Cadmium is one of the heavy metal found in the wastewater of many industries. The electrocoagulation offers many advantages for the removal of cadmium over other methods. So the removal of cadmium from wastewater by using electrocoagulation was studied to investigate the effect of operating parameters on the removal efficiency. The studied parameters were the initial pH, initial concentration, and applied voltage. The study experiments were conducted in a batch reactor with  with two pairs of aluminum electrodes with dimension  and 2mm in thick with 1.5 cm space between them. The optimum removal was obtained at pH =7, initial concentration = 50 mg/L, and applied voltage = 20 V and it was 90%.

This article presents the simultaneous adsorption of bimetal Cu²⁺ and Zn²⁺ from an aqueous solution using activated carbon synthesized from a plum seed precursor by sulfuric acid and microwave activation: plum seeds chemically activated by 45% (w/w) sulfuric acid with 2:1 ratio for 4 h, then carbonized for 2 h at 700 °C and the product obtained activated in a microwave oven for 20 min at 700 W for final of activation. Plum seeds and activated carbon produced were characterized in terms of their physical and chemical composition using Brunauer–Emmett–Teller measurements, field emission scanning electr

Pharmaceuticals have been widely remaining contaminants in wastewater, and diclofenac is the most common pharmaceutical pollutant. Therefore, the removal of diclofenac from aqueous solutions using activated carbon produced by pyrocarbonic acid and microwaves was investigated in this research. Apricot seed powder and pyrophosphoric acid (45 wt%) were selected as raw material and activator respectively, and microwave irradiation technique was used to prepare the activated carbon. The raw material was impregnated in pyrophosphoric acid at 80◦C with an impregnation ratio of 1: 3 (apricot seeds to phosphoric acid), the impregnation time was 4 h, whereas the power of the microwave was 700 watts with a radiation time of 20 min. A series o

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Introduction: The current study investigated the use of acid-treated rice husks to remove heavy metals and organic pollutants from water containing heavy metals (R2C and Cd2) and organic pollutants (phenol and atrazine). Methods: The adsorption effect of acid-treated rice husks was compared with other adsorbents such as activated carbon, chitosan, and bentonite clay. Result: both acid-treated rice husks and activated carbon were highly efficient materials, and thus, rice husks were established as a cost-effective alternative. It was revealed that acid treatment of rice husks enhanced adsorption capacity by half, and lead removal was nearly doubled. The most effective pH value for optimizing organic pollutants and heavy metals while

Transference numbers of the aqueous zinc chloride and zinc sulphate solutions have been measured for the concentrations 0.03, 0.05, 0.07, 0.09 and 0.1 mol.dm-3at 298.15K, by using the modified Hittorf method. The dependence of transference number on concentration of each electrolyte was also investigated in an attempt to explain the value of the limiting transference number. The Longsworth method has been used for the extrapolation of zinc transference number in aqueous solutions, using the values of the limiting transference numbers of the appropriate values of the limiting equivalent conductance, it was possible to determine the corresponding values of the limiting ion conductance for the cations and anions of the electrolytes. The