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

This work deals with thermal cracking of heavy vacuum gas oil which produced from the top of vacuum distillation unit at Al- DURA refinery, by continuous process. An experimental laboratory plant scale was constructed in laboratories of chemical engineering department, Al-Nahrain University and Baghdad University. The thermal cracking process was carried out at temperature ranges between 460-560^oC and atmospheric pressure with liquid hourly space velocity (LHSV) equal to 15hr^-1.The liquid product from thermal cracking unit was distilled by atmospheric distillation device according to ASTM D-86 in order to achieve two fractions, below 220^oC as a gasoline fraction and above 220^oC as light cycle o

A new set of metal complexes by the general formula [M(P)2(H2O)2]Cl2 has been prepared through the interaction of the new Ligand [N1, N4-bis(4-methoxyphenyl)succinamide] (P) derived from succinyl chloride with p-anisidine with the transition metal ions [Cu(II), Mn(II), Cd(II), Co(II) and Ni(II)]. Compounds diagnosed by TGA, 1 H, 13CNMR and Mass spectra (for (P)), Fourier-transform infrared and Electronic spectrum, Magnetic measurement, molar conduct, (%M, %C, %H, %N). These measurements indicate that (P) is associated with the metal ion in a bi-dentate fashion by nitrogen atoms (the amide group), and the octahedral composition of these complexes is suggested. Staphylococcus Aureus (+) and Escherichia Coli (–) were studied for the antibact

A low-cost reverse flow plasma system powered by argon gas pumping was built using homemade materials in this paper. The length of the resulting arc change was directly proportional to the flow rate, while using the thermal camera to examine the thermal intensity distribution and demonstrating that it is concentrated in the centre, away from the walls at various flow rates, the resulting arc's spectra were also measured. The results show that as the gas flow rate increased, so did the ambient temperature. The results show that the medium containing the arc has a maximum temperature of 34.1 ˚C at a flow rate of 14 L/min and a minimum temperature of 22.6 ˚C at a flow rate of 6 L/min.

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

The composites were manufactured and study the effect of addition of filler (nanoparticles SiO2 treated with silane) at different weight ratios (1, 2, 3, 4 and 5) %, on electrical, mechanical and thermal properties. Materials were mixed with each other using an ultrasound, and then pour the mixture into the molds to suit all measurements. The electrical characteristics were studied within a range of frequencies (50-1M) Hz at room temperature, where the best results were shown at the fill ratio (1%), and thermal properties at (X=3 %), the mechanical properties at the filler ratio (2%).

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

This work studies with produce of light fuel fractions of gasoline, kerosene and gas oil from treatment of residual matter that will be obtained from the solvent extraction process as by product from refined lubricate to improve oil viscosity index in any petroleum refinery. The percentage of this byproduct is approximately 10% according to all feed (crude oil) in the petroleum refinery process. The objective of this research is to study the effect of the residence time parameter on the thermal cracking process of the byproduct feed at a constant temperature, (400 °C). The first step of this treatment is the thermal cracking of this byproduct material by a constructed batch reactor occupied with control device at a selective range of re

12 membered Schiff base macrocyclic ligands, 6,7,14,15-tetra phenyl-1,2,3,4, 4a,8a, 9,10, 11,12, 12a,16a-dodecahydro dibenzo [b,h] [1,4,7,10] tetraazacyclododecine L1, and 14 membered Schiff base macrocyclic ligands, 6,8,15,17-tetramethyl-1,2,3,4, 4a,7,9a, 10,11,12,13,13a,16,18a-tetra decahydro dibenzo[b,i] [1, 4,8,11] cyclotetradecine tetraaza L2, 7,16-bis(2,4- dichloro benz ylidene)-6,8,15,17-tetra methyl-1,2,3,4, 4a,7,9a, 10, 11,12, 13, 13a,16,18a-tetra deca hydro dibenzo [b,i] [1,4,8,11] tetra azacyclo tetra decine L3 and 6,8,15, 17-tetramethyl-1,2,3, 4,4a,9a,10, 11,12,13,13a,18a-dodecahydro dibenzo [b,i] [1,4,8, 11] tetraazacyclo tetradecine (7,16-diylidene) bis(methanylyli dene) bis (N,N-dimethylaniline) L4 were synthesized by condens