• Journal of Navigation and Port Research
• /
• v.45 no.3
• /
• pp.165-172
• /
• 2021

Breaking wave is one of the important design factors in the design of coastal and port structures as they are directly related to various physical phenomena occurring on the coast, such as onshore currents, sediment transport, shock wave pressure, and energy dissipation. Due to the inherent complexity of the breaking wave, many empirical formulas have been proposed to predict breaker indices such as wave breaking height and breaking depth using hydraulic models. However, the existing empirical equations for breaker indices mainly were proposed via statistical analysis of experimental data under the assumption of a specific equation. In this study, a new Munk-type empirical equation was proposed to predict the height of breaking waves based on a representative linear supervised machine learning technique with high predictive performance in various research fields related to regression or classification challenges. Although the newly proposed breaker height formula was a simple polynomial equation, its predictive performance was comparable to that of the currently available empirical formula.

• Korean Chemical Engineering Research
• /
• v.56 no.4
• /
• pp.568-576
• /
• 2018

In order to investigate the adsorption characteristics of the antibiotics trimethoprim (TMP) by activated carbon (WCAC) prepared from waste citrus peel, the effects of operating parameters on the TMP adsorption were investigated by using a response surface methodology (RSM). Batch experiments were carried out according to a four-factor Box-Behnken experimental design with four input parameters : concentration ($X_1$: 50-150 mg/L), pH ($X_2$: 4-10), temperature ($X_3$: 293-323 K), adsorbent dose ($X_4$: 0.05-0.15 g). The experimental data were fitted to a second-order polynomial equation by the multiple regression analysis and examined using statistical methods. The significance of the independent variables and their interactions was assessed by ANOVA and t-test statistical techniques. Statistical results showed that concentration of TMP was the most effective parameter in comparison with others. The adsorption process can be well described by the pseudo-second order kinetic model. The experimental data of isotherm followed the Langmuir isotherm model. The maximum adsorption amount of TMP by WCAC calculated from the Langmuir isotherm model was 144.9 mg/g at 293 K.

• Journal of Animal Science and Technology
• /
• v.45 no.5
• /
• pp.739-748
• /
• 2003

The objective of this study was to estimate genetic parameters for test-day milk production and somatic cell score using field data collected by dairy herd improvement program in Korea. Random regression animal models were applied to estimate genetic variances for milk production and somatic cell score. Heritabilities for milk yields, fat percentage, protein percentage, solid-not-fat percentage, and somatic cell score from test day records of 5,796 first lactation Holstein cows were estimated by REML algorithm in single trait random regression test-day animal models. For these analyses, Legendre polynomial covariate function was applied to model the fixed effect of age-season, the additive genetic effect and the permanent environment effect as random. Homogeneous residual variance was assumed to be equal throughout lactation. Heritabilities as a function of time were calculated from the estimated curve parameters from univariate analyses. Heritability estimates for milk yields were in range of 0.13 to 0.29 throughout first lactation. Heritability estimates for fat percentage, protein percentage and solid-not-fat percentage were within 0.09 to 0.11, 0.12 to 0.19 and 0.17 to 0.23, respectively. For somatic cell score, heritabilities were within 0.02 to 0.04. Heritabilities for milk productions and somatic cell score were fluctuated by days in milk with comparing 305d milk production.

• Korean Journal of Remote Sensing
• /
• v.30 no.1
• /
• pp.47-59
• /
• 2014

Volcanic ash (VA) can be estimated by remote sensing sensors through their spectral signatures determined by the inherent optical property (IOP) including complex refractive index and the scattering properties. Until now, a very limited range of VA refractive indices has been reported and the VA from each volcanic eruption has a different composition. To improve the robustness of VA remote sensing, there is a need to understanding of VA - radiation interactions. In this study, we calculated extinction coefficient, scattering phase function, asymmetry factor, and single scattering albedo which show different values between andesite and pumice. Then, IOPs were used to analyze the relationship between theoretical remote sensed radiation calculated by radiative transfer model under various aerosol optical thickness (${\tau}$) and sun-sensor geometries and characteristics of VA. It was found that the mean rate of change of radiance at top of atmosphere versus ${\tau}$ is six times larger than in radiance values at 0.55 ${\mu}m$. At the surface, positive correlation dominates when ${\tau}$ <1, but negative correlation dominates when ${\tau}$ >1. However, radiance differences between andesite and pumice at 11 ${\mu}m$ are very small. These differences between two VA types are expressed as the polynomial regression functions and that increase as VA optical thickness increases. Finally, these results would allow VA to be better characterized by remote sensing sensors.

• Journal of the Korean Society of Tobacco Science
• /
• v.20 no.1
• /
• pp.131-138
• /
• 1998

In order to minimize the trial frequency in the new filter cigarette design, we studied the relationship between smoke yield and tipping materials of cigarette. A three levels full factorial design involving filament denier (X1,2.5-3.3d), Porosity of the acetate filter plug wrap (X2, 3,500-16,000CU) and porosity of the tip paper (X3, 400-1,200CU) was used. Three independent factors (Xl, X2, X3) were chosen for their effects on the various responses and the function was expressed in terms of a quadratic polynomial equation, Y : $\beta$o + $\beta$1Xl + $\beta$2X2 + $\beta$3X3 + $\beta$11Xl2 + $\beta$22X22+ $\beta$33X32 + $\beta$12X1X2 + $\beta$13XIX3 $\beta$23X2X3 which measures the linear, quadratic, and interaction effects. Twenty-nine trial numbers were obtained as a results of using a three levels full factorial design and it was analyzed by the multiple regression analysis with backward stepwise in STATISTICA/pc under restricted conditions. Tar yields of the cigarette was affected by porosity of tip paper (0.66), filament denier (0.47) and porosity of plug wrap (0.28) in the decreasing order, and linear effect of tip paper porosity (B3) and filament denier (91) were significant at a level of 0.01($\alpha$). The filament denier and tipping paper porosity interaction F ratio among three factors had a P-value of 0,000041, indicating higher interaction between these factors. Based on the analysis of variance, the model fitted for Tar (Y1) was significant at 5% confidence level and the coefficient of determination (0.96) was the proportion of variability in the data fitted for by the model.

• Korean Journal of Food Science and Technology
• /
• v.35 no.5
• /
• pp.884-892
• /
• 2003

This study was conducted to optimize the water homogenization process of mandarin orange peel for colored rice. Four variables were used to determine the optimum conditions for homogenization speed, time, temperature, and water volume with a five level central composite design and response surface methodology. The process was optimized using the combination of EI and b values of rice coated with water extract of the mandarin orange peel. The effect of water volume was the most significant compared to the other variables on the quality of water homogenate. The regression polynomial model was a suitable (p>0.05) model by lack-of-fit analysis showing high significance. To optimize the process, based on surface response and contour plots, individual contour plots for the response variables were superimposed. The optimum conditions for manufacturing water extract from mandarin orange was with 8,500 rpm homogenization speed, 2.8 min time, $53^{\circ}C$ temperature, and 42 mL water volume with the maximum of restricted variables of EI above 400 and h value above 24.

• The Journal of the Korea Contents Association
• /
• v.22 no.7
• /
• pp.55-62
• /
• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.4A
• /
• pp.385-393
• /
• 2009

This study grasped the relationship between relative humidity in concrete and concrete shrinkage followed by pre-absorbed water of porous lightweight aggregates through measurements of concrete shrinkage and humidity and comparisons with established research results. It was showed that shrinkage reduction effect of lightweight concrete is 36% at 7 days early ages and 25% at 180 days long-term ages when water-binder ratio is 0.3. It also showed that shrinkage reduction effect is 19% at 7 days and 16% at 180 days when water-binder ratio is 0.4 and 37%, 32% when water-binder ratio is 0.5. The moisture supply effect of lightweight aggregates was remarkable at early age within 7~10 days irrespective of water-binder ratio. In case of waterbinder ratio is 0.3, the relationship between shrinkage and internal humidity of concrete has been underestimated regardless of applied existing model type and in case of water-binder ratio is 0.4, 0.5, measurement values are relatively similar with existing model equations. Finally this study did regression analyses about the relation among the humidity change and the shrinkage strain as a high-degree polynomial and derived parameters that can connect moisture movement analysis with differential shrinkage analysis in case of considering relative humidity at the time by moisture movement analysis of concrete.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.34 no.4
• /
• pp.567-571
• /
• 2005

In this study, the effects of varying the amount of water, soaking time at $25^{\circ}C$ and drying time after soaking at $45^{\circ}C$ on the induction of resveratrol were evaluated to optimize the soaking treatment by response surface methodology (RSM). After response surface regression (RSREG), the second-order polynomial equation was fitted to the experimental data. The analysis of variance showed that the model appeared to be adequate $(R^2=0.9547)$ with no significant lack of fit (p>0.1). From statistical analysis, amount of water and soaking time were found to be significant factors. On the other hand, drying time was not significant. Ridge analysis showed that the optimized parameters were $67.15\%$ for amount of water, 19.58 hr for soaking time, 65.56 hr for drying time. It was confirmed that resveratrol content was increased from $0.1\;{\mu}g/g$ to $4.55\;{\mu}g/g$ under the optimized conditions. In addition, the experimental values at the optimized condition agreed with values predicted by ridge analysis. The analytical method validation parameters such as accuracy, precision, and specificity were calculated to ensure the method's validity.

• Korean Journal of Food Science and Technology
• /
• v.22 no.5
• /
• pp.539-542
• /
• 1990

The effects of immersion temperature $(20,\;40\;and\;60^{\circ}C)$ and immersion times (6. 12 and 18 min) in a distilled water prior to air dehydration upon the browning reaction and pyruvic acid content of air dried onions to a 4.071 moisture content (wet basis) were analyzed by a response surface methodology (RSM). Those values were also predicted by using a second degree polynomial regression model. Immersion temperature had more influence to browning reaction and pyruvic acid content than immersion time in these experimental ranges. The processing conditions to minimize the browning reaction of dried onions at $50^{\circ}C$ of air temperature (O.D.=0.071) were $60^{\circ}C$ of immersion temperature and 18 min of immersion time compared to control (O.D.=0.168) of air dehydration at $50^{\circ}C$ Pyruvic acid contents of dried onions at $50^{\circ}C$ of air temperature were maximized $(39.85{\mu}mole/g\;onion\;solid)$ at $60^{\circ}C$ of immersion temperature and 12 min of immersion time compared to control $(24.08{\mu}mole/g\;onion\;solid)$ of air dehydration at $50^{\circ}C$.