• Journal of Powder Materials
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• v.17 no.4
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• pp.276-280
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• 2010

In the present work, ethylene glycol-based (EG) copper oxide nanofluids were synthesized by pulsed wire evaporation method. In order to explode the pure copper wire, high voltage of 23 kV was applied to the both ends of wire and argon/oxygen gas mixture was used as reactant gas. EG-based copper oxide nanofluids with different volume fraction were prepared by controlling explosion number of copper wire. From the transmission electron microscope (TEM) image, it was found that the copper oxide nanoparticles exhibited an average diameter about 100 nm with the oxide layer of 2~3 nm. The synthesized copper oxide consists of CuO/$Cu_2O$ phases and the Brunauer Emmett Teller (BET) surface area was estimated to be $6.86\;m^2\;g^{-1}$. From the analyses of thermal properties, it is suggested that viscosity and thermal conductivity of EG-based copper oxide nanofluids do not show temperature-dependent behavior over the range of 20 to $90^{\circ}C$. On the other hand, the viscosity and thermal conductivity of EG-based copper oxide nanofluids increase with volume fraction due to the active Brownian motion of the nanoparticles, i.e., nanoconvection.

• Asian Journal of Atmospheric Environment
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• v.8 no.2
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• pp.96-107
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• 2014

Extreme recovery of the thermal energy from the combustion of flue gas may bring about early gas condensation resulting in the increased formation of nitric acid vapor. The behavior of the nitric acid formed inside the stack and in the atmosphere was investigated through a computer-aided simulation in this study. Low temperatures led to high conversion rates of the nitrogen oxide to nitric acid, according to the Arrhenius relationship. Larger acid plumes could be formed with the cooled flue gas at $40^{\circ}C$ than the present exiting gas at $115^{\circ}C$. The acid vapor plume of 0.1 ppm extended to 25 m wide and 200 m high. The wind, which had a seasonal local average of 3 m/s, expanded the influencing area to 170 m along the ground level. Its tail stretched 50 m longer at $40^{\circ}C$ than at $115^{\circ}C$. The emission concentration of the acid vapor in the summer season was a little lower than in the winter. However, a warm atmosphere facilitated the Brownian motion of the discharged flue gas, finally leading to more vigorous dispersion.

• Korea-Australia Rheology Journal
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• v.19 no.3
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• pp.99-107
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• 2007

A nanofluid is a mixture of solid nanoparticles and a common base fluid. Nanofluids have shown great potential in improving the heat transfer properties of liquids. However, previous studies on the characteristics of nanofluids did not adequately explain the enhancement of heat transfer. This study examined the distribution of particles in a fluid and compared the mechanism for the enhancement of heat transfer in a nanofluid with that in a general microparticle suspension. A theoretical model was formulated with shear-induced particle migration, viscosity-induced particle migration, particle migration by Brownian motion, as well as the inertial migration of particles. The results of the simulation showed that there was no significant particle migration, with no change in particle concentration in the radial direction. A uniform particle concentration is very important in the heat transfer of a nanofluid. As the particle concentration and effective thermal conductivity at the wall region is lower than that of the bulk fluid, due to particle migration to the center of a microfluid, the addition of microparticles in a fluid does not affect the heat transfer properties of that fluid. However, in a nanofluid, particle migration to the center occurs quite slowly, and the particle migration flux is very small. Therefore, the effective thermal conductivity at the wall region increases with increasing addition of nanoparticles. This may be one reason why a nanofluid shows a good convective heat transfer performance.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.1
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• pp.79-90
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• 2005

In this paper we study the numerical solutions of the stochastic differential equations of the form $$du(x,\;t)=f(x,\;t,\;u)dt\;+\;g(x,\;t,\;u)dW(t)\;+\;\sum\limits_{|q|\leq2m}\;A_q(x,\;t)D^qu(x,\;t)dt$$ where $0\;{\leq}\;t\;{\leq}\;T,\;x\;{\in}\;R^{\nu}$, ($R^{nu}$ is the $\nu$-dimensional Euclidean space). Here $u\;{\in}\;R^n$, W(t) is an n-dimensional Brownian motion, $$f\;:\;R^{n+\nu+1}\;{\rightarrow}\;R^n,\;g\;:\;R^{n+\nu+1}\;{\rightarrow}\;R^{n{\times}n},$$, and $$A_q\;:\;R^{\nu}\;{\times}\;[0,\;T]\;{\rightarrow}\;R^{n{\times}n}$$ where ($A_q,\;|\;q\;|{\leq}\;2m$) is a family of square matrices whose elements are sufficiently smooth functions on $R^{\nu}\;{\times}\;[0,\;T]\;and\;D^q\;=\;D^{q_1}_1_{\ldots}_{\ldots}D^{q_{\nu}}_{\nu},\;D_i\;=\;{\frac{\partial}{\partial_{x_i}}}$.

