Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

To produce Zinc Oxide NanoParticles, ZnO-NPs, different methods can be used. However, the utilization of Liquid-Phase Pulsed Laser Ablation, LP-PLA, methodology of three distinct environment of aqueous using pure zinc plate will be one of the approaches for this job. Thus, in this work, concentrates on the influence of the results after employing some changes on the environment in other words, the influence of the NPs size and/or the NPs availability/appearance. Cetyltrimethylammonium Bromide, CTAB, is one of the three surfactants that have been used in the water-based solution. That is, the Sodium Dodecyl Sulfate, SDS, besides the Distilled Water, DW, the three surfactants will be ready when the molarity of the DW is around 10− 3 M. Th

KE Sharquie, JR Al-Rawi, AA Noaimi, RA Al-Khammasi, Iraqi Journal of Community Medicine, 2018

KE Sharquie, HR Al-Hamamy, AA Noaimi, AF Tahir, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 2