• Journal of Radiation Protection and Research
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• v.48 no.4
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• pp.175-183
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• 2023

Background: Recently, biological adsorbents have been developed for removing radionuclides from radioactive liquid waste due to their high selectivity, eco-friendliness, and renewability. However, since they can be damaged by radiation in radioactive waste, a method for estimating the bio-adsorbent performance as a time should consider the radiation damages in terms of their renewability. This paper aims to develop a simulation method that applies a deep learning technique to rapidly and accurately estimate the adsorption performance of bio-adsorbents when inserted into liquid radioactive waste. Materials and Methods: A model that describes various interactions between a bio-adsorbent and liquid has been constructed using numerical methods to estimate the adsorption capacity of the bio-adsorbent. To generate datasets for machine learning, Monte Carlo N-Particle (MCNP) simulations were conducted while considering radioactive concentrations in the adsorbent column. Results and Discussion: Compared with the result of the conventional method, the proposed method indicates that the accuracy is in good agreement, within 0.99% and 0.06% for the R² score and mean absolute percentage error, respectively. Furthermore, the estimation speed is improved by over 30 times. Conclusion: Note that an artificial neural network can rapidly and accurately estimate the survival rate of a bio-adsorbent from radiation ionization compared with the MCNP simulation and can determine if the bio-adsorbents are reusable.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.595-611
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• 2016

We use nonlinear regression models (such as the Hill Model) when we analyze data in toxicology and/or pharmacology. In nonlinear regression models an estimator of parameters and estimation of measurement about uncertainty of the estimator are influenced by the variance structure of the error. Thus, estimation methods should be different depending on whether the data are homoscedastic or heteroscedastic. However, we do not know the variance structure of the error until we actually analyze the data. Therefore, developing estimation methods robust to the variance structure of the error is an important problem. In this paper we propose a method to estimate parameters in nonlinear regression models based on a preliminary test. We define an estimator which uses either the ordinary least square estimation method or the iterative weighted least square estimation method according to the results of a simple preliminary test for the equality of the error variance. The performance of the proposed estimator is compared to those of existing estimators by simulation studies. We also compare estimation methods using real data obtained from the National Toxicology program of the United States.

• Aerospace Engineering and Technology
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• v.4 no.2
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• pp.153-162
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• 2005

Through a preliminary design process, four design candidates for a 1.4MW class partial admission turbine have been chosen and the numerical analyses using a frozen rotor method are applied to estimate their performance. Each flow analysis result was compared with others and the optimum design was selected. Flow characteristics in the passages and some types of losses induced by shocks and wakes were found from calculation results. A new rotor blade was redesigned based on these calculations and this result is compared with previous one through flow analysis.

• JSTS:Journal of Semiconductor Technology and Science
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• v.4 no.4
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• pp.286-292
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• 2004

In this paper we present a static performance estimation technique of on-chip bus architectures. The proposed technique requires the static scheduling of function blocks of a task to analyze bus conflicts caused by simultaneous accesses from processing elements to which function blocks are mapped. To apply it to multitask applications, the concurrent execution of the function blocks of different tasks also should be considered. Since tasks are scheduled independently, considering all cases of concurrency in each processing element is impractical. Therefore we make an average estimate on the effects of other tasks with respect to bus request rate and bus access time. The proposed technique was incorporated with our exploration framework for on-chip bus architectures, Its viability and efficiency are validated by a preliminary example.

• Earthquakes and Structures
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• v.1 no.1
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• pp.129-146
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• 2010

This paper proposes an approximate procedure to estimate seismic displacement capacity - defined as yield displacement times the displacement ductility - of piles in marine oil terminals. It is shown that the displacement ductility of piles is relatively insensitive to most of the pile parameters within ranges typically applicable to most piles in marine oil terminals. Based on parametric studies, lower bound values of the displacement ductility of two types of piles commonly used in marine oil terminals - reinforced-concrete and hollow-steel - with either pin connection or full-moment-connection to the deck for two seismic design levels - Level 1 or Level 2 - and for two locations of the hinging in the pile - near the deck or below the ground - are proposed. The lower bound values of the displacement ductility are determined such that the material strain limits specified in the Marine Oil Terminal Engineering and Maintenance Standard (MOTEMS) are satisfied at each design level. The simplified procedure presented in this paper is intended to be used for preliminary design of piles or as a check on the results from the detailed nonlinear static pushover analysis procedure, with material strain control, specified in the MOTEMS.

