A new series of morpholine derivative were prepared by reacting the morpholine with ethyl chloro acetate in the presence triethylamine as an catalyst and benzene as a solvent gave the ethyl morpholin-4-ylacetate reaction with hydrazine hydrate and ethanol as a solvent gave the 2-(morpholin-4-yl)acetohydrazide gave series of Schiff base were prepared by reacting 2-(morpholin-4- yl)acetohydrazide with different aromatic aldehydes and ketons . The new series of (3-9 )were synthesis by reaction of Schiff base (10-14) with chloroacetyl chloride, triethyl amine as an catalyst and 1,4dioxane as a solvent .The chemical structures of the synthesis compound were identified by spectral methods their [ IR ,1H-NMR and 13C-NMR ].The synthesised compoun

The present study aims to explore determinants of entrepreneurial behavior from perspective of social theory. It is based on model notions of (Tyler & Blader, 2003) which have focused on studying role of positively personal and social identity in motivating employees to practicing desired behavior which serves the organization in which they work. Based on these notions and previous literature, study model were built. This model explains the relationship between status judgments (perceived internal respect and perceived external prestige)  and entrepreneurial behavior. It includes three main hypotheses. The first and second hypothesis are concerning the relationship between status judgmen

There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network sim

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to