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Problems Facing University Students in Distance Learning
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The current study aims to examine the level of problems faced by university students in distance learning, in addition to identify the differences in these problems in terms of the availability of internet services, gender, college, GPA, interactions, academic cohort, and family economic status. The study sample consisted of (3172) students (57.3% females). The researchers developed a questionnaire with (32) items to measure distance learning problems in four areas: Psychological (9 items), academic (10 items), technological (7 items), and study environment (6 items). The responses are scored on a (5) point Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree). Means, standard deviations, and Multivariate Analysis of Variance (MANOVA) were used to analyze the data. The findings showed that students faced high levels of psychological and academic problems and medium levels of technological and study environmental problems. The findings also indicated statistically significant differences in the levels of all problems based on the availability of internet services. In addition, the sample in scientific colleges manifested higher levels of academic problems, and females showed higher levels of study environmental problems. Statistically significant differences also appeared in all types of problems based on study cohort and family economic status.

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
الألفاظ المَعبِّرة عن المطر في القرآن الكریم دراسة دلالیة
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The Holy Koran is the highest text in the eloquence, It is one of the
important sources of the linguistic syntactic and eloquent study; it impacts
upon these sciences Avery intense impact through advancing its verses as an
argument in the confirmation of the significance of the term
The holy Koran was and still the fountain of the linguistic studies, as
they tend towards it since the second century of the hegira. So this research is
a study of the expressive terms concerning the rain in the holly Koran, a
linguistic study; it aims to study the term concerning its linguistic and
conjugate significance and its expression concerning the rain through reality
and metaphor.

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Publication Date
Thu Dec 27 2018
Journal Name
Arab Science Heritage Journal
نبذة عن معاني الحروف في العربية دراسة توثيقية نحوية
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اهتمام العلماء العرب بالحروف مبينين معانيه موضحين مقاصده 

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Publication Date
Thu Feb 04 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Economic losses caused by mole cricket Gryllotalpa gryllotalpa on some vegetable plants and agricultural crops: Economic losses caused by mole cricket Gryllotalpa gryllotalpa on some vegetable plants and agricultural crops
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The study was conducted to estimate the economic losses caused by insect mole cricket Gryllotalpa gryllotalpa on some agricultural crops and Potato tubers in collage of Agriculture- Abu Ghraib season 2012-2013. Study showed Mole cricket caused percentage of infestation in spring potato tubers variety Luciana reached to 11.61% and the percentage of loss in weight of tubers reached 18.88%. The study showed that addition of animal manure (organic fertilizer) to the soil when planting potatoes in the autumn increased the incidence of infestation and the number of tunnels caused by mole cricket which led to from increased economic losses. When matured potato tubers were left for a longer period in the soil percentage of infestation by mole cr

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Cervical Pain Related to Position of the Neck during E-Learning
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Background: During the pandemic, Corona virus forced many people, especially students, to spend more time than before on the computer and smartphone to study and communicate. The poor posture of the body may have worse effect on its body parts , most of which is the cervical spine (forward head posture). Objective: To assess the incidence of neck pain and the associated factors among undergraduate medical students related to position during E learning Subjects and Methods: Cross-sectional study was conducted among medical students in three Iraqi universities during 2021. The sample size was 152. Online questionnaire by Google forms sampling method were used to collect the data which was analysed using SPSS 25. Results: The perce

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Sat Aug 10 2024
Journal Name
Cureus
Machine Learning and Vision: Advancing the Frontiers of Diabetic Cataract Management
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