• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.28-41
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• 2017

In this paper, the fast encoding algorithm in High Efficiency Video Coding (HEVC) encoder was studied. For the encoding efficiency, the current HEVC reference software is divided the input image into Coding Tree Unit (CTU). then, it should be re-divided into CU up to maximum depth in form of quad-tree for RDO (Rate-Distortion Optimization) in encoding precess. But, it is one of the reason why complexity is high in the encoding precess. In this paper, to reduce the high complexity in the encoding process, it proposed the method by determining the maximum depth of the CU using a hierarchical clustering at the pre-processing. The hierarchical clustering results represented an average combination of motion vectors (MV) on neighboring blocks. Experimental results showed that the proposed method could achieve an average of 16% time saving with minimal BD-rate loss at 1080p video resolution. When combined the previous fast algorithm, the proposed method could achieve an average 45.13% time saving with 1.84% BD-rate loss.

• Journal of Food Hygiene and Safety
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• v.31 no.4
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• pp.278-285
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• 2016

This study used response surface methodology (RSM) in an effort to optimize the ultrasoundassisted extraction condition of Camellia sinensis L. and Artemisia argyi mixture in order to increase extraction yield in the extract. The effects of three independent variables, $X_1$ (Mixture ratio, 60-80%), $X_2$ (Ratio of water to raw material, 20~100 mL/g), and $X_3$ (Extraction time, 25-145 min), were investigated at three levels using Box-Behnken design (BBD) to obtain the highest extraction efficiency. Y (Extraction yield) was chosen as dependent variable. Our result showed that the coefficient of determination ($R^2$) of the model was 0.9747, with significant at the level of p < 0.002. Furthermore, the predicted values of each variable were similar to the actual values. The optimum extraction conditions were as follows: mixture ratio of 85.86%, ratio of water to raw material of 92.73 mL/g, and extraction time of 56.52 min. At these conditions, predicted extraction yield was 30.03%. The analysis of variance (ANOVA) indicated a high goodness of model fit and the success of the RSM method for optimizing extraction conditions of Camellia sinensis L. and Artemisia argyi mixture.

• 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 Korea Water Resources Association
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• v.53 no.6
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• pp.395-408
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• 2020

This paper aims to develop and apply three different machine learning approaches (i.e., artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and wavelet-based neural networks (WNN)) combined with an evolutionary optimization algorithm and the k-fold cross validation for multi-step (days) streamflow forecasting at the catchment located in Algeria, North Africa. The ANN and ANFIS models yielded similar performances, based on four different statistical indices (i.e., root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), correlation coefficient (R), and peak flow criteria (PFC)) for training and testing phases. The values of RMSE and PFC for the WNN model (e.g., RMSE = 8.590 ㎥/sec, PFC = 0.252 for (t+1) day, testing phase) were lower than those of ANN (e.g., RMSE = 19.120 ㎥/sec, PFC = 0.446 for (t+1) day, testing phase) and ANFIS (e.g., RMSE = 18.520 ㎥/sec, PFC = 0.444 for (t+1) day, testing phase) models, while the values of NSE and R for WNN model were higher than those of ANNs and ANFIS models. Therefore, the new approach can be a robust tool for multi-step (days) streamflow forecasting in the Seybous River, Algeria.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.3
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• pp.458-465
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• 2011

Response surface methodology (RSM) was applied to optimize substrate conditions of ribose and hydrolyzed wheat gluten solution for Maillard reaction. Independent variables were NaCl concentration of hydrolyzed wheat gluten ($X_1$), concentration of ribose ($X_2$) and concentration of hydrolyzed wheat gluten ($X_3$), while the dependent variables of the central composite design (CCD) were browning index (absorbance 420 nm), DPPH radical scavenging activity (DF) and sensory preference (score). Optimum substrate conditions at $140^{\circ}C$, 30 min reaction were 3% NaCl concentration of hydrolyzed wheat gluten, 6.2% concentration of ribose and 13.27% concentration of hydrolyzed wheat gluten. The coefficients of determination ($R^2$) were 0.975, 0.960 and 0.854, the model fit was very significant (p<0.001). DPPH radical scavenging activities and sensory preferences were predicted as 700 (DF) and 8.42 (score), respectively. The model solution increased more browning and DPPH radical scavenging activities with increasing ribose and hydrolyzed wheat gluten concentration. Especially hydrolyzed wheat gluten concentration was the most influential factor, while NaCl concentration of hydrolyzed wheat gluten hardly affected the responses. Sensory preference was increased with rising wheat gluten concentration and decreasing NaCl concentration of hydrolyzed wheat gluten.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.2 s.42
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• pp.37-46
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• 2005

To date, many viable smart base isolation systems have been proposed and investigated. In this study, a novel friction pendulum system (FPS) and an MR damper are employed as the isolator and supplemental damping device, respectively, of the smart base isolation system. A fuzzy logic controller (FLC) is used to modulate the MR damper because the FLC has an inherent robustness and ability to handle non linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. The main purpose of employing a GA is to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. To this end, a GA with a local improvement mechanism is applied. This method is efficient in improving local portions of chromosomes. Neuro fuzzy models are used to represent dynamic behavior of the MR damper and FPS. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can find optimal fuzzy rules and the GA optimized FLC outperforms not only a passive control strategy but also a human designed FLC and a conventional semi active control algorithm.

