Vagrancy is global problem, but its geographical distribution differs from one society
to another and from one place to another inside the same society.Till now there isn't a real factor that can explain the phenomenon, spite that economy plays aconstituent and distinguishing part, and spite the fact that Vagrancy is considered a realdeviation that can be compared with criminality level, and cannot be separated from its effecton family, local society and school. In addition to unprecedented work under heavily pressurethat attack to a minimum protection and safety. Vagrant may be a child, a teen, a young, or
even an old man. Vagrancy thus means different people with different ages and not onlyprecisely children. Vagrant is not neces

  In this study a DFT calculation on cyclopropanone, cyclopropandione and cyclopropantrione molecules was performed using the basis function 6-31G ** / MP2 and exchange correlation potential B3-LYP. The results showed that the ground state of all molecules geometry belong to the point group 𝐶2𝑣where a vibronic coupling between the vibrational motion with the electronic ground state in the molecule C3O3 this leads to a reduction in symmetry of the molecule from𝐷3â„Žto 𝐶2𝑣, the driving force of this process is accessing to the electronic configuration complies with Hückel aromatic systems with two electrons. Also in this, study the normal modes of vibration, frequencies, intensities and symm

This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.

Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

In this paper, first we   refom1Ulated   the finite   element  model

(FEM)   into   a   neural   network   structure   using   a   simple   two   - dimensional problem. The structure of this neural network is described

, followed  by its   application   to   solving  the forward    and  inverse problems. This model is then extended to the general case and the advantages and  di sadvantages  of  this  approach  are  descri bed  along with an analysis  of  the sensi tivity   of

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

The present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar

This research investigated the effectiveness of using different thickness values of polyimide (PI) interfacial layer in order to improve electrical and thermal properties of Al/ PI /c-Si capacitor. The PI spectra produced by poly(amic acid) (PAA) were characterized by using FT-IR analysis. After imidization of PAA, some absorption peaks vanished, whereas PI peaks appeared, due to the complete conversion of PAA to PI.

    The results show that thermal decomposition resistance of polyimide films increases with the increase of polyimide thickness, because of the increase of the imide bond and the decrease of the average distance between amide groups.