Academic writing is a key skill for success in academic life, particularly for graduate students of a foreign language. The importance of writing to academic culture, practice, and knowledge building has led to a great deal of research in many fields, including rhetoric and composition, linguistics, applied linguistics, and English for Academic Purposes (EAP). Often, studies and research investigating academic writing are motivated by the need to inform the learning of writing to native and non-native English-speaking students, through both descriptions of professional academic writing as well as through comparisons of novice writer (native and non-native Englishspeaking) and expert production. However, while learning about academic writing

The study aims to investigate the degree of student teachers at Sultan Qaboos University acquired skills in teaching Arabic via a virtual micro-teaching lab, as well as to reveal the difficulties they faced and their development proposals. To do this, the researchers developed a questionnaire divided into four dimensions: planning, implementation, evaluation, and

ethical values for the teaching profession, in addition to two open-ended questions to identify difficulties and suggestions. It was administered to (30) student teachers. The results revealed that the average degree of student-teacher acquisition of skills was high in its four dimensions. It ranged between (39.2) to (82.2), while the overall average was (56.2).

It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems. The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

Stroke is the second largest cause of death worldwide and one of the most common causes of disability. However, several approaches have been proposed to deal with stroke patient rehabilitation like robotic devices and virtual reality systems, researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. In this study, the electroencephalography (EEG) dataset from post-stroke patients were investigated to identify the effects of the motor imagery (MI)-based BCI therapy by investigating sensorimotor areas using frequency and time-domain features and to select particular methods that help in enhancing the MI-based BCI systems for stroke patients using EEG signal processing. Therefore, to detect

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in