Petroleum is one of the most important substances consumed by man at present times, a major energy source in this century, petroleum oils can cause environmental pollution during various stages of production, transportation, refining and use, petroleum hydrocarbons pollutions ranging from soil, ground water to marine environment, become an inevitable problem in the modern life, current study focused on bioremediation process of hydrocarbons contaminants that remaining in the bottom of gas cylinders and discharged to the soil. Twenty-four bacterial isolates were isolated from contaminated soils all of them gram negative bacteria, bacterial isolates screening to investigate the ability of biodegradation of hydrocarbons, these isolates inocula

This study focuses on diagnosis of Candida species causing Vulvovaginal Candidiasis using phenotype and genotype analyzing methods, and frequencies of candida species also using Vulvovaginal Candidiasis patients. 130 samples (100 from patients and 30 from non infected women) were collected and cultured on biological media. Identifying the yeasts, initially some phenotypic experiments were carried out such as germ tube, from motion of pseudohyphae and clamydospores in CMA+TW80 medium, API20 candida and CHROMagar Candida. Genomic DNA of all species were extracted and analyzed with PCR and subsequent Polymerase Chain Reaction - Restriction Fragments Length Polymorphism (PCR-RFLP) methods. Frequency of C. albicans, C. krusei, C. tropicalis , C.

سها علي حسين, هويدة إسماعيل إبراهيم, Journal of Physical Education, 2017 - Cited by 1

Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

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