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Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Thu May 28 2015
Journal Name
International Journal Of Recent Scientific Research
HYBRID MACHINES PET/CT SCANNERS BY USING 18F, 82SR AND 68GE RADIONUCLIDE
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The increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Laser
PDF Tunable Optical filters Using Etched Polarization Maintaining Fiber Hybrid Sagnac Interferometer
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: In modern optical communication system, noise rejection multiple access interference (MAI) must be rejected in dense access network (DAN). This paper will study the dual optical band pass and notch filters. They will be extracted with tunable FWHM using 10cm (PMF) with different cladding diameters formed with etching 125μm PMF after immersing it with 40% of hydrofluoric acid (HF). This fiber acts as assessing fiber to perform Sagnac interferometer with splicing regions that placed 12cm (SMF) for performing hybrid Sagnac interferometer that consists of Mach-Zehnder instead of Sagnac loop which is illuminated by using laser source with centroid wavelength of 1546.7nm and FWHM of 286 pm or 9 ns in the time domain. . Firs

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials & Continua
A New Hybrid Feature Selection Method Using T-test and Fitness Function
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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
Grey-Level Image Compression Using 1-D Polynomial and Hybrid Encoding Techniques
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Climate change and its effect on water and vegetation cover over shary region using GIS techniques
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Publication Date
Tue Nov 09 2021
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
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Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p> ... Show More
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Publication Date
Wed Jun 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Global virtual teams management system: project manager guide
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Global virtual teams (GVTs) are a recent organizational adaptation created to meet the needs of globalizatized marketplace. GVTs are essentially teams that are distributed across national boundaries and concerned through advanced information and communication technology (ICT) such as email, instant messaging, and video conferencing. The research on GVTs is important in the information system (IS) field because GVTs are dependent on information communication technology and the use of other technologies; GVTs also consists of people from different cultures. This paper tried to answer two research questions. The first one is: what are the GVTs problems facing the project manager (PM). A literature review was conducted to answer the fir

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Publication Date
Thu Sep 26 2019
Journal Name
Processes
Fine-Tuning Meta-Heuristic Algorithm for Global Optimization
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This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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