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Secure communications by chaotic carrier signal using Lorenz model
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In this paper, the generation of a chaotic carrier by Lorenz model
is theoretically studied. The encoding techniques has been used is
chaos masking of sinusoidal signal (massage), an optical chaotic
communications system for different receiver configurations is
evaluated. It is proved that chaotic carriers allow the successful
encoding and decoding of messages. Focusing on the effect of
changing the initial conditions of the states of our dynamical system
e.i changing the values (x, y, z, x1, y1, and z1).

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Aesthetic Levels in Shape Variables in Spectacular Films the Indian Film (Main Tera Hero) a Model: غسان محسن حمد
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The spectacular film is a type of feature films which has specific elements that contribute in increasing the aesthetics of the shape in its structure. The researcher started studying this type of films by researching the spectacular film concept, the history of its development, who are its most important stars and then tackling the Indian cinema represented by Bollywood, which is considered a school for this type of film. The researcher addressed the most important influential elements that entre in its production as well as studying these elements that contribute to building the shape including the configuration, movements of cameras, lenses, the lighting, colors, costumes etc. and what influence they have in forming a special aestheti

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Publication Date
Sun Apr 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The impact of the model and follows on the collection and Retention of fifth grade students (oiterary) in history
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The first chapter the importance of research and need for education scientists see that the roots of the use of a specimen Wheatley in learning and teaching back to Grayson Wheatley, one of the largest supporters of a modern construction, which lay the groundwork for the specimen stage and the form in which it is. That was attributed to him, often called his name called while some educators based learning strategy on the issue. He sees the learner in this model make him a meaningful understanding of problems during his progress, thereby acting with his colleagues to find solutions to them in small groups. He

        Borders Search: Search by students is determined by th

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The use of the Biz method and classical methods in estimating the parameters of the binary logistic regression model
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Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
ESTIMATION OF COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES WITH APPLICATIONS
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In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

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Publication Date
Mon Mar 25 2019
Journal Name
Al-academy
Direction Structure of the Imaginary and Interpretation Controversy in the Theatre Reception "Mukashafat" Play -A Model: ثابت رسول جواد
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The current research deals with the argument of delusion and interpretation in the direction structure and its reflected impact in the reception activity and the amount of conceptual displacement it is subjected to in an aesthetic approach to abstract conceptual definitions of the reception activity , by the effect of this dialectic in the direction structure, which can be summed up by the following question: (What are the characteristics of the direction structure of the imaginary and what is the argument of interpretation in the theatre reception activity?) in order to stand on the aesthetic framework and conceptual definition of the direction structure in the controversy of interpretation and imagination, and its impact on the concept

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Wed Aug 10 2022
Journal Name
Mathematics
Modeling and Analysis of the Influence of Fear on the Harvested Modified Leslie–Gower Model Involving Nonlinear Prey Refuge
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Understanding the effects of fear, quadratic fixed effort harvesting, and predator-dependent refuge are essential topics in ecology. Accordingly, a modified Leslie–Gower prey–predator model incorporating these biological factors is mathematically modeled using the Beddington–DeAngelis type of functional response to describe the predation processes. The model’s qualitative features are investigated, including local equilibria stability, permanence, and global stability. Bifurcation analysis is carried out on the temporal model to identify local bifurcations such as transcritical, saddle-node, and Hopf bifurcation. A comprehensive numerical inquiry is carried out using MATLAB to verify the obtained theoretical findings and und

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Publication Date
Fri Jun 02 2023
Journal Name
East European Journal Of Physics
Electroexcitation Form Factors and Deformation of 20,22Ne Isotopes Based on the Shell Model and Hartree-Fock plus BCS Calculations
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Nuclear structure of 20,22Ne isotopes has been studied via the shell model with Skyrme-Hartree-Fock calculations. In particular, the transitions to the low-lying positive and negative parity excited states have been investigated within three shell model spaces; sd for positive parity states, spsdpf large-basis (no-core), and zbme model spaces for negative parity states. Excitation energies, reduced transition probabilities, and elastic and inelastic form factors were estimated and compared to the available experimental data. Skyrme interaction was used to generate a one-body potential in the Hartree-Fock calculations for each selected excited states, which is then used to calculate the single-particle matrix elements. Skyrme interac

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
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Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

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