This research is carried out to investigate the externally post-tensioning technique for strengthening RC beams. In this research, four T-section  RC beams having the same dimensions and material properties were casted and tested up to failure by applying two mid-third concentrated loads. Three of these beams are strengthened by using external tendons, while the remaining beam is kept without strengthening as a control beam. Two external strands of 12 mm diameter were fixed at each side of the web of the strengthened beams and located at depth of 200 mm from top fiber of the section (d_ps). So that the depth of strands to overall depth of the section ratio (d_ps

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content.

Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by u

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Selenium is naturally present in the human body, animals, and plants, and is one of the important elements in their growth and maintenance. Recently, the nanoform of selenium has attracted attention due to its low toxicity and a high degree of adsorption compared to its organic and inorganic forms. The current study aimed to examine the effect of Cress leaves (Lepidium sativum L.) extract in combination with selenium nanoparticles in alleviating polycystic ovary syndrome in letrozole-induced PCOS in adult female rats. Nonthermal or cold plasma was used in the synthesis of selenium nanoparticles. Subsequently, the produced nanoparticles were identified, the 30 rats were divided into 6 equal groups, the first group was healthy (negative contr

The mucilage from the seeds of Lallemantia royleana family Labiatae was extracted and subjected to preformulation study for evaluation of its suitability for use as suspending agent. Furosemide suspensions were prepared using (1.5% w/v) of the extracted Lallemantia royleana mucilage, (1.5% w/v) chitosan and (0.35% w/v) xanthan gum. The mucilage was white in color and the average yield of dried mucilage obtained from L.royleana nutlets was 14 % w/w of the seeds used. It is sparingly soluble in water but swells in contact with it, giving a highly viscous solution. It is slightly acidic to neutral. It was found that the extracted natural mucilage of Lallemantia royleana exhibited a higher viscosity profil

This research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement. Consequently, HSNA can serve as an

مشكلة البحث   The Problem of the Research

          يعّد التحصيل الدراسي للطلبة عموما من أهم أركان النشاط العقلي في المجال التربوي، فلا تكاد تخلو منه أيه مدرسة، أبتداءً من المدارس الابتدائية وقد تسبقها رياض الأطفال، إلى المدرسة الإعدادية والجامعية ، وقد تمتد إلى مراحل متقدمة في العمر، فكان الطالب وما يزال هو محور العملية ال