The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.

This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural

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

            The research aims to identify the elements of performance supervisory good and effective and availability in the Governmental council through examination and analysis of the reality and practice of censorship in this Council through study and evaluate the characteristics of the regulatory effective upon which the Governmental council in the performance of his work and knowledge of their adequacy by comparing the established criteria , and determine the effect of characteristics supervisory the performance standards for the Governmental council, Based search to two assumptions key to check the level of the relationship and the influence of the dimensions of the con

Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) network with thickness 4μm was made by the vacuum filtration from suspension (FFS) method. The morphology, structure and optical properties of the MWCNTs film were characterized by SEM and UV-Vis. spectra techniques. The SEM images reflected highly ordered network in the form of ropes or bundles with close-packing which looks like spaghetti. The absorbance spectrum revealed that the network has a good absorbance in the UV-Vis. region. The gas sensor system was used to test the MWCNT-OH network to detect NH₃gas at room temperature. The resistance of the sensor was increased when exposed to the NH₃gas. The sensitivities of the network w

Abstract  

This research aims to study and improve the passivating specifications of rubber resistant to  vibration. In this paper, seven different rubber recipes were prepared based on mixtures of natural rubber(NR)  as an essential part in addition to the synthetic rubber (IIR, BR_cis, SBR, CR)with different rates. Mechanical tests such as tensile strength, hardness, friction, resistance to compression, fatigue and creep testing in addition to the rheological test were performed. Furthermore, scanning electron microscopy (SEM)test was used to examine the structure morphology of rubber. After studying and analyzing the results, we found that, recipe containing (BRcis) of 40% from th

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

          This study deals with the role of compensation system in improving the quality of educational services (University of Halabja as a Model) also our problem was the following question ; What is the role of compensation system in its different dimensions in improving the quality of educational services? And what is the relationship and impact of using the dimensions of the compensation system to improve the quality of educational services? The hypothesis of the research included the correlation and the impacts between the compensation system and its combined variables in the quality of educational services. This was proved through a field study and the distribution of questionn