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Sustainable ENERGY by using AI
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As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations, if the summer season witnesses it. The Iraqis have a major interruption of electrical power, which forces them to buy electricity from the owners of private generators, and they are subject to their implementation and exploitation. Prices per ampere, as the price of an ampere in hot summer reaches $20, according to their desires, in addition to the environmental pollution left by those generators, as they are usually in residential neighborhoods and near homes, which increases From pollution of fresh air and the environment in residential neighborhoods, and this is what necessitated the aim of this study to find realistic solutions that are in line with the current situation that wounded Iraq is living, as it possesses enormous natural resources, and praise be to God, Lord of the Worlds. Despite all this, Iraq provides energy to most countries, and it suffers from severe power outages. Our study aims to find other alternatives to obtain renewable energy. By building more solar panels and wind turbines to play a decisive role in achieving this goal, which is to provide clean energy, especially since the climate of the Middle East in general and Iraq in particular has solar energy available throughout the year, especially in the hot summer season, and by using artificial intelligence it may be possible to store that energy and save it when needed.

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
Image Reconstruction Using Modified Hybrid Transform
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In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment, And Sustainability: Tmrees23fr
Hyperspectral pansharpening improvement using MNF transformation
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Deposited Cu (In, Ga) Se2 (CIGS) by spin-coating technique as an absorber layer of solar-cells
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Cu (In, Ga) Se2 (CIGS) nano ink were synthesized from molecular precursors of CuCl, In Cl3, GaCl3 and Se metal heated to 240 °C for 1 hour in N2-atmosphere to form CIGS nanocrystal ink, Thin films were deposited onto Au/soda-lime glass (SLG) substrates. This work focused on CIGS nanocrystals, including their synthesis and application as the active light absorber layer in photovoltaic devices (PVs). This approach, using spin-coating deposition of the CIGS light absorber layers (75 mg/ml and 150 nm thickness), without high temperature selenization, has enabled up to 1.398 % power conversion efficiency under AM 1.5 solar illumination. X-ray diffraction (XRD) studies show that the structural formation of CIGS chalcopyrite structure. The mo

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date
Tue Dec 01 2015
Journal Name
Solar Energy
A review of studies on using nanofluids in flat-plate solar collectors
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Continuous escalation of the cost of generating energy is preceded by the fact of scary depletion of the energy reserve of the fossil fuels and pollution of the environment as developed and developing countries burn these fuels. To meet the challenge of the impending energy crisis, renewable energy has been growing rapidly in the last decade. Among the renewable energy sources, solar energy is the most extensively available energy, has the least effect on the environment, and is very efficient in terms of energy conversion. Thus, solar energy has become one of the preferred sources of renewable energy. Flat-plate solar collectors are one of the extensively-used and well-known types of solar collectors. However, the effectiveness of the coll

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Effect of Diffusion Temperature on the some Electrical Properties of CdS:In Thin Films Prepared by Vacuum Evaporation
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CdS films were prepared by thermal evaporation technique at thickness 1 µm on glass substrates and these films were doped with indium (3%) by thermal diffusion method. The electrical properties of these have been investigated in the range of diffusion temperature (473-623 K)> Activation energy is increased with diffusion temperature unless at 623 K activation energy had been decreased. Hall effect results have shown that all the films n-type except at 573 and 623 K and with increase diffusion temperature both of concentration and mobility carriers were increased.

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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
Ag-SiO2 nanoparticales prepared by Sol-Gel methods for antibacterial effect
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Sol-gel method was use to prepare Ag-SiO2 nanoparticles. Crystal structure of the nanocomposite was investigated by means of X-ray diffraction patterns while the color intensity was evaluated by spectrophotometry. The morphology analysis using atomic force microscopy showed that the average grain sizes were in range (68.96-75.81 nm) for all samples. The characterization of Ag-SiO2 nanoparticles were investigated by using Scanning Electron Microscopy (SEM). Ag-SiO2 NPs are highly stable and have significant effect on both Gram positive and negative bacteria. Antibacterial properties of the nanocomposite were tested with the use of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The results have shown antibacteri

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Publication Date
Tue Nov 30 2021
Journal Name
Research Journal Of Pharmacy And Technology
Diagnostic approach to Perimenopausal bleeding by Pipelle or Dilatation and Curettage
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Perimenopausal bleeding, is a very common problem, which is an alarming symptom for both; women and their doctors because of the rising fears of cellular changes or tumor of endometrium. In our study we tried to prove that collecting endometrial samples using the outpatient method of Pipelle is as effective as collecting the endometrial samples in the traditional method of Dilation and Curettage (DandC) in operation theatre which necessitates general anesthesia. Ninety four patients more than 40 years old were included in the study, all of them were complaining of abnormal uterine bleeding (pregnant ladies and ladies using hormonal contraception were excluded from the study) and endometrial samples were collected first in outpatient

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Publication Date
Tue Oct 04 2022
Journal Name
Caspian Journal Of Environmental Sciences
Detecting genetics of several isolated bacterial species from soils by hydrocarbons
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The presence of hydrocarbons in the soil is considered one of the main problems of pollution. In our current study, eight samples isolated from soil saturated with hydrocarbons were taken from different areas of Baghdad, Iraq. In this study, 5 isolates belonging to Pseudomonas aeruginosa by 99%, 4 isolates to Klebsiella pneumoniae by 98%, and 3 isolates to Enterobacter hormaechei by 97% were diagnosed in different ways. A molecular examination was also conducted by 16sRNA. We recorded P. aeruginosa, K. Pneumoniae and E. hormaechei as new local isolates in NCBI. In addition, a comparison was made between our isolates and the global isolates to determine the degree of convergence in the evolutionary line. The genes alkB and nahAc7 were diagno

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