The aim of this study was to develop a simple and reliable high-performance chromatographic (HPLC) method for simultaneous analysis of adapalene and benzoyl peroxide in pharmaceutical formulation by response surface methodology (RSM). An optimized mobile phase composed of acetonitrile, tetrahydrofuran and water containing 0.1% acetic acid at a ratio of 25:50:25 by volume was successfully predic...

Device robust-design is inherently a multiple-objective optimization problem. Using design of experiments (DoE) combined with response surface methodology (RSM) can satisfy the great incentive to reduce the number of TCAD simulations that need to be performed. However, the errors of RSM models may large enough to diminish the validity of the results for some nonlinear problems. To find the feas...

exergy analysis and response surface methodology (rsm) is applied to reduce the exergy loss and improve energy and exergy efficiency of acetic acid production plant. exergy analysis is run as a thermodynamic tool to assess exergy loss in reactor and towers of acetic acid production process. the process is simulated in aspen plus(v.8.4) simulator and the necessary thermodynamics data for calcula...

Classifier combining techniques have become popular for improving weak classifiers in recent years. The random subspace method (RSM) is an efficient classifier combining technique that can improve classification performance of weak classifiers for the small sample size (SSS) problems. In RSM, the feature subsets are randomly selected and the resulting datasets are used to train classifiers. How...

Optimization plays a key role in environmental engineering parameters since the best system performance mainly is on optimum point or optimum range. The majority of wastewater treatment processes are multi-variable and optimization through the classical method is inflexible, unreliable and time-consuming. Thus, response surface methodology (RSM), as a very efficient design and widely used techn...

Finite element (FE) models are widely used to predict the dynamic characteristics of aerospace structures. These models often give results that differ from the measured results and therefore need to be updated to match the measured data. FE model updating entails tuning the model so that it can better reflect the measured data from the physical structure being modeled 1. One fundamental charact...

Response Surface Methodology (RSM) is a popular class of methods used to build empirical models through statistical means. Rarely in the literature is the RSM applied to model characteristics of Evolutionary Algorithm (EA) based techniques used to solve dynamic optimization problems. This paper presents RSM as a modelling tool of some characteristics of a memory and EA-based approach referred t...

This study presents the random-effects rating scale model (RE-RSM) which takes into account randomness in the thresholds over persons by treating them as randomeffects and adding a random variable for each threshold in the rating scale model (RSM) (Andrich, 1978). The RE-RSM turns out to be a special case of the multidimensional random coefficients multinomial logit model (MRCMLM) (Adams, Wilso...

PURPOSE The purpose of this study was to develop an algorithm based on region-based segmentation for automated calculations of human cone photoreceptor density of en face images obtained by an adaptive optics scanning laser ophthalmoscope (AOSLO). SUBJECTS AND METHODS Cone mosaics of 15 eyes of 15 healthy subjects were photographed by a custom-built AOSLO. The cone density was calculated at 0...