The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

Sustainable development has recently gained significant attention in the field of water Quality (WQ), which is critical for a healthy lifestyle. Our work suggests an intelligent hybrid model for assessing water quality using a water portability dataset, which was used to evaluate the water quality. The dataset contains physical and chemical features such as pH, Organic Carbon, sulfate, etc. Based on the combination of a Decision Tree Algorithm (DTA) and fuzzy logic Approaches, the findings revealed that sulfate was the most important factor in the model, with an accuracy of 1.00, followed by pH with an accuracy of 0.9667, and solids and chloramines with an accuracy of 0.95. The other parameters achieved a similar accuracy of 0.9167, showing

As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller

Abstract

    This work deals with a numerical investigation to evaluate the utilization of a water pipe buried inside a roof to reduce the heat gain and minimize the transmission of heat energy inside the conditioning space in summer season.     The numerical results of this paper showed that the reduction in heat gain and energy saving could be occurred with specific values of parameters, like the number of pipes per square meter, the ratio of pipe diameter to the roof thickness, and the pipe inlet water temperature. Comparing with a normal roof (without pipes), the results indicated a significant reduction in energy heat gain which is about 37.8% when the number of pipes per m

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

A new reversed phase- high performance liquid chromatographic (RP-HPLC) method with Ultraviolet-Visible spectrophotometry has been optimized and validated for the simultaneous extraction and determination of organic acids present in Iraqi calyces of Hibiscus Sabdraffia Linn. The method is based on using ultrasonic bath for extracting organic acids. Limit of detection in µg/ml of Formic acid, Acetic acid, Oxalic acid, Citric acid, Succinic acid, Tartaric acid, and Malic acid 126.8498×10-6, 113.6005×10-6, 97.0513×10-6, 49.7925×10-6, 84.0753×10-6, 92.6551×10-6, and 106.1633×10-6 ,respectively. The concentration of organic acids found in dry spacemen of calyces of Iraqi Hibiscus Sabdraffia Linn. under study: Formic acid, Acetic acid,