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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 2014
Journal Name
The Scientific World Journal
Heat Transfer Enhancement of Laminar Nanofluids Flow in a Circular Tube Fitted with Parabolic-Cut Twisted Tape Inserts
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Numerical investigation has been carried out on heat transfer and friction factor characteristics of copper-water nanofluid flow in a constant heat-fluxed tube with the existence of new configuration of vortex generator using Computational Fluid Dynamics (CFD) simulation. Two types of swirl flow generator: Classical twisted tape (CTT) and Parabolic-cut twisted tape (PCT) with a different twist ratio (y= 2.93, 3.91 and 4.89) and different cut depth (w= 0.5, 1.0 and 1.5 cm) with 2% and 4% volume concentration

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Role of System Strategic Learning Smart In Sustainability Success of Managing Network e-Business
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Purpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.

Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.

Methodology:

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Publication Date
Thu Jun 28 2012
Journal Name
Journal Of Physical Education
The Study of the Motor coincidence and sensitive- Kinetic Perception and its Relation them with Artistic Performance Level in Gymnastics Skills for Women
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The aim of this study was Identifying the relation of coordination and kinesthetic perception with artistic performance level in gymnastics skills for students in second class from the college of physical education/ university of Baghdad/ Al - jadreia .The searchers have been used the descriptive method in scanning style .The subject of this search has been taken (45) female - student in second class from the college of physical education/ university of Baghdad . The searchers have reached into specific conclusions concerning with statistic analysis about immoral joint relation between sensitive- kinetic coincidence and realization and with Artistic Performance Level in Gymnastics Skills for Women for second class .The an important recommen

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Calculation of Lambda Doubling for 7LiH1 molecule Using the System band emission for electronic transmissions
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The A2?u-X1?g+ emission band system of 7LiH1 molecule has been calculated for Lambda doubling. The relation between wave number ?p , ?Q , ?R conducted the energies of the state of rotation F (J), and (J + 1) with rotational quantum number J, respectively, of 7LiH1 molecule for statehood A2?u using the rotation, fixed vibrational states of both the ground and raised crossovers vibrational against ???= 0 to V ' = 0-4using rotational levels J = 0 to J = 20 have found.

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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Sun Mar 21 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of the reliability system in model of stress- strength according to distribution of inverse Rayleigh
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Publication Date
Sun Sep 07 2025
Journal Name
Journal Of Physical Education
Proposed Exercises Using Flexible Resisters And Their Effect On Developing Strength Endurance And The Performance of Some Offensive Skills In Youth Basketball
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Publication Date
Wed Sep 15 2021
Journal Name
Geomechanics And Geoengineering
Effect of Deep Remediation and Improvement on Bearing Capacity and Settlement of Piled Raft Foundation Subjected to Static and Cyclic Vertical Loading
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Publication Date
Sun Sep 07 2025
Journal Name
Al.qadisiya Journal For The Sciences Of Physical Education
The Impact of weighted gloves on developing the effectiveness of performance and increasing the number of punches for youth boxers
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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Scopus (8)
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