• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.170-175
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• 1992

A leak detection method for diagnosis of the leak position in a pipeline was developed using an estimation theory with the assumption that the measured flow rates and pressures are stochastic processes. A notch filter was designed using power spectral density analysis of measurements to reduce the effects of disturbances. The noise model dimension was determined by hypothesis testing and then recursive extended least square method was applied to estimate the leak position in real time. The proposed method was applied to an experimental system for evaluation of its performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.438-442
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• 2006

Reasonably accurate estimation of the exposed population to the distinct levels of noise is essential to the efficient management of urban environmental noise. This study proposes a method of calculating the number of exposed people to industrial noise by using GIS tool and noise mapping. The exposed population of noise based on estimation of the number of people that lived in each building in urban area is compared with the one based on density of population. This study suggests the six step method that consists of gathering the fundamental data, extracting the property from the digital map, noise mapping based on the three dimensional topography, estimating population that lives in each building, merging the various results with GIS tool, and estimating exposed population to industrial noise through analyzing the noise map with GIS tools

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.715-723
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• 2002

This paper is to show a clustering application of a density estimation method that utilizes the Gaussian mixture model. We define "closeness measure" as a clustering criterion to see how close given two Gaussian components are. Closeness measure is defined as the ratio of log likelihood between two Gaussian components. According to simulations using artificial data, the clustering algorithm turned out to be very powerful in that it can correctly determine clusters in complex situations, and very flexible in that it can produce different sizes of clusters based on different threshold valuesold values

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.416-422
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• 2007

Prime movers in most large merchant ships adapt two stroke low speed diesel engine which has higher efficiency, mobility and durability. However, severe torsional vibration in these diesel engines may be induced by higher fluctuation of combustion pressures. Consequently, it may lead sometimes to propulsion shafting failure due to the accumulated fatigue stresses. Shaft fatigue strength analysis had been done traditionally in time domain but this method is complicated and difficult in analysing bi-modal vibration system such as the case of cylinder misfiring condition. In this paper authors introduce an assessment method of fatigue strength estimation for propulsion shafting system with two stroke low speed diesel engine in the frequency domain.

• Economic and Environmental Geology
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• v.28 no.4
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• pp.433-438
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• 1995

The most popular minimization method is based on the least-squares criterion, which uses the $L_2$ norm to quantify the misfit between observed and synthetic data. The solution of the least-squares problem is the maximum likelihood point of a probability density containing data with Gaussian uncertainties. The distribution of errors in the geophysical data is, however, seldom Gaussian. Using the $L_2$ norm, large and sparsely distributed errors adversely affect the solution, and the estimated model parameters may even be completely unphysical. On the other hand, the least-absolute-deviation optimization, which is based on the $L_1$ norm, has much more robust statistical properties in the presence of noise. The solution of the $L_1$ problem is the maximum likelihood point of a probability density containing data with longer-tailed errors than the Gaussian distribution. Thus, the $L_1$ norm gives more reliable estimates when a small number of large errors contaminate the data. The effect of outliers is further reduced by M-fitting method with Cauchy error criterion, which can be performed by iteratively reweighted least-squares method.

• Wind and Structures
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• v.31 no.5
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• pp.419-430
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• 2020

Weibull distribution is a conspicuous distribution known for its accuracy and its usage for wind energy analysis. The two and three parameter Weibull distributions are adopted in this study to fit wind speed data. The daily mean wind speed data of Ennore, Tamil Nadu, India has been used to validate the procedure. The parameters are estimated using maximum likelihood method, least square method and moment method. Four statistical tests namely Root mean square error, R2 test, Kolmogorov-Smirnov test and Anderson-Darling test are employed to inspect the fitness of Weibull probability density functions. The value of shape factor, scale factor, wind speed and wind power are determined at a height of 100m using extrapolation of numerical equations. Also, the value of capacity factor is calculated mathematically. This study provides a way to evaluate feasible locations for wind energy assessment, which can be used at any windy site throughout the world.

• Journal of Korean Society of Transportation
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• v.31 no.5
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• pp.48-59
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• 2013

Normally the benefits concerned in the feasibility study for highway constructions are travel time saving, vehicle operation cost, etc. which can be calculated using the simulation tool(EMME3). However, there must be extra benefits of driving amenity improvement that drivers can perceive through decreasing driving fatigue and improving driving comfortability. In this study, the definition of driving amenity was established and a method of estimation for the benefit of driving amenity improvement was developed. Highway type (urban/rural highway) and highway density was considered to estimate the driving amenity. And Double-bounded Dichotomous Choice among Contingent Valuation Method(CVM) was applied to survey the willingness-to-pay of drivers when highway density decreases. Finally the value of driving amenity was estimated using the results of survey and logit medel. As the existing highway density is high, willingness-to-pay increases in both urban and rural highways. Even though the changing rates of highway density are same, willingness-to-pay is different based on the existing highway density.

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.207-213
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• 2023

Computed tomography (CT) images are used as the basis for proton Bragg peak position estimation and treatment plan simulation. During the Hounsfield Unit (HU) based proton stopping power ratio (SPR) estimation, small differences in the patient's density and elemental composition lead to uncertainty in the Bragg peak positions along the path of the proton beam. In this study, we investigated the potential of dual-energy computed tomography image-based proton SPRs prediction accuracy to reduce the uncertainty of Bragg peak position prediction. Single- and dual-energy images of an electron density phantom (CIRS Model 062M electron density phantom, CIRS Inc., Norfolk, VA, USA) were acquired using a computed tomography system (Somatom Definition AS, Siemens Health Care, Forchheim, Germany) to estimate the SPRs of the proton beam. To validate the method, it was compared to the SPRs estimated from standard data provided by the National Institute of Standards and Technology (NIST). The results show that the dual-energy image-based method has the potential to improve accuracy in predicting the SPRs of proton beams, and it is expected that further improvements in predicting the position of the proton's Bragg peak will be possible if a wider variety of substitutes with different densities and elemental compositions of the human body are used to predict the SPRs.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.220-225
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• 2007

This paper presents an efficient input variable selection method using both principal component analysis(PCA) and adaptive partition mutual information(AP-MI) estimation. PCA which is based on 2nd order statistics, is applied to prevent a overestimation by quickly removing the dependence between input variables. AP-MI estimation is also applied to estimate an accurate dependence information by equally partitioning the samples of input variable for calculating the probability density function. The proposed method has been applied to 2 problems for selecting the input variables, which are the 7 artificial signals of 500 samples and the 24 environmental pollution signals of 55 samples, respectively. The experimental results show that the proposed methods has a fast and accurate selection performance. The proposed method has also respectively better performance than AP-MI estimation without the PCA and regular partition MI estimation.