The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

In recent years, the rapid development in the field of wireless technologies led to the appearance of a new topic, known as the Internet of things (IoT). The IoT applications can be found in various fields of our life, such as smart home, health care, smart building, and etc. In all these applications, the data collected from the real world are transmitted through the Internet; therefore, these data have become a target of many attacks and hackers. Hence, a secure communication must be provided to protect the transmitted data from unauthorized access. This paper focuses on designing a secure IoT system to protect the sensing data. In this system, the security is provided by the use of Lightweight AES encryption algorithm to encrypt the d

A new blind restoration algorithm is presented and shows high quality restoration. This
is done by enforcing Wiener filtering approach in the Fourier domains of the image and the
psf environments

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

n this study, data or X-ray images Fixable Image Transport System (FITS) of objects were analyzed, where energy was collected from the body by several sensors; each sensor receives energy within a specific range, and when energy was collected from all sensors, the image was formed carrying information about that body. The images can be transferred and stored easily. The images were analyzed using the DS9 program to obtain a spectrum for each object,an energy corresponding to the photons collected per second. This study analyzed images for two types of objects (globular and open clusters). The results showed that the five open star clusters contain roughly t

Rice is a major staple food for more than two thirds of the world population. Pathogenesis-related proteins-10 (PR10) have a range of 154 to 163 amino acid with molecular weight ~ 17 kDa.  They are acidic and generally intracellular and cytosolic proteins accumulate in plants in response to biotic and abiotic stresses. In the present study, a PR10 gene and its corresponding protein were characterized in O. sativa, O.  barthii, O. glaberrima, O. glumipatula, O. meridionalis, O. nivara, O. rufipogon and  O. punctata. The results revealed a narrow range of variation at both DNA and protein levels in all examined species except O. glumipatula. The latter showed a relatively

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin