• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.69-81
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• 2012

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• KIEAE Journal
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• v.8 no.4
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• pp.19-27
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• 2008

The carbon dioxide is brought from the energy consumption and regarded as a criteria material to estimate the Global Warming Potential. Building shares about 30% in national energy consumption and affects to environment as much as the energy consumption. But there is not enough data to forecast the amount of the carbon dioxide during the maintenance stage. Various factors are related with the energy consumption and carbon dioxide emission such as the physical area, the building exterior area, the maintenance type and location. Among these factors, the building carbon-dioxide emission can be estimated by the overall building characteristics such as the maintenance area, the number of household, the heating type, etc., The physical amount such as the thickness of the insulation and window infiltration could explained the limited scope and might not be use to estimate the total carbon-dioxide emission energy because the each value could not include or represent the overall building. In this paper, it provided the estimation model of the carbon-dioxide emission, explained by the overall building characteristics. These factors are shown as the maintenance area, no. of household, the heating type, the volume of the building, the ratio of the window to wall area etc., For providing the estimation model of th carbon-dioxide emission, it conducted the corelation analysis to filter the variables and suggested the estimation model with the power model and multiple regression model. Most of the model have a good statistics and fitted in the curve line.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.106.1-106
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• 2002

$\textbullet$ Current status of reliability estimation techniques for robot systems $\textbullet$ Description of Bayesian Belief Nets(BBN) With an example $\textbullet$ Description of proposed reliability estimation method which combines all information necessary $\textbullet$ Application example of the method : the reactor inspection robot $\textbullet$ Results from the reliability estimation of reactor inspection robot $\textbullet$ Discussion on the proposed method (advantages and problems) $\textbullet$ Conclusion

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.135-141
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• 2006

This paper presents offline estimation of equivalent physical damping parameter in haptic interaction systems where damping is the most important parameter for stability. Based on the previous energy bounding algorithm, an offline procedure is developed in order to estimate the physical damping parameter of a haptic device by measuring energy flow-in to the haptic device. The proposed method does not use force/torque sensor at the handgrip. Numerical simulation and experiments verified effectiveness of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2374-2379
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• 2011

The fundamental frequency of the voiced speech is estimated using the instantaneous frequency based on the symmetric higher order differential energy operator. The instantaneous frequency based on the symmetric higher order energy operator shows better frequency estimation result since it is aligned to the time instance of the signal. The speech is pre-processed by a lowpass filter to remove higher frequency components. Then, it is processed by the instantaneous frequency to obtain the fundamental frequency estimates. The symmetric higher order energy operator has been used as an indicator to determine the voiced/unvoiced speech. The fundamental frequency estimates are further processed by a moving average filter to obtain the monotonically changed estimates. The obtained fundamental frequency estimates have been compared with the spectrogram of the speech to confirm its accuracy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.369-374
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• 2008

This paper presents the evaluation procedures and the estimation method for the estimation of optimal rebate level for EE(Energy Efficiency) programs. The penetration amount of each appliance is estimated by applying price function to preferred diffusion model resulted from model compatibility test. To estimate the optimal rebate level, two objective functions which express the maximum energy saving and operation benefit are introduced and by multi-objective function which can simultaneously consider two objective functions the optimal rebate level of each appliance is estimated. And then, using the decided rebate level and each penetration amount, the priority order for reasonable investment of each high-efficiency appliance is estimated compared to the results of conventional method. Finally, using a benefit/cost analysis based on California standard practice manual, the economic analysis is implemented for the four perspectives such as participant, ratepayer impact measure, program administrator cost and total resource cost.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.11-15
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• 2018

The application of Wireless Sensor Networks requires a wise utilization of limited energy resources. Therefore, a wide range of routing protocols with a motivation to prolong the lifetime of a network has been proposed in recent years. Hierarchical clustering based protocols have become an object of a large number of studies that aim to efficiently utilize the limited energy of network components. In this paper, the effect of mismatch in parameter estimation is discussed to evaluate the robustness of a distanced based algorithm called distributed clustering protocol in homogeneous and heterogeneous environment. For quantitative analysis, performance simulations for this protocol are carried out in terms of the network lifetime which is the main criteria of efficiency for the energy limited system.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.8
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• pp.13-18
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• 2018

The purpose of this study was to study on the estimation of green remodeling energy reduction tool in building construction. Green Remodeling Decision System that can predict the energy reduction effect in green remodeling is developed as a tool for simple remodeling of green remodeling considering users' convenience, so that it can quickly and comprehensively determine power peak load reduction factor technology. A preliminary simulation result of a short preliminary remodeling evaluation is DB. It will be developed as a tool that can be easily accessed by users such as web and apps.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.581-605
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• 2021

The purpose of this study is to provide basic data for improving energy efficiency by estimating the regional energy efficiency in Korea using the stochastic frontier approach beyond the energy intensity that has been traditionally used as an indicator of energy efficiency. In this paper, energy efficiency and energy intensity efficiency were estimated as a stochastic distance function from 1998 to 2018 for 16 cities and provinces in Korea. In addition, the robustness of energy efficiency according to the capital stock estimation methods which had been mixed in previous studies was reviewed. As a result of the analysis, there is a significant change in regional rankings according to the three energy efficiency indicators, so they should be used complementary to each other. Second, while the energy efficiency improved little by little over time, the energy intensity efficiency decreased slightly though. Lastly, energy efficiency by region according to the capital stock estimation method was not robust. Care must be taken in estimating capital stock, which is important in economic analysis.