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bsj-5159
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage and Selection Operator (Lasso), and Tikhonov Regularization (Ridge). The simulation studiesshow that the performance of our method is better than the othersaccording to the error and the time complexity. Thesemethodsare applied to a real dataset, which is called Rock StrengthDataset.The new approach implemented using the Gibbs sampler is more powerful and effective than other approaches.All the statistical computations conducted for this paper are done using R version 4.0.3 on a single processor computer.

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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
An Investigation Study of Thinning Distribution in Single Point Incremental Forming Using FEM Analysis
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Single Point Incremental Forming (SPIF) is a forming technique of sheet material based on layered manufacturing principles. The sheet part is locally deformed through horizontal slices. The moving locus of forming tool (called as toolpath) in these slices constructed to the finished part was performed by the CNC technology. The toolpath was created directly from CAD model of final product. The forming tool is a Ball-end forming tool, which was moved along the toolpath while the edges of sheet material were clamped rigidly on fixture.

This paper presented an investigation study of thinning distribution of a conical shapes carried out by incremental forming and the validation of finite element method to evaluate the limits of the p

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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

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Publication Date
Sun Nov 19 2017
Journal Name
Iraqi Journal Of Laser
Effects of Diode Laser 940 nm with and without 5 % Sodium Fluoride White Varnish with Tri-calcium Phosphate on Dentin Permeability (In vitro study)
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It is found that hypersensitive teeth have a larger number and wider patent tubules than those of non-sensitive teeth. Objective: The aim of this study is to compare between the effects of diode laser at different power densities, with and without sodium fluoride on the sealing of exposed dentinal tubules and dentin permeability. Materials and methods: 118 teeth were used. Samples were divided into three major groups. The first consisted of 100 teeth used for permeability test. The second consisted of 16 teeth for measuring external surface temperature elevation while irradiation. The third, in turn, consisted of one pair of teeth observed under SEM for dentine surface morphology analysis. Results: For dentin permeability measurement, th

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Study the Quality of Nasopharyngeal plans Using Evaluation Indexes of IMRT and VMAT Treatment planning Techniques
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Radiation treatment has long been the conventional approach for treating nasopharyngeal cancer (NPC) tumors due to its anatomic features, biological characteristics, and radiosensitivity. The most common treatment for nasopharyngeal carcinoma is radiotherapy. This study aimed to assess the better quality of radiotherapy treatment techniques using intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT). The VMAT and IMRT are comparative techniques. Forty patients with nasopharyngeal carcinoma and forwarded for radiotherapy were treated with both advanced techniques, IMRT and VMAT, using eclipse software from Varian. The x-ray energy was set at 6 MV. The total prescribed dose was 70 Gy. The results show that the

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Fri Apr 01 2022
Journal Name
Separation And Purification Technology
Application of central composite design approach for optimisation of zinc removal from aqueous solution using a Flow-by fixed bed bioelectrochemical reactor
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Publication Date
Fri Apr 01 2022
Journal Name
Separation And Purification Technology
Application of central composite design approach for optimisation of zinc removal from aqueous solution using a Flow-by fixed bed bioelectrochemical reactor
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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Hydrogen Energy
Improvement of bioenergy generation using innovative application of food waste materials for coating carbon nanotubes-loaded bioanode in 3D-microbial fuel cells
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Publication Date
Wed Feb 15 2023
Journal Name
Environmental Technology
Bio-synthesis of TiO<sub>2</sub> using grape leaves extract and its application for photocatalytic degradation of ibuprofen from aqueous solution
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