• Bulletin of the Korean Chemical Society
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• v.12 no.3
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• pp.315-322
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• 1991

In a recent $paper^1$ we reported equilibrium (EMD) and non-equilibrium (NEMD) molecular dynamics simulations of liquid argon using the Green-Kubo relations and NEMD algorithms to calculate the thermal transport coefficients-the self-diffusion coefficient, shear viscosity, and thermal conductivity. The overall agreement with experimental data is quite good. In this paper the same technique is applied to calculate the thermal transport coefficients of liquid water at 298.15 K and 1 atm using TIP4P model for the interaction between water molecules. The EMD results show difficulty to apply the Green-Kubo relations since the time-correlation functions of liquid water are oscillating and not decaying rapidly enough except the velocity auto-correlation function. The NEMD results are found to be within approximately ${\pm}$30-40% error bars, which makes it possible to apply the NEMD technique to other molecular liquids.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.515-524
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• 2012

Fault attacks are a powerful side channel analysis extracting secret information by analyzing the result after injecting faults physically during the implementation of a cryptographic algorithm. First, this paper analyses vulnerable points of existing Digital Signature Algorithm (DSA) schemes secure against fault attacks. Then we propose a new signature algorithm immune to all fault attacks. The proposed DSA scheme is designed to signature by using two nonce and an error diffusion method.

• Textile Coloration and Finishing
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• v.13 no.6
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• pp.33-33
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• 2001

The physical properties and the dyeability of the easily dyeable polyester yarn(EDY) were investigated and compared with those of regular polyester (REG-PET). The EDY, copolymerized with small amount of polyethylene glycol(PEG), showed higher intensity of aliphatic CH peak in IR spectrum, lower density and lower compactness than those of the REG-PET from the analysis of IR, density gradient column and XRD respectively. In the physical properties, the EDY has lowers $T_g,\;T_m$, specific stress and initial modulus, and also has higher strain than that of the REG-PET. The EDY can be dyed under atmospheric pressure and its dyeing rate was faster than REG-PET due to low $T_d$, and this seems to be caused by the increased flexibility of Polymer chain in amorphous region of the EDY due to the copolymerization of PEG.ns being within the experimental error, the average values of lifetim.
$\tau$(t) are taken for further calculations. Rate constants such as Stern-Volmer quenching constants K$_{sv}$, quenching rate parameters k$_q$ and k''$_q$, static quenching constant V and kinetic distance r are determined using the modified Stern-Volmer eq.
tion and sphere of action static quenching model. In order to see whether the reactions are diffusion limited, equations k$_q$ = e$^{-Eq/RT}$ and k''$_q$ = e$^{-Eq/RT}$ are used to determine the values of E$_q$ and E''$_q$, the activati.
energies for collisional quenching and the values of E$_q$ are 14.53, 17.28 and 16.20 kJ mole$^{-1}$ for MPNO1, MPNO2 and 2-PI respectively and the values of E''$_q$ are 14.62 and 17.73 for MPNO1 and MPNO2 respectively. From the magnitudes of various quantities it has.
een concluded that the reactions are diffusion limited and the observed positive deviations in the S-V plot are due to static and dynamic quenching.

• Membrane Journal
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• v.11 no.1
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• pp.14-21
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• 2001

Rapid backpulsing to reduce membrane fouling of hollow fiber ultrafiltration module (polyacrylonitrile with 50000 l'vlWCO, 1.4 rom OD and 0,9 mm ID) was studied with latex solutions. Values estimated by a theoretical model were compared with the ones obtained from the systems with or without backpulsing, Specific Cake resistance, time consUmt for cake growth, diffusion coefficient, and the rate constants of fnur fouling models; the complete, intermediate. standard blocking and cake filtration were calculated to obtain the theoretical values. High frequency backpulsing gave net increase of fluxes by 40~120%. Fluxes predicted by the model were in good agreement with experimental ones within 14% error bound, The optimum backpulsing strength was acquired at 20% in the ranges of 20~40% strength and the optimum frequcncv was acquired at 2 Hz in the ranges of 0.67~3 Hz.

• Journal of Photoscience
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• v.4 no.3
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• pp.97-103
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• 1997

The effect of temperature on the fluorescence quenching of 2-(4-Methoxyphenyl)-5-(1-naphthyl)-1,3,4-oxadiazole (MPNO1), 2-(4-Methoxyphenyl)-5-(2-naphthyl)-1,3,4-oxadiazote(MPNO2), by aniline, and 2-Phenylindole (2-PI) by CCk, in toluene by steady state method and in benzene by time-resolved method have been carried out in the temperature range 30 - 70$\circ$C. The Stem-Volmer (S-V) plots, I$_0$/I against quencher concentration [Q] at different temperanares show positive deviations. The fluorescence lifetimes determined at different temperatures show no systematic variations and the variations being within the experimental error, the average values of lifetimes $ $\tau$ (t) are taken for further calculations. Rate constants such as Stem-Volmer quenching constants K$_sv}$, quenching rate parameters k$_q$ and k'$_q$, static quenching constant V and kinetic distance r are determined using the modified Stem-Volmer equation and sphere of action static quenching model. In order to see whether the reactions are diffusion limited, equations k$_q$ = e$^{-Eq/RT}$ and k'$_q$ = e$^{-Eq/RT}$ are used to determine the values of E$_q$ and E'$_q$, the activation energies for collisional quenching and the values of E$_q$ are 14.53. 17.28 and 16.20 kJ mole$^{-1}$ for MPNO1, MPNO2 and 2-PI respectively and the values of E'$_q$ are 14.62 and 17.73 for MPNO1 and MPNO2 respectively. From the magnitudes of various quantities it has been concluded that the reactions are diffusion limited and the observed positive deviations in the S-V plot are due to static and dynamic quenching.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.3
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• pp.407-414
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• 2015

