السياسة الروسية في الشرق الاوسط الكبير او (فن اقامة علاقات الصداقة مع كل دول العالم)

لقد أدت التطورات العلمية والتقنية وتطبيقاتها العملية في مختلف ميادين الحياة بشكل عام وميدان التربية والتعليم بشكل خاص إلى ظهور تغيرات في البناء التعليمي وطرائق التدريس بصيغتها الحديثة التي تنسجم في مجملها وروح العصر مما دعى المؤسسات التربوية والتعليمية وبإيعاز إلى الباحثين والمهتمين بهذا الميدان الى ضرورة متابعة الاتجاهات الحديثة ونواحي التجديد لمحتوى العملية التعليمية فيما يتعلق بالمجالات المعر

Most researchers concentrate their studies on the design, stress and pressure distributions of the prosthetic socket. A little attention is considered for the stiffness of the various materials of the prosthetic sockets. Prosthetic laminated sockets in Iraq are costly to be manufactured while polypropylene socket is relatively cheap in comparing with the laminates.

Experimental study is conducted to compare the stiffness of five prosthetic sockets made of different materials. Compression, three point flexural and tensile tests are implemented by the Testometric machine. The laminate sockets give better results in compression than polypropylene. Polypropylene gives good results in bending compared with the laminate sockets. When t

The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive convers

An overall mathematical model for copper pipe corrosion in flowing water was derived based on mass transfer fundamentals where we introduced the effects of boundary layer velocity, bulk flow velocity and the surface oxide protective film on the corrosion rate. A set of experiments were conducted in a straight 10mm diameter copper pipe, flow of water include six velocities of maximum value 7.33m/sec at 200C and 350C. The good agreement between the calculated and experimental corrosion rate values were achieved , the agreement reached 92% .

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented