In order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.

This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)

COVID-19 is a coronavirus disease caused by the severe acute respiratory syndrome. According to the World Health Organization (WHO), coronavirus-2 (SARS-CoV-2) was responsible for 87,747,940 recorded infections and 1,891,352 confirmed deaths as of January 9, 2021. Antibodies that target the Sprotein are efficient in neutralizing the virus. Methodology: 180 samples were collected from clinical sources (Blood and Nasopharyngeal swabs) and from different ages and genders at diverse hospitals in Baghdad / IRAQ between November 5, 2021, to January 20, 2022. All samples were confirmed infected with COVID-19 disease by RT-PCR technique. Haematology analysis and blood group were done for all samples, and Enzyme-Linked Immunosorbent Assay used an Ig

The study of cohomology groups is one of the most intensive and exciting researches that arises from algebraic topology. Particularly, the dimension of cohomology groups is a highly useful invariant which plays a rigorous role in the geometric classification of associative algebras. This work focuses on the applications of low dimensional cohomology groups. In this regards, the cohomology groups of degree zero and degree one of nilpotent associative algebras in dimension four are described in matrix form.

For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

A new blind restoration algorithm is presented and shows high quality restoration. This
is done by enforcing Wiener filtering approach in the Fourier domains of the image and the
psf environments

Rehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID

The design of safe pedestrian facilities usually depends on the assessment of pedestrian characteristics and behavior. In this investigation, pedestrian walking speed through the religious occasion have been monitored at three locations, Al- Kadhimiya (Imam AL-Kadim), Najaf and Karbala (Imam AL-Husain) holy shrines. Video captures of the pedestrian through their walking to the two holy shrines have been prepared and analyzed for walking speed, gender, age groups, and clothing tradition. The pedestrian sample size is 468, 501, and 447 for Al- Kadhimiya, Karbala, and Najaf respectively. When the gender is taken into consideration, it can be noted that the walking speed of male and female pedestrian is (0.97, 1.68, and 1.63

Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin