This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method to complete one cycle of LHS-FD simulation iteration. This process is repeated until [Formula: see text] final iterations of LHS-FD are obtained. The means of these [Formula: see text] final solutions (MLHFD solutions) are tabulated, graphed and analyzed. The numerical simulation results of MLHFD for the SEIR model are presented side-by-side with deterministic solutions obtained from the classical FD scheme and homotopy analysis method with Pade approximation (HAM-Pade). The present MLHFD results are also compared with the previous non-deterministic statistical estimations from 1995 to 2015. Good agreement between the two is perceived with small errors. MLHFD method can be used to predict future behavior, range and prediction interval for the epidemic model solutions. The expected profiles of the cocaine abuse subpopulations are projected until the year 2045. Both the statistical estimations and the deterministic results of FD and HAM-Pade are found to be within the MLHFD prediction intervals for all the years and for all the subpopulations considered.
The prepared nanostructure SiO2 thin films were densified by two techniques (conventional and Diode Pumped Solid State Laser (DPSS) (532 nm). X-ray diffraction (XRD), Field Emission Scanning electron microscopy (FESEM), and Atomic Force Microscope (AFM) technique were used to analyze the samples. XRD results showed that the structure of SiO2 thin films was amorphous for both Oven and Laser densification. FESEM and AFM images revealed that the shape of nano silica is spherical and the particle size is in nano range. The small particle size of SiO2 thin film densified by DPSS Laser was (26 nm) , while the smallest particle size of SiO2 thin film densified by Oven was (111 nm).
Receipt date:6/3/2021 acceptance date:4/5/2021 Publication date:31/31/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
The research in the role of variables contact for non-state actors have become more influential in the current of contemporary events, that related with the reality of seeking services and providing all of that in favor of maintaining the social peace, and ensuring its empowerment in order to make peace and stability outcomes as a real fa
... Show MoreThe investment government expenditure is considered the fundamental of enhancing the economic activity as it has become a mean for achieving capital accumulation in all economic sectors, The Iraqi economy is characterized of being yield unilateral depending petroleum revenues as an essential resource of financing government expenditure , as the contribution of petroleum sector in GDP is large in proportions to other economic sectors contribution.
The relationship between investing government expenditure, and non-oil GDP is about to be not existent during the
... Show MoreA general velocity profile for a laminar flow over a flat plate with zero incidence is obtained by employing a new boundary condition to the other available boundary conditions. The general velocity profile is mathematically simple and nearest to the exact solution. Also other related values, boundary layer thickness, displacement thickness, momentum thickness and coefficient of friction are nearest to the exact solution compared with other corresponding values for other researchers.
A general velocity profile for a laminar flow over a flat plate with zero incidence is obtained by employing a new boundary condition to the other available boundary conditions. The general velocity profile is mathematically simple and nearest to the exact solution. Also other related values, boundary layer thickness, displacement thickness, momentum thickness and coefficient of friction are nearest to the exact solution compared with other corresponding values for other researchers.
In this study, the use of non-thermal plasma theory to remove toxic gases emitted from a vehicle was experimentally investigated. A non-thermal plasma reactor was constructed in the form of a cylindrical tube made of Pyrex glass. Two stainless steel rods were placed inside the tube to generate electric discharge and plasma condition, by connecting with a high voltage power supply (up to 40 kV). The reactor was used to remove the contaminants of a 1.25-liter 4-cylinder engine at ambient conditions. Several tests have been carried out for a ranging speed from 750 to 4,500 rpm of the engine and varying voltages from 0 to 32 kV. The gases entering the reactor were examined by a gas analyzer and the gases concentration ratio
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This study aimed to explore self and public stigma towards mental illness and associated factors among university students from 11 Arabic‐speaking countries. This cross‐sectional study included 4241 university students recruited from Oman, Saudi Arabia, the United Arab Emirates (UAE), Syria, Sudan, Bahrain, Iraq, Jordan, Lebanon, Palestine and Egypt. The participants completed three self‐administrative online questionnaires—Demographic Proforma (age, gender, family income, etc.), Peer Mental Health Stigmatization Scale and Mental Health Knowledge Questionnaire. There was a significant difference in the average mean between the 11 countries (
Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
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