• Journal of Pharmaceutical Investigation
• /
• v.40 no.1
• /
• pp.1-7
• /
• 2010

K-$BEtest^{(R)}$ is a well known program for bioequivalence test using a $2{\times}2$ design. Lee et al.(1998) and Park et al.(1999) suggested a $3{\times}3$ and $3{\times}2$ design, and also discussed their benefits. We developed a computer program, called BioEquiv, which can analyze some complex experimental designs such as, $3{\times}3$ design and $3{\times}2$ design including a standard $2{\times}2$ design. This program is a user-friendly one and overcomes the disadvantages of K-$BEtest^{(R)}$. The detailed statistical formula and structure of BioEquiv are presented with some examples. The comparison between K-$BEtest^{(R)}$ and BioEquiv are given with actual data analysis. BioEquiv is able to present a table of ANOVA test over some complex experimental designs. Moreover K-$BEtest^{(R)}$ and BioEquiv draw the same result when data consists of $2{\times}2$ design.

• Journal of Industrial Technology
• /
• v.21 no.B
• /
• pp.307-315
• /
• 2001

The purpose of this study was to provide the evaluation and prediction of strengths of SB latex modified concrete(LMC) using a statistical method and factorial experimental design method. The main experimental variables were as follows ; W/C ( 4 levels ; 31, 33, 35, 42%), S/a( 2 levels ; 55, 58%) and L/C(2 levels ; 5, 15%). The compressive strength and flexural strength of LMC were selected as a factor of response. The statistical method was carried out to analyze the results, together with factorial experimental design method and response surface method. The analysis showed that if L/C had been 15%, W/C appeared to be around 33% to achieve the design strength of $350kgf/cm^2$. In this case, the flexural strength and the slump came to around $68kgf/cm^2$ and 18cm, respectively. Eventhough the L/C varied, the design strength and W/C could be predictable together with slump value and flexural strength. As a result of series of experiments in this study, W/C and L/C were proved to be the main factors influencing on the compressive and flexural strength of LMC. Both of strength and slump values could be predictable from the mixing proportion of LMC.

• Microbiology and Biotechnology Letters
• /
• v.45 no.4
• /
• pp.330-342
• /
• 2017

Statistical design of experiments was employed to optimize the media composition for the production of laccase from Bacillus sp. PK4. In order to find the key ingredients for the best yield of enzyme production from the selected eleven variables viz yeast extract, glucose, zinc sulphate, copper sulphate, potassium chloride, magnesium sulphate, calcium chloride, ferrous sulphate, sodium chloride, potassium dihydrogen phosphate ($KH_2PO_4$) and dipotassium hydrogen phosphate ($K_2HPO_4$), Plackett-Burman design was applied. The $MgSO_4$, $FeSO_4$, and $CuSO_4$ showed positive estimate, and their concentration optimized further. The steepest ascent method and Box-Behnken method revealed that 1.5 mM $MgSO_4$, 0.33 g/l $FeSO_4$ and 1.41 mM $CuSO_4$ were optimal for the laccase production by Bacillus sp. PK4. This optimization strategy leads to enhancement of laccase production from 2.13 U/ml to 40.79 U/ml. Agro-wastes residues replace the carbon source glucose in the optimized media namely sugarcane bagasse, wheat bran, rice husk, and groundnut shell, among these groundnut shells (117 U/ml) was found to enhance the laccase production significantly. The laccase produced by Bacillus sp. PK4 was found to have the potential to degrade persistent organic pollutant benzo[a]pyrene.

• Journal of Korean Society for Quality Management
• /
• v.7 no.2
• /
• pp.22-28
• /
• 1979

The problem considered in this paper is to select the vital factor effect to the product quality through the experimental design and analysis of response surface, so as to control the quality improvement of industrial product. In this time, even through the mathematical model is unknown it could be applicable to control the quality of industrial products and to determine optimum operating condition for many technical fields, particulary, for industrial manufacturing process. When a set of data is available from an experimental design, it is often of interest 1:0 fit polynominal repression model in independent variables (eg, time, temperature, pressure, etc) the optimize the response variable (eg. yield, strength etc). This paper proposes a method known to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model. A criterion can be applied determining to optimum operating conditions in manufacturing industry and improving the fit of response surface which may be used for prediction of responses and quality control of industrial products.

