The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

  Powder Silica (SiO2) was added to epoxy polymer with different weight percentages  (3.75,7.5,11.25 and 15 wt%) for particle size ï‚£ 63 µm. Hand lay-up method it is used to prepared (Epoxy-Silica) composite, and cutting appropriate specimens for testing. Electrical strength varies nonlinearly with specimens thickness, also decreasing with average time for the rise of voltage decreases due to electro thermal effects. Clearly, electrical strength decreases with the increase of the proportion of added silica. The hardness, tensile strength and young modulus increased with the added silica increases due to changing in material characteristics from ductility to brittle. Microscopic cracks and irregularity deformation were a

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

An    Experimental     comparison     between     the     current-voltage

characteristic and    the  efficiency    conversion from  solar  to  electric energy   were studied  for square  and circular  single crystal  silicon  solar

cell of equal area (35.28  cm2)  . The results show  that the solar shape is

an  important factor  in  calculating the  current-voltage characteristics and  efficiency of  the  solar  cell.  It was  shown   that  the  performance effici

The research aims to explain the References of receiving the explicit and implicit knowledge mentioned in the Noble Qur'an. The two researchers adopted the documentary and inductive approach to study the topic. Among the conclusions of the research: The Noble Qur'an dealt with many terms and concepts that refer to the References of making explicit knowledge available, including books, which were represented by the divine books (the Qur'an, the Torah, the Zabur and the Gospel) and their concepts (the book, the Qur'an, the guidance, the remembrance, the revelation, the light, the newspapers, the plates). He dealt with many concepts that refer to the References of providing tacit knowledge, which was represented by the communication between tw

Abstract
The research aims to build a training program to develop some executive functions for kindergarten children. To achieve this goal, the two researchers built the program according to the following steps:
1. Determining the general objective of the program.
2. Determining the behavioral objectives of the program.
3. Determining the included content in the program.
4. Implementing the content of the activities of the program.
5. Evaluating the Program.
The program included (12) training activities, the training activities included several items: the title of the activity, the time of implementation of the activity, the general objective of the activity, the procedural behavioral objective, the means and tools u

Sliding Mode Controller (SMC) is a simple method and powerful technique to design a robust controller for nonlinear systems. It is an effective tool with acceptable performance. The major drawback is a classical Sliding Mode controller suffers from the chattering phenomenon which causes undesirable zigzag motion along the sliding surface. To overcome the snag of this classical approach, many methods were proposed and implemented. In this work, a Fuzzy controller was added to classical Sliding Mode controller in order to reduce the impact chattering problem. The new structure is called Sliding Mode Fuzzy controller (SMFC) which will also improve the properties and performance of the classical Sliding Mode control

In some cases, surgeons need to navigate through the computer system for reconfirmation patients’ details and unfortunately surgeons unable to manage both computer system and operation at the same time. In this paper we propose a solution for this problem especially designed for heart surgeon, by introducing voice activation system with 3D visualization of Angiographic images, 2D visualization of Echocardiography processed video and selected patient’s details. In this study, the processing, approximation of the 3D angiography and the visualization of the 2D echocardiography video with voice recognition control are the most challenging work. The work involve with predicting 3D coronary three from 2D angiography image and also image enhan