The use of antibiotics (AB) in surgery focused in either treating established infection or to prevent suspected post-operative infection. Inappropriate use of antibiotic for treatment of patients with common infections is a major problem worldwide, with great implications with regards to cost of treatment and development of resistance to the antimicrobial agent. Moreover, antibiotics may often be dispensed without a clear clinical indication. This study was conducted to estimate the medication errors in using antibiotic for surgery patients which may effect their wound healing. A 260 patients with clean-contaminated and contaminated surgery were included from two teaching hospitals, 160 patient from Medical city hospital and 100 from Al-

In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.

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

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

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

The present study addresses the behavior of gases in cultivation media as an essential factor to develop the relationship between the microorganisms that are present in the same environment. This relationship was explained via mass transfer of those gases to be a reasonable driving force in changing biological trends. Stripping and dissolution of oxygen and carbon dioxide in water and dairy wastewater were investigated in this study. Bubble column bioreactor under thermal control system was constructed and used for these processes. The experimental results showed that the removal of gases from the culture media requires more time than the dissolution. For example, the volumetric mass transfer coefficient for the removal