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 results of previous scientific studies showed that knowledge is something and application is something else, that's why teachers' preparation programs focused, in the present time, on special standards for knowledge and performance, i.e., who has knowledge is not necessary able to apply it in his life or in his field of work, which led to the existence of a gap between knowledge and application. Based on that, those interested in (teachers' preparation) reconsidered their work evaluation, thus the concept of competency appeared at the end of the sixties of the past century to address the negative in teachers' preparation.
The following contains a number of competency features in teachers' preparation programs:
Teachers' effec

The objective of this investigation was to study the effects of amixture of three arbuscular mycorrhizal species : Glomus etunicatum , G. leptotichum and Rhizophagus intraradices on the induced resistance of Lycopersicon esculentum roots infected with Fusarium oxysporum f.sp.lycopersici which is causal agent of wilt in the presence of organic matter peatmose (O). The work was achieved in aplastic house ( Shed) using pot culture planted for 10 weeks. Results indicated significant increase of all mycorrhizal colonization parameters ( F% , M% , m% , a% , A% ) . Highest percentage of mycorrhization was detected in roots infected with the pathogen 4 weeks after mycorrhizal colonization . On the other hand least colonization was shown in the dual

Abstract: Despite the distinct features of the continuous wave (CW) Terahertz (THz) emitter using photomixing technique, it suffers from the relatively low radiation output power. Therefore, one of effective ways to improve the photomixer emitter performance was using nanodimensions electrodes inside the optical active region of the device. Due to the nanodimension sizes and good electrical conductivity of silver nanowires (Ag-NWs), they have been exploited as THz emitter electrodes. The excited surface plasmon polariton waves (SPPs) on the surface of nanowire enhances the incident excitation signal. Therefore, the photomixer based Ag-NW compared to conventional one significantly exhibits higher THz output signal. In thi

This mixed method research analyses urban heritage and identity management concerning Karbala, and important spiritual and historical center. Homing in on particular spatial issues germane to Muharram’s rites, this study explores spiritual activities for the remembrance of the martyrdoms of Imam Hussein (A) and his brother Abbas (A), and their followers (RA), and identifies the way in which such activities construct urban identity in Karbala. Furthermore, this study contemplates the deployment of contemporary AR and VR technologies for urban identity. After reviewing extensive studies on religious, cultural, and urban heritage, a field survey of the Muharram pilgrimage in Karbala was conducted, spatially analyzing pilgrims’ movements in

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti