This research aims to find out the impact on the receptive style according to the specimen in the collection of material Brawner and retention as students at the Arabic Department at the Faculty of Education for Girls. For confirmation from the goal of the research, the researcher placed two hypotheses, one to two for collections and one for pods. - chosen as the College of Education for Girls / Department of Arabic language for the application of choice Intentionally search experience for reasons of researcher he is teaching them and thus ensures cooperation of teachers and students in them. - selected Division (b) of the fourth grade students of the Arabic language section at random to represent the experimental group, while the Division

نتيجة للتطورات الأخيرة في أبحاث الطرق السريعة بالإضافة إلى زيادة استخدام المركبات، كان هناك اهتمام كبير بنظام النقل الذكي الأكثر حداثة وفعالية ودقة (ITS) في مجال رؤية الكمبيوتر أو معالجة الصور الرقمية، يلعب تحديد كائنات معينة في صورة دورًا مهمًا في إنشاء صورة شاملة. هناك تحدٍ مرتبط بالتعرف على لوحة ترخيص السيارة (VLPR) بسبب الاختلاف في وجهة النظر، والتنسيقات المتعددة، وظروف الإضاءة غير الموحدة في وقت الحصول

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

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

Background: Expectoration of blood that originated in the lungs or bronchial tubes is a frightening symptom for patients and often is a manifestation of significant and possibly dangerous underlying disease. Tuberculosis was and still one of the common causes followed by bronchiactasis , bronchitis, and lung cancer. Objectives: The aim of this study is to find the frequency of causes of respiratory tract bleeding in 100 patients attending alkindy teaching hospital.Type of the study: : Prospective descriptive observational study Methods of a group of patients consist of one hundred consecutive adult patients, with Lower respiratory tract bleeding are studied. History, physical examination, and a group of selected investigations performed,

Password authentication is popular approach to the system security and it is also very important system security procedure to gain access to resources of the user. This paper description password authentication method by using Modify Bidirectional Associative Memory (MBAM) algorithm for both graphical and textual password for more efficient in speed and accuracy. Among 100 test the accuracy result is 100% for graphical and textual password to authenticate a user.

Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet