Earticle

본 연구는 루틴, 퀘르세틴, 식이섬유가 전분 소화율에 미치는 영향을 통계적 혼합물 설계방법을 이용하여 확인 하고자 하였다. 세 가지 성분들은 모두 농도가 증가함에 따라 전분소화 지연 효과가 나타났으며, 그 중에서도 퀘르세틴 과 식이섬유가 함께 섞였을 때 가장 높은 지연 효과를 보였다. 이 혼합물 설계는 simplex-centroid 실험설계법을 이 용하였고, 최적 모델은 quadratic 모델에서 나타났다. 이때 얻어진 회귀방정식을 통하여 유의한 상승효과를 확인할 수 있었다. 최적화 통계 방법을 사용하여 혼합비를 분석한 결과 퀘르세틴과 식이섬유가 72: 28 비율에서 전분 소화 지연 효과가 최대로 나타나는 것을 확인하였다. 전분소화에 대한 영향을 3차원 표면 도표로 시각화하여 나타내었으며, 이 결과로 퀘르세틴과 식이섬유의 상호작용으로 인하여 전분 소화를 15% 이상 지연시키는 것을 확인할 수 있었다.

This study was conducted to develop the efficient system for starch hydrolysis suppression using rutin, quercetin and dietary fiber through the statistical mixture design. The three components were replaced with wheat flour at the level of 10% and the mixed gel with three components was characterized by in vitro starch digestion. The mixture design was applied by simplex-centroid experimental model. The quadratic model (R2=0.86) was well fitted and the obtained regression equation indicated that the significant positive effects was observed in the quercetin and fiber mixture. Based on the statistical results, the best mixing ratio of quercetin and fiber was 72: 28 that led to the lowest predicted glycemic index (pGI). Their interactions on the pGI of starch digestibility were clearly visualized in the 3D surface plot. These results suggested that the mixture of quercetin and fiber interact strongly with wheat flour, consequently retarding starch hydrolysis by 15%.

In this study, we aimed to develop a mixed tea prepared with roasted mulberry leaf and fruit using response surface methodology (RSM). Roasting of mulberry leaf was by 6 stages, as shown in Fig. 1; and mulberry fruit was roasted in 4 stages, as shown in Fig. 2. Subsequently, physicochemical measurements such as total polyphenol content, nitric oxide production content, and ${\alpha}$-glucosidase inhibitory effect were obtained for each sample. Central composite design was applied to prepare samples containing varying contents of roasted mulberry leaf (RoML) and roasted mulberry fruit (RoMF); subsequently, sensory evaluation was conducted. The total polyphenol content of roasted samples (RoML and RoMF) were significantly higher than that of raw samples (RaML and RaMF), respectively. The nitric oxide (NO) production of roasted samples were significantly lower than that of control (LPS induced RAW 264.7 cell). The ${\alpha}$-glucosidase inhibitory effect of roasted samples was significantly higher than that of raw samples, respectively. Based on the RSM estimation for determination of optimum ratio by sensory evaluation (taste, color, and flavor) among 13 mixed samples, the optimum mixing ratio of RoML and RoMF for taste, color, and flavor were 1.64 g (RoML) and 0.88 g (RoMF), 1.35 g (RoML) and 0.92 g (RoMF), 1.65 g (RoML) 1.03 g (RoMF), respectively. Based on results of three sensory evaluations, mixing ratio comprising 1.54 g of RoML and 0.92 g of RoMF is desirable for delicious tea with functionality.

다양한 원재료를 혼합하여 원하는 성분 함유량을 가진 제품을 최소의 비용으로 생산하는 혼합 최적화 문제에 대해 일반적으로 O(n4)의 수행 복잡도의 선형계획법을 적용하고 있다. 본 논문에서는 이 문제에 대해 O(nlogn)복잡도 로 해를 얻을 수 있는 휴리스틱 알고리즘을 제안한다. 제안된 알고리즘은 합금 강판에서 요구하는 성분들의 함유량 범위 를 충족시키면서 최소의 원자재비용을 얻기 위해, 원재료 단가 오름차순으로 성분별 함유량을 충족시키도록 원재료 양을 결정하였다. 3가지 사례에 대해 적용한 결과 제안된 알고리즘은 O(nlogn) 복잡도로 단순한 결정기법을 적용하였음에도 불구하고, LP의 최적화 기법과 동일하거나 보다 좋은 해를 얻을 수 있었다.

