Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

     The nuclear size radii, density distributions and elastic electron scattering charge form factors for Fluorine isotopes (17,19,20,24,26F) were studied using the radial wave functions (WF) of harmonic-oscillator (HO) potential and free mean field described by spherical Hankel functions (SHF) for the core and the valence parts, respectively for all aforementioned isotopes. The parameters for HO potential (size parameter ) and SHF were chosen to regenerate the available experimental size radii. It was found that using spherical Hankel functions in our work improved the calculated results quantities in comparison with empirical data.   

Nitrogen (N) is a key growth and yield-limiting factor in cultivated rice areas. This study has been conducted to evaluate the effects of different conditions of N application on rice yield and yield components (Shiroudi cultivar) in Babol (Mazandaran, Iran) during the 2015- 2016 season. A factorial experiment executed of a Randomized Complete Block Design (RCBD) used in three iterations. In the first factor, treatments were four N amounts (including 50, 90, 130, and 170 kg N ha^-1), while in the second factor, the treatments consisted of four different fertilizer splitting methods, including T₁:70 % at the basal stage + 30 % at the maximum tillering stage, T₂:1/3 at the basal stage + 1/3 at the maximum ti

Abstract

The study presents a mathematical model with a disaggregating approach to the problem of production planning of a fida Company; which belongs to the ministry of Industry. The study considers disaggregating the entire production into 3 productive families of (hydraulic cylinders, Aldblatt (dampers), connections hydraulics with each holds similar characteristics in terms of the installation cost, production time and stock cost. The Consequences are an ultimate use of the available production capacity as well as meeting the requirements of these families at a minimal cost using linear programming. Moreover, the study considers developing a Master production schedule that drives detailed material and production requi

Credit derivatives (CDs) have been increasingly acknowledged as an important requirement to hedge and transfer credit risk CR. Nonetheless, they have been extensively criticized for destabilizing the whole economic system bringing about the latest subprime credit crisis. The study’s main aim is to investigate the reason for the use of (CDs), whether it is used for hedging or trade purpose, for four of the US international financial institutions that had made it through the 2007 crisis to resume functioning post-crisis. This will be for three different and critical periods, namely the pre, during and after crisis periods (Q1, 2000-Q1, 2014). Adopting the SUR technique, the investigation of the factors that influence the net position of (CD

Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

The removal of commercial orange G dye from its aqueous solution by adsorption on tobacco leaves (TL) was studied in respect to different factor that affected the adsorption process. These factors including the tobacco leaves does, period of orange G adsorption, pH, and initial orange G dye concentration .Different types of isotherm models were used to describe the orange G dye adsorption onto the tobacco leaves. The experimental results were compared using Langmuir, and frundlich adsorption isotherm, the constants for these two isotherm models was determined. The results fitted frundlich model with value of correlation coefficient equal to (0.981). The capacity of adsorption for the orange G dye was carried out using various kinetic models

Reuse of spent hydrodesulphurization (HDS) of middle petroleum fractions catalyst CoMo/γAl₂O₃ was accomplished via removal of coke and contaminants such as vanadium, Iron, Nickel, and sulfur. Three processes were adopted; extraction, leaching, decoking. Soluble and insoluble coke was removed. Leaching step used three different solvents (oxalic acid, ammonium peroxydisulfate and oxalic acid + H₂O₂) in separate in order to remove contaminant metals (V, S, Ni and Fe).

   The effect of soluble coke removal on leaching step was studied. It was found that the removal of soluble coke significantly enhances the leaching of contaminants and barely affected the removal of active metals