One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our cameras system to capture the images and upload them to the Amazon Simple Storage Service (AWS S3) cloud. Then two detectors were running, Haar cascade and multitask cascaded convolutional neural networks (MTCNN), at the Amazon Elastic Compute (AWS EC2) cloud, after that the output results of these two detectors are compared using accuracy and execution time. Then the classified non-permission images are uploaded to the AWS S3 cloud. The validation accuracy of the offline augmentation face detection classification model reached 98.81%, and the loss and mean square error were decreased to 0.0176 and 0.0064, respectively. The execution time of all AWS cloud systems for one image when using Haar cascade and MTCNN detectors reached three and seven seconds, respectively.
This research aimed at recognizing the properties of curricula that fitted to preeminent and talent students. Many types of these curricula were exposed, enrichment curriculum was explained as one of alternatives of available curricula.
The research used the analytical methodology for local and international literature in the field of preeminent and talent education to meet the properties of curricula that fitted to this special group of students. Many results was obtained as:
• This type of school enrichment curriculum consists of three levels( general discovery activities, individual and groups training activities, and individual or groups real problems).
• Investigation the effectively both sides of brain: right and left,
The approach of greening existing buildings, is an urgent necessity, because the greening operation provides the speed and optimal efficiency in the environmental performance, as well as keeping up with the global green architecture revolution. Therefore, greening existing buildings in Iraq is important for trends towards renewable energies, because of what the country went through economic conditions and crises and wars which kept the country away from what took place globally in this issue. The research problem is: insufficient knowledge about the importance and the mechanism of the greening of existing buildings, including its environmental and economic dimensions, by rationalization of energy consumption and preservi
... Show MoreAs the bit rate of fiber optic transmission systems is increased to more than , the system will suffer from an important random phenomena, which is called polarization mode dispersion. This phenomenon contributes effectively to: increasing pulse width, power decreasing, time jittering, and shape distortion. The time jittering means that the pulse center will shift to left or right. So that, time jittering leads to interference between neighboring pulses. On the other hand, increasing bit period will prevent the possibility of sending high rates. In this paper, an accurate mathematical analysis to increase the rates of transmission, which contain all physical random variables that contribute to determine the transmission rates, is presen
... Show MoreReducing the drag force has become one of the most important concerns in the automotive industry. This study concentrated on reducing drag through use of some external modifications of passive flow control, such as vortex generators, rear under body diffuser slices and a rear wing spoiler. The study was performed at inlet velocity (V=10,20,30,40 m/s) which correspond to an incompressible car model length Reynolds numbers (Re=2.62×105, 5.23×105, 7.85×105 and 10.46×105), respectively and we studied their effect on the drag force. We also present a theoretical study finite volume method (FVM) of solvi
Acquisition provisions in Islamic jurisprudence
In this paper, 3D simulation of the global coronal magnetic field, which use observed line of sight component of the photosphere magnetic field from (MDI/SOHO) was carried out using potential field model. The obtained results, improved the theoretical models of the coronal magnetic field, which represent a suitable lower boundary conditions (Bx, By, Bz) at the base of the linear force-free and nonlinear force free models, provides a less computationally expensive method than other models. Generally, very high speed computer and special configuration is needed to solve such problem as well as the problem of viewing the streamline of the magnetic field. For high accuracy special mathematical treatment was adopted to solve the computation comp
... Show MoreTime series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ
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In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach
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