Abstract

The study aims to build a training program based on the Connectivism Theory to develop e-learning competencies for Islamic education teachers in the Governorate of Dhofar, as well as to identify its effectiveness. The study sample consisted of (30) Islamic education teachers to implement the training program, they were randomly selected. The study used the descriptive approach to determine the electronic competencies and build the training program, and the quasi-experimental approach to determine the effectiveness of the program. The study tools were the cognitive achievement test and the observation card, which were applied before and after. The study found that the effectiveness of the training program

Abstract

       Although the subject of biofuels industry is linked directly to the energy sector, but has links and numerous indirect effects, in particular effects on the environment and agriculture, this study (opportunities and challenges of biofuels industry and impact on the development of the agricultural sector in developing countries) a modest step to identify the industry in detail and identify the types of products and raw materials entering, then define or limit the positive and negative impacts of this industry in General and for specific products In particular, detailed, and then flip all those effects on the agricultural sector in developing countries can benef

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

This research seeks to identify the dimensions of the development of staff performance (training ', incentives, management skills) and its impact on the settlement of compensatory claims adopted in the current research in the Iraqi insurance company،This research aims to highlight the role of developing insurance company’s workers’ performance in settling insurance compensation, and to check this process, the research was applied in the general Iraqi insurance company as it considered as the research community, and a sample was taken from this community that represented by company’s insurance department workers or by collecting actual data that is related to the research’s sample, in addition to the financial compensation data.<

The aim of the current research is to develop the social studies curriculum at the primary stage in light of the standards of the next generation, which was represented in three main dimensions (pivotal ideas, scientific practices, and comprehensive concepts). The researcher designed a tool for the study, which is a content analysis card in the light of (NGSS) standards, based on the previous main dimensions. The descriptive analytical approach was adopted in analyzing the social studies curriculum for the primary stage to determine the degree to which the standards of the next generation are available, as well as to establish the theoretical framework related to the research variables. To develop the social studies curriculum in light o

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi