Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recogn

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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

A new Schiff base ligand [L] [3-methyl-9,10 phenyl -6,7 dihydro-5,8 –dioxo-1,2 diazo –cyclo dodecu 2,11-diene ,4-one ] and its complexes with (Co(II), Ni(II), Cu (II), Zn(II) and Cd(II)) were synthesis.This ligand was prepared in three steps, in the first step a solution of salicyladehyed in methanol reacted under refluxed with hydrazine monohydrate to give an (intermediate compound 1) which reacted in the second step with sodium pyruvate to give an (intermediate compound 2) which gave the ligand [L] in the three step when it reacted with 1,2- dichloro ethane.The complexes were synthesized by direct reaction of the corresponding metal chloride with the ligand. The ligand and complexes were characterized by spectroscopic methods [IR, UV-

Anew Schiff base (NaHL) has been prepared from the reaction between the salt of amino acid glycine with 2-hydroxy naphthaldehyde. By tridentate Schiff base of (ONO), donors were characterized by using U.V and spectrophotometer techniques. Complexes of Co(II) Ni(II) Cu(II) and Zn(II) ion with the ligand have been prepared, these complexes were identified by infrared, electronic spectral data, elemental analysis, magnetic moments, and molar conductivity measurements. It is concluded from the elemental analysis that all the complexes have (1:2) [metal:ligand] molar ratios, octahedral, with the exception to Zn(II) complex which have (1:1)[metal:ligand] molar ratio.

In this work, the plasma parameters (electron temperature and
electron density) were determined by optical emission spectroscopy
(OES) produced by the RF magnetron Zn plasma produced by
oxygen and argon at different working pressure. The spectrum was
recorded by spectrometer supplied with CCD camera, computer and
NIST standard of neutral and ionic lines of Zn, argon and oxygen.
The effects of pressure on plasma parameters were studied and a
comparison between the two gasses was made.

In this work, the spectra for plasma glow produced by pulse
Nd:YAG laser (λ=532 and 1064nm) on Ag:Al alloy with same molar
ratio samples in distilled water were analyzed by studying the atomic
lines compared with aluminum and silver strong standard lines. The
effect of laser energies of the range 300 to 800 mJ on spectral lines,
produced by laser ablation, were investigated using optical
spectroscopy. The electron temperature was found to be increased
from 1.698 to 1.899 eV, while the electron density decreased from
2.247×1015 to 5.08×1014 cm-3 with increasing laser energy from 300
to 800 mJ with wavelength of 1064 nm. The values of electron
temperature using second harmonic frequency are greater than of<