• 센서학회지
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• 제25권4호
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• pp.243-246
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• 2016

The characteristics of a bimetallic surface plasmon resonance (SPR) chip were investigated to detect a tumor biomarker, carcinoembryonic antigen (CEA). The linewidth and the tangential slope of the reflectance curve of the bimetallic SPR chip was compared with those of the reflectance curve of a conventional gold (Au) SPR chip. The changes in reflectance in response to the variation in CEA in the critical concentration range were analyzed at an angle where the tangential slope of the reflectance curve was maximum. From linear regression analysis, the sensitivity of the bimetallic SPR chip with respect to the CEA in critical concentration was obtained.

• 한국지반환경공학회 논문집
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• 제12권10호
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• pp.57-62
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• 2011

이 연구는 Methyl tert Btyl Ether(MTBE)의 광촉매반응을 통한 제거시에 다양한 음이온($Cl^-$, $NO_3{^-}$, $HCO_3{^-}$)들의 영향을 통계적 방법을 사용하여 조사하였다. 이 공정은 일반적으로 UV의 존재 하에 수용액상에 생성되는 Hydroxyl radicals(OH라디칼)의 생성에 기초하며, 이러한 라디칼들의 생성은 수용액 상의 무기 음이온들이 OH라디칼과의 반응에 의해 광분해를 방해한다. 이런 무기음이온들의 영향은 반응표면법(RSM)의 한 종류인 혼합물분석(Mixture analysis)를 통해 $Cl^-$, $NO_3{^-}$와 $HCO_3{^-}$의 독립변수들을 수학적으로 표현하였다. 분산분석(Analysis of variance; ANOVA)의 회귀분석항은 유의한 p값(p<0.0001)과 높은 결정계수($R^2$=99.28%, ${R^2}_{adj}$=98.91%)를 나타냈다. 그리고 등고선도(Contour plot)와 반응표면도(Response surface plot)는 $UV/H_2O_2$ 공정에 기초한 MTBE 광분해에 대한 무기 이온들의 영향을 나타내었다. 이 연구의 결과는 MTBE의 광분해에 대해 $Cl^-$와 $HCO_3{^-}$ 이온이 OH라디칼의 생성을 방해하는 것으로 나타났고 이 두 인자에 의한 상호작용이 관찰되었다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제11권3호
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• 한국환경과학회지
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• 제20권7호
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• pp.907-917
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• 2011

This study investigated the application of experimental design methodology to optimization of conditions of air-plasma and oxygen-plasma oxidation of N, N-Dimethyl-4-nitrosoaniline (RNO). The reactions of RNO degradation were described as a function of the parameters of voltage ($X_1$), gas flow rate ($X_2$) and initial RNO concentration ($X_3$) and modeled by the use of the central composite design. In pre-test, RNO degradation of the oxygen-plasma was higher than that of the air-plasma though low voltage and gas flow rate. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the RNO removal efficiency and test variables in a coded unit: RNO removal efficiency (%) = $86.06\;+\;5.00X_1\;+\;14.19X_2\;-\;8.08X_3\;+\;3.63X_1X_2\;-\;7.66X_2^2$ (air-plasma); RNO removal efficiency (%) = $88.06\;+\;4.18X_1\;+\;2.25X_2\;-\;4.91X_3\;+\;2.35X_1X_3\;+\;2.66X_1^2\;+\;1.72X_3^2$ (oxygen-plasma). In analysis of the main effect, air flow rate and initial RNO concentration were most important factor on RNO degradation in air-plasma and oxygen-plasma, respectively. Optimized conditions under specified range were obtained for the highest desirability at voltage 152.37 V, 135.49 V voltage and 5.79 L/min, 2.82 L/min gas flow rate and 25.65 mg/L, 34.94 mg/L initial RNO concentration for air-plasma and oxygen-plasma, respectively.

• Journal of Ginseng Research
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• 제40권3호
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• pp.229-236
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• 2016

Background: Extraction conditions greatly affect composition, as well as biological activity. Therefore, optimization is essential for maximum efficacy. Methods: Korean Red Ginseng (KRG) was extracted under different conditions and antioxidant activity, extraction yield, and ginsenoside Rg1 and phenolic content evaluated. Optimized extraction conditions were suggested using response surface methodology for maximum antioxidant activity and extraction yield. Results: Analysis of KRG extraction conditions using response surface methodology showed a good fit of experimental data as demonstrated by regression analysis. Among extraction factors, such as extraction solvent and extraction time and temperature, ethanol concentration greatly affected antioxidant activity, extraction yield, and ginsenoside Rg1 and phenolic content. The optimal conditions for maximum antioxidant activity and extraction yield were an ethanol concentration of 48.8%, an extraction time 73.3 min, and an extraction temperature of $90^{\circ}C$. The antioxidant activity and extraction yield under optimal conditions were 43.7% and 23.2% of dried KRG, respectively. Conclusion: Ethanol concentration is an important extraction factor for KRG antioxidant activity and extraction yield. Optimized extraction conditions provide useful economic advantages in KRG development for functional products.

• 한국전기전자재료학회논문지
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• 제23권11호
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• pp.831-836
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• 2010

In this paper, Plasma Enhanced Chemical Vapor Deposition (PECVD) $SiO_2$ film properties are modeled using statistical analysis and neural networks. For systemic analysis, Box-Behnken's 3 factor design of experiments (DOE) with response surface method are used. For characterization, deposited film thickness and film stress are considered as film properties and three process input factors including plasma RF power, flow rate of $N_2O$ gas, and flow rate of 5% $SiH_4$ gas contained at $N_2$ gas are considered for modeling. For film thickness characterization, regression based model showed only 0.71% of root mean squared (RMS) error. Also, for film stress model case, both regression model and neural prediction model showed acceptable RMS error. For sensitivity analysis, compare to conventional fixed mid point based analysis, proposed sensitivity analysis for entire range of interest support more process information to optimize process recipes to satisfy specific film characteristic requirements.

