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

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

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This paper presents the effect of relativistic and ponderomotive nonlinearity on cross-focusing of two intense laser beams in a collisionless and unmagnetized plasma. It should be noted here that while considering the self-focusing due to relativistic electron mass variation, the electron ponderomotive density depression in the channel may also be important. Therefore/these two nonlinearties may simultaneously affect the self-focusing process. These nonlinearities depend not only on the intensity of one laser but also on the second laser. Therefore, one laser beam affects the dynamics of the second beam and hence the process of cross-focusing takes place. The electric field amplitude of the excited electron plasma wave (EPW) has been cal

Autorías: Muwafaq Obayes Khudhair, Sanaa Rabeea Abed, Hayder Talib Jasim. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2023. Artículo de Revista en Dialnet.

Background: Asthma is a pulmonary disorder characterized by reversible stenosis of the peripheral bronchi. This disease could affect the oral health; as a result asthmatic patients may have a higher risk of developing dental diseases. This study was conducted to evaluate the caries experience and salivary elements among asthmatic patients using Ventoline inhaler. Materials and methods: The study group consisted of 30 male asthmatic patients with an age range 20-24years (under Ventoline inhaler). The control group includes 30 subjects matching with study group in age and gender. Plaque and DMFS index were used for recording caries experience. Stimulated salivary samples were collected and then salivary flow rate, S-IgA and salivary elements

   Increasingly, public organizations in the federal state are required to work together, as well as to work with others to achieve their objectives. In Iraq there are two levels of organizations, including federal and local, and these organizations have been forced to work for many years in an environment in which the responsibility for service delivery is shared between policy makers and service providers, and between local governments and the federal government. It is sometimes difficult to manage the relationship between these organizations (federal and local) and do not always provide the best possible outcome of this relationship. This paper reviews how to manage the relationship between local administrations and

The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k