A series of coordination compounds of Zr(IV), Cd(II) and Sn(II) ions with 4-(((3-mercapto-5-phenyl-4H-1,2,4-triazole-4-yl)imino)methyl)-2-methoxyphenol, as a ligand has been successfully prepared in alcoholic medium. The prepared complexes were characterized quantitatively and qualitatively by using: elemental analysis CHNS, FT-IR spectroscopy, UV-visible spectroscopy, 1H and 13CNMR, atomic absorption measurements, magnetic susceptibility, thermal analysis)TG and DTG) and conductivity measurements. This ligand coordinates as a bidentate that to the metal ions through sulphur and nitrogen of (azomethine group) atoms. According to the spectral data, Cd(II)- and Sn(II)-complexes have coordination of 6 with octahedral geometry while the Zr(I

يناقش هذا البحث مشكلة التعدد الخطي شبه التام في انموذج الانحدار اللاخطي ( انموذج الانحدار اللوجستي المتعدد) ، عندما يكون المتغير المعتمد متغير نوعيا يمثل ثنائي الاستجابة اما ان يساوي واحد لحدوث استجابة او صفر لعدم حدوث استجابة ، من خلال استعمال مقدرات المركبات الرئيسية التكرارية(IPCE)  التي تعتمد على الاوزان الاعتيادية والاوزان البيزية الشرطية .

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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

   Integration of laminar bubbling flow with heat transfer equations in a novel internal jacket airlift bioreactor using microbubbles technology was examined in the present study. The investigation was accomplished via Multiphysics modelling to calculate the gas holdup, velocity of liquid recirculation, mixing time and volume dead zone for hydrodynamic aspect. The temperature and internal energy were determined for heat transfer aspect.

   The results showed that the concentration of microbubbles in the unsparged area is greater than the chance of large bubbles with no dead zones being observed in the proposed design.  In addition the pressure, due to the recirculation velocity of liquid around the draft