The effect of activated carbon particle diameter (i.e. US sieve No. $8{\times}10$ ($d_p{\approx}2.19mm$), $18{\times}20$ ($d_p{\approx}0.92mm$), $50{\times}60$ ($d_p{\approx}0.27mm$) and $170{\times}200$ ($d_p{\approx}0.081mm$) on caffeine adsorption is investigated. BET surface area was increased with decreasing particle diameter ($d_p$), and caffeine adsorption rates increased with decreasing $d_p$. Moreover, pseudo-second order model is predicted the experimental data more accurately than pseudo-first order model, and the fastest rate constant ($k_2$) was $1.7g\;mg^{-1}min^{-1}$ when $d_p$ was 0.081 mm. Surface diffusion coefficient (Ds) was decreased with decreasing $d_p$ based on the minimum sum of square error (SSE). Practically, certain ranges of Ds are acceptable with high reliability ($R^2$) and it is determined that the effect of $d_p$ on Ds is unclear. The effect of pH on caffeine adsorption indicated the dependency of m/L ratio (mass liquid ratio) and $pH_{pzc}$. The $pH_{pzc}$ (i.e. $7.9{\pm}0.2$) was not affected by $d_p$. The higher caffeine adsorption at pH 4 and pH 7 than at pH 10 is due to $pH_{pzc}$, not $pk_a$ of caffeine.

• Fire Science and Engineering
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• v.31 no.4
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• pp.20-25
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• 2017

In the present study, the temperature distribution of droplet diffusion flames was predicted from the measurements of radiative emissions of soot particles formed. In order to predict the temperature distributions, the radiative emissions from soot particles filtered at both 700 nm and 900 nm were measured using CCD cameras and local emission distributions within the flame deconvoluted with Abel transformation were plugged into a two color method. The experimental results obtained from the present study demonstrate that the two color method as tool for temperature measurements is feasible but can introduce approximately 2% maturement errors in a deconvolution process depending on intervals for the line of sight. The estimated error in temperature measurements was found to be within 18 K at 2000 K.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of the Korea Concrete Institute
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• v.22 no.3
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• pp.335-343
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• 2010

Steel corrosion in reinforced concrete (RC) structures is a critical problem to structural safety and many researches are being actively conducted on developing methods to maintain the required performance of the RC structures during their intended service lives. In this study, concrete mixture proportioning technique through genetic algorithm (GA) for RC structures under carbonation, which is considered to be serious in underground site and big cities, is investigated. For this, mixture proportions and diffusion coefficients of $CO_2$ from the previous researches were analyzed and fitness function for $CO_2$ diffusion coefficient was derived through regression analysis. This function based on the 12 experimental results consisted of 5 variables including water-cement ratio (W/C), cement content, sand percentage, coarse aggregate content per unit volume of concrete in unit, and relative humidity. Through genetic algorithm (GA) technique, simulated mixture proportions were proposed for 3 cases of verification and they showed reasonable results with less than relative error of 10%. Finally, assuming intended service life, different exposure conditions, design parameters, intended $CO_2$ diffusion coefficients, and cement contents were determined and related mixture proportions were simulated. This proposed technique is capable of suggesting reasonable mix proportions and can be modified based on experimental data which consider various mixing components like mineral admixtures.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.357-364
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• 2016

Purpose: This study was performed to define the drying characteristics of sorghum by developing thin layer drying equations and evaluating various grain drying equations. Thin layer drying equations lay the foundation characteristics to establish the thick layer drying equations, which can be adopted to determine the design conditions for an agricultural dryer. Methods: The drying rate of sorghum was measured under three levels of drying temperature ($40^{\circ}C$, $50^{\circ}C$, and $60^{\circ}C$) and relative humidity (30%, 40%, and 50%) to analyze the drying process and investigate the drying conditions. The drying experiment was performed until the weight of sorghum became constant. The experimental constants of four thin layer drying models were determined by developing a non-linear regression model along with the drying experiment results. Result: The half response time (moisture ratio = 0.5) of drying, which is an index of the drying rate, was increased as the drying temperature was high and relative humidity was low. When the drying temperature was $40^{\circ}C$ at a relative humidity (RH) of 50%, the maximum half response time of drying was 2.8 h. Contrastingly, the maximum half response time of drying was 1.2 h when the drying temperature was $60^{\circ}C$ at 30% RH. The coefficient of determination for the Lewis model, simplified diffusion model, Page model, and Thompson model was respectively 0.9976, 0.9977, 0.9340, and 0.9783. The Lewis model and the simplified diffusion model satisfied the drying conditions by showing the average coefficient of determination of the experimental constants and predicted values of the model as 0.9976 and Root Mean Square Error (RMSE) of 0.0236. Conclusion: The simplified diffusion model was the most suitable for every drying condition of drying temperature and relative humidity, and the model for the thin layer drying is expected to be useful to develop the thick layer drying model.