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

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

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

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

في الدراسة الحالية، تم تصنيع جسيمات ZrO2 النانوية باستخدام مستخلص نباتي مشتق من نبات Vitex agnus castus، ووسط قلوي مثل هيدروكسيد الصوديوم. تم استخدام أسلوب التخليق الحيوي لتحضير جزيئات أوكسيد الزركونيوم النانوية لهذا المشروع البحثي. تتميز هذه الطريقة عن غيرها بسبب فعاليتها من حيث التكلفة وبساطتها وقلة المخاطر المحتملة. وتم تشخيص العينات المحضرة باستخدام المجهر الإلكتروني النافذ TEM، المجهر الإلكتروني الماسح SEM،

          In this paper, we have investigated some of the most recent energy efficient routing protocols for wireless body area networks. This technology has seen advancements in recent times where wireless sensors are injected in the human body to sense and measure body parameters like temperature, heartbeat and glucose level. These tiny wireless sensors gather body data information and send it over a wireless network to the base station. The data measurements are examined by the doctor or   physician and the suitable cure is suggested. The whole communication is done through routing protocols in a network environment. Routing protocol consumes energy while helping non-stop communic

Today technology using nanoparticle when treatment pathogentic microorganism and we focused on this here. It was found that the species of streptococcus used in present study were sensitive to erythromycin. In present study focusing biofilm formation by Streptococcus spp was evaluated. Species S. mutans was found that highest amount of biofilm compare with the other species. The aim of report effect (SNPs) on ability of biofilm form different species of streptococcus. The anti-biofilm effect of SNPs was in concentration dependent manner. The highest effect of SNP against biofilm formation was found the concentration 160 μg/ml, while the lowest effect was found the lowest used concentration (80 μg/ml) of SNPs. In vivo study revealed that s

In recent years, infectious diseases are increasingly being encountered in clinical settings. Due to the development of antibiotic resistance and the outbreak of these diseases caused by resistant pathogenic bacteria, the pharmaceutical companies and the researchers are now searching for new unconventional antibacterial agents. Recently, in this field, the application of nanoparticles is an emerging area of nanoscience and nanotechnology. For this reason, nanotechnology has a great deal of attention from the scientific community and may provide solutions to technological and environmental challenges. A common feature that these nanoparticles exhibit their antimicrobial behavior against pathogenic bacteria. In this report, we evaluate

In the present study, a pressure drop technique was used to identify the phase inversion point of oil-in-water to water-in-oil flows through a horizontal pipe and to study the effect of additives (nanoparticles, cationic surfactant and blend  nanoparticles-surfactant) on the critical dispersed volume fraction (phase inversion point). The measurements were carried  for mixture velocity ranges from 0.8 m/sec to 2.3 m/sec. The results showed that at low mixture velocity 0.8 and 1 m/sec there is no effect of additives and velocity on phase inversion point, while at high mixture velocities the phase inversion point for nanoparticles and blend (nanoparticles/surfactant) systems was delayed (postponed) to a higher value of the dispers