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

Objective: To assess knowledge and skills level regarding oxygen administration methods at p
ediatric teaching hospitals in Mosul City.
Methodology: A descriptive study was applied at pediatric teaching hospitals (Al-Kansaa, and Ibn Al-Atheer) in Mosul City from 8 of October / 2018 till 29 of May / 2019. The selection of the sample was non- probability (Purposive). This sample involved of (52) nurses. The questionnaire was constructed which consists of three parts and provided for nurses. The questionnaire validity was carried out through a panel of experts. To evaluate statistically the reliability of instruments, the pilot study was applied through period from 20– till –31 of January / 2019. Non-randomly (6) nurses from Ibn S

In this work, the possibility to use new suggested carriers (D= Aspirin, Ibuprofen, Paracetamol, Tramal) is discussed for diclofenac drug (voltarine) by using quantum mechanics calculations. The calculation methods (PM3) and (DFT) have been used for determination the reaction path of (O-D) bond rupture energies. Different groups of drugs as a carrier for diclofenac prodrugs (in a vacuum) have been used; at their optimized geometries. The calculations included the geometrical structure and some of the physical properties, in addition to the toxicity, biological activity, and NLO properties of the prodrugs, investigated using HF method. The calculations were done by Gaussian 09 program. The comparison was made for total energies of reactan

The current research aims at finding out how to properly and correctly manage waste and solid waste and reduce the difficulties faced by all countries. However, it is becoming increasingly acute in developed cities because their economies are growing rapidly. It is necessary to identify the modern methods used in developed countries in managing wastes. The use of modern waste management techniques is a coordinated effort by international agencies within the borders responsible for them. The problem of the study can be identified in the lack of clarity of environmental management procedures in place. The importance of the research contributes to providing greater capacity to the administrative and technical leadership in the municipality

One of the serious problems in any wireless communication system using multi carrier modulation technique like Orthogonal Frequency Division Multiplexing (OFDM) is its Peak to Average Power Ratio (PAPR).It limits the transmission power due to the limitation of dynamic range of Analog to Digital Converter and Digital to Analog Converter (ADC/DAC) and power amplifiers at the transmitter, which in turn sets the limit over maximum achievable rate.

        This issue is especially important for mobile terminals to sustain longer battery life time. Therefore reducing PAPR can be regarded as an important issue to realize efficient and affordable mobile communication services.

Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par