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ijp-1026
Positron Interactions with Some Human Body Organs Using Monte Carlo Probability Method
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In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this work, elastic cross sections (ECS) and inelastic cross-sections (ICS) for positron interaction in human tissues were studied. The elastic scattering is obtained from the Rutherford differential cross-section. Gryzinski's excitation function is used within the first-born approximation to determine the core and valence of ICS. The results are presented graphically. The ECS increases rapidly as the scattering energy approaches zero and becomes dependent on the atomic number of elements in organs. The ICS has reached a maximum value of around 100 eV. Increasing positron energy leads to an increase in the elastic and inelastic mean free paths. The simulations agree with many other studies dealing with the same parameters and conditions.

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Calculation of Full Energy Peak Efficiency for HPGe Detector Using Monte Carlo Method
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This research presents results on the full energy peak efficiency of a high purity germanium (HPGe) detector from point source as a function of photon energy and source-detector distance. The directions of photons emitted from the source and the photon path lengths in the detector were determined by Monte Carlo technique. A major advantage of this technique is the short computation time compared to the experiments. Another advantage is the flexibility for inputting detector-related parameters (such as source–detector distance, detector radius, length and attenuation coefficient) into the algorithm developed, thus making it an easy and flexible method to apply to other detector systems and configurations. It has been designed and writte

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Publication Date
Thu Dec 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Simulation the Radiation Zone of Al-Mussaib Power Plant by Using Monte Carlo Method
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The temperature distributions are to be evaluated for the furnace of Al-Mussaib power plant. Monte Carlo simulation procedure is used to evaluate the radiation heat transfer inside the furnace, where the radiative transfer is the most important process occurring there. Weighted sum of gray-gases model is used to evaluate the radiative properties of the non gray gas in the enclosure. The energy balance equations are applied for each gas, and surface zones, and by solving these equations, both the temperature, and the heat flux are found.

   Good degree of accuracy has been obtained, when comparing the results obtained by the simulation with the data of the designing company, and the data obtained by the zonal method. In

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Simulation the Radiation Zone of Al-Mussaib Power Plant by using Monte Carlo Method
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Publication Date
Thu Oct 20 2016
Journal Name
Sociological Methods & Research
Mean Monte Carlo Finite Difference Method for Random Sampling of a Nonlinear Epidemic System
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In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

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Publication Date
Thu Jun 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Theoretical Calculations of the Electron Transport Parameters in CH4-Ar and CH4-Ne Mixtures Gases Using Monte Carlo Method
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    The result of concentration varying of mixture methane with argon and neon gas are believed to study the change in electrons energy distribution function and then the change of the electrons transport parameters including the drift velocity, the mean energy, characteristics energy and diffusion coefficient. In the present work,a contemporary developed computer, simulation program known as Bolsig+ is being used for calculating the electron transport parameters.
 

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
monte carlo simulation in the kinetics and mileculare
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The primary focus of the study factor reverse polymerization styrene polymer kinetics and distribution weight Aljaia in Blma Aldhur free reverse The study was conducted wi Mamahakah and using the Monte Carlo method

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Monte Carlo Simulation of the Backscattering Gamma Ray System
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A Monte Carlo simulation has been used to design program which simulate gamma rays backscattering system. Gamma ray backscattering is very important to get useful information about shielding, absorption and counting problems. Simulation was done of a 661.6 KeV from a collimated point source of 137Cs. When increasing the scattering angle of photon which emerging from Iron target , as the incident gamma beam angles of 15°, 45° and 75°, the results showed that the single scattering count decreases. Whereas, this count increased by increasing the incident angle. In addition, the single scattering peak (count) increases according to the sample thickness until „saturation thickness‟. Our simulation results are useful to evaluate the opt

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Reliability Estimation for the Exponential Distribution Based on Monte Carlo Simulation
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        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

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Publication Date
Sat Sep 30 2023
Journal Name
Al–bahith Al–a'alami
Interactivity on the Website of Monte Carlo International Radio Regarding Iraqi Topics
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This research aims to identify the means and forms of interactive communication concerning Iraqi topics on the websites of global radio stations, namely Sawa and Monte Carlo. It also seeks to uncover the editorial and artistic interactions related to Iraqi topics on the selected websites chosen as the research sample, comparing them with the editorial interaction within the Iraqi context between the Radio Monte Carlo and Sawa websites.
The research yields several conclusions, including the following:
Iraqis focus their interaction with topics related to Iraq on Facebook for both Radio Monte Carlo and Sawa; Arabs show higher levels of interaction on Twitter with Radio Monte Carlo; Participants on the webs

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Sensors
Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review
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The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages

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