• International Journal of Reliability and Applications
• /
• v.2 no.3
• /
• pp.209-240
• /
• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2355-2358
• /
• 2003

The purpose of this paper is to investigate two major feature extraction techniques based on generic modular face recognition system. Detailed algorithms are described for principal component analysis (PCA) and independent component analysis (ICA). PCA and ICA ate statistical techniques for feature extraction and their incorporation into a face recognition system requires numerous design decisions. We explicitly state the design decisions by introducing a modular-based face recognition system since some of these decision are not documented in the literature. We explored different implementations of each module, and evaluate the statistical feature extraction algorithms based on the FERET performance evaluation protocol (the de facto standard method for evaluating face recognition algorithms). In this paper, we perform two experiments. In the first experiment, we report performance results on the FERET database based on PCA. In the second experiment, we examine performance variations based on ICA feature extraction algorithm. The experimental results are reported using four different categories of image sets including front, lighting, and duplicate images.

• International Journal of Automotive Technology
• /
• v.6 no.6
• /
• pp.625-633
• /
• 2005

Vehicle drift was reduced using statistical six sigma tools. The study was performed through four steps: M (measure), A (analyze), I (improve), and C (control). Step M measured the main factors which were derived from a fishbone diagram. The measurement system capabilities were analyzed and improved before measurement. Step A analyzed critical problems by examining the process capability and control chart derived from the measured values. Step I analyzed the influence of the main factors on vehicle drift using DOE (design of experiment) to derive the CTQ (critical to quality). The tire conicity and toe angle difference proved to be CTQ. This information enabled the manufacturing process related with the CTQ to be improved. The respective toe angle tolerance for the adjustment process was obtained using the Monte Carlo simulation. Step C verified and controlled the improved results through hypothesis testing and Monte Carlo simulation.

• Journal of the Korean Statistical Society
• /
• v.24 no.2
• /
• pp.519-536
• /
• 1995

In the design of experiments for response surface analysis, sometimes it is of interest to estimate the difference of responses at two points. If differences at points close together are involved, the design that reliably estimates the slope of response surface is important. This idea was conceptualized by slope rotatability by Hader & Park (1978) and Park (1987). Until now, second order polynomial models were only studied for slope ratatability. In this paper, we will propose the necessary and sufficient conditions for slope rotatability over all directions for the thired order polynomial models in two, three and four independent variables. Also practical slope rotatable designs over all directions for two independent variables are suggested.

• Communications for Statistical Applications and Methods
• /
• v.13 no.2
• /
• pp.285-295
• /
• 2006

As more generic drugs become available, the quality, safety, and efficacy of generic drugs have become a public concern. Specifically, drug interchangeability among generic copies of the same brand-name drug is a safety concern. This research proposes a Bayesian method for assessing bioequivalence between two generic copies of the same brand-name drug from two independent $2{\times}2$ crossover design experiments. Uninformative priors are considered for general use and the posterior distribution of the difference of two generic drug effects is derived from which the highest probability density interval can be evaluated. Examples are presented for illustration.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.13 no.5
• /
• pp.364-374
• /
• 2003

The performance of an acoustic transducer is determined by the effects of many design variables. and mostly the influences of these design variables are not linearly independent of each other To achieve the optimal performance of an acoustic transducer, we must consider the cross-coupled effects of the design variables. In this study with the FEM. we analyzed the variation of the resonance frequency and sound pressure of a flextensional transducer in relation to Its design variables. Through statistical multiple regression analysis of the results, we derived functional forms of the resonance frequency and sound pressure in terms of the design variables, and with which we determined the optimal structure of the transducer by means of a constrained optimization technique, SQP-PD. The proposed method can reflect all the cross-coupled effects of multiple design variables, and can be utilized to the design of general acoustic transducers.