Generally, the linear programming (LP) with O(n4) time complexity is applied to mixture optimization problem that can be produce the given ingredients grade product with minimum cost from mixture of various raw materials. This paper suggests heuristic algorithm with O(nlogn) time complexity to obtain the solution of this problem. The proposed algorithm meets the content range of the components required by the alloy steel plate while obtaining the minimum raw material cost, decides the quantity of raw material that is satisfied with ingredients grade for ascending order of unit cost. Although the proposed algorithm applies simple decision technique with O(nlogn)time complexity, it can be obtains same solution as or more than optimization technique of linear programing.

This paper proposes an improved training procedure in speech recognition based on the continuous density of the Hidden Markov Model (CDHMM). Of the three parameters (initial state distribution probability, state transition probability, output probability density function (p.d.f.) of state) governing the CDHMM model, we focus on the third parameter and propose an efficient algorithm that determines the p.d.f. of each state. It is known that the resulting CDHMM model converges to a local maximum point of parameter estimation via the iterative Expectation Maximization procedure. Specifically, we propose two independent algorithms that can be embedded in the segmental K -means training procedure by replacing relevant key steps; the adaptation of the number of mixture Gaussian p.d.f. and the initialization using the CDHMM parameters previously estimated. The proposed adaptation algorithm searches for the optimal number of mixture Gaussian humps to ensure that the p.d.f. is consistently re-estimated, enabling the model to converge toward the global maximum point. By applying an appropriate threshold value, which measures the amount of collective changes of weighted variances, the optimized number of mixture Gaussian branch is determined. The initialization algorithm essentially exploits the CDHMM parameters previously estimated and uses them as the basis for the current initial segmentation subroutine. It captures the trend of previous training history whereas the uniform segmentation decimates it. The recognition performance of the proposed adaptation procedures along with the suggested initialization is verified to be always better than that of existing training procedure using fixed number of mixture Gaussian p.d.f.

In this study, the enzymatic process for biodiesel production was optimized using a mixture of immobilized Rhizopus oryzae and Candida rugosa lipases. The optimal temperature and agitation speed for biodiesel production were $45^{\circ}C$ and 300 rpm, respectively. The optimal ratio of R. oryzae and C. rugosa lipases in the mixture was 3:1 (w:w). When 3 mmol of methanol was the initial reaction medium and 3 mmol of methanol was added every 1.5 h during biodiesel production, biodiesel conversion was over 98% at 4 h. In addition, when the immobilized lipase mixture was reused, biodiesel conversion exceeded 80% after 5 reuses.

