This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

Toxoplasmosis is a parasitic infection that triggers immune cells to produce cytokines and inflammatory mediators that are responsible for abnormal or aborted immune responses. This study highlights the evaluation of the Dectin-1 receptor and cytokine IL-37 in the serum of 80 patients who had miscarried in the first trimester and were infected with toxoplasmosis, as well as 40 pregnant women in the first trimester who had a successful pregnancy (control groups). The serum was first screened for the T. gondii IgM and IgG antibodies by an enzyme-linked immunosorbent assay (ELISA) and then the serum levels of IL-37 and Dectin-1 were determined. The results showed that the serum level of Dectin-1 was significantly increased in anti-

High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

Moisture damage is described as a reduction in stiffness and strength durability in asphalt mixtures due to moisture. This study investigated the influence of adding nano silica (NS) to the Asphalt on the moisture susceptibility of hot-mix-asphalt (HMA) mixtures under different aging conditions. NS was mixed with asphalt binder at concentrations of 2%, 4%, and 6% by weight of the binder. To detect the microstructure changes of modified Asphalt and estimate the dispersion of NS within the Asphalt, the field emission scanning electron microscope (FE-SEM) was used. To examine the performance of Asphalt mixed with NS at different aging stages (short-term and long-term aging), asphalt mixture tests such as Marshall stability,

single and binary competitive sorption of phenol and p-nitrophenol onto clay modified with
quaternary ammonium (Hexadecyltrimethyl ammonium ) was investigated to obtain the
adsorption isotherms constants for each solutes. The modified clay was prepared from
blending of local bentonite with quaternary ammonium . The organoclay was characterized
by cation exchange capacity. and surface area. The results show that paranitrophenol is
being adsorbed faster than phenol . The experimental data for each solute was fitted well with
the Freundlich isotherm model for single solute and with the combination of Freundlich-
Langmuier model for binary system .

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every