Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

The world faced many communication challenges in 2020 after the Covid-19 pandemic, the most important of which was the continuation of schooling. Therefore, the research aimed to analyze the current reality of the studied universities in terms of strengths and weaknesses and measure the implementing level of quality requirements of e-learning. This research studies the impact of knowledge sharing in its dimensions (behavior, organizational culture, work teams, and technology) on the e-learning quality and its dimensions (e-learning management, educational content, evaluation ,and evaluation). After conducting the survey, there was a difference in the universities’ application of the quality requirements of e-learning, as the study

The process of granting loans by banks is the confidence they give to their customers, but this trust should not be a cornerstone in granting loans even if granted these loans on the basis of sound banking should involve risks that may be exposed to the bank because of the failure of the client to meet The bank's financial obligations to the bank due to the unexpected economic conditions affecting the customers, which makes them in a state of faltering, which weaken the ability of banks to provide loans, which are the most important sources of revenue and profits, so the problem of non-performing loans is one of the main problems facing most of the banks Which impede the functioning of its work and the reasons that led to the agg

This research aimed to definite Blending learning (BL) technique, and to know the impact of its use onacademic achievement in Biology course of second class students in secondary special schools in Omdurman Locality and attitudes towards it, to achieve this; researcher adopted the experimental method. The sample was selected of (41) students, chosen from Atabiyah school, were divided into two equals groups: one experimental group reached (26) students studied by using the  BL technique, and the second control group (25) students have been taught in the traditional method.

   Data has collected by using two tools: achievement test and a questionnaire for measuring the attitudes towards Blend

In the present work we prepared heterojunction not homogenous CdS/:In/Cu2S) by spray and displacement methods on glass substrate , CdS:In films prepared by different impurities constration. Cu2S prepared by chemical displacement method to improve the junction properties , structural and optical properties of the deposited films was achieved . The study shows that the film polycrystalline by XRD result for all film and the energy gap was direct to 2.38 eV with no effect on this value by impurities at this constration .

The study aims to identify the students’ attitudes toward recent techniques’ use in teaching; using power point software and data show to facilitate teaching approaches as well as following the approach of lecture in giving subjects, do these techniques facilitate, increase, and tackle the difficulties of subjects, do these attitudes positive or negative?, and to what extent these techniques raise up students’ motivation.   

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

The study focuses on the causes of minaret tilting as well as possible solutions. The major aims of this study are to improve knowledge of historical tall structure stability and rehabilitation operations using the finite element approach to model the soil and minaret (PLAXIS 3D 2020), a platform for computational soil investigation and modeling. The numerical analysis aims to identify stresses, settlement, and deformation of the soil and minaret in various scenarios like Earthquakes, explosions, and winds. The simulation of the problem by the PLAXIS 3D revealed that the greatest lateral displacement computed at the Top Minaret is 5.5 cm, and the greatest vertical movement is calculated to be 3 cm. Seismic settlement is the effect of ear