Mobile Application to Detect Covid-19 Pandemic by Using Classification Techniques: Proposed System

Al-zubidi, Azhar F.; AL-Bakri, Nadia F.; Hasoun, Rajaa K.; Hashim, Soukaena Hassan; Alrikabi, Haider Th.Salim

doi:10.3991/ijim.v15i16.24195

Cited by 37 publications

(34 citation statements)

References 29 publications

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“…E-learning is a smart technique and it is a very efficient method to provide and exchange information with the learner's team in different countries at the same time [7][8][9]. The electronic educational platforms are that interactive educational situation that employs web technology, combines the benefits of electronic content management systems and social networks, and enables teachers to publish lessons and goals, set assignments, implement educational activities, and communicate with teachers through multiple technologies, as it enables teachers from conducting electronic exams, distributing roles, dividing students into working groups are helping to exchange ideas and opinions between students and teachers which led to sharing scientific content and allowing parents to communicate with teachers and see the results of their children, which helps to achieve high-quality educational outcomes [10][11][12][13][14]. E-learning has also gained an increasing desire among students, and educational platforms have witnessed leaps in providing a complete interactive educational experience [15,16,4,17,18].…”

Section: Introductionmentioning

confidence: 99%

The Influence E-Learning Platforms of Undergraduate Education in Iraq

Alrikabi¹,

Al-Malah²,

Majeed³

et al. 2021

Int. J. Recent Contrib. Eng. Sci. IT

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continue learning. Technology has become not only an activity but also a fundamental tool. Moreover, technology becomes the core media that allows education to happen. In Iraq Blended Learning used to overcome the pandemic and counting education Therefore, the use of computers and digital applications became part of daily life and for long hours. Therefore, properly designed digital educational activities linked to social media have become a powerful educational tool aimed at finding ways of effective learning. The use of interactive activities contributed to the growth of self-learning motivation and the building of a healthy mind capable of finding a way out for the advancement of educational reality when crises occurred. It has become impossible to do without mobile devices, because of the attractive features they have and the multiple advantages they provide in teaching mathematical, medical, and engineering sciences in universities of our study relied on comparing the most important educational platforms with the best operation for managing virtual classes and the auxiliary tools they contain, including adding materials, assignments, tests, and electronic attendance records with archiving classes and migrating students to the advanced stages, as it relied on the electronic administration mechanism. All of these procedures take place through the availability of the Internet.

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Section: Introductionmentioning

confidence: 99%

The Influence E-Learning Platforms of Undergraduate Education in Iraq

Alrikabi¹,

Al-Malah²,

Majeed³

et al. 2021

Int. J. Recent Contrib. Eng. Sci. IT

View full text Add to dashboard Cite

show abstract

“…In conducting research, it follows a descriptive/study relationship that focuses on the investigation of one of the psychological phenomena as they exist at present intending to diagnose them, revealing their aspects, and determining the relationships between their elements or between them and other phenomena [31][32][33][34][35][36][37][38]. The current research community includes all the computer departments in the colleges of education in the province of Baghdad/the morning study for the academic year (2014-2013).…”

Section: Methodsmentioning

confidence: 99%

The Skill of Making a Decision and its Relationship of Academic Achievement Among Students

Majeed

2021

Int. J. Recent Contrib. Eng. Sci. IT

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This research aims to know the essence of the correlative relationship between decision-making skills and academic achievement among students of computer science departments in the colleges of education in the Baghdad governorate. The size of the research sample of students in the two colleges amounted to (200) male and female students distributed by (104) male and (96) female students. To measure the decision-making skill and academic achievement, the researcher built two tests, the first to measure the decision-making skill, and the second an achievement test in the numerical analysis subject prescribed for second-year students, Department of Computer Science, and the validity and reliability of each test was verified. After collecting and analyzing the data, the researchers concluded that the students of the computer science departments in the colleges of education in the province of Baghdad possessed the decision-making skill compared to the hypothetical average that was compared, while the female students outperformed the male students in the decision-making skill test that was prepared for this research. And their achievement is good compared to the hypothetical average that was compared, while the female students outperformed the male students in the achievement test for the subject of numerical analysis. There is a correlation between the decision-making skill and the academic achievement of the students as a whole. However, there is no correlation between the decision-making skill and the students' academic achievement, while there is an inverse correlation between the decision-making skill and the student's achievement. The research reached several recommendations.

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“…Since before DL era, synthesizing accurate pictures of the ocular fundus has been a difficult job. Initially, it was addressed by developing sophisticated mathematical models of ocular anatomy [18,19]. Nowadays, technological advancements have resulted in significant computing capacity, allowing ML to be applied to neural networks with deep architectures.…”

Section: Related Workmentioning

confidence: 99%

DR-LL Gan: Diabetic Retinopathy Lesions Synthesis using Generative Adversarial Network

et al. 2022

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— Diabetic Retinopathy (DR) is a serious consequence of diabetes that seriously impact on the eyes and is a leading cause of blindness. If the lesions in DR arise in the central portion of the fundus, they may result in significant vision loss, which we refer to as Diabetic Macular Edema (DME). Deep learning (DL) techniques are commonly used utilized in ophthalmology for discriminative tasks such as diabetic retinopathy or age-related macular degeneration (AMD) diagnosis. Deep learning techniques typically need huge picture data sets for deep convolutional neural networks (DCNNs) training, it should be graded by human specialists. According to international protocol, it is classified into five severity categories. However, improving a grading model for high generality needs a significant quantity of balanced training data, which is challenging to obtain, especially at high levels of severity. Typical techniques for data augmentation, in many applications of deep learning in the retinal image processing domain, the difficulty of access to huge annotated datasets and legal concerns about patient privacy are limiting issues. As a result, the concept of creating synthetic retinal pictures that are indistinguishable from actual data has garnered more attention. GANs have been certain to be an effective framework for creating synthetic databases of anatomically accurate retinal fundus pictures. GANs, in particular, have garnered increasing attention in ophthalmology. in this article, we present a loss-less generative adversarial network (DR-LL GAN) to generate good resolution fundus pictures that May be adjusted to include random grading and information about the lesion. As a result, large-scale generated data may be used to train a DR grading and lesion segmentation model with more appropriate augmentation. Our model experiments evaluated on IDRID and MESSIDOR datasets, it's obtained a discrimination loss of 0.69374 and a generation loss of 1.10438, as well as a segmentation accuracy of 0.9840 in our tests. This might support in the optimization techniques of the neural network design and in computer-aided screening of medical picture, thus increasing diagnostic reliability for clinical assessment in the future of sophisticated technological healthcare.

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Mobile Application to Detect Covid-19 Pandemic by Using Classification Techniques: Proposed System

Cited by 37 publications

References 29 publications

The Influence E-Learning Platforms of Undergraduate Education in Iraq

The Influence E-Learning Platforms of Undergraduate Education in Iraq

The Skill of Making a Decision and its Relationship of Academic Achievement Among Students

DR-LL Gan: Diabetic Retinopathy Lesions Synthesis using Generative Adversarial Network

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