YouTube is not just a platform that individuals share, upload, comment on videos; teachers and educators can utilize it to the best maximum so that students can have benefits. This study aims at investigating how active and influential YouTube can be in the educational process and how it is beneficial for language teachers to enhance the skills of students. The study demonstrates different theoretical frameworks that tackle the employment of technology to enhance the learning/teaching process. It relies on the strategies of Berk (2009) for using multimedia media, video clips in particular to develop the abilities of teachers for using technology in classrooms. To achieve the objective of the study, the researchers develop a questionnair

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

Introduction: The aim of this study was to compare the reliability and the agreement of the Pederson and Pernambuco difficulty indexes in predicting the surgical extraction difficulty of the impacted mandibular third molars. Materials and methods: A prospective observational cohort study was conducted on 83 patients who had undergone surgical removal of impacted mandibular third molar. The difficulty of extraction was determined preoperatively according to the total scores obtained from the Pederson and Pernambuco difficulty indexes, the operative difficulty was determined by the surgical technique and the duration of extraction. The accuracy of prediction of the surgical difficulty and

--The objective of the current research is to identify: 1) Preparing a scale level for e-learning applications, 2) What is the relationship between the applications of e-learning and the students of the Department of Chemistry at the Faculty of Education for Pure Sciences/ Ibn Al-Haytham – University of Baghdad. To achieve the research objectives, the researcher used the descriptive approach because of its suitability to the nature of the study objectives. The researcher built a scale for e-learning applications that consists of (40) items on the five-point Likrat scale (I agree, strongly agree, neutral, disagree, strongly disagree). He also adopted the scale of scientific values, and it consists of (40) items on a five-point scale as wel

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

Continual learning on edge platforms remains challenging because recurrent networks depend on energy-intensive training procedures and frequent data movement that are impractical for embedded deployments. This work introduces M2RU, a mixed-signal architecture that implements the minion recurrent unit for efficient temporal processing with on-chip continual learning. The architecture integrates weighted-bit streaming, which enables multi-bit digital inputs to be processed in crossbars without high-resolution conversion, and an experience replay mechanism that stabilizes learning under domain shifts. M2RU achieves ∼13 GOPS at 16.76 mW, corresponding to 776 GOPS per watt, and maintains accuracy within 5 percent of software baselines on seque

Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut

Learn new methods of teaching mathematics contribute to raising the level of pupils to acquire mathematical concepts primary stage
Attempt advancement in the level of mathematics teaching for the better through the use of modern teaching strategies. The research aims at the progress in the acquisition of mathematical concepts schoolgirls after subjecting the fourth grade to teach in active learning strategies, the number of research sample (60) schoolgirl, by (30) schoolgirl experimental group and 30 pupils of the control group. Clear from the results shown the presence of a statistically significant difference between the acquisition of concepts of schoolgirls two groups (experimental and control) for the benefit of pupils of the exp