Plasma enhanced chemical vapor deposition (PECVD) silicon dioxide thin films have many applications in semiconductor manufacturing such as inter-level dielectric and gate dielectric metal oxide semiconductor field effect transistors (MOSFETs). Fundamental chemical reaction for the formation of SiO2 includes SiH4 and O2, but mixture of SiH4 and N2O is preferable because of lower hydrogen concentration in the deposited film [1]. It is also known that binding energy of N-N is higher than that of N-O, so the particle generation by molecular reaction can be reduced by reducing reactive nitrogen during the deposition process. However, nitrous oxide (N2O) gives rise to nitric oxide (NO) on reaction with oxygen atoms, which in turn reacts with ozone. NO became a greenhouse gas which is naturally occurred regulating of stratospheric ozone. In fact, it takes global warming effect about 300 times higher than carbon dioxide (CO2). Industries regard that N2O is inevitable for their device fabrication; however, it is worthwhile to develop a marginable nitrous oxide free process for university lab classes considering educational and environmental purpose. In this paper, we developed environmental friendly and material cost efficient SiO2 deposition process by substituting N2O with O2 targeting university hands-on laboratory course. Experiment was performed by two level statistical design of experiment (DOE) with three process parameters including RF power, susceptor temperature, and oxygen gas flow. Responses of interests to optimize the process were deposition rate, film uniformity, surface roughness, and electrical dielectric property. We observed some power like particle formation on wafer in some experiment, and we postulate that the thermal and electrical energy to dissociate gas molecule was relatively lower than other runs. However, we were able to find a marginable process region with less than 3% uniformity requirement in our process optimization goal. Surface roughness measured by atomic force microscopy (AFM) presented some evidence of the agglomeration of silane related particles, and the result was still satisfactory for the purpose of this research. This newly developed SiO2 deposition process is currently under verification with repeated experimental run on 4 inches wafer, and it will be adopted to Semiconductor Material and Process course offered in the Department of Electronic Engineering at Myongji University from spring semester in 2012.

A simplex-centroid experimental design was used for the optimization of both reducing and oxidizing improvers, namely Aspergillus oryzae S2 ${\alpha}$-amylase (Amy), ascorbic acid (Asc), and glucose oxidase (GOD). This optimization was performed to enhance the dough and breadmaking qualities of soft French wheat flour and a composite counterpart that contained 30% Ukrainian wheat flour. Statistically significant correlations were calculated between the W index and textural parameters (e.g., dough chewiness and bread cohesiveness). The findings revealed that while the best mixture for French flour comprised 21.8% of Amy, 41.2% of Asc, and 37% of GOD, for the composite counterpart, it comprised 2.3% of Amy, 66% of Asc, and 31.7% of GOD. These optimized mixtures rearranged soft French wheat flour and its composite counterpart to a good quality and an improved flour texture, respectively. Additionally, they increased the loaf specific volumes of the breads made from soft French wheat flour and its counterpart by 25.8 and 45.43%, respectively, significantly decreased the breads' susceptibility to microbial contamination, and reclassified the breads as "good" in terms of sensory attributes.

호흡기계 질환에 효과적이라고 알려져 있는 식물성분들을 이용하여 기능성 음료를 개발하고자, 혼합물 실험계획법을 통해 혼합 최적 비율을 찾기 위한 실험을 수행하였다. 즉, 머위 30~70%, 수세미 10~30% 및 어성초 10~30%의 비율로 혼합하여 중앙점 반복을 포함하여 총 12개의 실험점을 설계하였고, 이 설계를 바탕으로 혼합물은 121℃에서 45분간 중탕 추출을 하여 anti-allergy activity 및 anti-microbial activity를 측정하였다. anti-allergy activity 효과는 Response surface와 trace plot을 보면 머위의 함량이 많을수록 좋은 효과를 나타내었고 수세미는 다소약한 영향을 미친다는 것을 알 수 있었다. 다중회귀분석 결과 상관계수 R²=82.10%이며 유의적인 회귀식으로 설명이 가능한 것으로 확인되었다. 따라서 최적비율은 머위 0.75, 수세미 0.14 그리고 어성초 0.11의 비율로 결정되었다. anti-microbial activity는 혼합비율에 따른 각 추출물들이 그람양성균인 Staphylococcus aureus (KCCM 40881), Staphylococcus epidermidis (KCCM 35494)에 대해서는 유효하나 그람음성균인 Escherichia coli (KCCM 11234), Pseudomonas aeruginosa (KCCM 11328)에 대해서는 미미하거나 효과가 나타나지 않았다.

