-eitu measurements as well as prior estimates, the Extended Bayesian Method(EBM) is utilized and implemented with Finite Element Program. The parameter estimation model utilized in this study is applied to two underground structures : the one Pusan subway tunnel: and the other Darlington intake tunnel in Canada, and the effectiveness of the proposed model is illustrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.814-821
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• 2009

In an ultrawide band (UWB) indoor wireless localization, time of arrival (TOA) parameter estimation techniques have some difficulties in acquiring a reasonable TOA estimate because of the clustered multipath components overlapping or random time intervals mainly due to non line-of-sight (NLOS) environment. In order to solve that problem and achieve an excellent UWB indoor wireless localization, we propose a UWB signal model and a robust TOA parameter estimation technique that has little effect on the clustered problems unlike the conventional technique. Through simulation studies, the validity of the proposed model and the TOA estimation technique are examined. The performance of estimation error is also analyzed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.97-103
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• 2012

In this paper, we propose a novel voice activity detection (VAD) algorithm to effectively distinguish speech from nonspeech in various noisy environments. Global speech absence probability (GSAP) derived from likelihood ratio (LR) based on the statistical model is widely used as the feature parameter for VAD. However, the feature parameter based on conventional GSAP is not sufficient to distinguish speech from noise at low SNRs (signal-to-noise ratios). The presented VAD algorithm utilizes GSAP based on Teager energy (TE) as the feature parameter to provide the improved performance of decision for speech segments in noisy environment. Performances of the proposed VAD algorithm are evaluated by objective test under various environments and better results compared with the conventional methods are obtained.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.511-516
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• 1994

Parameter estimation techniques are discussed for the complex frequency analysis of an electromagnetic scatterer. The paper suggests how the Maximum Likelihood estimation technique can be applied for this purpose. Experiments on hypothetical data sets demonstrate that the Maximum Likelihood technique is better than the Pencil of Functions technique. Although there have been several techniques including MLE suggested as tools of the parameter estimation, the proposed method has strong advantages under the noise-contaminated sample data environment because it uses minimal dimension of system matrix that stands totally independent of the length of extracted data set.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.16-24
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• 1999

This paper deals with the dynamic vehicle arbitration algorithm for communication between vehicles and a roadside control init on multilane environment. The suggested algorithm varies its parameter values according to the current vehicle arrival rate to get the maximum performance. To get the optimum parameter values, arbitration methods that use random delay counter and persist mechanism were taken into account and the performance of these methods with respect to the vehicle arrival rate was analyzed by computer simulation. After applying the optimum parameter values to suggested algorithm, it is shown that more enhanced reliability was acquired This algorithm could be applied to various systems which include the communication between a transponder and a control unit.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1400-1404
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• 2010

In this study the flow duration curves and load duration curves for Nakdong river basin are analyzed. The TANK model is used as s hydrologic simulation model whose parameters are estimated from 8-days intervals flow data measured by Nakdong River Water Environment Laboratory. also in this study a Minimum Variance Unbiased Estimator(MVUE) is confirmed that it provides satisfactory load estimate. The Seven-Parameter Log Linear Model for estimating Total Organic Carbon(TOC) and Biochemical Oxygen Demand(BOD) loads in Nakdong river using a MVUE.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4102-4111
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• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.

• Environmental Engineering Research
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• v.20 no.3
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• pp.254-259
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• 2015

In this study, the characteristics as well as the maturity and stability of chicken manure collected from nine chicken farms in South Korea during the summer and winter seasons of 2014 are evaluated. The physicochemical parameter values of the manure, such as BOD, $NO_3-N$ and $PO_4-P$ etc. were determined using the Korea Standard test Method, HPLC, and APHA standard methods. The results showed that the alkalinity content and COD concentration in winter chicken manure were higher than those of summer chicken manure. The moisture content of summer manure was positively correlated with almost all of the other parameters of the manure, whereas it was negatively correlated with almost all of the other parameters in the winter manure. According to the criterion of C/N ratio, chicken manure indicated good quality compost. However, composted chicken manure showed immature and unstable compost when considering the criteria of the $NH_4-N/NO_3-N$ ratio and $NH_4-N$ concentrations.