The need to constantly and consistently improve the quality and quantity of the educational system is essential. E-learning has emerged from the rapid cycle of change and the expansion of new technologies. Advances in information technology have increased network bandwidth, data access speed, and reduced data storage costs. In recent years, the implementation of cloud computing in educational settings has garnered the interest of major companies, leading to substantial investments in this area. Cloud computing improves engineering education by providing an environment that can be accessed from anywhere and allowing access to educational resources on demand. Cloud computing is a term used to describe the provision of hosting services on the Internet. It is predicted to be the next generation of information technology architecture and offers great potential to enhance productivity and reduce costs. Cloud service providers offer their processing and memory resources to users. By paying for the use of these resources, users can access them for their calculations and processing anytime and anywhere. Cloud computing provides the ability to increase productivity, save information technology resources, and enhance computing power, converting processing power into a tool with constant access capabilities. The use of cloud computing in a system that supports remote education has its own set of characteristics and requires a unique strategy. Students can access a wide variety of instructional engineering materials at any time and from any location, thanks to cloud computing. Additionally, they can share their materials with other community members. The use of cloud computing in e-learning offers several advantages, such as unlimited computing resources, high scalability, and reduced costs associated with e-learning. An improvement in the quality of teaching and learning is achieved through the use of flexible cloud computing, which offers a variety of resources for educators and students. In light of this, the current research presents cloud computing technology as a suitable and superior option for e-learning systems.
The study aims at finding out:
1. The students' attitude towards the mixed learning at the university.
2. The statistically significant differences in attitude towards the mixed learning at the university according to the specialization variable.
3. The statistically significant differences in attitude towards the mixed learning at the university according to the gender variable.
The researcher has constructed a scale for measuring the students' attitude towards the mixed learning at the university.
After assuring its validity and reliability, the scale has been given to a sample of (100) students. The sample is selected randomly from (4) colleges of the university of Baghdad, (2) for scientific specialization and (2)for h
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
... Show Moreيتضمن البحث دراسة لزوجة محاليل تحتوي على املاح كلوريد البوتاسيوم وبروميد البوتاسيوم في مزيج من الماء وداي مثيل سلفوكسايد 60% وزنا داي مثيل سلفوكسايد.وقد اجريت الدراسة بست درجات حرارية مختلفة ونوقشت امكانية في ضوء معادلة جونز- دول حيث اخذ بنظر الاعتبار الحجم الايوني والشحنة وشكل جزيئات المذاب.
Escherichia coli has been recognized worldwide as the most common causative agent for severe infections of the urinary tract. Colibactin is a genotoxin produced through a gene cluster called polyketide synthase (pks) island by members of Enterobacteriaceae. Limited information is available about the frequency of colibactin in E. coli isolates in Iraq. Hence, this study aimed to examine the frequency of some colibactin genes (CIbA and CIbQ) in clinical isolates of E. coli obtained from urinary tract infections (UTIs) in Iraq. Between October 2023 and January 2024, 120 urine samples were collected from females diagnosed with UTIs in Iraqi hospitals. 70 E. coli isolates were isolated after identification by biochemical methods and confirmed by
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