This study was performed to determine the optimal ratio of Petasites japonicus, Luffa cylindrica, and Houttuynia cordata, all of which are supposed to have anti-respiratory disease effects, such as against rhinitis. The experiment incorporated a mixture design and included 12 experimental points with center replicates for three different independent variables (Petasites japonicus 30~70%; Luffa cylindrica 10~30%; and Houttuynia cordata 10~30%). Based on this design, the mixture was extracted in hot water at 121℃ for 45 min and anti-allergy and anti-microbial activities were observed. The response surface and trace plot described for the anti-allergy activity showed Petasites japonicas was a relatively important factor. The correlation coefficient (R²) value 82.10% for the inhibition effect of degranulation was analyzed by the regression equation. The analysis of variance showed the model fit was statistically significant (p<0.05). The optimal ratio of the mixture was Petasites japonicus 0.75%, Luffa cylindrica 0.11%, and Houttuynia cordata 0.14%. The anti-microbial activity for each extraction of the mixture was valid on gram-positive, such as Staphylococcus aureus (KCCM 40881) and Staphylococcus epidermidis (KCCM 35494), while it was less effective on gram-negative, such as Escherichia coli (KCCM 11234) and Pseudomonas aeruginosa (KCCM 11328).

최고 품질의 클렌징 제품 개발을 위해서 계면활성제 혼합물 조성의 최적화를 시도하였다. 사전실험을 통해 세정력, 기포형성력, 오염률에서 각각 우수한 특성을 나타내는 계면활성제 3종 sodium cocoyl alaninate (SCoA), cocamidopropyl betaine (CPB), decyl glucoside (DG)을 선정하였다. 계면활성제 혼합물의 심플렉스 중심 설계 배열에 따른 실험을 수행하고, 실험에서 얻어진 데이터를 가지고 회귀분석을 실시하였다. 통계적으로 유의미한 반응 표면 모델식을 구하고, 세 개의 반응변수의 동시 최적화 과정을 통해 계면활성제 혼합물의 최적 조성은 SCoA (0.22), CPB (0.78), DG (0.00)으로 구해졌다.

The main goal of this study was to find an optimal surfactant mixture composition for the development of the best performing cleansing products. Three different surfactants including sodium cocoyl alaninate (SCoA), cocamidopropyl betaine (CPB), and decyl glucoside (DG) were selected, which showed excellent properties in detergency, foaming height, and contamination rate through preliminary experiments. The experiments by simplex centroid design matrix for surfactant mixtures were performed, and the regression analysis was conducted with the experimental data. Surface response model equations, which is statistically significant (p < 0.05), were obtained. The optimal composition of the surfactant mixture was also determined as SCoA (0.22), CPB (0.78), and DG(0.00) from simultaneous optimization of three response variables.

본 논문은 HMM 기반 임베디드 음성인식 시스템 구현에 관한 몇 가지 주제들을 설명한다. 임베디드 환경은 한정된 자원을 가지고 있고 그러한 가운데 타당한 인식률과 향상된 인식 속도를 얻기 위해서 몇가지 방법들을 이 논문에서 설명한다. 구현 환경은 DSP6711 기반에서 이루어졌다. 가우시안 mixture 계산 루틴을 부동소수점 연산에서 고정소수점 연산 및 software pipelining을 적용하였다. 고정소수점 변환 전과 후 비슷한 인식률을 얻었고 고정소수점 변환과 software pipelining 적용 후 연산 속도의 향상을 얻었다.

This study was conducted to manufacture salt to which the peel and flesh of lemon were added, using a mixture experiment design. Analyses of the general composition and anti-oxidation of the peel and flesh of lemon were conducted, and the mixing ratio was designed in an augmented design, and 14 types of samples were manufactured to conduct a sensory test and a physico-chemical test. In the general composition analysis, there were significant differences in all parts of moisture, crude ash, crude fat, crude carbohydrate, and Kcal, except for crude protein, and anti-oxidation was higher in the peel of lemon than in the flesh. With the findings of the sensory test of the 14 types of lemon salt mixtures, the peel of lemon, the flesh of lemon, and salt interaction were analyzed for optimization. The 1st optimization showed the degree of convergence of 72.7%; however, color (3.96) and appearance (3.77) showed lower-than-average preference, so the optimization was conducted again, dropping the color and appearance. The degree of convergence increased to 84.1%, and the optimum mixing ratio estimated based on that was as follows. Peel of lemon : flesh of lemon : salt=39.5% : 40.6% : 19.9%=100%. At this time, the physico-chemical characteristics were as follows. Salinity: 2.15, pH: 2.79, Sugar content: 2.69, Brightness: 54.12, redness: ?0.42, and yellowness: 0.587. An analysis of complex changes in the product in which other values are affected by one value when it is changed, since the characteristics of ingredients are different, based on this study that developed lemon salt that could reduce salt intake, using the mixture experiment design can get results with high accuracy even with fewer experiments. It is judged that this would be an economic and effective experimental method in the experiments for developing foods, which take a lot of time and cost.

Purpose: In this paper we present a case study of developing fast curing adhesives for insulation material of LNG carriers using an extreme vertices design with four mixture components. Three material properties are considered - shear strength, viscosity, and tensile strength. In the optimization experiment, we used hardness instead of tensile strength due to shortage of specimens. Methods: We employ four-factor extreme vertices design with 19 runs and desirability function approach for simultaneously optimizing three responses. After selecting optimal condition of the mixture components, we do confirmation experiments to verify the reproducibility of the optimal condition under manufacturing circumstance. Results: Simultaneous optimal condition for the three responses, that is, shear strength, viscosity, and harness is obtained. At the optimal condition, confirmation experiments are executed in manufacturing circumstance. The variation for the shear strength is not satisfactory, which is due to the variation of the humidity. Conclusion: At the optimal condition three material properties are satisfactory. To reduce the variability for the shear strength, robust design is needed.

본 연구는 초음파 진동에 의해 발생하는 공동현상을 이용하여 다양한 유용성분과 생리활성을 가지고 있는 녹차와 애엽을 혼합하여 새로운 식품소재를 개발하기 위해서 반응표면분석법에 의한 추출특성을 모니터링 하여 최적 추출조건을 예측하였다. 초음파를 지속적으로 가하는 조건에서 Box-Behnken design에 의해 녹차와 애엽의 혼합비, 용매와 용질의 비, 추출시간을 독립변수로 하여 15구간의 추출조건을 설정하고 추출수율(Y)을 종속변수로 하여 모니터링 하였다. 반응표면분석결과 녹차 및 애엽 혼합 추출물은 녹차의 함량과 추출용매의 양이 증가 할수록 추출수율이 증가 하였으며, 추출시간은 결과에 큰 영향을 주지 않는 것으로 나타났다. 추출수율을 최대로 얻을 수 있는 녹차 및 애엽 혼합물의 최적 추출조건은 녹차와 애엽의 혼합비 85.86%, 용매와 용질의 비 92.73 mL/g, 추출시간 56.52분으로 확인되었으며, 추출수율의 최대값은 30.03%로 예측되었다.

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.

본 연구에서는 Isobutyl Acetate와 Isobutyl Alcohol의 공비혼합물을 압력변환증류공정(PSD; Pressure Swing Distillation Process)을 이용하여 99.9 mol% 이상의 Isobutyl Acetate를 분리하는 공정모사를 수행하였다. 압력변환증류공정은 공비혼합물의 상대휘발도와 공비조성이 압력의 변화에 따라 차이가 나는 특성을 이용한 공정이다. 액상에서는 Non-Random Two Liquid (NRTL) model을 그리고 기상에서는 Peng-Robinson equation을 이용하였다. 최적화 방법으로 환류비와 주입단 위치를 변수로 두고 총 재비기 소요 열량을 최소화시키는 목적으로 최적화를 수행하였다. 압력변환 증류공정은 두 개의 증류탑을 필요로 함에 따라 고압 증류탑과 저압 증류탑의 배열에 따른 최적화 조건 또한 비교를 수행하였다.

In this study, an optimization process design has been performed to separate 99.9 mol% of Isobutyl Acetate from binary azeotropic mixture of Isobutyl Acetate and Isobutyl Alcohol system using a Pressure Swing Distillation (PSD). PSD is used to separate binary azeotropic mixtures using the difference between the relative volatilities and azeotropic compositions by changing the system pressure. Non-Random Two Liquid (NRTL) model for liquid phase and the Peng-Robinson equation for vapor phase are used. An optimization study for the reflux ratio and feed stage locations which minimize the total reboiler heat duties are studied. Since PSD process consists of two columns, i.e. high pressure and low pressure, the effect of column sequence on the optimum conditions is reported.

Purpose: To derive the optimal conditions for the Rubber based colloidal suspension manufacturing process, which made using a stirrer, to apply the mixture design method. Methods: We used two process component and one process variable Mixture design to derive the optimal conditions for the process. The response variables were selected for rotational viscometer measures which can represent Rubber based colloidal suspension quality. The input variables were selected as the values of rubber-organic solvent expressed in proportions as process components and stirring amount as a process variable which are controllable factors in the process. Results: Based on the results of the experiment, rubber and organic solvent and the interaction between stirring amount and rubber and the interaction between stirring amount and rubber and organic solvent were significant. Reproducibility of the regression model was confirmed by the observation that the values obtained from the reproducibility experiment fell within the confidence interval. Additionally, the model predictions were found to be in close agreement with the field measurements. Conclusion: In this study, a regression model was developed to predict the viscosity change of colloidal suspensions based on the proportion of rubber based colloidal suspension. The developed regression model can lead to improved product quality.

본 연구는 홍시라떼 분말화의 최적조건 설정을 위하여 반응표면분석법(RSM)을 이용하였으며, 독립변수는 inlet temperature($X_1$), air flow rate($X_2$), 시료의 공급속도인 feed flow rate($X_3$)로 설정하고 종속변수로는 회수량($Y_1$), 수분흡수지수($Y_2$), total phenolic compounds($Y_3$)로 설정하였다. 각 종속변수에 따른 회귀식은 모두 p<0.001 수준에서 유의성이 인정되었다. 홍시라떼의 경우 과당이 풍부하여 분말의 부착성이 높기 때문에 유리전이 온도와 입자의 표면 온도차이가 낮을수록 회수량은 높아졌으며, 분말의 결정성과 응집성은 증가하여 수분흡수지수는 낮아졌다. 또한 낮은 inlet temperature($X_1$)와 높은 feed flow rate($X_3$)는 입자의 표면 온도와 열의 접촉 시간을 모두 낮추어 total phenolic compounds의 손실을 최소화 하였다. 각 독립변수와 종속변수의 영향을 나타내는 반응표면그래프를 이용하여 최적 분말화 조건을 예측한 결과 inlet temperature($X_1$) $90^{\circ}C$, air flow rate($X_2$) 53 mL/min, feed flow rate($X_3$) 17.00 mL/min로 결정되었다.

The purpose of this study was to determine the optimum spray drying conditions of soft persimmon latte using response surface methodology that is a statistical procedure used for optimization studies. A central composite design was applied to investigate the effects of independent variables, inlet temperature ($X_1$), air flow rate ($X_2$), and feed flow rate ($X_3$), on responses such as yield, water absorption index, and total phenolic compounds. Statistical analysis revealed that independent variables significantly affected all the responses. A maximum yield of 8.11 g was obtained at $90^{\circ}C$ of $X_1$, 51.82 mL/min of $X_2$ and 7.00 mL/min of $X_3$. A minimum water absorption index of 0.58 was obtained at $101^{\circ}C$ of $X_1$, 60.00 mL/min of $X_2$ and 17.00 mL/min of $X_3$. A maximum total phenolic compounds of $298.02{\mu}g/mL$ was obtained at $90^{\circ}C$ of $X_1$, 43.33 mL/min of $X_2$ and 17.00 mL/min of $X_3$. In conclusion, the best spray drying conditions were as follows: $X_1$, $90^{\circ}C$; $X_2$, 53 mL/min; $X_3$, 17 mL/min. Under those optimal conditions, the powder's yield (7.46 g), water absorption index (0.54), and the content of total phenolic compounds ($294.75{\mu}g/mL$) were estimated.

