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Performance Enhancement of Metasurface Grating Polarizer Using Deep Learning for Quantum Key Distribution Systems
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction ration of »60000 at visible spectral wavelength of 632 nm, could be achieved.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Using Machine Learning to Control Congestion in SDN: A Review
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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Block-Iterative Frequency-Domain Equalizations for SC-IDMA Systems
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In wireless broadband communications using single-carrier interleave division multiple access (SC-IDMA) systems, efficient multiuser detection (MUD) classes that make use of joint hybrid decision feedback equalization (HDFE)/ frequency decision-feedback equalization (FDFE) and interference cancellation (IC) techniques, are proposed in conjunction with channel coding to deal with several users accessing the multipath fading channels. In FDFE-IDMA, the feedforward (FF) and feedback (FB) filtering operations of FDFE, which use to remove intersymbol interference (ISI), are implemented by Fast Fourier Transforms (FFTs), while in HDFE-IDMA the only FF filter is implemented by FFTs. Further, the parameters involved in the FDFE/

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Publication Date
Sat Apr 01 2017
Journal Name
25th Gis Research Uk Conference
VGI data collection for supplementing official land administration systems
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This article explores the process of VGI collection by assessing the relative usability and accuracy of a range of different methods (Smartphone GPS, Tablet, and analogue maps) for data collection amongst different demographic and educational groups, and in different geographical contexts. Assessments are made of positional accuracy, completeness, and data collectors’ experiences with reference to the official cadastral data and the administration system in a case-study region of Iraq. Ownership data was validated by crowd agreement. The result shows that successful VGI projects have access to varying data collection methods.

Publication Date
Thu Dec 01 2011
Journal Name
Proceedings Of 2011 International Conference On Computer Science And Network Technology
A new proposed handoff scheme for mobile communication systems
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There are many studies dealt with handoff management in mobile communication systems and some of these studies presented handoff schemes to manage this important process in cellular network. All previous schemes used relative signal strength (RSS) measurements. In this work, a new proposed handoff scheme had been presented depending not only on the RSS measurements but also used the threshold distance and neighboring BSS power margins in order to improve the handoff management process. We submitted here a threshold RSS as a condition to make a handoff when a mobile station moves from one cell to another this at first, then we submitted also a specified margin between the current received signal and the ongoing BS's received signal must be s

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials & Continua
Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM approaches
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Publication Date
Tue Jan 01 2013
Journal Name
Iraqi Journal Of Physics
A comparison between PCA and some enhancement filters for denoising astronomical images
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This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

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Publication Date
Fri Mar 01 2024
Journal Name
Physical Chemistry Research
Exploring the Potential of Quantum Chemical Calculations for Synthesized Quinazoline Derivatives as Superior Corrosion Inhibitors in Acidic Environment
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Hydrochloric acid (HCl) is a substance that is frequently utilized in industrial operations for important tasks such as chemical cleaning and pickling metallic surfaces.Therefore, the corrosion inhibition ability of three newly synthesized quinazoline derivatives namely, 3-allyl-2-(propylthio) quinazolin-4(3H)-one) (APQ), (3-allyl-2-(allylthio) quinazolin-4(3H)-one) (AAQ), (3-allyl- 2-( Prop -2-yn -1-ylthio) Quinazolin - 4 (3H) - one) (AYQ) were theoretically determined and these compounds were characterized using Fourier Transform Infra-Red (FTIR) and 1H and 13C Nuclear Magnetic Resonance (NMR) spectroscopic. A series of quantum chemical properties of these derivatives: EHOMO, ELUMO, energy gap (ΔE),dipole moment (μ), hardness (η), soft

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