This paper attempts to shed light on the most influential factors in the importance of religious buildings were destroyed because of the recent war due to the control of terrorist gangs of ISIS over the city of Mosul, and to prioritize their reconstruction and their role in reviving the historical center of Mosul.

The research’s problem emerged in the lack of knowledge about the identifying the most influential factors in the importance of religious buildings and utilizing them to prioritize their reconstruction. This study aims to analyze the factors influencing the importance of religious buildings using the Expert Choice software through the Analytic Hierarchy Process (AHP) to reach an analysis of their weights and propose p

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

As a result of the exacerbation of the problem of water pollution, research was directed towards studying the treatment using ceramic membranes, which proved to be highly effective in treating all water sources. The research aims to study the possibility of preparing a new type of ceramic membranes from Syrian zeolite that was not previously used in this field. In this research, ceramic membranes were prepared from Syrian raw zeolite in several stages. Zeolite sample was characterized, grinded, mixed with boric acid, pressed to form desks, treated thermally according to experiment program, finally coated with silver nanoparticles. Specifications of prepared membranes were determined according to reference methods, effectiveness of prepar

Objective: The goal of this research was to evaluate where selenium nanoparticles impact the activity of antibodies in immunized lambs with foot and mouth vaccines by modulating the immune system. Materials and Methods: Two groups of lambs of 3–4 months of age were injected with 1 ml of ARRIAH-VAC vaccine intramuscularly in the neck, five Lambs were given selenium nanoparticles (size 100 nm) oral administration of selenium nano dose of 0.1 mg/kg of body mass once every day for sixty days considered as group one (G1) while the other five used as control Group 2 (G2). Results: This resulted in the establishment of an immune response, as evidenced by a rise in antibody titer in the blood using the ELISA test for three serotypes A,

The new novel polymers nanocomposites based modified chitosan (CS) blending with polyvinyl alcohol (PVA) and coated gold or silver nanoparticles (AuNPs), AgNPs) were synthesized from many sequence reactions as presented in (Scheme1, 2 and 3). By utilizing 1H-NMR spectroscopy, FTIR, and Field Emission Scanning electron microscope , the synthesized compounds have been identified. Molecular docking is studied, where operations are used to predict the binding status of compounds with the enzyme and to calculate the free energy (ΔG) of the compounds prepared. Also, the antibacterial activity regarding the synthesized compounds against two resistant pathogenic bacteria (G+) S. aureus and E. coli (G-) was examined in vitro compare with standard a

In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PI^aD^b (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of