• Applied Chemistry for Engineering
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• v.29 no.6
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• pp.746-752
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• 2018

In this study, an optimized process for the waste cooking oil based biodiesel production using microwave energy was designed by using Box-Behnken design model. The process variables were chosen as a mole ratio of the methanol to oil, microwave power, and reaction time. Fatty acid methyl ester (FAME) content was then measured. Through the results of basic experiments, the range of optimum operation variables for the Box-Behnken design model, such as the methanol/oil mole ratio and reaction time, were set as between 8 to 10 and between 4 to 6 min, respectively. Ranges of the microwave power were set as from 8 to 12 W/g for 1.30 mg of KOH/g, acid value, while from 10 to 14 W/g for 2.00 mg of KOH/g, acid value. The optimum methanol/oil mole ratio, microwave power, and reaction time were reduced to 7.58, 10.26 W/g, and 5.1 min, respectively, for 1.30 mg KOH/g of acid value. Also, the optimum methanol/oil mole ratio, microwave power, and reaction time were 7.78, 12.18 W/g, and 5.1 min, respectively, for 2.00 mg KOH/g of acid value. Predicted FAME contents were 98.4% and 96.3%, with error rates of less than 0.3%. Therefore, when the optimized process of biodiesel production using microwave energy was applied to the Box-Behnken design model, the low error rate could be obtained.

• Clean Technology
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• v.27 no.2
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• pp.152-159
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• 2021

Volatile organic compounds (VOCs) occur in indoor and outdoor industrial and urban areas and cause environmental problems. Malodorous VOCs, along with aesthetic discomfort, can have a serious effect on the human body. Compared with the existing method of reducing malodorous VOCs, a wet scrubbing method using an electrolytic oxidant has the advantage of reducing pollutants and regenerating oxidants. This study investigated the optimal conditions for producing OCl^-, a chlorine-oxidant. Experiments were conducted by changing the type of anode and cathode electrode, the type of electrolyte, the concentration of electrolytes, and the current density. With Ti/IrO₂ as the anode electrode and Ti as the cathode electrode, OClproduction was highest and most stable. Although OCl^- production was similar with the use of KCl or NaCl, NaCl is preferable because it is cheap and easy to obtain. The effect of NaCl concentration and current density was examined, and the OCl^- production rate and concentration were highest at 0.75 M NaCl and 0.03 A cm^-2. However, considering the cost of electric power, OCl^- production under the conditions of 1.00 M NaCl and 0.01 A cm^-2 was most effective among the conditions examined. It is desirable to produce OCl^- by adjusting the current density in accordance with the concentration and characteristics of pollutants.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Food Science and Preservation
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• v.24 no.7
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• pp.949-956
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• 2017

This study attempted to find optimum extract range of active ingredient for barley sprouts (Hordeum vulgare L.). Extracts from Hordeum vulgare L. were made by microwave extraction method and total polyphenol content (TPC), total flavonoid content (TFC), DPPH radical scavenging activity (DPPH) were measured with extract of Hordeum vulgare L.. Response surface methodology (RSM) was applied to a extraction process, and central composite design (CCD) was also used for this process to examine the optimum condition. Independent variables ($X_n$) are concentration of ethanol ($X_1$: 0, 25, 50, 75, 100%), microwave power ($X_2$: 60, 120, 180, 240, 300 W), extraction time ($X_3$: 4, 8, 12, 16, 20 min). Dependent variables ($Y_n$) are TPC ($Y_1$), TFC ($Y_2$), DPPH radical scavenging ($Y_3$). It is formed by sixteen conditions to extract. The $R^2$ value of dependent variables is ranged from 0.90 to 0.97 (p<0.05). Experiments values within the optimal range (40% of ethanol concentration, 120 W of microwave power, 18 min of extraction time) were 3.74 mg GAE/g (TPC), 3.00 mg RE/g (TFC), 35.43% (DPPH), respectively. Under the optimized conditions, predicted value showed no significant difference comparing with the experimental values.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.105-113
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• 2016

Fire radiative power(FRP), which means the power radiated from wildfire, is used to estimate fire emissions. Currently, the geostationary satellites of East Asia do not provide official FRP products yet, whereas the American and European geostationary satellites are providing near-real-time FRP products for Europe, Africa and America. This paper describes the first retrieval of Himawari-8 FRP using the mid-infrared radiance method and shows the comparisons with MODIS FRP for Sumatra, Indonesia. Land surface emissivity, an essential parameter for mid-infrared radiance method, was calculated using NDVI(normalized difference vegetation index) and FVC(fraction of vegetation coverage) according to land cover types. Also, the sensor coefficient for Himawari-8(a = 3.11) was derived through optimization experiments. The mean absolute percentage difference was about 20%, which can be interpreted as a favourable performance similar to the validation statistics of the American and European satellites. The retrieval accuracies of Himawari FRP were rarely influenced by land cover types or solar zenith angle, but parts of the pixels showed somewhat low accuracies according to the fire size and viewing zenith angle. This study will contribute to estimation of wildfire emissions and can be a reference for the FRP retrieval of current and forthcoming geostationary satellites in East Asia.

