This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

The design of future will still be the most confusing and puzzling issue and misgivings that arouse worry and leading to the spirit of adventures to make progress and arrive at the ways of reviving, creativity and modernism. The idea of prevailing of a certain culture or certain product in design depends on the given and available techniques, due to the fact that the computer and their artistic techniques become very important and vital to reinforce the image in the design. Thus, it is very necessary to link between these techniques and suitable way to reform the mentality by which the design will be reformed, from what has been said, (there has no utilization for the whole modern and available graphic techniques in the design proce

Nonlinear diffraction patterns can be obtained by focusing a laser beam through a thin slice of the material. Here, we investigated experimentally the formation of the far field nonlinear diffraction patterns of cw laser beam at 532 nm passing through a quartz cuvette containing multi-wall carbon nanotubes (MWCNT's) suspended in acetone and in DI water at concentrations of 0.030.wt.%, 0.045 wt.%, 0.060 wt.%, and 0.075 wt.%. Our results show that increasing the concentration of both types of suspensions (MWCNTs in acetone and MWCNTs DI water) led to increase in the number of pattern rings which indicates an increase in their nonlinear refractive indices. Moreover, MWCNTs DI water suspension at a concentration of 0.075 wt. % was more effic

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

ZnO organic hybrid junction (electroluminescence EL device) was fabricated using phase segregation method. ZnO-nanoparticle (NPs) was prepared as a colloidal by self–assembly method of Zinc acetate solution with KOH solution. Nanoparticle is employed to form organic-inorganic hybrid film and generate white light emission, while N,N’–diphenyl-N,N’ –bis(3-methylphenyl)-1,1’-biphenyl 4,4’-diamine (TPD) and polymethyl methacrylate (PMMA) are adopted as the organic matrices. ZnO NPs was used to fabricate TPD: PMMA: ZnO NPs hybrid junction device. The photoluminescence (PL) and electroluminescence (EL) spectra of the TPD: PMMA: ZnO NPs hybrid device provided a broad emission band covering entirely the visible spectrum (∼350-∼700

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121