Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

In this paper we use the Markov Switching model to investigate the link between the level of Iraqi inflation and its uncertainty; forth period 1980-2010 we measure inflation uncertainty as the variance of unanticipated  inflation. The results ensure there are a negative effect of inflation level on inflation uncertainty and  all so there are a positive effect of inflation uncertainty on inflation level.                                                   &nbsp

One of the most important phenomenon that occurs in sheet metal forming processes is the spring-back, which causes several geometrical alterations in the parts. The accurate prediction of springback after bending unloading is the key to the tool design, operation control, and precision estimate concerning the part geometry. This study investigated experimentally the effect of pretension in three rolling direction (0, 90, 45 degree) on the springback behavior of the yellow brass, sheet under V shape bending die. The pre-tension ranges from five different levels starting of 11% to 55% from the total strain in each rolling direction by regular increase of 11 %, then bent on a V-die 90 degree for the springback estimate. From experiment the

The primary purpose of the present research was to study the effect of polyvinyl chloride (PVC) powder content on ultrasonic wave velocity in PVC/Epoxy composites. The second part is concerned with the relations of dynamic elastic moduli with the ultrasonic wave velocities, to determine how ultrasonic waves can affect them.
Experimental data have been obtained using the sonic viewer (model -5217 A) device to generate two types of waves, longitudinal waves of frequency 63 kHz and transverse waves of frequency 33 kHz and to measure the transit time required for those waves to travel through individual sample.
The experimental results have shown that the propagation of the ultrasonic velocity increases directly with PVC content in the

Thermal conductivity measurement was done for specimens of Polystyrene/ titanium dioxide, Polycarbonate/ titanium dioxide and Polymethylmetha acrylate/ titanium dioxide composites for weight ratio of 1.9/ 0.1 and 1.8/ 0.2 wt% for different thickness of the samples. The experimental results show that the thermal conductivity is increased with the increasing of thickness of layers and with the weight ratio of TiO2

Brainstorming is one of the fundamental and necessary concepts for practicing the auditing profession, as auditing standards encouraged the implementation of brainstorming sessions to reach reasonable assurance about the validity of the evidence and information obtained by the auditor to detect fraud, as the implementation of brainstorming sessions and the practice of professional suspicion during the audit process lead to increase the quality of auditing and thus raise the financial community's confidence in the auditing profession again after it was exposed to several crises that led to the financial community losing confidence in the auditing profession.

The research aims to explain the effect of brain