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

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

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

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

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

هدف ال الأسلوب المعرفيّ 􀇼 م الإد ا ركيّ 􀥽 اضة للبنات، والتعرّف على علاقة التنظ 􀈄 ة وعلوم الر 􀥽 ة البدنّ 􀥽􀈃 ة التر 􀥽 لّ 􀘗 ة في 􀥽 ات المرحلة الثانّ 􀥼 طال إنّه 􀇼 احثتان 􀥼 اضة للبنات، وأفترضت ال 􀈄 ة وعلوم الر 􀥽 ة البدنّ 􀥽􀈃 ة التر 􀥽 ل􀘗 ة في 􀥽 ات المرحلة الثان 􀥼 عض طال 􀇼 التأمّليّ الاندفاعيّ لدى اس الأسلوب المعرفيّ التأمّليّ الاندفاعيّ لدى عیّنة 􀥽 م الإد ا ركيّ ونتائج مق 􀥽 اس التنظ 􀥽 ة بین نتائج مق

هدف البحث الى التعرف على القياس المحاسبي عن التنمية المستدامة، وبيان العلاقة بين القياس المحاسبي عن التنمية المستدامة وتقارير الابلاغ المالي، وكذلك بيان أثر القياس المحاسبي عن الاستدامة على تقارير الإبلاغ المالي في الشركة العامة للمنتوجات الغازية، وقد تمحورت مشكلة البحث في بيان أثر عناصر المحاسبة عن التنمية المستدامة، البيئية، والاجتماعية، والاقتصادية، على تقارير الإبلاغ المالي في الشركة العامة للمنتو