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Linear Prediction of Sum of Two Poisson Process
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Our goal from this work is to find the linear prediction of the sum of two Poisson process
) ( ) ( ) ( t Y t X t Z + = at the future time 0 ), ( ≥ + τ τ t Z and that is when we know the values of
) (t Z in the past time and the correlation function ) (τ βz

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Solving Linear Volterra – Fredholm Integral Equation of the Second Type Using Linear Programming Method
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In this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree  and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Engineering
REMOVAL OF OIL FROM WASTEWATER BY ADVANCED OXIDATION PROCESS / HOMOGENEOUS PROCESS
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In the present work advanced oxidation process, photo-Fenton (UV/H2O2/Fe+2) system, for the treatment of wastewater contaminated with oil was investigated. The reaction was influenced by the input concentration of hydrogen peroxide H2O2, the initial amount of the iron catalyst Fe+2, pH, temperature and the concentration of oil in the wastewater. The removal efficiency for the system UV/ H2O2/Fe+2 at the optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=3, temperature =30o C) for 1000mg/L load was found to be 72%.

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Sum Rate Maximization Versus MSE Minimization in FDD Massive MIMO Systems With Short Coherence Time
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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The role of modern manufacturing systems in process Design
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The aim of the research to measure the correlation relationship between modern manufacturing systems and process design and measure the effect by adopting the regression; the research consists of two main variables, which are modern manufacturing systems and process design; it was applied in the production lines of the General Company for Construction Industries, There is a sample of managers, engineers, technicians, administrators, and some workers were selected to fill the special questionnaire with (70) forms which distributed and (65) were approved suitable for use, For data analysis the correlation coefficient was adopted to measure the relationship and regression analysis to find out the effect, Using (SPSS), So the first h

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Some Statistical Characteristics Depending on the Maximum Variance of Solution of Two Dimensional Stochastic Fredholm Integral Equation contains Two Gamma Processes
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   In this paper, we find the two solutions of two dimensional stochastic Fredholm integral equations contain two gamma processes differ by the parameters in two cases and equal in the third are solved by the Adomain decomposition method. As a result of the solutions probability density functions and their variances at the time t are derived by depending upon the maximum variances of each probability density function with respect to the three cases. The auto covariance and the power spectral density functions are also derived. To indicate which of the three cases is the best, the auto correlation coefficients are calculated.

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Publication Date
Mon May 01 2017
Journal Name
Energy Procedia
A Coupled Model of the Linear Joule Engine with Embedded Tubular Permanent Magnet Linear Alternator
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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
Oscillations of Third Order Half Linear Neutral Differential Equations
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In this paper the oscillation criterion was investigated for all solutions of the third-order half linear neutral differential equations. Some necessary and sufficient conditions are established for every solution of (a(t)[(x(t)±p(t)x(?(t) ) )^'' ]^? )^'+q(t) x^? (?(t) )=0, t?t_0, to be oscillatory. Examples are given to illustrate our main results.

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Stochastic Non-Linear Pseudo-Random Sequence Generator
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Many of the key stream generators which are used in practice are LFSR-based in the sense that they produce the key stream according to a rule y = C(L(x)), where L(x) denotes an internal linear bit stream, produced by small number of parallel linear feedback shift registers (LFSRs), and C denotes some nonlinear compression function. In this paper we combine between the output sequences from the linear feedback shift registers with the sequences out from non linear key generator to get the final very strong key sequence

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Maximum Likelihood Method And Bayesian Method For Estimating Some Non-Homogeneous Poisson Processes Models
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Abstract

The Non - Homogeneous Poisson  process is considered  as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).

This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto ,   to estimate th

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