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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
Fri Sep 09 2022
Journal Name
Research Anthology On Improving Medical Imaging Techniques For Analysis And Intervention
Groupwise Non-Rigid Image Alignment Using Few Parameters
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Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

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Publication Date
Sun Mar 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Estimation Liquid Permeability Using Air Permeability Laboratory Data
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Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas

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Publication Date
Thu Jan 21 2021
Journal Name
Recent Innovations In Chemical Engineering (formerly Recent Patents On Chemical Engineering)
Soap Production Using Vacuum Reactive Distillation: Batch Model
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Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Nurse Scheduling Problem Using Hybrid Simulated Annealing Algorithm
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Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Estimation of Bladder pressure by using poiseuilles equation
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Equation Boizil used to Oatae approximate value of bladder pressure for 25 healthy people compared with Amqas the Alrotinahh ways used an indirect the catheter Bashaddam and found this method is cheap and harmless and easy

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Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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Scopus
Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Produced Water Treatment Using Ultrafiltration and Nanofiltration Membranes
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The application of ultrafiltration (UF) and nanofiltration (NF) processes in the handling of raw produced water have been investigated in the present study. Experiments of both ultrafiltration and nanofiltration processes are performed in a laboratory unit, which is operated in a cross-flow pattern. Various types of hollow fiber membranes were utilized in this study such as poly vinyl chloride (PVC) UF membrane, two different polyether sulfone (PES) NF membranes, and poly phenyl sulfone PPSU NF membrane. It was found that the turbidity of the treated water is higher than 95 % by using UF and NF membranes. The chemical oxygen demand COD (160 mg/l) and Oil content (26.8 mg/l) were found after treatment according to the allowable limits set

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Microbubbles to Improve Transmission Oil in Pipes
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Drag reduction (DR) techniques are used to improve the flow by spare the flow energy. The applications of DR are conduits in oil pipelines, oil well operations and flood water disposal, many techniques for drag reduction are used. One of these techniques is microbubbles.  In this work, reduce of drag percent occurs by using a small bubbles of air pumped in the fluid transported. Gasoil is used as liquid transporting in the pipelines and air pumped as microbubbles. This study shows that the maximum value of drag reduction is 25.11%.

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Nonparametric Regression Function Using Canonical Kernel
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    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

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