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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 Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
"Comparison of Approximate Estimation Methods for Logistics Distribution Teachers"
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The goal beyond this Research is to review methods that used to estimate Logistic distribution parameters. An exact estimators method which is the Moment method, compared with other approximate estimators obtained essentially from White approach such as: OLS, Ridge, and Adjusted Ridge as a suggested one to be applied with this distribution. The Results of all those methods are based on Simulation experiment, with different models and variety of  sample sizes. The comparison had been made with respect to two criteria: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).  

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Publication Date
Thu Feb 01 2018
Journal Name
Iet Signal Processing
Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Wed Mar 16 2022
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
Smart Learning based on Moodle E-learning Platform and Digital Skills for University Students
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Strategic Information Systems and their effects on the Developing of Intellectual Capital in the Electricity Distribution Company in the Hashemite Kingdom of Jordan
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This research aims to study the impact of strategic information systems on the development of intellectual capital in the Public Shareholding Electricity Distribution Company in the Hashemite Kingdom of Jordan. To achieve the objectives of the study, a questionnaire was developed for the purpose of data collection, as the number of valid questionnaires for analysis was about (135), and SPSS and AMOS 0.26 software was used to analyze the collected data. The study found out that the respondents' perceptions of the level of importance of strategic information systems and the level of importance of intellectual capital were high, and that the relational capital has ranked as first, followed by structural capital, and h

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Estimating the general exponential distribution parameters using the simulation method
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The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation technique .. It was obse

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Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Computer Science
Peer-to-Peer Video Conferencing Using Hybrid Content Distribution Model
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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Fri Jul 12 2024
Journal Name
Aaps Pharmscitech
Nanosuspension-Based Repaglinide Fast-Dissolving Buccal Film for Dissolution Enhancement
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Drug solubility and dissolution remain a significant challenge in pharmaceutical formulations. This study aimed to formulate and evaluate repanglinide (RPG) nanosuspension-based buccal fast-dissolving films (BDFs) for dissolution enhancement. RPG nanosuspension was prepared by the antisolvent-precipitation method using multiple hydrophilic polymers, including soluplus®, polyvinyl alcohol, polyvinyl pyrrolidine, poloxamers, and hydroxyl propyl methyl cellulose. The nanosuspension was then directly loaded into BDFs using the solvent casting technique. Twelve formulas were prepared with a particle size range of 81.6-1389 nm and PDI 0.002-1 for the different polymers. Nanosuspensions prepared with soluplus showed a favored mean particle size o

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
System Identification Algorithm for Systems with Interval Coefficients
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In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

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