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Formation Engineering and Pedagogy of E-Learning in Light of Corona Pandemic
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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Scopus (13)
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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Scopus (9)
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Publication Date
Tue Dec 30 2014
Journal Name
College Of Islamic Sciences
Ignite the burn on those who did not sign          The divorce of the buoy                  For the mark Muhammad ibn al-Haj Hassan alani Kurdish (1111 - 1196 e)
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One of the Kurdish scholars who have research on the doctrinal issues of the author of this brief message that we are about to achieve; to bring it out better and in order to preserve the Islamic heritage, and revive what can be revived after being close to death by staying in libraries here and there, out of reach of hands, carrying dust Years of forgetting and marginalization, and this letter is the papers in the door of the divorce entitled his author "Iqdar al-dream for those who did not sign divorce commoner," and the name is evident the name, and the intention of the author through writing, where he wrote it to answer some of the knowledgeable among the public at the time So they decreed that there was no divorce from commoners D w

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Publication Date
Mon Feb 13 2023
Journal Name
Journal Of Educational And Psychological Researches
A Blended Learning Program Based on the Next Generation Standards (NYS) to Develop the Teaching Performance of Middle School Mathematics Teachers and Some Students’ Future Thinking Skills
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Abstract

The aim of the current research is to prepare an integrated learning program based on mathematics standards for the next generation of the NYS and to investigate its impact on the development of the teaching performance of middle school mathematics teachers and the future thinking skills of their students. To achieve the objectives of the research, the researcher prepared a list of mathematics standards for the next generation, which were derived from a list of standards. He also prepared a list of the teaching competencies required for middle school mathematics teachers in light of the list of standards, as well as clarified the foundations of the training program and its objectives and the mathematical

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Publication Date
Mon Nov 13 2023
Journal Name
Published By Iraqi Translators Association
Congruencia estilística en la estructuración temática de la novela contemporánea árabe e hispánica Muhsin al-Ramli y Gabriel García Márquez Como muestra
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AbstractoEl presente estudio tiene como objetivo realizar un análisis comparativo entre dos obras literarias destacadas: “El amor en los tiempos del cólera” del célebre escritor Gabriel García Márquez y la novela “Los jardines del presidente” del escritor iraquí Mohsen al-Ramli. Estas dos novelas, escritas en diferentes contextos culturales y geográficos, comparten una serie de elementos contextuales y narrativos que nos invitan a explorar sus similitudes y diferencias.Principalmente, ambas obras pertenecen al género del realismo y se sumergen en las circunstancias y experiencias de sus personajes en sociedades oscuras dominadas por la opresión, la guerra y las tradiciones impuestas. Los autores ofrecen una perspectiva crí

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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
Designing an E-marketing Website for Sustainable Fashion: صيته بنت محمد المطيري .....بشاير يوسف التويجري .....روان يوسف العلي....شهد عبد الحكيم المقرن
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The importance of websites appears as a modern tool that helps people connect with each other and exchange information rapidly. An increase number of new websites have been created in public or private spheres, which benefit individuals and society as a whole. This research aims to design a website specialized in marketing sustainable fashion that meets the needs of the Saudi market. It followed a descriptive and analytical approach. A survey has been conducted on a random sample of e-marketing users. The sample number is 101 users. The study resulted in: Determining the effectiveness of e-marketing, studying consumer purchasing tendencies, and designing a website for sustainable fashion based on the survey’s results. The study recomme

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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Publication Date
Sun Jan 01 2017
Journal Name
البحوث التربويةوالنفسية
Preparing a teacher’s guide for computer books for the intermediate stage according to learning styles
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Scopus (13)
Crossref (7)
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