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bsj-2306
A Combinatorial Approach to Obtain the Yield Probability Distribution along a Linearly-Loaded Cantilever Beam
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The substantial key to initiate an explicit statistical formula for a physically specified continua is to consider a derivative expression, in order to identify the definitive configuration of the continua itself. Moreover, this statistical formula is to reflect the whole distribution of the formula of which the considered continua is the most likely to be dependent. However, a somewhat mathematically and physically tedious path to arrive at the required statistical formula is needed. The procedure in the present research is to establish, modify, and implement an optimized amalgamation between Airy stress function for elastically-deformed media and the multi-canonical joint probability density functions for multivariate distribution completion, so that the developed distribution is to exhibit a sophisticated illustration of yield probability distribution along a cantilever beam whose structure is subjected to a linearly-distributed load. This combinatorial approach is to clarify the intensity of the stresses exerted onto the beam, to standardize the terms of stresses and their affection and to convert them into a more significant depiction of a probability distribution.

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Publication Date
Wed Dec 01 2021
Journal Name
Iraqi Journal Of Physics (ijp)
Structural and Infrared Spectroscopy of Polyvinylpyrrolidone/Multi-walled Carbon Nanotubes Nanocomposite
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In this work, polyvinylpyrrolidone (PVP)/ Multi-walled carbon nanotubes (MWCNTs) nanocomposites were prepared with two concentrations of MWCNTs by casting method. Morphological, structural characteristics and electrical properties were investigated. The state of MWCNTs dispersion in a PVP matrix was indicated by Field Effect-Scanning Electron Microscopy (FESEM) which showed a uniform dispersion of MWCNTs within the PVP matrix. X-ray Diffraction (XRD) indicate strong bonding of carbonyl groups of PVP composite chains with MWCNTs. Fourier transfer infrared (FTIR) studies shows characteristics of various stretching and bending vibration bands, as well as shifts in some band locations and intensity changes in others. Hall effect was stu

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

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Publication Date
Tue Oct 30 2018
Journal Name
Civil Engineering Journal
Equivalent Modulus of Asphalt Concrete Layers
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A flexible pavement structure usually comprises more than one asphalt layer, with varying thicknesses and properties, in order to carry the traffic smoothly and safely. It is easy to characterize each asphalt layer with different tests to give a full description of that layer; however, the performance of the whole; asphalt structure needs to be properly understood. Typically, pavement analysis is carried out using multi-layer linear elastic assumptions, via equations and computer programs such as KENPAVE, BISAR, etc. These types of analysis give the response parameters including stress, strain, and deflection at any point under the wheel load. This paper aims to estimate the equivalent Resilient Modulus (MR) of the asphalt concrete

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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Publication Date
Sun Aug 06 2023
Journal Name
Journal Of Economics And Administrative Sciences
Probit and Improved Probit Transform-Based Kernel Estimator for Copula Density
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Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

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Publication Date
Sat Feb 15 2025
Journal Name
Iraqi Journal Of Science
Effect of Aluminum Dust Particles on Plasma Parameters at Different Gas Pressure with Different Dust Contents
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In this work, the effect of aluminum (Al) dust particles on the DC discharge plasma properties in argon was investigated. A magnetron is placed behind the cathode at different pressures and with varying amounts of Al. The plasma temperature (Te) and density (ne) were calculated using the Boltzmann equation and Stark broadening phenomena, which are considered the most important plasma variables through which the other plasma parameters were calculated. The measurements showed that the emission intensity decreases with increasing pressure from 0.06 to 0.4 Torr, and it slightly decreases with the addition of the NPs. The calculations showed that the ne increased and Te decreased with pressure. Both Te and ne were reduced by increasing

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Charge density distributions and electron scattering form factors of 25Mg, 27Al and 29Si nuclei
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An effective two-body density operator for point nucleon system
folded with the tenser force correlations( TC's), is produced and used
to derive an explicit form for ground state two-body charge density
distributions (2BCDD's) applicable for 25Mg, 27Al and 29Si nuclei. It is
found that the inclusion of the two-body TC's has the feature of
increasing the central part of the 2BCDD's significantly and reducing
the tail part of them slightly, i.e. it tends to increase the probability of
transferring the protons from the surface of the nucleus towards its
centeral region and consequently makes the nucleus to be more rigid
than the case when there is no TC's and also leads to decrease the
1/ 2
r 2 of the nucleu

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Publication Date
Fri Nov 30 2018
Journal Name
Oriental Journal Of Chemistry
Viscosity and Density Studies of Drugs in Aqueous Solution and in Aqueous Threonine Solution at 298.15 K
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Viscosities (η) and densities (ρ) of atenolol and propranolol hydrochloride in water and in concentrations (0.05 M) and (0.1 M) aqueous solution of threonine have been used to reform different important thermodynamic parameters like apparent molal volumes fv partial molal volumes at infinite dilution fvo , transfer volume fvo (tr), the slop Sv , Gibbs free energy of activation for viscous flow of solution ΔG*1,2 and the B-coefficient have been calculated using Jones-Dole equation. These thermodynamic parameters have been predicted in terms of solute-solute and solute-solvent interaction.

Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Microstructure properties of lead silicate glasses
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In the present work, lead silicate glasses have been prepared with
different amount of lead oxide content. Structure properties such as
X-ray diffraction, AFM, and FTIR analyses have been done. The
exceeding of PbO content more than 25wt% revealed a decreasing in
density. The X- ray revealed that the strongest peak related to
Hexagonal silica dioxide and the other crystal phases formed were
related to silica oxide (SiO2) and lead oxide (PbO). Growth and
decayed phases in X-ray have been observed with changing lead
oxide content. Homogeneous surface was obtained using AFM
analyzer with an average diameter around 100 nm. Infrared spectrum
is characterized by the presence of large absorption band between
120

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