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Estimation of the Standard Atmospheric Earth Model Parameters at 86 km Altitude
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     Utilizing the Turbo C programming language, the atmospheric earth model is created from sea level to 86 km. This model has been used to determine atmospheric Earth parameters in this study. Analytical derivations of these parameters are made using the balancing forces theory and the hydrostatic equation. The effects of altitude on density, pressure, temperature, gravitational acceleration, sound speed, scale height, and molecular weight are examined. The mass of the atmosphere is equal to about 50% between sea level and 5.5 km. g is equal to 9.65 m/s2 at 50 km altitude, which is 9% lower than 9.8 m/s2 at sea level. However, at 86 km altitude, g is close to 9.51 m/s2, which is close to 15% smaller than 9.8 m/s2.  These results have been compared with an international standard atmosphere. The presumed atmosphere model differs significantly from the actual atmosphere because weather fluctuations are not taken into consideration in this model.

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Publication Date
Sun Jan 01 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
A reliable numerical simulation technique for solving COVID-19 model
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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Statistical Model for Polarization Mode Dispersion in Single Mode Fibers
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As the bit rate of fiber optic transmission systems is increased to more than , the system will suffer from an important random phenomena, which is called polarization mode dispersion. This phenomenon contributes effectively to: increasing pulse width, power decreasing, time jittering, and shape distortion. The time jittering means that the pulse center will shift to left or right. So that, time jittering leads to interference between neighboring pulses. On the other hand, increasing bit period will prevent the possibility of sending high rates. In this paper, an accurate mathematical analysis to increase the rates of transmission, which contain all physical random variables that contribute to determine the transmission rates, is presen

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Publication Date
Sat Dec 20 2025
Journal Name
Journal Of Engineering
Drag Reduction Using Passive Methods on KIA PRIDE Car Model
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An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the average drag estimated on

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Sun Jun 01 2014
Journal Name
2014 International Conference On Computer And Information Sciences (iccoins)
Proposed conceptual model for E-service quality in Malaysian universities
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATED NON-PARAMETRIC AND SEMI-PARAMETRIC MODEL FOR LONGITUDINAL DATA
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Scopus
Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Tue Nov 27 2018
Journal Name
The Iraqi Geological Journal
CHRONOSTRATIGRAPHICALLY BASED RESERVOIR MODEL FOR CENOMANIAN CARBONATES, SOUTHEASTERN IRAQ OILFIELDS
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The Cenomanian – Turronian sedimentary succession in the south Iraq oil fields, including Ahmadi, Rumaila, Mishrif and Khasib formations have undergone into high-resolution reservoir-scale genetic sequence stratigraphic analysis. Some oil-wells from Majnoon and West-Qurna oil fields were selected as a representative case for the regional sequence stratigraphic analysis. The south Iraqi Albian – Cenomanian – Turronian succession of 2nd-order depositional super-sequence has been analyzed based on the Arabian Plate chronosequence stratigraphic context, properly distinguished by three main chrono-markers (The maximum flooding surface, MFS-K100 of the upper shale member of Nahr Umr Formation, MFS-K140 of the upper Mishrif carbonate

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Four Level Prior Distributions
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Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Drag Reduction Using Passive Methods on KIA PRIDE Car Model
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An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the avera

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View Publication Preview PDF
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