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 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

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.

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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

Purpose: The main objective of this paper is, to determine the optimal no. of technicians’ men in a workshop crew of an Industrial System.   Theoretical framework: The purpose of applying these tools is to explore their ability to reduce costs and improvements that can be obtained in the process of providing services to the end customer.   Design/methodology/approach: The literature structure review was built from analyzing 12 of scientific papers and books, from web sciences and the Elsevier database. The papers were analyzed from descriptive, methodologic, and citation characteristics.   Finding:  By applying the equation model of the paper, the optimal no. of technician men in the crew of the workshop can be determined when

This research seeks to attempt to reveal the intention of Al-Hafiz Al-Mazi from his market to hadiths from Imam Ahmad’s Musnad in his book “Masterpiece of Supervision in Knowing the Parties”, and researchers know that this book was classified by Al-Mazi to collect the parties to the six books: Sahih Al-Bukhari, Sahih Muslim, Sunan Abi Dawud, Jamea Al-Tirmidhi and Sunan Al-Nasa’i and Sunan Ibn Majah, in addition to some of the books ’authors’ books, and arranging them according to the Musnad, and it is not Musnad Ahmad from his condition, even if it is close to the arrangement of Mazi’s work, as he was a follower of that to the original owner Abu al-Qasim bin Asaker in his book “Supervising Knowledge of the Parties” in M

Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising technology for a wide range of ocean monitoring applications. The UWSNs suffer from unique challenges of the underwater environment, such as dynamic and sparse network topology, which can easily lead to a partitioned network. This results in hotspot formation and the absence of the routing path from the source to the destination. Therefore, to optimize the network lifetime and limit the possibility of hotspot formation along the data transmission path, the need to plan a traffic-aware protocol is raised. In this research, we propose a traffic-aware routing protocol called PG-RES, which is predicated on the ideas of Pressure Gradient and RESistance concept. The proposed

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p