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

BSTRACT: BACKGROUND: Acne vulgaris(AV)is chronic inflammatory disease of pilosebaceous unit of young people. Patients with acne with or with out scarring might differ in regard to their immunological background from those free from acne. OBJECTIVES: To evaluate the problem of facial AV especially patients with scarring and to determine the frequency of associated skin diseases and to be compared with acne free control. METHODS: A cross sectional randomized controlled epidemiological study was conducted from Oct.2005-Oct. 2006.Three hundred students from Basra University; 132 (44%) males and 168 (56%) females were enrolled, their ages ranged from 18-25 (20.9±1.8) years. They were divided into: Group A those free from acne (98 individuals),G

S Khalifa E, AH Khalil I, N Adil A, AB Razan A…, 2009

Chlopheniramine maleate ( CPM ) , is  one  of   the  H- receptor antagonist  ,  widely used  in allergic  diseases ,like skin rash  and  pruritis .CPM 3%w/w was successfully  loaded in  2%w/w  sodium alginate (SA)    as a gel    base ,  and  to be considered   as  a  selected  formula .It was found  that  the diffusion   of  CPM    through   the  skin  of  albino  rat   was     increased   as  the concentration  of  CPM  increased from 2 %w/w sodium alginate  ,  More

The process involved isolating E. faecium from the gut of honeybees, screening the bacterium for bacteriocin-like inhibitory substance (BLIS), evaluating its impact on the expression of the mexA gene in multidrug-resistant (MDR) P. aeruginosa, and determining the role of bacteriocin in treating infected wounds in mice through histopathological examination. After evaluating the best circumstances for producing BLIS, it was discovered that glucose was a superior carbon source and yeast extract was the best source of nitrogen. The pH was found to be 5, the ideal incubation time was 72 hours, and ammonium sulfate salt was used for partial purification at 80% saturation. The identification of MDR P. aeruginosa isolates from pus infection

In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod