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

Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolution

Nicotine was separated from eggplant and green pepper seeds (Solanaceous) by High Performance Liquid Chromatography (HPLC).The concentration of nicotine in the eggplant extract (0.871-0.877 μg/ml) was determined by injecting standard material with 0.5 and 1.5 μg/ml, while the concentrations of nicotine in green pepper extract (0.613-0.618 μg/ml) was determined when the standard material was injected with 0.5 and 1.5 μg/ml. The qualitative chemical data was calculated from derivations of the standard material. Nicotine concentration was measured qualitatively in both extracts through the calibration curve and method of the standard addition. This technique has high accuracy and compatibility, bringing the proportion of relati

Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

A 3D geological model is an essential step to reveal reservoir heterogeneity and reservoir properties distribution. In the present study, a three-dimensional geological model for the Mishrif reservoir was built based on data obtained from seven wells and core data. The methodology includes building a 3D grid and populating it with petrophysical properties such as (facies, porosity, water saturation, and net to gross ratio). The structural model was built based on a base contour map obtained from 2D seismic interpretation along with well tops from seven wells. A simple grid method was used to build the structural framework with 234x278x91 grid cells in the X, Y, and Z directions, respectively, with lengths equal to 150 meters. The to

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

Metal complexes chrome(III), manganese(II), iron(III), cobalt(II), nickel(II), cupper(II) and zinc(II) with diazonium of 3-amino-2-chloropyridine of general formula [2-Cl-C₅H₃N≡N]_n[MX_m], where n=2 or 3 for divalent and trivalent metal, m= 4 or 6  were synthesized. The complexes have been characterized by flame atomic absorption, (C.H.N), molar conductance, magnetic susceptibility UV-vis spectra, infrared spectra,¹H-NMR spectroscopy and thermo gravimetric analysis (TGA and DTA). The measurements showed that the divalent metal ion complexes (M²⁺) have (1:2) M:L ratio with tetrahedral geometry around metal ions while the trivalent metal ions (M³⁺) formed (1:3) m