The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot

This paper discussed the solution of an equivalent circuit of solar cell, where a single diode model is presented. The nonlinear equation of this model has suggested and analyzed an iterative algorithm, which work well for this equation with a suitable initial value for the iterative. The convergence of the proposed method is discussed. It is established that the algorithm has convergence of order six. The proposed algorithm is achieved with a various values of load resistance. Equation by means of equivalent circuit of a solar cell so all the determinations is achieved using Matlab in ambient temperature. The obtained results of this new method are given and the absolute errors is demonstrated.

يعد التقطيع الصوري من الاهداف الرئيسة والضرورية في المعالجات الصورية للصور الرقمية، فهو يسعى الى تجزئة الصور المدروسة الى مناطق متعددة اكثر نفعاً تلخص فيها المناطق ذات الافادة لصور الاقمار الصناعية، وهي صور متعددة الاطياف ومجهزة من الاقمار الصناعية باستخدام مبدأ الاستشعار عن بعد والذي اصبح من المفاهيم المهمة التي تُعتمد تطبيقاته في اغلب ضروريات الحياة اليومية، وخاصة بعد التطورات المتسارعة التي شهد

This paper aims to study the rate of star formation (SFR) in luminous infrared galaxies at different wavelengths using distance measurement techniques (dl, dm) and to know which methods are the most accurate to determine the rate of star formation as we present through this research the results of the statistical analysis (descriptive statistics) for a sample of luminous infrared galaxies. The data used in this research were collected from the NASA Extragalactic Database (NED) and HYPERLEDA, then used to calculate the star formation rate and indicate the accuracy of the distance methods used (dl, dm). Two methods were tested on Hα, OII, FIR, radio continuum at 1.4 GHz, FUV, NUV, and total (FUV + FIR). The results showed that the dl

Abstract 

In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust  at 30cm , angle 60

Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i