This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I

In this study a polymeric composite material was prepared by hand
lay-up technique from epoxy resin as a matrix and magnesium oxide
(MgO) as a reinforcement with different weight fraction (5,10,15,
and 20)% to resin. Then the prepared samples were immersed under
normal condition in H₂So₄(1 M) solution, for periods ranging up to
10 weeks. The result revealed that the diffusion coefficient
decreasing as the concentration of MgO increase. Also we studied
Hardness for the prepared samples before and after immersion. The
result revealed that the hardness values increase as the concentration
of MgO increase, while the hardness for the samples after immersion
in H₂SO₄ dec

This work aims to enhance acoustic and thermal insulation properties for polymeric composite by adding nanoclay and rock wool as reinforcement materials with different rations. A polymer blend of (epoxy+ polyester) as matrix materials was used. The Hand lay-up technique was used to manufacture the castings. Epoxy and polyester were mixed at different weight ratios involving (50:50, 60:40, 70:30, 80:20, and 90:10) wt. % of (epoxy: polyester) wt. % respectively. Impact tests for optimum sample (OMR), caustic and thermal insulation tests were performed. Nano clay (Kaolinite) with ratios ( 5 and 7.5% ) wt.% , also hybrid reinforcement materials involving (Kaolite 5 & 7.5 % wt.% + 10% volume fraction of rockwool ) were added as reinforcem

Random laser gain media is synthesized with different types of dye at the same concentration (1×10^-3 M) as an active material and silicon dioxide NPs (silica SiO₂) as scatter centers through the Sol-Gel technique. The prepared samples are tested with UV–Vis spectroscopy, Fluorescence Spectroscopy, Field Emission Scanning Electron Microscopy (FESEM), and Energy Dispersive X-ray Diffraction (EDX). The end result demonstrates that doped dyes with silica nanoparticles at a concentration of 0.0016 mol/ml have lower absorbance and higher fluorescence spectra than pure dyes. FESEM scans revealed that the morphology of nanocrystalline silica is clusters of nano-sized spherical particles in the range (25-67) nm. It is con

A pulsed (TEA-0O2) laser was used to dissociate molecules of silane ethylene (C2I-14) and ammonia (NH3) gases, through collision assisted multiple photon dissociation (MPD) to deposit(SiC i_xNx) thin films, where the X-values are 0, 0.13 and 0.33, on glass substrate at T,----648 K. deposition rate of (0.416-0.833) nm/pulse and thickness of (500-1000)nm .Fourier transform infrared spectrometry (FT-IR) was used to study the nature of the chemical bonds that exist in the films. Results revealed that these films contain complex networks of the atomic (Si, C, and N), other a quantity of atomic hydrogen and chemical bonds such as (Si-N, C-N, C-14 and N-H).Absorbance and Transmittance spectra in the wavelength range (400-1100) nm were used to stud

Al-Si alloys which are widely used in engineering applications due to their outstanding properties can be modified for more enhancements in their properties. Current work investigated the ability of these alloys to be modified by casting them through the addition of nanoparticles. So, Multi-wall carbon nanotubes (CNT) and titanium carbide ceramic particles (TIC) with size of (20 nm) were added with different amounts started from (0.5 up to 3%) weight  to cast alloy A356 that was considered to be the base metal matrix, then stirred with different speeds of (270, 800, 1500, 2150) rpm at 520 °C for one minute. The results showed change in microstructure’ shape of the casted alloys from the dendritic to spherical gra