Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

The removal of boron from aqueous solution was carried out by electrocoagulation (EC) using magnesium electrodes as anode and stainless steel electrodes as cathode. Several operating parameters on the removal efficiency of boron were investigated, such as initial pH, current density, initial boron ion concentration, NaCl concentration, spacing between electrodes, electrode material, and presence of carbonate concentration. The optimum removal efficiency of 91. 5 % was achieved at a current density of 3 mA/cm² and  pH = 7 using (Mg/St. St. ) electrodes, within 45 min of operating time. The concentration of NaCl was o. 1 g/l with a 0.5cm spacing between the electrodes. First and second order rate equation were applied to study adsorp

The presence of residual antibiotics in water results in the development of antibiotics resistant genes. The available wastewater treatment systems are not capable of removing such antibiotics from sewage. Thus, antibiotics need to be removed before the discharge of wastewater. Adsorption is among the promising techniques for the wastewater treatment to aid the removal of a wide range of organic and inorganic pollutants. The present work is a contribution to the search for an economical method for the removal of low concentrations of amoxicillin (AMX) from water by adsorption on water treatment residue, WTR, taken from a local drinking water facility. The chemical composition and the adsorptive characteristics of the material were first

This study focused on treating wastewater to remove phosphorus by adsorption onto naturaland local materials. Burned kaolin, porcelinite, bauxite and limestone were selected to be testedas adsorption materials.The adsorption isotherms were evaluated by batch experiments, studyingthe effects of pH, temperature and initial phosphorus concentration. The results showed that at pH6, temperature 20°C and 300 mg/l initial phosphorus concentration; the sorption capacity was0.61, 9, 10 and 13 mg/g at 10 h contact time, for burned kaolin, porcelanite, limestone and bauxiterespectively. As the pH increased from 2 to 10 the removal efficiency for the materials differs inbehaviour. The removal efficiency increased from 40 to 90 % for limestone, and dec

Industrial wastewater containing nickel, lead, and copper can be produced by many industries. The reverse osmosis (RO) membrane technologies are very efficient for the treatment of industrial wastewater containing nickel, lead, and copper ions to reduce water consumption and preserving the environment. Synthetic industrial wastewater samples containing Ni(II), Pb(II), and Cu(II) ions at various concentrations (50 to 200 ppm), pressures (1 to 4 bar), temperatures (10 to 40 ^oC), pH (2 to 5.5), and flow rates (10 to 40 L/hr), were prepared and subjected to treatment by RO system in the laboratory. The results showed that high removal efficiency of the heavy metals could be achieved by RO process (98.5%, 97.5% and 96% for Ni(II),

This research aimed to examine the effect of concentration of dyes stuff, contact time, temperature and ratio of adsorbent weight in (gm) to volume of solution in (ml) on the percentage removal. Two dyes were used; direct blue 6 and direct yellow and the adsorbent was the maize cob. Batch experiments were performed by contacting different weights of adsorbent with 50 ml of solution of desired concentration with continuous stirring at various temperatures. The percentage of removal was calculated and the maximum percentage of removal was 80%. And as the concentration of solution, contact time, temperature and the ratio of adsorbent to volume of solution increase the percentage of removal increase.

The degradation and mineralization of 4-chlorophenol (4-CP) by advanced oxidation processes (AOPs) was investigated in this work, using both of UV/H2O2 and photo-Fenton UV/H2O2/Fe+3 systems.The reaction was influenced by the input concentration of H2O2, the amount of the iron catalyst, the type of iron salt, the pH and the concentration of 4-CP. A colored solution of benzoquinon can be observed through the first 5 minutes of irradiation time for UV/H2O2 system when low concentration (0.01mol/L) of H2O2 was used. The colored solution of benzoquinon could also be observed through the first 5 minutes for the UV/H2O2/Fe+3 system at high
concentration (100ppm) of 4-CP. The results have shown that adding Fe+3 to the UV/H2O2 system enhanced

In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare