In recent years images have been used widely by online social networks providers or numerous organizations such as governments, police departments, colleges, universities, and private companies. It held in vast databases. Thus, efficient storage of such images is advantageous and its compression is an appealing application. Image compression generally represents the significant image information compactly with a smaller size of bytes while insignificant image information (redundancy) already been removed for this reason image compression has an important role in data transfer and storage especially due to the data explosion that is increasing significantly. It is a challenging task since there are highly complex unknown correlat

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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

Background: Most adolescent girls experience some degree of dysmenorrhea, which can impact on their daily activities. It is responsible for school absenteeism or interruption of social activities. Therefore, investigating dysmenorrhea among secondary school students is important to provide caregivers with data necessary for interventions

Objectives: This study was conducted to estimate the prevalence of dysmenorrhea among secondary school students in Basra, Iraq and to study its impact on their daily activities.

Materials & methods: A cross sectional study was conducted from Jan. 2011 to May 2011 among 350 secondary school students using a semi-structured questionnair

Abstract

The aim of the current research is to identify the effect of the effective reading strategy on the achievement of second-middle students in biology, as well as the imaginative thinking skills of students. The researcher adopted the experimental design with partial control to achieve the goal of the research. The current research community identified the second-middle students in the government schools of the Baghdad Education Directorate / Rusafa I for the academic year (2021-2022 AD). The Safina Intermediate School for Girls was chosen to be the research sample in the form of intentionally, two classes were randomly selected from a total of four classes, one of them is experimental and the other is con

     Education and lifelong learning are necessary components of daily city life for urban communities to encourage sustainable and positive communities. The study attempts to analyze the actual school distribution patterns and densities in Baghdad, the Iraqi capital. The significance of this study is that it is associated with one of the essential aspects of humanity: the improvement and affluence of schooling; it impacts school attendance limitations and educational evolution. The education process has been inextricably tied to students' timely and orderly entrance to their schools. Hence the decision maker and planner are concerned by this. The statistics examined elementary and high schools, and the investigated

Praise be to God, Lord of the worlds, and prayers and peace be upon our master Muhammad and his family and companions until the Day of Judgment.
      The words of God Almighty are for the sake of the greatest and greatest speech, and the scholars, may God have mercy on them, raced.
To dive into knowing the word of God and what he intended, so they wrote in it the literature and collected works in it, and explained it to those after them.
      And when the noble companions, were extremely eloquent and eloquent, because the Holy Qur’an was revealed in the language of the Quraysh, and all the Arabs knew their language, they understood the Holy Qur’an and applied it p