The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

In this study, aromatic polyamide reverse osmosis membranes were used to remove zinc ions from electroplating wastewater. Influence of different operating conditions such as time, zinc concentration and pressure on reverse osmosis process efficiency was studied. The experimental results showed, concentration of zinc in permeate increase with increases of time from 0 to 70 min, and flux of water through membrane decline with time. While, the concentrations of zinc in permeate increase with the increase in feed zinc concentration (10–300 mg/l), flux decrease with the increment of feed concentration. The raise of pressure from 1 to 4 bar, the zinc concentration decreases and the flux increase. The highest recovery percentage was found is 54.

In this study, aromatic polyamide reverse osmosis membranes were used to remove zinc ions from electroplating wastewater. Influence of different operating conditions such as time, zinc concentration and pressure on reverse osmosis process efficiency was studied.  The experimental results showed, concentration of zinc in permeate increase with increases of time from 0 to 70 min, and flux of water through membrane decline with time. While, the concentrations of zinc in permeate increase with the increase in feed zinc concentration (10–300 mg/l), flux decrease with the increment of feed concentration. The raise of pressure from 1 to 4 bar, the zinc concentration decreases and the flux increase. The highest recovery percentage was fou

This work was conducted to study the extraction of pelletierine sulphate from Punica granatum L. roots by liquid membrane techniques. Pelletierine sulphate is used widely in medicine. The general behavior of extraction process indicates that pelletierine conversion increased with increasing the number of stages and the discs rotation speed but high rotation speed was not favored because of the increased risk of droplet formation during the operation. The pH of feed and acceptor solution was also important. The results exhibit that the highest pelletierine conversion was obtained when using two stages,(10 rpm) discs speed of stainless steel discs,(pH= 9.5) of feed solution and (pH= 2) of acceptor solution in n-decane. Assuming the existence

Abstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo

This work was conducted to study the extraction of pelletierine sulphate from Punica granatum L. roots by liquid membrane techniques. Pelletierine sulphate is used widely in medicine. The general behavior of extraction process indicates that pelletierine conversion increased with increasing the number of stages and the discs rotation speed but high rotation speed was not favored because of the increased risk of droplet formation during the operation. The pH of feed and acceptor solution was also important. The results exhibit that the highest pelletierine conversion was obtained when using two stages, (10 rpm) discs speed of stainless steel discs, (pH=9.5) of feed solution and (pH=2) of acceptor solution in n-decane. Assuming the existen

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed