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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 eyes' observation of the different colors and features of images. We propose a multi-layer hybrid system for deep learning using the unsupervised CAE architecture and using the color clustering of the K-mean algorithm to compress images and determine their size and color intensity. The system is implemented using Kodak and Challenge on Learned Image Compression (CLIC) dataset for deep learning. Experimental results show that our proposed method is superior to the traditional compression methods of the autoencoder, and the proposed work has better performance in terms of performance speed and quality measures Peak Signal To Noise Ratio (PSNR) and Structural Similarity Index (SSIM) where the results achieved better performance and high efficiency With high compression bit rates and low Mean Squared Error (MSE) rate the results recorded the highest compression ratios that ranged between (0.7117 to 0.8707) for the Kodak dataset and (0.7191 to 0.9930) for CLIC dataset. The system achieved high accuracy and quality in comparison to the error coefficient, which was recorded (0.0126 to reach 0.0003) below, and this system is onsidered the most quality and accurate compared to the methods of deep learning compared to the deep learning methods of the autoencoder

Publication Date
Mon Jul 01 2019
Journal Name
Opcion
Gender differences in motivation toward learning EFL skills among international students
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This paper aims to examine the effects of the gender differences on learners‟ motivation in learning the four skills of English as a foreign language as well as to identify the proper types of motivation for males and females via a qualitative semi-structured interview. The findings showed that all the males have extrinsic motivation in all four skills. On the other hand, females differ among themselves in their motivation. In conclusion, it is also the teachers‟ responsibility to guide and direct their learners to achieve better outcomes in learning the four EFL skills.

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Scopus (1)
Scopus
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 w

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Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

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Scopus (2)
Crossref (1)
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Publication Date
Wed Dec 20 2023
Journal Name
Migration Letters
Women's Image in Arabic Songs (An Analytical Study of how Women Appear in the Most Viewed Songs on YouTube for the Year 2021)
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Publication Date
Sat Oct 01 2016
Journal Name
Al–bahith Al–a'alami
Spiritual Communication in Sufi Discourse- A communicative –Semiotic Approach to the Sufi Symbolic Image
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This paper deals with a central issue in the field of human communication and reveals the roaming monitoring of the incitement and hatred speech and violence in media, its language and its methods. In this paper, the researcher seeks to provide a scientific framework for the nature of the discourse of incitement, hatred speech, violence, and the role that media can play in solving conflicts with their different dimensions and in building community peace and preventing the emergence of conflicts among different parties and in different environments. In this paper, the following themes are discussed:
The root of the discourse of hatred and incitement
The nature and dimensions of the discourse of incitement and hatred speech
The n

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Scoping Review of Machine Learning Techniques and Their Utilisation in Predicting Heart Diseases
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Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

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Crossref (3)
Crossref
Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
The Effect of Combining Video Lectures and Kolb Experiential Learning on EFL Student-Teachers’ Ability to Teach Communicative Coursebook and their Teaching Competencies
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Communicative-based textbooks are developed and disseminated throughout the country.
However, it is difficult for teachers who themselves have learnt English through the traditional
approaches to suddenly be familiar with CLT (Communicative Language Teaching) principles
and teach communicatively. Therefore, many teachers remain somewhat confused about what
exactly CLT is and others familiar with CLT but unable to achieve communicative classroom
teaching. Consequently, those teachers need to be introduced to the CLT principles and they need
training in how to put CLT principles into practice. Accordingly, this study aims to find out the
effect of combining video lectures and Kolb experiential learning on EFL student-t

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Publication Date
Fri Feb 15 2019
Journal Name
Route Educational & Social Science Journal
The effect of the 4-H model on self-regulated learning and life skills for female chemistry students in the second intermediate year
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Publication Date
Tue Jan 01 2019
Journal Name
الأستاذ
Teaching-learning design according to constructivist theory models and its impact on the achievement of chemistry among second-year intermediate school female students
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Publication Date
Sat May 10 2025
Journal Name
Journal Of Physical Education
The impact of proposed approach for flexibility and agility in learning some basic skills on the table land movements in the artistic gymnastics
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