The fractional order partial differential equations (FPDEs) are generalizations of classical partial differential equations (PDEs). In this paper we examine the stability of the explicit and implicit finite difference methods to solve the initial-boundary value problem of the hyperbolic for one-sided and two sided fractional order partial differential equations (FPDEs). The stability (and convergence) result of this problem is discussed by using the Fourier series method (Von Neumanns Method).

Two of the main advantages of segmental construction are economics, as well as the rapid construction technique. One of the forms of segmental construction, for structural elements, is the segmental beams that built-in short sections, which referred to segments. This research aims to exhibit a new technique for the fabrication of short-span segmental beams from wedge-shaped concrete segments and carbon fiber reinforced polymers (CFRP) in laminate form. The experimental campaign included eight short-span segmental beams. In this study, two selected parameters were considered. These parameters are; the number of layers of CFRP laminates and the adhesive material that used to bond segments to each other, forming short-span segmental be

The main objective of this study is to introduce a systematic design procedure for short-span segmental beams following a sophisticated ACI 440.2R-17 design procedure. The general aspects of innovative short-span segmental beams are easy to fabricate, economical and rapidly placed in pre-specified positions. Short-span segmental beams fabricated from individual precast plain-concrete blocks and CFRP plates. Recently, experimental tests performed on short-span segmental beams, by the authors, investigated CFRP plate-bonding, CFRP plate cross-sectional area, the thickness of plate-bonding epoxy resin, surface-to-surface condition of concrete blocks, as well as, interface condition of the bonding surface. The experimental program comprises tes

In this paper, the path of the extracted and focused ions by the electrostatic lense having three electrodes of the same size and shape have been studied. However, the first and third electrodes had a different potential from the second electrode and the distance between any three electrodes was (d).The beams of the charged particles were controlled by using electrostatic fields which are used for accelerating and focusing. This paper focuses also on the effect of electrodes potentials on ion beam focusing. It is found that the best focusing was achieved when the values of the potential of the first and third electrode are equal to half of the value of the second electrode. Concerning transmiting and acumulating the ions beams, the study sh

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

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re