• Korean System Dynamics Review
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• v.12 no.2
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• pp.153-176
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• 2011

This paper is a summary of how we constructed a national R&D investment model. Although a national R&D investment is an important decision making for the government as well as industries, currently there were little efforts on making a model reflecting governmental decision making on the individual size of national R&D. We constructed a simple national R&D model through discussion with 3 researchers who have rich experience of governmental investment of national R&D. In this paper, we tried to show how our simple R&D model can reflect the perception on the R&D efficiency that changes as the industry reach to its saturation level.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.337-340
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• 2011

This study investigates the rheological characteristics of $SiO_2$-Kerosene gel propellants with Aerosil(R) R972, Silica 230, Silica 530. Power-law rheological model is used to confirm whether or not gelification is achieved. It was found that the produced gel have shear-thinning effect, and that the viscosity of the gel propellants increases with increasing $SiO_2$ concentration. Among gellants used in this study, gel propellant with Aerosil(R) R972 fits most to the power law model as the shear rate increases. However, gels produced with Silica 230 and Silica 530 gellant deviate from the power law model when the shear rate regime is below 100 [1/s].

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.377-385
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• 2016

The previous Adaptive Control of Thought-Rational (ACT-R) cognitive architecture model has a limitation in that it cannot accurately predict human visual search strategy, because time effect, one of important human cognitive features, is not considered. Thus, the present study proposes ACT-R cognitive modeling that contains the impact of time using a revised utility system in the ACT-R model. Then, the validation of the model is performed by comparing results of the model with eye-tracking experimental data and SEEV-T (SEEV-Time; SEEV model which considers time effect) model in "Where's Wally" game. The results demonstrate that the model data fit fairly well with the eye-tracking data ($R^2=0.91$) and SEEV-T model ($R^2=0.93$). Therefore, the modeling method which considers time effect using a revised utility system should be used in predicting the human visual search paradigm when the available time is limited.

• Computers and Concrete
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• v.28 no.6
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• pp.635-642
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• 2021

In this paper, soft learning techniques are used to predict the ultimate torsional capacity of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. Soft computing techniques, namely Artificial Neural Network, trained by various back propagation algorithms, and Particle Swarm Optimization (PSO) algorithm, have been used to model and predict the torsional strength of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. The performance of each model has been evaluated by using statistical parameters such as coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The hybrid PSO NN model resulted in an R² of 0.9292 with an RMSE of 5.35 for training and an R² of 0.9328 with an RMSE of 4.57 for testing. Another model, ANN BP, produced an R² of 0.9125 with an RMSE of 6.17 for training and an R² of 0.8951 with an RMSE of 5.79 for testing. The results of the PSO NN model were in close agreement with the experimental values. Thus, the PSO NN model can be used to predict the ultimate torsional capacity of RC beams strengthened with FRP with greater acceptable accuracy.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2749-2753
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• 2009

Structural characteristics that influence on the insecticidal activity ($pI_{50}$) of 2-(n-octyl)isothiourea analogues (1-45) against the diamondback moth (Plutella xylostella, L.) based on three dimensional quantitative structure activity relationships (3D-QSARs) were discussed quantitatively using a comparative molecular field analysis (CoMFA) and a comparative molecular similarity indeces analysis (CoMSIA) methods. The statistical values of the CoMFA 2 model were better than those of the CoMSIA 1 model. The CoMFA 2 model was the optimized model with the correlativity (the training set: Ave. = 0.104 & PRESS = 0.613) and the predictability (the test set: Ave. = 0.086 & PRESS = 0.096). Insecticidal activities with the optimized CoMFA 2 model were dependent upon steric factors (79.4%) of $R_1-R_3$ substituents. From the analytical results of CoMFA contour maps, it is predicted that the R1 substituent of 1-45 which has a steric favor in a broad space, $R_2\;and\;R_3$ groups with a steric favor in a narrow space and a H-bond donor favor would have better the insecticidal activity.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.40 no.4
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• pp.383-390
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• 2014

