Many countries, including the Arab countries, have sought to establish the free zones because of their important economic importance to diversify financial income, especially in rentier countries, in light of the trend towards the capitalist economy in light of what has been produced by economic globalization, in addition to that many Arab countries have turned towards establishing the free zones that many countries of the world have turned to, to support their economy, especially in the field of attracting foreign investments for these regions, and using them in transferring modern technology, and operating the national workers of the countries that have established those areas, and adopting their products in meeting the needs of t

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

Non-alcoholic fatty liver disease (NAFLD) is one of chronic liver and defines by fat accumulation ≥5% in liver which can progresses to non-alcoholic steatohepatitis (NASH). NAFLD related to obesity as well as non obese individuals. Adiponectin is a cytokine secreted from adipose tissue involved NAFLD pathogenesis and liked with obesity. Irisin is a myokine, has a convenient effect against metabolic diseases such as obesity, disylipemia diabetes type 2 and reversed liver steatosis and may be related with NAFLD.  Vitamin D is one of the fat soluble vitamins and more precisely as a pro-hormone through its metabolite (1,25(OH)2 cholecalciferol) the major steroid hormone. After the skin exposure to the light, vitamin D undergoes to

The game of volleyball, like all other sports, has been made by new amendments, the most important of which is the system of what is not the system of the free player in 1998, which gave added importance to the skills of receiving the transmission and defending the stadium being one of the important skills where the law allowed the free player to move and position in the back positions of the stadium Limited support mainly defensive skills. This is to make the state of stability and balance between defensive and offensive skills, which helps in the development of the game and make it exciting and enjoyable for players and fans. Therefore, the researchers decided to shed light by identifying the percentage of the contribution of the free pla

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col