• Investigative Magnetic Resonance Imaging
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• v.20 no.2
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• pp.81-87
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• 2016

Purpose: To analyze the feasibility of three-dimensional (3D) diffusion-weighted (DW) PSIF (reversed FISP [fast imaging with steady-state free precession]) sequence in order to evaluate peripheral nerves in the elbow. Materials and Methods: Ten normal, asymptomatic volunteers were enrolled (6 men, 4 women, mean age 27.9 years). The following sequences of magnetic resonance images (MRI) of the elbow were obtained using a 3.0-T machine: 3D DW PSIF, 3D T2 SPACE (sampling perfection with application optimized contrasts using different flip angle evolution) with SPAIR (spectral adiabatic inversion recovery) and 2D T2 TSE (turbo spin echo) with modified Dixon (m-Dixon) sequence. Two observers used a 5-point grading system to analyze the image quality of the ulnar, median, and radial nerves. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of each nerve were measured. We compared 3D DW PSIF images with other sequences using the Wilcoxon-signed rank test and Friedman test. Inter-observer agreement was measured using intraclass correlation coefficient (ICC) analysis. Results: The mean 5-point scores of radial, median, and ulnar nerves in 3D DW PSIF (3.9/4.2/4.5, respectively) were higher than those in 3D T2 SPACE SPAIR (1.9/2.8/2.8) and 2D T2 TSE m-Dixon (1.7/2.8/2.9) sequences (P < 0.05). The mean SNR in 3D DW PSIF was lower than 3D T2 SPACE SPAIR, but there was no difference between 3D DW PSIF and 2D T2 TSE m-Dixon in all of the three nerves. The mean CNR in 3D DW PSIF was lower than 3D T2 SPACE SPAIR and 2D T2 TSE m-Dixon in the median and ulnar nerves, but no difference among the three sequences in the radial nerve. Conclusion: The three-dimensional DW PSIF sequence may be feasible to evaluate the peripheral nerves around the elbow in MR imaging. However, further optimization of the image quality (SNR, CNR) is required.

• Food Science and Preservation
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• v.20 no.2
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• pp.257-264
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• 2013

Central composite design along with response surface methodology (RSM) was applied to improve the fermentation process in onion (Allium cepa) wine production. The effects of different fermentation parameters (time, temperature, and initial sugar content) were found to be significant with respect to the physicochemical and sensory properties of wine. The maximum score for the alcoholic content was obtained at $29.27^{\circ}C$ fermentation temperature, 103.43 h fermentation time, and $27.52^{\circ}Brix$ initial sugar content. The maximum score for overall palatability was obtained at $39.27^{\circ}C$ fermentation temperature, 57.28 h fermentation time, and $22.14^{\circ}Brix$ initial sugar content. The coefficients of determination ($R^2$) were 0.9620 and 0.9060 for alcoholic content and overall palatability, respectively. The ranges of the optimum fermentation conditions ($28{\sim}32^{\circ}C$, 80~90 hr, and $20{\sim}25^{\circ}Brix$) were obtained by superimposing the response surfaces with regard to the alcoholic content and overall palatability of onion wine.

• Food Science and Preservation
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• v.24 no.1
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• pp.60-67
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• 2017

In this study, we tried to establish the best method for fresh blueberry beverage production using enzyme treatment as well as low temperature extraction. During extraction of physiologically functional materials, we used low temperature to prevent nutritional loss by heat. In addition, we investigated optimal blueberry extraction conditions using various enzyme treatments (cellulase, pectinase, cellulase:pectinase (1:1) mixture) to increase extraction efficiency and reduce turbidity. A variety and ratio of enzymes, extraction temperature, extraction time, and shaking speed were considered for the best extraction efficiency rate. We observed high extraction efficiency rates of 85.72-86.55% and 87.06-87.93%, respectively, upon cellulase or pectinase treatment. In addition, a mixture of cellulase:pectinase (1:1) showed an extraction efficiency rate of 86.84-88.14%. The best extraction efficiency rate was observed when crude blueberry was treated at $45^{\circ}C$ (87.91%), for 3 h (87.88%), in a 90 rpm shaker (89.19%). Sugar content and acidity of blueberry extract were not affected by the various treatments. However, total phenolic compounds were detected upon pectinase treatment (18.62 mg/g). Only fructose and glucose as free sugars were found in all samples regardless of treatments and extraction conditions.

• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.3
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• pp.451-459
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• 2002

High strength flour (12.5% protein) and low strength flour (10.5% protein)were used to determine optimum formulation far steamed bread added with green tea powder (GTP). The response surface study consisted of the following independent variables : GTP (1.5∼4.5%), mixing time (8∼14 min), fermentation time (30∼50min). Bread Quality attributes measured for total bread score of each combination were loaf volume, spread ratio, surface glossiness, smoothness, grain and texture (firmness, cohesiveness, elasticity and adhesiveness). The required amount of GTP, mixing time and fermentation time for steamed bread made from two kinds of flour were different. GTP could be more added to lower strength flour than higher strength flour without losing bread quality. GTP highly affected the loaf volume, spread ratio, surface smoothness, firmness and total bread score of steamed bread (p<0.001). The results suggested that the functional steamed bread added with GTP having excellent quality can be made from low strength flour using green tea powder 3.2%, mixing time 11 min 8 sec and fermentation time 39 min 55 sec.