Combining ultrasonic irradiation and the Fenton process as a sono-Fenton process, the chemical oxygen demand (COD) in refinery wastewater was successfully eliminated using response surface methodology (RSM) with central composite design (CCD). The impact of two main influential operational parameters (iron dosage and reaction time) on the COD removal from wastewater generated by an Iraqi petroleum refinery facility was explored. Removal of 85.81% was attained under the optimal conditions of 21 minutes and 0.289 mM of  concentration. Additionally, the results revealed that the concentration of has the highest effect on the COD elimination, followed by reaction time. The high R² value (96.40%) validated the strong fit of the mo

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

A series of experiments were conducted for the first time in Iraq to evaluate the efficiency of five plant leaves extracts (Ibicella lutea, Nerium oleander, Clerodendron inerme, Allium cepa and Eucalyptus spp.) in treating the common carp (Cyprinus carpio) infected with monogenetic trematodes of genera Dactylogyrus. Five different concentrations of such extracts were used to bathe fishes for 5,10,15,20 and 25 minutes. A concentration of 15% A. cepa for 25 minutes of bath exposure was affective in trematode eradication. Extracts of both Eucalyptus and N. oleander at a concentration of 10% each were also affective for ten minutes exposure. Extracts of C. inerme had no any effect on such parasites. On the otherhand, extracts of 1. hitea caused

The productivity of oil wells may be improved by determining the value of enhancing well productivity and the likely reasons or sources of formation damage after the well has been recognized as underperforming. Oil well productivity may be improved, but the economics of this gradual improvement may be compromised. It is important to analyze the influence of the skin effect on the recovery of the reserve.

   The acid treatment evaluated for the well AD-12, primarily for the zone Mi4;  using a license of Stimpro Stimulation Software to validate the experimental work to the field scale, this software is considered the most comprehensive instrument for planning and monitoring matrix acid treatments and utilizing actual data to prov

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

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