This study was conducted for the optimization of ingredients in salad dressing using Hwangdo peach (Prunus persica L. Batsch). The experiment was designed according to the D-optimal design of mixture design, which included 14 experimental points with 4 replicates for three independent variables (olive oil 40～65%, peach puree 27～50%, vinegar 8～20%). The linear regression models for pH, viscosity and color value and the quadratic regression models for emulsion stability, all sensory evaluation of the products were proven to be valid by the F-test for the overall significance of the regression model at a 5% level. Viscosity and pH of the products increased as olive oil content. Color value, viscosity and pH of the products increased as peach puree content. pH, viscosity, redness, and yellowness of the products decreased as vinegar content. Sensory evaluation result of the products showed that general preference for the products were increasingly affected by the increases in contents then decreased as they exceeded the optimum levels. In consequence, according to result from the first stage of the experiment, the optimum ingredients ratios of the raw materials were set in olive oil 52.43%, peach puree 35.07%, and vinegar 13.91% for ingredients of apricot dressing. These results provided the possibility that peach can be applied to the preparation of a dressing, and thereby present baseline data for the development of new dressings. This is also presumed to meet demands of customers who are always in pursuit of new products.

반응표면분석법은 최적화 연구에 자주 사용되는 통계적 분석방법이다. 본 연구는 반응표면분석법에 의해 Staphylococcus aureus, Bacillus cereus, Escherichia coli, Salmonella typhimurium, Pseudomonas fluorescens 및 Vibrio parahaemolyticus에 대한 자몽종자 추출물과 젖산 혼합물의 항균활성을 검토하여 최적화하였다. 중심합성계획에 따라 1% 자몽종자 추출물 (GFSE)과 10% 젖산 (LA)의 비율 ($X_1$, 0:100-100:0 v/v)과 1% GFSE와 10% LA 혼합물의 농도 ($X_2$, 20-100%)를 독립변수로 하고 S. aureus ($Y_1$), B. cereus ($Y_2$), E. coli ($Y_3$), S. typhimurium ($Y_4$), P. fluorescens ($Y_5$) 및 V. parahaemolyticus ($Y_6$)에 대한 항균활성을 종속변수로 하여 항균활성을 측정하였다. 미생물에 대한 1% GFSE와 10% LA의 항균활성 처리조건의 최적범위는 다양한 조건하에서 얻어진 반응변수의 항균활성에 관하여 중첩된 등고선도로 예측하였고, 항균활성을 최대화하기위한 최적범위는 1% GFSE와 10% LA의 비율 35.73:64.27-56.58:43.42 (v/v)이었고 혼합물의 농도는 $51.70{\sim}100%$였다. 최적 항균활성 범위내의 주어진 조건 (1% GFSE:10% LA 비율 40:60, 1% GFSE:10% LA 혼합물 70%)에서 S. aureus ($Y_1$), B. cereus ($Y_2$), E. coli ($Y_3$), S. typhimurium ($Y_4$), P. fluorescens ($Y_5$) 및 V. parahaemolyticus ($Y_6$)에 대한 1% GFSE:10% LA 혼합물의 비율 및 농도의 항균활성은 각각 24.55, 25.22, 20.20, 22.49, 23.89 및 28.04 mm로 예측되었다. 최적조건 범위내의 임의의 조건에서 실험한 결과 각 종속변수들의 예측값과 실제값이 유사한 항균활성을 보였다.

