Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

The purpose of this research is to demonstrate the effectiveness of a program to address the problem of mixing similar letters in the Arabic language for students in the second grade of primary and to achieve the goal of the research. The researcher followed the experimental method to suit the nature of this research and found that there are statistically significant differences between the tribal and remote tests, The effectiveness of the proposed educational program. At the end of the research, the researcher recommends several recommendations, the most important of which are: 1 - Training students to correct pronunciation of the outlets, especially in the first three stages of primary education (primary) and the use of direct training

The book of the summary in the control of the laws of Arabic is one of the most important books of Andalusian grammar, the resonance of which is clearly evident among the mother of the language books in the seventh century AH because of the character of the educational style easy and simplified service for anyone who wants the Nile Arabic grammar, that end through what is pursued in his book (Summary) on according to visual standards, as was Ibn Abi Al-Rabeea of first- type, and illustrated in which he addressed the analogies, and he followed the modalities expressed and its consequences relating to each attachment in which a (illness and reasoning factor) And what he said in the framework of each service for the study material in his ha

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Аннотация

Взгляд на пол как на комплексное социальное отношение означает,что роль женщины в истории следует рассматривать не просто как новый для исторической науки предмет исследования, а как обойденный вниманием ученых вопрос об отношениях между людьми или группами людей.

Женщина играет особую и важную  роль в обществе , даже скажут ,что она половина нашего общества ,поэтому она яв

The research study focused on the need to clarify the relationship between the Websites of Iraqi Newspapers and their roles in covering the internal crises in Iraq. The selection of Iraqi websites for the newspapers Al-Zaman and Al-Sabah was adopted as one of the most important media with a wide audience; and as a model of hot news and continuous coverage of those sites since 2003 so far. As a result, this necessitated the emergence of new types of methods of editing and writing news stories related to Iraq.

Consequently, the enormous and rapidly changing amount of Iraq news, the process of preparing and creating news has become a complex industry

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS,