The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

The performance grading system (superpave) has provided means to incorporate binder characteristics with
pavement failure types. It’s a comprehensive system that relates climate, traffic conditions and aging with
critical pavement distress. The objective of this paper is to develop an improved asphalt binder grading
system for Iraq based on the principal of superpave. The country was divided into different zones according
to the highest and lowest temperature ranges and traffic loading. The Performance graded binder proposed
for each zone was compared with some States of USA that have same hot weather of Iraq by using Long
Term Pavement Performance (LTPP v3.1) software. Iraqi asphalt samples were tested using the Supe

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slun

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

In this work, the emission spectra and atomic structure of the aluminum target had been studied theoretically using Cowan code. Cowan code was used to calculate the transitions of electrons between atomic configuration interactions using the mathematical method called (Hartree-Fock). The aluminum target can give a good emission spectrum in the XUV region at 10 nm with oscillator strength of 1.82.
The hydrodynamic properties of laser produced plasma (LPP) were investigated for the purpose of creating a light source working in the EUV region. Such a light source is very important for lithography (semiconductor manufacturing). The improved MEDUSA (Med103) code can calculate the plasma hydrodynamic properties (velocity, electron density,

A demonstration of the inverse kinematics is a very complex problem for redundant robot manipulator. This paper presents the solution of inverse kinematics for one of redundant robots manipulator (three link robot) by combing of two intelligent algorithms GA (Genetic Algorithm) and NN (Neural Network). The inputs are position and orientation of three link robot. These inputs are entering to Back Propagation Neural Network (BPNN). The weights of BPNN are optimized using continuous GA. The (Mean Square Error) MSE is also computed between the estimated and desired outputs of joint angles. In this paper, the fitness function in GA is proposed. The sinwave and circular for three link robot end effecter and desired trajectories are simulated b

In this work, the elemental constituents of smoker and nonsmoker
teeth samples of human were analyzed by Laser induced breakdown
spectroscopy method (LIBS). Many elements have been detected in
the healthy teeth samples, the important once are Ca, P, Mg, Fe, Pb
and Na. Many differences were found between (female and male)
teeth in Ca, P, Mg, Na and Pb contents. The concentrations of most
toxic elements were found significantly in the smoker group. The
maximum concentrations of toxic elements such as Pb, Cd and Co
were found in older male age above 60 year. Also, it was found that
the minimum concentrations of trace elements such as Ca, P and Na
exist in this age group. From these results it is clear that the

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f