• Particle and aerosol research
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• v.5 no.3
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• pp.123-131
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• 2009

This paper presents simulation results of particle transport in low-pressure, low-temperature plasma environment. The size dependent transport of particles in the plasma is investigated with a two-dimensional simulation tool developed in-house for plasma chamber analysis and design. The plasma model consists of the first two and three moments of the Boltzmann equation for ion and electron fluids respectively, coupled to Poisson's equation for the self-consistent electric field. The particle transport model takes into account all important factors, such as gravitational, electrostatic, ion drag, neutral drag and Brownian forces, affecting the motion of particles in the plasma environment. The particle transport model coupled with both neutral fluid and plasma models is simulated through a Lagrangian approach tracking the individual trajectory of each particle by taking a force balance on the particle. The size dependant trap locations of particles ranging from a few nm to a few ${\mu}m$ are identified in both electropositive and electronegative plasmas. The simulation results show that particles are trapped at locations where the forces acting on them balance. While fine particles tend to be trapped in the bulk, large particles accumulate near bottom sheath boundaries and around material interfaces, such as wafer and electrode edges where a sudden change in electric field occurs. Overall, small particles form a "dome" shape around the center of the plasma reactor and are also trapped in a "ring" near the radial sheath boundaries, while larger particles accumulate only in the "ring". These simulation results are qualitatively in good agreement with experimental observation.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.51-57
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• 2010

Steganography techniques can be used to hide data within digital images with little or no visible change in the perceived appearance of the image. I propose a steganalysis to detecting hidden message in sequential steganography. This paper presents adjusted technique for detecting abrupt jumps in the statistics of the stego signal during steganalysis. The repeated statistical test based on CUSUM-SPRT runs constantly until it reaches decision. In this paper, I deal with a new and improved statistic $g_t$ by computing $S^{t^*}_j$.

• Computers and Concrete
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• v.32 no.4
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• pp.399-410
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• 2023

This study proposes a novel use of backpropagated Levenberg-Marquardt neural networks based on computational intelligence heuristics to comprehend the examination of hybrid nanoparticles on the flow of dusty liquid via stretched cylinder. A two-phase model is employed in the present work to describe the fluid flow. The use of desulphated nanoparticles of silver and molybdenum suspended in water as base fluid. The mathematical model represented in terms of partial differential equations, Implementing similarity transformationsis model is converted to ordinary differential equations for the analysis . By adjusting the particle mass concentration and curvature parameter, a unique technique is utilized to generate a dataset for the proposed Levenberg-Marquardt neural networks in various nanoparticle circumstances on the flow of dusty liquid via stretched cylinder. The intelligent solver Levenberg-Marquardt neural networks is trained, tested and verified to identify the nanoparticles on the flow of dusty liquid solution for various situations. The Levenberg-Marquardt neural networks approach is applied for the solution of the hybrid nanoparticles on the flow of dusty liquid via stretched cylinder model. It is validated by comparison with the standard solution, regression analysis, histograms, and absolute error analysis. Strong agreement between proposed results and reference solutions as well as accuracy provide an evidence of the framework's validity.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.578-598
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• 2011

This study estimates the value of photovoltaic core material technology, which is getting attention as a clean energy source. The estimation is based on the real option pricing model (ROPM). This study has two main contributions. The first is in the methodology. The process of modeling volatility, which is the most complicated stage in ROPM, is greatly simplified by using the stock price as a covariate representing the volatility of the real option's basic asset. The second contribution is the application of technology. In this study, the economic value of poly-silicon, a core material in the photovoltaic industry and recently surging in demand, is evaluated as a manufacturing technology. In a case study of a company in the photovoltaic industry, the stochastic process of a basic asset follows geometric Brownian motion (GBM), and the option value of firm A's poly-silicon manufacturing technology is estimated at 3.4 trillion won.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.513-522
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• 2014

Using the assumption that the price of a stock follows a geometric Brownian motion with constant volatility, Black and Scholes (BS) derived a formula that gives the price of a European call option on the stock as a function of the stock price, the strike price, the time to maturity, the risk-free interest rate, the dividend rate paid by the stock, and the volatility of the stock's return. However, implied volatilities of BS method tend to depend on the stock prices and the time to maturity in practice. To address this shortcoming, we estimate the implied volatility function as a function of the strike priceand the time to maturity for data consisting of the daily prices for KOSPI200 call options from January 2007 to May 2009 using support vector regression (SVR), the multiple additive regression trees (MART) algorithm, and ordinary least squaress (OLS) regression. In conclusion, use of MART or SVR in the BS pricing model reduced both RMSE and MAE, compared to the OLS-based BS pricing model.

• Textile Coloration and Finishing
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• v.6 no.1
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• pp.62-70
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• 1994

Silk fibroin was dissolved in 9.3 M LiBr aqueous solution at 4$0^{\circ}C$ for 1 hour. The dissolved silk fibroin was regenerated by casting the dialyzed solution into the membrane. The freshly prepared silk fibroin membrane was soluble in water and was. mainly consisted of random coil conformation. By the treatments in saturated water vapor at 3$0^{\circ}C$ and in 75% ethanolic aqueous solution (V/V), the insoluble membranes were obtained and the structure and morphology of those were investigated for the structure by means of X-ray diffraction analysis, infrared spectroscopy, thermal analysis. Rheovibron and scanning electron micrograph. Silk II type crystals were obtained by treating amorphous silk fibroin membrane in the random coil conformtion with 75% ethanol solution(V/V). Crystallization to silk II type crystals occured even after a few minutes, and a large number of silk II type crystals were formed after 30 mins. On the other and, the membrane treated in saturated water vapor was composed of the mixtures of silk I and silk II type crystals. A large number of silk I and silk II type crystals were formed after 24 hours. The micro brownian motion in the amorphous regions of silk fibroin membrane started at about 175~185$^{\circ}C$. $\alpha$ dispersion appeared at about 20$0^{\circ}C$ in the amorphous membrane, and at about 22$0^{\circ}C$ in the crystalline membrane. The crystallization of random coil conformation to silkII type crystals occured at about 215$^{\circ}C$. The surface, bottom and cross-section of the membranes were observed by scanning electrom microscope. Fine forms alike spherulites appeared at the surface of crystalline membrane.