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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 is tested under static and dynamic load conditions. The simulation and models are done by using MATLAB/Simulink. The simulation results from the proposed NARMA-L2 controller have been compared with existing Perturb and observe PO-MPPT and Incremental Conductance INC -MPPT methods.

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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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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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Publication Date
Sat Jul 26 2025
Journal Name
Arab World English Journal
YouTube as a Learning Tool Among EFL Learners: A Systematic Review
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This review paper examines the crucial impact of YouTube on learning English as a Foreign Language. Recently, learners’ interaction and development of their skills have been improved due to the integration of digital platforms into language education. YouTube is regarded as one of the most prevalent platforms due to its accessibility, multimodal content, and capacity to simulate real-life communication. This study tackles thirty selected research articles from various cultural and institutional backgrounds to identify the pedagogical benefits and challenges associated with using YouTube in teaching English. Conventional methods of teaching English as a foreign language encounter difficulties in improving students’ engagement and

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Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Enhancement of Photoconductive Detector Based on Carbon Nanotubes Decorated with Silver Nanoparticles by Adding Conductive Polymer
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In this work, wide band range photo detector operating in UV, Visible and IR was fabricated using carbon nanotubes (MWCNTs, SWCNTs) decorated with silver nanoparticles (Ag NPs). Silicon was used as a substrate to deposited CNTs/Ag NPs by the drop casting technique. Polyamide nylon polymer was used to coat CNTs/Ag NPs to enhance the photo-response of the detector. The electro-exploding wire technology was used to synthesize Ag NPs. Good dispersion of silver NPs achieved by a simple chemistry process on the surface of CNTs. The optical, structure and electrical characteristic of CNTs decorated with Ag NPs were characterized by X-Ray diffraction and Field Emission Scanning Electron Microscopy.  X-ray diffra

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Comparison of Some Suggested Estimators Based on Differencing Technique in the Partial Linear Model Using Simulation
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In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

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Publication Date
Fri Jun 30 2023
Journal Name
Ingénierie Des Systèmes D Information
Performance Evaluation of a Multi Organizations Secure Internet of Vehicles Based on Hyperledger Fabric Blockchain Platform
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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Engineering
Influence of Using Various Percentages of Slag on Mechanical Properties of Fly Ash-based Geopolymer Concrete
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In order to implement the concept of sustainability in the field of construction, it is necessary to find an alternative to the materials that cause pollution by manufacturing, the most important of which is cement. Because factory wastes provide siliceous and aluminous materials and contain calcium such as fly ash and slag that are used in the production of high-strength geopolymer concrete with specifications similar to ordinary concrete, it was necessary for developing this type of concrete that is helping to reduce CO2 (dioxide carbon) in the atmosphere. Therefore, the aim of this study was to study the influence of incorporating various percentages of slag as a replacement for fly ash and the effect of sl

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Publication Date
Sun Dec 01 2019
Journal Name
Indian Journal Of Ecology
Evaluation of maize hybrids, their inbred lines and estimation of genetic divergence based on cluster analysis
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Al-farabi For Engineering Sciences Vol
Prototyping of Multi-Factors Based Vehicle Accident Detection and Reporting System Relying on GPS and GSM
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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Polluted Water Sensor Based on Carbon Quantum Dots/Alq3 Using Drop Casting and Spin Coating Techniques
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Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of

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