In cognitive radio networks, there are two important probabilities; the first probability is important to primary users called probability of detection as it indicates their protection level from secondary users, and the second probability is important to the secondary users called probability of false alarm which is used for determining their using of unoccupied channel. Cooperation sensing can improve the probabilities of detection and false alarm. A new approach of determine optimal value for these probabilities, is supposed and considered to face multi secondary users through discovering an optimal threshold value for each unique detection curve then jointly find the optimal thresholds. To get the aggregated throughput over transmission

Background: The aim of this study was for estimation and comparism of masticatory efficiency in patient wearing heat cured acrylic and flexible base partial denture, finding out the role of peanuts and carrots on the measurement of chewing efficiency, and to find out whether the types of P.D. (being single or two opposing each other) has any effect on the masticatory performance. Materials and methods: Twenty partially edentulous patients were selected. Five of these patients were selected having Kennedy class I with no modification against natural dentition, other 5patients having Cl.I against Cl.I . The other 5 patients having Cl.III against natural dentition and the last 5 patients were with Cl.III against Cl.III. several ways were used

The permanent deformation of flexible pavement represent serious problem in hot climate region. Numerous efforts are devoted to mitigate this distress such as modifying asphalt binder by polymers. The present study demonstrate the effect of utilizing four types of polymers to reduce the permanent deformation, these polymers are Polyethylene Wax (PEW), Styrene Butadiene Rubber (SBR), Ethylene Propylene Dien Monomer (EPDM) and Ethylene Vinyl Acetate (EVA). The prepared mixtures composed of 4.9 % of 40/50 asphalt binder, 12.5 mm nominal aggregate maximum size and limestone dust as filler. The permanent and resilient strains have been recorded when the cylindrical specimens, 101.6 mm in diameter and 203.2 mm in height, tested by repeated loa

Soil-structure frictional resistance is an important parameter in the design of many foundation systems. The soil-structure interface area is responsible for load transferring from the structure to the surrounding soil. The mobilized shaft resistance of axially loaded, long slender pile embedded in dense, dry sand is experimentally and numerically analyzed when subjected to pullout force. Experimental setup including an instrumented model pile while the finite element method is used as a numerical analysis tool. The hypoplasticity model is used to model the soil adjacent to and surrounding the pile by using ABAQUS FEA (6.17.1). The soil-structure interface behavior depends on many factors, but mainly on the interface soi

Flexible pavement design and analysis were carried out in the past with semi-experimental methods, using elastic characteristics of pavement layers. Due to the complex interferences between various layers and their time consumption, the traditional pavement analysis, and design methods were replaced with fast and powerful methods including the Finite Element Method (FEM) and the Discrete Element Method (DEM). FEM requires less computational power and is more appropriate for continuous environments. In this study, flexible pavement consisting of 5 layers (surface, binder, base, subbase, and subgrade) had been analyzed using FEM. The ABAQUS (6.14-2) software had been utilized to investigate the influence of the base layer depth on ver

A new class of higher derivatives  for harmonic univalent functions defined by a generalized fractional integral operator inside an open unit disk E is the aim of this paper.

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

In this paper we use non-polynomial spline functions to develop numerical methods to approximate the solution of 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of these method, and to compare the computed results with other known methods.