This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

Data security is a fundamental parameter on communication system development. The capability of protecting and securing the information is a great essence for the growth of the data security and electronic commerce. The cryptography has a significant influence upon information security systems against the variety of the attacks, in which higher complexity in secret keys results in the increase of security and the cryptography algorithms’ complexity. The sufficient and newer cryptographic methods’ versions may helpful in the reduction of the security attacks. The main aim of this research is satisfying the purpose of the information security through the addition of a new security level to the Advanced Encryption Standard (AES) algorithm

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O

A simulated ion/electron optical transport and focusing system has been put forward to
be mounted on high voltage transmission electron microscope for in situ investigations.
The suggested system consists of three axially symmetric electrostatic lenses namely an
einzel lens, an accelerating immersion lens, and a decelerating immersion lens, in addition
to an electrostatic quadrupole doublet lens placed on the image side. The electrodes
profile of these lenses is determined from the proposed axial field distributions. The
optical properties of the whole system have been computed together with the trajectory of
the accelerated charged-particles beam along the optical axis of the system. The computed
dimensions of th

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se