• Journal of Ocean Engineering and Technology
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• v.23 no.3
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• pp.14-19
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• 2009

The present study developed a model to estimate the light weight of an ultra-large container ship. The weight estimation model utilized container ship data obtained from shipyards and the subdivided this weight data into appropriate weight groups. Parameters potentially affecting the group weight were selected and expanded based on experience for weight estimation, and a correlation analysis was performed by the SPSS program to determine the key parameters characterizing the group weight. A weight estimation model applying the multi-regression analysis was proposed to assess the weight of an ultra-large container ship at the preliminary design stage, and the results obtained by the suggested method showed good agreement with the shipyard data.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.495-501
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• 1997

A preliminary and parametric sensitivity study on recriticality risk of fast reactor cores after a hypothetical total core meltdown accident was performed. Only neutronic aspects of the accident were considered, independent of the accident scenario, and efforts were made to estimate the quantity of molten fuel which must be ejected out of the core to assure a sub-critical state after the accident. Two types of parameters were examined : characteristic parameters of molten core such as geometry, molten pool type (homogenized or stratified), fuel temperature, environment, and relative parameters to normal core such as core size(small or large), and fuel type (oxide, nitride, metal). The first type of parameters was found to intervene more directly in the recriticality risk than the second type of parameters.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.437-447
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• 2010

Spatial estimation of environmental variables has been regarded as an important preliminary procedure for decision-making. A minimum variance criterion, which has often been adopted in traditional kriging algorithms, does not always guarantee the optimal estimates for subsequent decision-making processes. In this paper, a geostatistical framework is illustrated that consists of uncertainty modeling via stochastic simulation and risk modeling based on loss functions for the selection of optimal estimates. Loss functions that quantify the impact of choosing any estimate different from the unknown true value are linked to geostatistical simulation. A hybrid loss function is especially presented to account for the different impact of over- and underestimation of different land-use types. The loss function-specific estimates that minimize the expected loss are chosen as optimal estimates. The applicability of the geostatistical framework is demonstrated and discussed through a case study of copper mapping.

• Korean Journal of Organic Agriculture
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• v.18 no.3
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• pp.291-313
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• 2010

The objective of this paper is to apply choice experiment methods to estimate non-market value of organic farming and its policy implication. A preliminary survey shows that the attributes of organic farming are reduce environmental pollution, bio-diversity improvements, cultural diversity improvements and maintain local community, reduce green-house gas emissions, energy saving, landscape improvements and tax for organic farming improvement policy. Questionnaire was eight different choice sets presented to each respondent. Implicit values of the attributive levels of organic farming have been calculated into tax money costs per house. This paper compared the six feasible scenarios in terms of willingness to pay per year. This study is expected to contribute to government's organic farming policies and quantitative information related to practice of organic farming.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.2021-2031
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• 2004

A new nondimensional method for predicting the windmilling performance of centrifugal -flow turbojet engines in flight has been developed. The method incorporates loss correlations to estimate the performance of major engine components. Given basic engine geometry, flight Mach number, and ambient conditions, this method predicts transient and steady-state windmilling performance. Thus, this method can be used during the preliminary design stage when detailed hardware geometry and component performance data are not yet available. A nondimensional time parameter is newly defined, and using this parameter, the transient performance of different types of turbojets (e.g. centrifugal vs. axial) is compared. In addition, the predictions' sensitivity to loss correlations, slip factors, and inlet ambient temperatures are analyzed.