The main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).

A Photo Dynamic Therapy (PDT) is a technique which is used with Laser to treat many of cancer
tissues. This paper deals with the relatively new therapeutic technique (PDT) with pulsed Nd:glass Laser
which was applied to human soft tissues (Ovary and Kidney tissues), and to the hard tissues (freshly
extracted human teeth), with power density of 280 watt/mm2 and exposure time 330 usec. Different
dyes (Blue, methylene, eosin, and orange) were applied to the area before irradiation to study the effect
of the pigments on the laser interaction with biological tissues. The zone of treatment (Z-necrosis) with
aid of MATLAB was determined. The relationship of zone of treatment with exposure time,
accumulated damage and fracti

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Abstract

The aim of this paper is to model and optimize the fatigue life and hardness of medium carbon steel CK35 subjected to dynamic buckling. Different ranges of shot peening time (STP) and critical points of slenderness ratio which is between the long and intermediate columns, as input factors, were used to obtain their influences on the fatigue life and hardness, as main responses. Experimental measurements of shot peening time and buckling were taken and analyzed using (DESIGN EXPERT 8) experimental design software which was used for modeling and optimization purposes. Mathematical models of responses were obtained and analyzed by ANOVA variance to verify the adequacy of the models. The resul

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Here, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity

Spatial data analysis is performed in order to remove the skewness, a measure of the asymmetry of the probablitiy distribution. It also improve the normality, a key concept of statistics from the concept of normal distribution “bell shape”, of the properties like improving the normality porosity, permeability and saturation which can be are visualized by using histograms. Three steps of spatial analysis are involved here; exploratory data analysis, variogram analysis and finally distributing the properties by using geostatistical algorithms for the properties. Mishrif Formation (unit MB1) in Nasiriya Oil Field was chosen to analyze and model the data for the first eight wells. The field is an anticline structure with northwest- south

: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

In the last years, the research of extraction the movable object from video sequence in application of computer vision become wide spread and well-known . in this paper the extraction of background model by using parallel computing is done by two steps : the first one using non-linear buffer to extraction frame from video sequence depending on the number of frame whether it is even or odd . the goal of this step is obtaining initial background when over half of training sequence contains foreground object . in the second step , The execution time of the traditional K-mean has been improved to obtain initial background through perform the k-mean by using parallel computing where the time has been minimized to 50% of the conventional time