The following conclusion was made from the 2D-QSAR model for the tyrosinase inhibitory activity according to the variation of the substituents R1 and R2 in analogues of compound 2-[(2,6-dioxocyclohexyl)methyl]cyclohexane- 1,3-dione (1-23). The best optimized 2D-QSAR model was $Obs.pI_{50}=-0.295({\pm}0.031)TDM$ $-0.120({\pm}0.014)DMZ+0.135({\pm}0.050)DMX.R_2+6.382({\pm}0.17)$, and the correlation $r^2=0.905$) of which was greater than its predictability ($q^2=0.843$). The magnitude of the effect of tyrosinase inhibitory activities was in order of TDM > $DMX.R_2{\geq}DMZ$, and it tended to increase as the hydrophobicity of substrate molecule (ClogP > 0) as well as the steric favor of substituent $R_1$ increased. The analysis of the model implies that inhibitory activity of substrate molecule will increase as $DMX.R_2$ (Dipole moment X component of $R_2$-substituent) increases, while TDM (Total Dipole Moment) and DMZ(Dipole Moment of Z-Component) decrease. As such, it is deemed feasible to conclude, that in order to increase the inhibitory effect, it would be rather desirable to replace the polar groups within the molecules with non-polar functional groups.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.22-31
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• 2010

In R&D project evaluation, we consider the technical couple. And we set technology modular alternatives, after evaluating technical group based on technical couple. So we solve the problem extracted from existing research of R&D project evaluation. We use Conjoint Analysis(CA) for this research. CA is usually used for confirming customers' preference. However we use it for researchers' preference in the side of technology. This research is followed by the next 4 steps. (1) Hierarchical model of goal technology (2) Composition model of modular alternatives (3) Evaluation model of modular alternatives (4) Setting model of technology modular alternatives.

• Journal of Powder Materials
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• v.8 no.2
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• pp.124-130
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• 2001

A centrifugally atomized 2024A1/SiC/sub p/ composites were extruded to study effect of clusters on mechanical properties, and a model was proposed that the strength of MMCs would be estimated from the load transfer model approach that taken into consideration of the clusters. This model has been successfully utilized to predict the strength and fracture toughness of MMCs. The experimental and calculated results show coincidence and that the fracture toughness decreases with increasing the volume fraction of particles. On the basis of experimental observations, we suggest that the strength and fracture toughness of particle reinforced MMCs may be calculated from; σ/sub y/=σ/sub m/V/sub m/+σ/sub r/(V/sub r/-V/sub c)-σ/sub r/V/sub c/, K/sub IQ/=σ/sub Y/((3πt)((r/sub r//V/sub r/)(r/sub c//V/sub c/))/sup 1/2/)/sup 1/2/, respectively.

• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.107-109
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• 1979

Consider a linear model with n observations and k explanatory variables: (1)b $y=X\beta+u, u\simN(0,\sigma^2I_n)$. We assume that the model satisfies the ideal conditions. Consider the general linear constraints on regression coefficient vector: (2) $R\beta=r$, where R and r are known matrices of orders $q\timesk$ and q\times1$ respectively, and the rank of R is $qk+q$.

• Korean System Dynamics Review
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• v.15 no.2
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• pp.27-50
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• 2014

Korea government established the energy technology development plan (2011-2020) and declared to be a leader of the green energy technologies. The plan aims for 10% market share in the green energy industry, 12% energy efficiency improvement, and 15% greenhouse gas reduction. In order to achieve these goals, the government has tried to calculate the whole scale of national energy R&D investment, annual budget and specific expenditures for new technologies by computer simulation. The simulation modules include the R&D investment model, GDP model, energy consumption and $CO_2$ emission model by System Dynamics. Based on these simulation modules, I tested various scenarios for effectiveness of energy R&D investments until 2020. The results show that Korea should increase national energy R&D investment to 2.3 billion U.S. dollars, and switch the investment from electricity and nuclear power to the renewable energy.