The work in this paper involves the planning, design and implementation of a mobile learning system called Nahrain Mobile Learning System (NMLS). This system provides complete teaching resources, which can be accessed by the students, instructors and administrators through the mobile phones. It presents a viable alternative to Electronic learning. It focuses on the mobility and flexibility of the learning practice, and emphasizes the interaction between the learner and learning content. System users are categorized into three categories: administrators, instructors and students. Different learning activities can be carried out throughout the system, offering necessary communication tools to allow the users to communicate with each other through forums, SMS and e-mails. NMLS platform is based on 3G mobile phone technology and adopted WAP as a solution for the system platform. The NMLS framework is based on three layers, which are presentation layer, business logic layer and data layer.
The variety of clean energy sources has risen, involving many resources, although their fundamental principles remain consistent in terms of energy generation and pollution reduction. The using of hydropower system for energy production also has a dynamic impact in which it utilizes to harness the water for the purpose of energy production. As it is important to overcome the problem of accidents in the highway and rural areas in the case of server rainfall and flood by implementation a smart system that used for energy production. This paper aims to develop a controlled hydropower system installed in the drainage sinks allocated in highway roads used for producing. The proposed system consists of storage unit represented by pipes used for t
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Background: Acute appendicitis is regarded as one of the most common inflammation that needs surgical intervention. Different scoring systems have been used for diagnosing of acute appendicitis. ALVARADO score is one of the most widely used score in diagnosing of acute appendicitis, but the accuracy of the latter is insufficiently low in Middle-East patients. Thus a new scoring system called RIPASA score has been designed for diagnosing of acute appendicitis in those patients. The aim of this study is to use RIPASA score and compare its result with ALVARADO score in diagnosing of acute appendicitis.
Subjects and Methods: The study includes 200 patients with symptoms and signs of
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The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w
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New trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teach
In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
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