Response surface methodology (RSM) is frequently used for optimization studies. In the present work, RSM was used to determine the antimicrobial activitiesof grapefruit seed extract (GFSE) and a lactic acid mixture (LA) against Staphylococcus aureus, Bacillus cereus, Escherichia coli, Salmonella typhimurium, Pseudomonas fluorescens, and Vibrio parahaemolyticus. A central composite design was used to investigate the effects of independent variables on dependent parameters. One set of antimicrobial preparations included mixtures of 1% (w/w) GFSE and 10% (w/w) LA, in which the relative proportions of component antimicrobials varied between 0 and 100%. In further experiments, the relative proportions were between 20% and 100%. Antimicrobial effects against various microorganisms were mathematically encoded for analysis. The codes are given in parentheses after the bacterial names, and were S. aureus ($Y_1$), B. cereus ($Y_2$), E. coli ($Y_3$), S. typhimurium ($Y_4$), P. fluorescens ($Y_5$), and V. parahaemolyticus ($Y_6$). The optimum antimicrobial activity of the 1% (w/w) GFSE:10% (w/w) LA mixture against each microorganism was obtained by superimposing contour plots ofantimicrobial activities on measures of response obtained under various conditions. The optimum rangesfor maximum antimicrobial activity of a mixture with a ratio of 1:10 (by weight) GFSE and LA were 35.73:64.27 and 56.58:43.42 (v/v), and the optimum mixture ratio was 51.70-100%. Under the tested conditions (a ratio of 1% [w/w] GFSE to 10% [w/w] LA of 40:60, and a concentration of 1% [w/w] GFSE and 10% [w/w] LA, 70% of the highest value tested), and within optimum antimicrobial activity ranges, the antimicrobial activities of the 1% (w/w) GFSE:10% (w/w) LA mixture against S. aureus ($Y_1$), B. cereus ($Y_2$), E. coli ($Y_3$), S. typhimurium ($Y_4$), P. fluorescens ($Y_5$), and V. parahaemolyticus ($Y_6$) were 24.55, 25.22, 20.20, 22.49, 23.89, and 28.04 mm, respectively. The predicted values at optimum conditions were similar to experimental values.

압력변환 증류공정(Pressure-Swing Distillation, PSD)을 통해서 1-프로판올과 벤젠 이성분계 혼합물의 분리공정에 대한 전산모사 및 공정 최적화를 수행하였다. Schneider Electric사의 PRO/II with PROVISION V10.0을 사용하였으며, 열역학 모델식으로는 NRTL 액체 활동도계수 모델식을 적용하였다. 고압에서 저압 증류탑 배열 공정과 저압에서 고압 증류탑 배열공정에 대한 재비기의 총 heat duty의 소모량의 합을 서로 비교하였다. 유틸리티 소모량을 최소화하기 위해서 각 공정의 저압 증류탑과 고압 증류탑 상부 벤젠의 조성, 이론단수와 원료 주입단의 위치를 최적화하였으며, 각각의 증류탑의 환류비를 조절하였다. 공정 최적화 수행결과, 총 재비기 heat duty 값은 각각 고압에서 저압 증류탑 배열 공정의 경우 $3.10{\times}10^6kcal/h$ 이었으며, 저압에서 고압 증류탑 배열 공정의 경우 $2.75{\times}10^6kcal/h$로 나타났다. 또한, 저압-고압 증류탑 배열 공정에 열통합 공정(heat integration)을 적용한 경우 재비기의 총 heat duty 값이 고압-저압 증류탑 배열 공정에 비해서 약 57.36%정도 적게 추산되었다.

Computer modeling and optimization works have been performed for the separation of the binary mixture of 1-propanol and benzene through a pressure-swing distillation. PRO/II with PRIVISION V10.0 at Schneider Electric company and NRTL liquid activity coefficient model were utilized. The sum of the total reboiler heat duties of the low-high and high-low pressure column configurations were compared. To minimize the utility consumptions, low column, and high column to obtain pure benzene at the top, the number of theoretical stages and optimal feed tray locations for each distillation column were determined and the reflux ratios for each distillation column were also adjusted. As a result of the optimization works, the sum of the total reboiler heat duties for the high-low and low-high pressure configurations were $3.10{\times}10^6kcal/h$ and $2.75{\times}10^6kcal/h$, respectively. In the case where heat integration was applied to low-high pressure configurations, 57.36 % of the total reboiler heat duties could be saved compared to the high-low pressure configurations.