The effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or

The present work reports the performance of three types of polyethersulfone (PES) membrane in the removal of highly polluting and toxic lead Pb2+ and cadmium Cd2+ ions from a single salt. This study investigated the effect of operating variables, including pH, types of PES membrane, and feed concentration, on the separation process. The transport parameters and mass transfer coefficient (k) of the membranes were estimated using the combined film theory-solution-diffusion (CFSD), combined film theory-Spiegler-Kedem (CFSK), and combined film theory-finely-porous (CFFP) membrane transport models. Various parameters were used to estimate the enrichment factors, concentration polarization modulus, and Péclet number. The pH values signif

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Some coordination complexes of Co(ІІ), Ni(ІІ), Cu(ІІ), Cd(ІІ) and Hg(ІІ) are reacted in ethanol with Schiff base ligand derived from of 2,4,6- trihydroxybenzophenone and 3-aminophenol using microwave irradiation and then reacted with metal salts in ethanol as a solvent in 1:2 ratio (metal: ligand). The ligand [H4L] is characterized by FTIR, UV-Vis, C.H.N, 1H-NMR,13C-NMR, and mass spectra. The metal complexes are characterized by atomic absorption, infrared spectra, electronic spectra, molar conductance, (C.H.N for Ni(ІІ) complex) and magnetic moment measurements. These measurements indicate that the ligand coordinates with metal (ІІ) ion in a tridentate manner through the nitrogen and oxygen atoms of the ligand, octahed

Some coordination complexes of Co(??), Ni(??), Cu(??), Cd(??) and Hg(??) are reacted in ethanol with Schiff base ligand derived from of 2,4,6- trihydroxybenzophenone and 3-aminophenol using microwave irradiation and then reacted with metal salts in ethanol as a solvent in 1:2 ratio (metal: ligand). The ligand [H4L] is characterized by FTIR, UV-Vis, C.H.N, 1H-NMR,13C-NMR, and mass spectra. The metal complexes are characterized by atomic absorption, infrared spectra, electronic spectra, molar conductance, (C.H.N for Ni(??) complex) and magnetic moment measurements. These measurements indicate that the ligand coordinates with metal (??) ion in a tridentate manner through the nitrogen and oxygen atoms of the ligand, octahedral structures

Some coordination complexes of Co(??), Ni(??), Cu(??), Cd(??) and Hg(??) are reacted in ethanol with Schiff base ligand derived from of 2,4,6- trihydroxybenzophenone and 3-aminophenol using microwave irradiation and then reacted with metal salts in ethanol as a solvent in 1:2 ratio (metal: ligand). The ligand [H4L] is characterized by FTIR, UV-Vis, C.H.N, 1H-NMR,13C-NMR, and mass spectra. The metal complexes are characterized by atomic absorption, infrared spectra, electronic spectra, molar conductance, (C.H.N for Ni(??) complex) and magnetic moment measurements. These measurements indicate that the ligand coordinates with metal (??) ion in a tridentate manner through the nitrogen and oxygen atoms of the ligand, octahedral st

Some coordination complexes of Co(??), Ni(??), Cu(??), Cd(??) and Hg(??) are reacted in ethanol with Schiff base ligand derived from of 2,4,6- trihydroxybenzophenone and 3-aminophenol using microwave irradiation and then reacted with metal salts in ethanol as a solvent in 1:2 ratio (metal: ligand). The ligand [H4L] is characterized by FTIR, UV-Vis, C.H.N, 1H-NMR,13C-NMR, and mass spectra. The metal complexes are characterized by atomic absorption, infrared spectra, electronic spectra, molar conductance, (C.H.N for Ni(??) complex) and magnetic moment measurements. These measurements indicate that the ligand coordinates with metal (??) ion in a tridentate manner through the nitrogen and oxygen atoms of the ligand, octahedral st