In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

In real conditions of structures, foundations like retaining walls, industrial machines and platforms in offshore areas are commonly subjected to eccentrically inclined loads. This type of loading significantly affects the overall stability of shallow foundations due to exposing the foundation into two components of loads (horizontal and vertical) and consequently reduces the bearing capacity.

Based on a numerical analysis performed using finite element software (Plaxis 3D Foundation), the behavior of model strip foundation rested on dry sand under the effect of eccentric inclined loads with different embedment ratios (D/B) ranging from (0-1) has been explored. The results display that, the bearing capacity of st

Quantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee

      This research concern to analyse and simulate the temperature distribution in the spot welding joints using tungsten arc welding shielded with inert gas (TIG Spot) for the aluminum-magnesium alloy type  (5052-O).

      The effect of and the quantity of the heat input that enter the weld zone has been investigated welding current, welding time and arc length on temperature distribution. The finite element method (by utilizing programme ANSYS 5.4) is presented  the temperature distribution in a circular weld pool and the weld pool penetration (depth of welding) through the top sheet ,across the interface into the lower sheet forming a weld spot.   &nbs