• Korean Journal of Materials Research
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• v.2 no.3
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• pp.180-190
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• 1992

Some solutions to several major problems in ZMR such as agglomeration of polysilicon, slips and local substrate melting are described. Experiments are performed with varying polysilicon thickness and capping oxide thickness. The aggmeration can be eliminated when nitrogen is introduced at the capping oxide layer-to-polysilicon interface and polysilicon-to-buried oxide layer interface by annealing the SOI samples at $1100^{\circ}$ in $NH_3$ ambient for three hours. The slips and local substrate melting are removed when the back surface of silicon substrate is sandblasted to produce the back surface roughness of about $20{\mu}m$. The subboundary spacing increases with increasing polysilicon thickness and the uniformity of recrystallized SOI film thickness improves with increasing capping oxide thickness, improving the quality of recrystallized SOI film. When the polysilicon thickness is about $1.0{\mu}m$ and the capping oxide thickness is $2.5{\mu}m$, the thickness variation of the recrystallized SOI film is about ${\pm}200{\AA}$ and the subboundary spacing is about $70-120{\mu}m$.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.13-20
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• 2004

In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efcient coding techniques that reduce the complexity of the encoder. Until recently, encoder optimization without shape coding has been a major concern in video for wire/wireless low bit rate coding services. Recently, we found out that the computational complexity of MPEG-4 shape coding plays a very important role in the object-based coding through experiments. We have made an experiment whether we could get optimized object-based coding method through successfully combining latest optimized texture coding techniques with our proposed optimized shape coding techniques. In texture coding, we applied the MVFAST method for motion estimation. We chose not to use IVOPF(Intelligent VOP Formation) but to use TRB(Tightest Rectangular Boundary) for positioning VOP and, finally, to eliminate the spiral search of shape motion estimation to reduce the complexity in shape coding. As a result of experiment, our proposed scheme achieved improved time complexity over the existing reference software by $57.3\%$ and over the optimized method on which only shape coding was applied by $48.7\%$, respectively.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.37 no.1
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• pp.43-53
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• 2011

The conditions in fluid-bed processor for nanoencapsulation of azelaic acid-milk nano powder for acne nanocosmetics were optimized by response surface methodology (RSM). The maximum value of yield was 70.97 %. The yield was appreciably influenced by inlet air temperature, atomizing pressure, and feeding speed. The particle size increased with an increase in the feeding speed and a decrease in the atomizing pressure. The elution rate in saline solutions was appreciably influenced by inlet air temperature and atomizing pressure. The moisture content increased with higher atomizing pressure, which was demonstrated to be similar to the nanoencapsulation characteristics related to water activity. The Hunter's L and b values increased with an increase in the inlet air temperature. The optimum conditions estimated by RSM for the maximized values of yield, moisture content, particle size and elution rate in skin suitability were $67{\sim}73^{\circ}C$ of inlet air temperature, 0.6 ~ 0.8 mL/min feeding speed and 1.8 ~ 2.0 kg/$cm^2$ of atomizing pressure, respectively. These estimated values were in agreement with those measured by real experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.230-236
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• 2020

A trash screen is installed in front of the inflow channel of a drainage pumping station, sewage treatment plant, and a power plant to block floating contaminants. The bottleneck phenomenon, which decreases the water inflow, causes damage to the damper as a result of clogging in between the screen if string type obstacles are not removed. In this paper, the apron was removed, and the screen was expanded, to prevent breakage of the bottleneck phenomenon and string type obstacles. This was designed using an extended rake by adding an inner rake in between the screen interspace to remove the bottleneck phenomenon and string type obstacles. To design the inner rake that satisfies the allowable stresses of the existing damper rake, the experiment points were determined according to the experimental design method using the inner rake vertical length and the thickness of the reinforced section as parameters. The use of the ANSYS static structural module and statistical analysis tool R software gives the optimized shape according to the response surface method. The relative error between the response surface analysis results and the simulation results was 1.63% of the determined optimal design-point rake length of 210.2 mm and the reinforcement section thickness of 2 mm. Through empirical experiments, a test rake was constructed to the actual size, and approximately 97% of the bottleneck phenomenon and string type obstacles could be removed.