In this research, we studied the impact of Magnetohydrodynamic (MHD) on Jeffrey fluid with porous channel saturated with temperature-dependent viscosity (TDV). It is obtained on the movement of fluid flow equations by using the method of perturbation technique in terms of number Weissenberg ( ) to get clear formulas for the field of velocity. All the solutions of physical parameters of the Reynolds number , Magnetic parameter , Darcy parameter , Peclet number  and are discussed under the different values, as shown in the plots.

The study aimed to identify the news framing on the Israeli Arabic-speaking i24 channel of the Israeli aggression on Gaza -2021 by analyzing the channel’s Program “this evening”. The study used the media survey method, and in its framework, it relied on the content analysis method for the program’s episodes from May 5, 2021 AD until June 4, 2021 AD, with 22 episodes. The study showed the program’s interest in launching the Palestinian resistance’s rockets significantly, followed by the Israeli military operations, and the program’s reliance on correspondents largely as a source of news material related to the aggression. It also proved that a news report and a reporter's report was the most important form of presenting news

This research asks what are negative social behaviours in the Kurdistan Region of Iraq (KRI) raised by the talk shows on the (NRT) channel? Furthermore, it aims to identify the most significant themes addressed by talk shows on the (NRT) channel regarding negative social behaviours in the KRI by using the content analysis approach through non-random purposive sampling to understand the dialogue contents that dealt with this subject. This study has reached a set of results: through its talk shows, the (NRT) channel attempts to create a media vision about the spread of negative social behaviours in the KRI and stand up to the dangers associated with these behaviours. At the same time, those programs tried to marginalize the behaviours that

     In this present paper , a special model was built to govern the equations of  two dimensional peristaltic transport to nanofluid  flow of a heat source in a tapered  considered in an asymmetric channel. The equations of dimensionless temperature concentration are analytical solve under assumption slow Reynolds number and long wave length. Furthermore, the results that receive by expressing the maximum pressure rise  communicates increased in case of  non-Newtonian fluid when equated with Newtonian fluid. Finally, MATHEMATICA  11 program has been used to solve such system after obtaining the initial conditions.  Most of the results  of drawing  for many are obtained via above program .

This paper deals with an up to date problem for oil and gas industry- separation of the gas -fluid fogs. Here is described the worked out physical model of the gas movement process in the sections of the inertial filtering (IF) gas separators. One can find the mathematical model for research of the fields of velocities and pressures in the inertial curvilinear channel. The main simplifications and assumptions are explained. This mathematical model has been made using mathematical program Maple and it is received the 3-d graphic of the distribution componential speed parts in the channel and also 2-d graphics at the channel sectional view when the flow is flat. The new method for gas - fluid systems separation is suggested.

     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

The autocorrelation function calculations have been carried out on photon-limited computer-simulated images of binary stars that recorded through kolmogorov atmospheric turbulence. The effect of the parameters of photon limited binary star on the variation of signal to noise, signal to background ratios, number of images that processed and the magnitude of binary stars are studied and mathematic equations are given to investigate this effect. The result indicates that signal to background ratio of photon limited images of a binary star is independent of the total number of recorded photons.

In the current research work, a system of hiding a text in a digital grayscale image has been presented. The algorithm system that had been used was adopted two transforms Integer Wavelet transform and Discrete Cosine transformed. Huffman's code has been used to encoding the text before the embedding it in the cover image in the HL sub band. Peak Signal to Noise Ratio (PSNR) was used to measure the effect of embedding text in the watermarked image; also correlation coefficient has been used to measure the ratio of the recovered text after applying an attack on the watermarked image and we get a good result. The implementation of our proposed Algorithm is realized using MATLAB version 2010a.