Sharif Digital Repository

This study is concerned with investigation of pressure oxidative leaching of entire molybdenum of a molybdenite concentrate. Effects of oxygen pressure, stirring speed, pulp density, acid concentration, and temperature on the leaching rate of molybdenum were studied. A three-layer feed-forward artificial neural network was applied to model the effect of the abovementioned parameters on the leaching ability. The leaching efficiency was considered as a target value for modeling. The quantified leaching efficiencies obtained by applying different parameters demonstrated a good agreement with neural network predictions  

In this study, neural network models have been used to predict the mechanical behaviors of mouse embryos. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. In order to reach these purposes two neural network models have been implemented. Experimental data earlier deduced-by [Flückiger, M. (2004). Cell Membrane Mechanical Modeling for Microrobotic Cell Manipulation. Diploma Thesis, ETHZ Swiss Federal Institute of Technology, Zurich, WS03/04]-were collected to obtain training and test data for the neural network. The results of these investigations show that the correlation... 

Gas flooding processes have emerged as attractive enhanced oil recovery (EOR) methods over the last few decades. Among different gas flooding processes, CO2 flooding is recognized as being most efficient for displacing oil through miscible displacement. Minimum miscibility pressure (MMP) is a crucial parameter for successfully designing CO2 flooding, which is traditionally measured through time-consuming, expensive, and cumbersome experiments. In the present study, a new reliable model based on feed-forward artificial neural networks was presented to predict both pure and impure CO2-crude oil MMP. Among various properties and parameters, reservoir temperature, reservoir oil composition, and... 

Flow stress behavior of AA5086 was determined using tensile testing at different temperatures from room temperature to 500 °C and strain rates varying between 0.002 and 1 s−1. The strain rate sensitivity parameter and occurrence of dynamic strain aging were then investigated in which an Arrhenius-type model was employed to study the serrated flow. Additionally, hot deformation behavior at temperatures higher than 320 °C was evaluated utilizing hyperbolic-sine constitutive equation. Finally, a feed forward artificial neural network model with back propagation learning algorithm was proposed to predict flow stress for all deformation conditions. The results demonstrated that the strain rate... 

Development of reliable and accurate models to estimate carbon dioxide–brine interfacial tension (IFT) is necessary, since its experimental measurement is time-consuming and requires expensive experimental apparatus as well as complicated interpretation procedure. In the current study, feed forward artificial neural network is used for estimation of CO2–brine IFT based on data from published literature which consists of a number of carbon dioxide–brine interfacial tension data covering broad ranges of temperature, total salinity, mole fractions of impure components and pressure. Trial-and-error method is utilized to optimize the artificial neural network topology in order to enhance its... 

Here we present an approach for processing neural cells images to analyze their growth process in culture environment. We have applied several image processing techniques for: 1- Environmental noise reduction, 2- Neural cells segmentation, 3- Neural cells classification based on their dendrites' growth conditions, and 4- neurons' features Extraction and measurement (e.g., like cell body area, number of dendrites, axon's length, and so on). Due to the large amount of noise in the images, we have used feed forward artificial neural networks to detect edges more precisely. © 2008 Springer-Verlag  

A new method for simultaneous determination of dopamine (DA) and ascorbic acid (ASC) is proposed. The method is based on the reaction of dopamine and ascorbic acid with the oxidizing agent (silver nitrate) in the presence of PVP (as a stabilizer) and the formation of silver nanoparticles in a slightly basic medium. Spectrophotometry is used to monitor the changes of the surface plasmon resonance (SPR) band at a maximum wavelength of silver nanoparticles (440 nm) vs. time. Three-layered feed-forward artificial neural networks (ANN) trained by back propagation learning algorithm is used to model the relationship between absorbance and concentration to quantify analyte in mixtures under optimum... 

This study describes an adaptive sliding mode technique for attitude and position control of a rigid body insect-like flapping wing model in the presence of uncertainties. For this purpose, a six-degrees-of-freedom nonlinear and time-varying dynamic model of a typical hummingbird is considered for simulation studies. Based on the quasi-steady assumptions, three major aerodynamic loads including delayed stall, rotational lift and added mass are presented and analyzed, respectively. Using the averaging theory, a time-varying system is then transformed into the time-invariant system to design the adaptive controller. The controller is designed so that the closed-loop system will follow any...