Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Using the Internet, nothing is secure and as we are in need of means of protecting our data, the use of passwords has become important in the electronic world. To ensure that there is no hacking and to protect the database that contains important information such as the ID card and banking information, the proposed system stores the username after hashing it using the 256 hash algorithm and strong passwords are saved to repel attackers using one of two methods: -The first method is to add a random salt to the password using the CSPRNG algorithm, then hash it using hash 256 and store it on the website. -The second method is to use the PBKDF2 algorithm, which salts the passwords and extends them (deriving the password) before being ha

In the present paper, three reliable iterative methods are given and implemented to solve the 1D, 2D and 3D Fisher’s equation. Daftardar-Jafari method (DJM), Temimi-Ansari method (TAM) and Banach contraction method (BCM) are applied to get the exact and numerical solutions for Fisher's equations. The reliable iterative methods are characterized by many advantages, such as being free of derivatives, overcoming the difficulty arising when calculating the Adomian polynomial boundaries to deal with nonlinear terms in the Adomian decomposition method (ADM), does not request to calculate Lagrange multiplier as in the Variational iteration method (VIM) and there is no need to create a homotopy like in the Homotopy perturbation method (H

Sol-gel method was use to prepare Ag-SiO2 nanoparticles. Crystal structure of the nanocomposite was investigated by means of X-ray diffraction patterns while the color intensity was evaluated by spectrophotometry. The morphology analysis using atomic force microscopy showed that the average grain sizes were in range (68.96-75.81 nm) for all samples. The characterization of Ag-SiO2 nanoparticles were investigated by using Scanning Electron Microscopy (SEM). Ag-SiO2 NPs are highly stable and have significant effect on both Gram positive and negative bacteria. Antibacterial properties of the nanocomposite were tested with the use of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The results have shown antibacteri

In this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A comparison between numerical and experimental data, illustrated

The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli