The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm³.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

All over the world and in different societies and cultures , people are always looking for different ways of favourable , gentle smooth and soft communication .The 'powerful linguistic devices ' that are embedded in the daily English language is called "euphemism". It plays an important and vital role in daily communication. It represents a significant part of English . It is used to express any aspect of everyday realities such as the business world , mass media , etc. The comprehension of such realities can not be verified unless a reasonable command of euphemism is achieved.
Euphemism is defined according to various perspectives and views. It is " that figure of speech which consists in the substitution of a word or expression of c

This review article summarizes our research focused on Cu(In, Ga)Se2 (CIGS) nanocrystals, including their synthesis and implementation as the active light absorbing material in photovoltaic devices (PVs). CIGS thin films were prepared by arrested precipitation from molecular precursors consisting of CuCl, InCl3, GaCl3 and Se metal onto Mo/soda-lime glass (SLG) substrates. We have sought to use CIGS nanocrystals synthesized with the desired stoichiometry to deposit PV device layers without high temperature processing. This approach, using spray deposition of the CIGS light absorber layers, without high temperature selenization, has enabled up to 1.5 % power conversion efficiency under AM 1.5 solar illumination. The composition and morphology

The photodynamic inactivation against Methicillin-resistant Staphylococcus aureus using two different lasers, 532 nm diode pumped solid state laser (DPSS) in combination with safranin O and 650 nm diode laser in combination with methylene blue was investigated in the present work. A hundred swab samples were collected from patients with burn and wound infections admitted to two hospitals in Baghdad (Specialized Burns Hospital in Medical City and Al Imamein Al Jwadein Medical City Hospital) from December 2015 to February 2016 Antimicrobial susceptibility was performed by using Kirby- Bauer method. The irradiation experiments included four groups; a control group, a photosensitizer only group, a laser irradiation only group and a laser irr

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used