Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

This study aimed for isolation and identification of Candida glabrata and identifying some virulence factors. The distribution of patients with candidemia thrush showed that the age group 50-65 years old recorded the highest incidence of candidiasis in female and male with leukemia by 50% and 37.9 % respectively compared to the lowest incidence of candidiasis in the age group under 17 years old in female and male 8.8% and 13.5%, respectively. While the age group between 5-8 years was high, reaching 18 cases of oral candidiasis and 42% of children with leukemia compared with the age group, which was the least, that reached 9 cases, 21%. The highest incidence of C. glabrata was 59 isolates of females and males with leukemia, while C. kefyer w

The subject of this study is one of the most interactive media networks, which is the Instagram.The study uses a descriptive approach and focuses on how Instagram turns from a media tool to a marketing tool. The study problematic consists of this question: How Instagram turns to a marketing tool, and what are the advantages and the disadvantages for that?This study highlights the definition of Instagram, the creation of it and its improvement, the Instagram in Bahrain, the Instagram uses, the Instagram as a marketing tool, and the advantages and disadvantages of using Instagram for marketing.The study confirms that Instagram is a new media network, and focuses on how it develops on later stages and mentions the increase of the percentage

The present work aims to investigate approaches, measures and detection of indoor radon level in buildings of the department of physics in college of science of Baghdad University. CR-39 solid state nuclear track detectors were used to measure the radon concentrations inside the rooms, including five laboratories and five workplace rooms in ground and first storey of the department. The average radon concentration at first storey was found to be 43.1±13.2 Bq/m3 and 40.1±13.4 Bq/m3 at the ground storey. The highest level of radon concentration at the first storey in the radioactive sources store was 87.5±29 Bq/m3 while at the ground storey in room(2) was 70.2±24 Bq/m3 which is due to the existence radioactive sources in some selected

synthesis, Composition, Spectral, Geometry and Antibacterial Applications ofMn(||),Ni(||),Co(||),Cu(||) and Hg(||) schiff Base complexes of N2O2 mixed donor with 1,10-phenanthroline