This work is dedicated to the economic scheduling of the required electric stations in the upcoming 10-year long-term plan. The calculation of the required electric stations is carried out by estimating the yearly consumption of electricity over a long-time plan and then determining the required number of stations. The aim is to minimize the total establishing and operating costs of the stations based on a mathematical programming model with nonlinear objective function and integer decision variables. The introduced model is applied for a real practical case study to conclude the number of

Daily, a big extent of colored, partially treated textile effluents drained into the sanitation systems causing serious environmental concerns. Therefore, the decolorization treatment process of wastewater is crucial to improve effluent quality. In the present study, 3 different sorbent materials, nano zerovalent iron (nZVI), activated carbon (AC), and green-synthesized nano zerovalent iron (GT-nZVI), have been prepared for raw textile wastewater decolourization. The prepared nanomaterials were characterized via X-ray diffraction (XRD) spectroscopy, scanning electron microscopy (SEM), energy

Introduction: The hyper-catabolic state is a devastating pathophysiological response to severe injury, infection or burns. Nandrolone decanoate (ND) is a potent anabolic steroid have many clinical indications, but not investigated in burn injuries yet. Patients and methods: A prospective randomized control study included 40 burned patients who were treated in Burn unit from burn injuries ranged from 20 to 40%. Both groups are objectively assessed, clinically and laboratory during treatment period till full recovery from burns’ injury. Recall assessment of the drug safety after many years is

This paper presents a framework for optimizing condition assessment policies by balancing the revealed value of information with the cost of obtaining such information. The computational platform is based on augmenting the asset condition state with an expected level of accuracy. Inaccuracies due to condition assessment reliability are evaluated using the partially observable Markov decision process. The single objective genetic algorithm is used to select the most cost-effective assets to assess considering information inaccuracy under a fixed budget. The model is extended using

With ageing water and sewer infrastructure in North America, assessing the condition of these assets has received increased attention in the past few years. Condition assessment is an integral component in any asset management program. Determining the condition of buried infrastructure tends to be more cumbersome, costly and error-prone compared to other surface infrastructure like roads and buildings. For sewers, CCTV is considered the industry standard for condition assessment technologies. For pressurized water pipelines, technologies tend to be more costly and uncertain (e.g

This paper illustrates the design of proportional–integral–derivative controller (PID) controller of 10 KW air heaters for achieving the set point temperature as fast as possible with minimum response overshoot. Computational fluid dynamic (CFD) numerical simulations are utilized to predict the natural response of 10 KW input power for the air heater. CFD results are validated with experimental empirical correlations that insure the reliability of open loop results. The open loop response of CFD transient simulations is used to model the air heater transfer function and design the classical

This study investigates the feasibility of applying coagulation/flocculation process for real textile wastewater treatment. Batch experiments were performed to detect the optimum performance of four different coagulants; Ferric Sulphate (Fe2(SO4)3), Aluminium Chloride (AlCl3), Aluminium Sulphate (Al2(SO4)3) and Ferric Chloride (FeCl3) at diverse ranges of pH (1–11) on the removal of chemical oxygen demand (COD), total suspended solids (TSS), colour, total nitrogen (TN) and turbidity from real textile wastewater. At pH 9, FeCl3 demonstrated the most effective removal for all studied

The gaining sharing knowledge based optimization algorithm (GSK) is recently developed metaheuristic algorithm, which is based on how humans acquire and share knowledge during their life-time. This paper investigates a modified version of the GSK algorithm to find the best feature subsets. Firstly, it represents a binary variant of GSK algorithm by employing a probability estimation operator (Bi-GSK) on the two main pillars of GSK algorithm. And then, the chaotic maps are used to enhance the performance of the proposed algorithm. Ten different types of chaotic maps are considered to adapt the

In this work, the Artificial Neural Networks (ANN) are used to model a chaotic system. A method based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to determine the best parameters of a Multilayer Perceptron (MLP) artificial neural network. Using NSGA-II, the optimal connection weights between the input layer and the hidden layer are obtained. Using NSGA-II, the connection weights between the hidden layer and the output layer are also obtained. This ensures the necessary learning to the neural network. The optimized functions by NSGA-II are the number of neurons in the

In this work, the Artificial Neural Networks (ANN) are used to model a chaotic system. A method based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to determine the best parameters of a Multilayer Perceptron (MLP) artificial neural network. Using NSGA-II, the optimal connection weights between the input layer and the hidden layer are obtained. Using NSGA-II, the connection weights between the hidden layer and the output layer are also obtained. This ensures the necessary learning to the neural network. The optimized functions by NSGA-II are the number of neurons in the