When a person found himself in a life he did not understand، he tried to create in his imagination powers and gods that tried to protect him from his ignorance of that world، and when he was reassured internally through those fantasy creatures when he made them the greatest protector and the source of his existence and his being، he began to weave myths and myths until he created his reality that he did not have. Any hint، and when we go back to the mechanism of embodying those myths، myths and fantasias in which he lived، we will find that the first building blocks were written on the walls of the caves in which he lived during that period. And when his thought developed and thus his expressive means developed، he began to embody

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

This study examines experimentally the performance of a horizontal triple concentric tube heat exchanger TCTHE made of copper metal using water as cooling fluid and oil-40 as hot fluid. Hot fluid enters the inner annular tube of the TCTHE in a direction at a temperature of 50, 60 and 70 ^oC and a flow rate of 20 l/hr. On the other hand, the cooling fluid enters the inner tube and the outer annular tube in the reverse direction (counter current flow) at a temperature of 25 ^oC and flow rates of 10, 15, 20, 25, 30 and 35 l/hr. The TCTHE is composed of three copper tubes with outer diameters of 34.925 mm, 22.25 mm, and 9.525 mm, and thicknesses of 1.27 mm, 1.143 mm, and 0.762 mm, respectively. TCTHE tube's length was 670

After the spread of the function of the scenographer in the modern theater, his vision has become present in most of the theatrical works and because the director is the master of the work and the owner of the vision that appears in front of the audience, the overlap between the visions of each of them was required. This research is an attempt to detect the overlap and disengagement in the work of each of them.
The research is divided into a methodological framework that included the research problem, importance, limits, and purpose, and then the definition of terms. In the theoretical framework, the research dealt with two theoretical sections that pave the way for raising ideas related to this subject: the first section (scenography

Das Verhaltnis des assimilierten arabischen VIII Stammes zum akkadischen

Nuclear emission rates for nucleon-induced reactions are theoretically calculated based on the one-component exciton model that uses state density with non-Equidistance Spacing Model (non-ESM). Fair comparison is made from different state density values that assumed various degrees of approximation formulae, beside the zeroth-order formula corresponding to the ESM. Calculations were made for 96Mo nucleus subjected to (N,N) reaction at Emax=50 MeV. The results showed that the non-ESM treatment for the state density will significantly improve the emission rates calculated for various exciton configurations. Three terms might suffice a proper calculation, but the results kept changing even for ten terms. However, five terms is found to give

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D