• 대한기계학회논문집A
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• 제32권8호
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• pp.693-700
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• 2008

The primary mirror system in a satellite camera is an opto-mechanically coupled system for a reason that optical and mechanical behaviors are intricately interactive. In order to enhance the opto-mechanical performance of the primary mirror system, opto-mechanical behaviors should be thoroughly investigated by using various analysis procedures such as elastic, thermo-elastic, optical and eigenvalue analysis. In this paper, optimal design of the bipod flexure mounts for high opto-mechanical performance is performed. Optomechanical performances considered in this paper are RMS wavefront error under the gravity and thermal loading conditions and 1st natural frequency of the mirror system. The procedures of the flexure mounts design based on design of experiments and statistics is as follows. The experiments for opto-mechanical analysis are constructed based on the tables of orthogonal arrays and analysis of each experiment is carried out. In order to deal with the multiple opto-mechanical properties, MADM (Multiple-attribute decision making) is employed. From the analysis results, the critical design variables of the flexure mounts which have dominant influences on opto-mechanical performance are determined through analysis of variance and F-test. The regression model in terms of the critical design variables is constructed based on the response surfaceanalysis. Then the critical design variables are optimized from the regression model by using SQP algorithm. Opto-mechanical performance of the optimal bipod flexure mounts is verified through analysis.

• 한국물환경학회지
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• 제26권1호
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• pp.35-43
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• 2010

This experimental design and response surface methodology (RSM) have been applied to the investigation of the electrocoagulation/flotation of dye wastewater. The electrocoagulation/flotation reactions were mathematically described as a function of parameters current (A), NaCl concentration (B), initial RhB concentration (C) and time (D) being modeled by use of the central composite design (CCD). The application of RSM using the CCD yielded the following regression equation, which is an empirical relationship between the RhB removal (%) and test variables in RhB removal (%) = $-300.42+129.21{\cdot}Current+46.99{\cdot}NaCl-0.11{\cdot}RhB-+43.71{\cdot}Time-5.67{\cdot}Current{\cdot}NaCl-3.18{\cdot}Current{\cdot}Time-2.41{\cdot}NaCl{\cdot}Time-19.79{\cdot}Current^2-2.27{\cdot}NaCl^2-1.59{\cdot}Time^2$. the model predictions agreed well with the experimentally observed result ($R^{2}=0.9728$). The estimated ridge of maximum response and optimal conditions for RhB removal (%) using canonical analysis was 99.4% (A: 1,77 A, NaCl concentration: 2.23 g/L, RhB concentration: 56.12 mg/L, Time: 9.98 min). To confirm this optimum condition, three additional experiments were performed and RhB removal (%) were within range of 86.87% (95% PI low)~111.93% (95% PI high) obtained.

• 한국식품저장유통학회지
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• 제10권3호
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• pp.320-325
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• 2003

대부분의 마는 건조분말제품으로 가공되고 있는데, 마를 다양한 가공품으로 개발하기 위한 방법의 하나로 삼투건조라는 전처리를 행하여 건조에 의한 품질손상을 억제하고 단맛으로 기호성을 높인 건조 마 제품을 얻을 수 있는 당절임 공정의 최적화를 시도하여 최적조건을 얻고자 하였다. 침지시간을 3-7시간, 온도는 20-6$0^{\circ}C$, 당농도는 30-70%로 하는 중심합성계획법으로 실험을 설계하여 최적화하였다. 이때의 종속변수로는 침지 후 수분함량, 당도, 색도, 그리고 동결건조후의 수분함량과 재수화율로 하여 분석한 결과 동결건조 후 수분함량에 대해서는 유의성이 없었다. 세 가지의 공정 변수 중 온도의 영향이 가정 적어 온도를 중심으로 고정한 후 침지시간과 당농도의 최적조건을 찾은 결과, 수분함량을 66-70%, 당도를 25-30%, L 75이상, a -2.1--2.4, b를 5이상 그리고 재수화율을 200-250을 제한 조건으로 하는 영역은 5.2-5.9시 간, 56-61%로 나타났다.

• Geomechanics and Engineering
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• 제16권6호
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• pp.655-667
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• 2018

To evaluate the stability of a rock slope with one pre-exiting vertical crack, this paper performs corresponding probabilistic stability analysis. The existence of cracks is generally ignored in traditional deterministic stability analysis. However, they are widely found in either cohesive soil or rock slopes. The influence of one pre-exiting vertical crack on a rock slope is considered in this study. The safety factor, which is usually adopted to quantity the stability of slopes, is derived through the deterministic computation based on the strength reduction technique. The generalized Hoek-Brown (HB) failure criterion is adopted to characterize the failure of rock masses. Considering high nonlinearity of the limit state function as using nonlinear HB criterion, the multivariate adaptive regression splines (MARS) is used to accurately approximate the implicit limit state function of a rock slope. Then the MARS is integrated with Monte Carlo simulation to implement reliability analysis, and the influences of distribution types, level of uncertainty, and constants on the probability density functions and failure probability are discussed. It is found that distribution types of random variables have little influence on reliability results. The reliability results are affected by a combination of the uncertainty level and the constants. Finally, a reliability-based design figure is provided to evaluate the safety factor of a slope required for a target failure probability.