• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.1-14
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• 2006

This study proposed a customer preference estimation model for production recommendation and a method to enhance the performance of product recommendation using the estimated customer preference information. That is, we suggested customer preference estimation model to estimate exactly customer's product preference with his behavior. This model shows the relationship of customer's behaviors with his preferences. The proposed estimation model is optimized by learning the relative weights of customer's behavior variables to have an effect on his preference and enables to estimate exactly his preference. To validate our proposed models, we collected virtual book store data and then made a comparative analysis of our proposed models and a benchmark model in terms of performance results of collaborative filtering for product recommendation. The benchmark model means a prior preference weighting model. The results of our empirical analysis showed that our proposed model performed better results than the benchmark model.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.239-250
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• 2022

In many applications, we frequently encounter correlated multiple outcomes measured on the same subject. Joint modeling of such multiple outcomes can improve efficiency of inference compared to independent modeling. For instance, in developmental toxicity studies, fetal weight and number of malformed pups are measured on the pregnant dams exposed to different levels of a toxic substance, in which the association between such outcomes should be taken into account in the model. The number of malformations may possibly have many zeros, which should be analyzed via zero-inflated count models. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint modeling framework for continuous and count outcomes with excess zeros. In our model, zero-inflated Poisson (ZIP) regression model would be used to describe count data, and a subject-specific random effects would account for the correlation across the two outcomes. We implement a Bayesian approach using MCMC procedure with data augmentation method and adaptive rejection sampling. We apply our proposed model to dose-response analysis in a developmental toxicity study to estimate the benchmark dose in a risk assessment.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.485-499
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• 2012

Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.389-401
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• 2012

This paper derives a benchmark dose(BMD) and its 95% lower confidence limit(BMDL) using a semi-parametric regression model for small lead based changes in attention-deficit hyperactivity disorder(ADHD) scores in the first wave of the Children's Health and Environment Research(CHEER) survey data, which have been regularly collected in South Korea since 2005. Ha et al. (2009) showed that the appearance of ADHD symptoms had a borderline trend of increasing with the blood lead concentration. Butdz-J${\o}$rgensen (EFSA, 2010a) derived the BMDL of lead corresponding to a benchmark region of 1 full intelligent quotient (IQ) score using the raw data in Lanphear et al. (2005, EHP). European Food Safety Authority (EFSA, 2010b) determined the BMDL of $1.2{\mu}g/dl$ as a reference point for the characterization of lead when assessing the risk of the intellectual deficit measured by IQ scores. Kim et al. (2011) indicated that an even lower BMDL could be obtained based on the ADHD score; however, the BMDLs depended heavily upon the model assumptions. We show in this paper that a semi-parametric approach resolves the model dependence of BMDLs.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.202-208
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• 2014

Friction force on robot systems is highly nonlinear and especially disturbs precise control of the robots at low speed. This paper deals with the dynamic friction compensation problem of a well-known one-link benchmark robot system. We consider the LuGre model because the model can successfully represent dynamic characteristics and various effects of friction phenomenon. The proposed controller is constructed as two parts. An adaptive controller based on dual observers is used to estimate and compensate the dynamic friction. In order to attenuate the friction estimation error and other disturbances, PI observer is additionally designed. Through the computer simulations with the benchmark system, this paper first examines the effects of nonlinear dynamic friction on the control performance of the benchmark robot system. Next, it is shown that the control performance against the dynamic friction is improved by using the proposed controller.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2230-2245
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• 2023

KANT (KAIST Advanced Nuclear Tachygraphy) is a PWR core simulator recently developed at Korea Advance Institute of Science and Technology, which solves three-dimensional steady-state and transient multigroup neutron diffusion equations under Cartesian geometries alongside the incorporation of thermal-hydraulics feedback effect for multi-physics calculation. It utilizes the standard Nodal Expansion Method (NEM) accelerated with various Coarse Mesh Finite Difference (CMFD) methods for neutronics calculation. For thermal-hydraulics (TH) calculation, a single-phase flow model and a one-dimensional cylindrical fuel rod heat conduction model are employed. The time-dependent neutronics and TH calculations are numerically solved through an implicit Euler scheme, where a detailed coupling strategy is presented in this paper alongside a description of nodal equivalence, macroscopic depletion, and pin power reconstruction. For validation of the steady, transient, and depletion calculation with pin power reconstruction capacity of KANT, solutions for various benchmark problems are presented. The IAEA 3-D PWR and 4-group KOEBERG problems were considered for the steady-state reactor benchmark problem. For transient calculations, LMW (Lagenbuch, Maurer and Werner) LWR and NEACRP 3-D PWR benchmarks were solved, where the latter problem includes thermal-hydraulics feedback. For macroscopic depletion with pin power reconstruction, a small PWR problem modified with KAIST benchmark model was solved. For validation of the multi-physics analysis capability of KANT concerning large-sized PWRs, the BEAVRS Cycle1 benchmark has been considered. It was found that KANT solutions are accurate and consistent compared to other published works.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.1
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• pp.58-64
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• 1989

This paper constructs a stochastic model for computer performance evaluation which has several parameters such as the kinds of instruction mix of benchmark programs, distribution and frequency of instruction mix. It shows, by applying the model to the performance evaluation of the Intel 8086/8088 microprocessor, that this model could be utilited not only for performance evaluation of existing computer systems but also for estimation of nonexisting systems.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.191-196
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• 1997

As a part of International Criticality Safety Benchmark Evaluation Project (ICSBEP), SAXTON critical experiments were reevaluated. The effects on $K_{eff}$ of the uncertainties in experiment parameters, fuel rod characterization, soluble boron, critical water level, core structure, $^{241}$ Am and $^{241}$ Pu isotope number densities, random pitch error, duplicated experiment, axial fuel position, model simplification, etc., were evaluated and added in benchmark-model $k_{eff}$. In addition to detailed model, the simplified model for Saxton critical experiments was constructed by omitting the top, middle, and bottom grids and ignoring the fuel above water.r.r.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.573-590
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• 2020

This study presents the current status of DECOVALEX-2023 project Task G and our research results so far. Task G, named 'Safety ImplicAtions of Fluid Flow, Shear, Thermal and Reaction Processes within Crystalline Rock Fracture NETworks (SAFENET)' aims at developing a numerical method to simulate the fracture creation and propagation, and the coupled thermohydro-mechanical processes in fracture in crystalline rocks. The first research step of Task G is a benchmark simulation, which is designed for research teams to make their modelling codes more robust and verify whether the models can represent an analytical solution for displacements of a single rock fracture. We reproduced the mechanical behavior of rock and embedded single fracture using a three-dimensional grain-based distinct element model for the simulations. In this method, the structure of the rock was represented by an assembly of rigid tetrahedral grains moving independently of each other, and the mechanical interactions at the grains and their contacts were calculated using 3DEC. The simulation results revealed that the stresses induced along the embedded fracture in the model were relatively low compared to those calculated by stress analysis due to stress redistribution and constrained fracture displacements. The fracture normal and shear displacements of the numerical model showed good agreement with the analytical solutions. The numerical model will be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated using various experiments in a further study.