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

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

The present study aimed to examine the concordance between FISH/CISH techniques for assessment of amplification of her2neu gene in Iraqi breast carcinoma patients. Seventy four (74) Iraqi breast cancer patients were involved at the study from the Histopathology Department at the Central Public Health Laboratory in Bagdad, Iraq. Amplification of HER2neu was detected in (33.8%) by fluorescence in situ hybridization and (13.51%) showed high amplification by chromogenic in situ hybridization and (32.43%) showed low amplification. The results of chromogenic in situ hybridization were significantly correlated with the results of two-color fluorescence in situ hybridization with the same tumors. In addition, the study involved the correlation betw

Background: preparation of root canals is an important step in root canal treatment. Mechanical instrumentation of root canals cause an irregular layer of debris, known as the smear layer. As a result, several studies reported that preferring the removal of the smear layer. Objective: To study the influence of the energy (100 mJ) of Erbium, Chromium: Yttrium Scandium Gallium Garnet (Er,Cr:YSGG) laser at short pulse duration (60 μs)  on smear layer removal of apical third after using Photon induced photoacoustic streaming technique. Materials and methods: Eighteen straight single-rooted mandibular premolars were used. The roots length were uniform to 14mm from the anatomic apex and