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

Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

ABSTRUCT

This research aims at examining the expected gap between the fact of planning and controlling process of production at the State Company for Electric Industries and implementation of material requirements planning system in fuzzy environment. Developing solutions to bridge the gap is required to provide specific mechanisms subject to the logic of fuzzy rules that will keep pace with demand for increased accuracy and reduced waiting times depending on demand forecast, investment in inventory to reduce costs to a minimum.

The proposed solutions for overcoming the research problem has required some  questions reflecting the problem with its multiple dimensions, which ar

The Boltzmann equation has been solved using (EEDF) package for a pure sulfur hexafluoride (SF6) gas and its mixtures with buffer Helium (He) gas to study the electron energy distribution function EEDF and then the corresponding transport coefficients for various ratios of SF6 and the mixtures. The calculations are graphically represented and discussed for the sake of comparison between the various mixtures. It is found that the various SF6 – He content mixtures have a considerable effect on EEDF and the transport coefficients of the mixtures

This paper presents the synthesis and study of some new mixed-ligand complexes containing anthranilic acid and amino acid phenylalanine (phe) with some metals . The resulting products were found to be solid crystalline complexes which have been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity . The proposed structure of the complexes using program , chem office 3D(2000) . The general formula have been given for the prepared complexes : [M(A-H)(phe-H)] M(II): Hg(II) , Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) . A = Anthranilic acid = C7H7NO2 Phe = phenylalanine = C9H11NO2

Thispaperpresentsthesynthesisandstudyofsomenewmixed-liagnd complexescontainingtowaminoacids[Alanine(Ala)andphenylalanine(phe)]withsome metals .Theresultsproductswerefoundtobesolidcrystallinecomplexeswhichhave been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity and solubiltyThe proposed structure of the complexes using program , chem office 3D(2000) .The general formula have been given for the prepared complexes :[M(A-H)(phe-H)]M(II): Hg , Mn ,Co , Ni , Cu ) , Zn , Cd(II) .Ala = Alanine acid = C3H7NO2Phe = phenylalanine = C9H11NO2

This paper presents the synthesis and study of some new mixed-liagnd complexes containing tow amino acids[Alanine(Ala) and phenylalanine (phe)] with some metals . The results products were found to be solid crystalline complexes which have been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity and solubilty The proposed structure of the complexes using program , chem office 3D(2000) . The general formula have been given for the prepared complexes : [M(A-H)(phe-H)] M(II): Hg , Mn ,Co , Ni , Cu ) , Zn , Cd(II) . Ala = Alanine acid = C3H7NO2 Phe = phenylalanine = C9H11NO2

This paper deals  with constructing mixed probability distribution  from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are (  .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β)  are estimated by three different methods, which are  maximum likelihood, and  Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.