The quality of drinking water is considered among the most urgent issues worldwide nowadays. Ensuring safe water for human consumption remains the highest priority, while challenges also persist in meeting the water quality needs for industrial and agricultural uses. Most of the relevant studies lack accuracy in assessing water quality. Therefore, this study aims to forecast the quality of drinking water along the Tigris River in Iraq following a new approach. A developed forecasting model that utilizes the gravitational search algorithm (GSA) was deployed. The heuristic optimization tool was utilized for the prediction of the water quality index (WQI) in the research area. Out of twelve water stations, 575 samples were gathered and used for modelling in this study. The water quality was classified according to World Health Organization (WHO) recommendations using the generally applied arithmetic method, the WQI. Based on the concentrations of eleven parameters (BOD, Ca, Cl, EC, HCO3, K, Mg, Na, NO3, pH, SO4, and TDS), the WQI for all samples was computed. The results of this study indicated that the water quality was significantly influenced. The evaluation of the applied model revealed that the GSA-based model exhibited statistically consistent performance (mean = 1.04, Standard deviation (SD) = 0.109, and Coefficient of variation (CoV) = 10.48%), indicating stable predictions compared to other models that demonstrated higher accuracy. The outcomes also showed greater variability in their results, positioning the GSA model as the preferred choice in scenarios that prioritize stability and reliability in water quality predictions.
A simple technique is proposed in this paper for estimating the coefficient of permeability of an unsaturated soil based on physical properties of soils that include grain size analysis, degree of saturation or water content, and porosity of the soil. The proposed method requires the soil-water characteristic curve for the prediction of the coefficient of permeability as most of the conventional methods. A procedure is proposed to define the hydraulic conductivity function from the soil water characteristic curve which is measured by the filter paper method. Fitting methods are applied through the program (SoilVision), after indentifying the basic properties of the soil such as Attereberg limits, specific gravity, void ratio, porosity, d
... Show MoreIn the present study, composites were prepared by Hand lay-up molding and investigated. The composites constituents were epoxy resin as the matrix, 6% volume fractions of Glass Fibers (G.F) as reinforcement and 3%, 6% of industrial powder (Calcium Carbonate CaCO3, Potassium Carbonate K2CO3 and Sodium Carbonate Na2CO3) as filler. Density, water absorption, hardness test, flexural strength, shear stress measurements and tests were conducted to reveal their values for each type of composite material. The results showed that the non – reinforced epoxy have lower properties than composites material. Measured density results had show an incremental increase with volume fraction increase
... Show MoreFor the most reliable and reproducible results for calibration or general testing purposes of two immiscible liquids, such as water in engine oil, good emulsification is vital. This study explores the impact of emulsion quality on the Fourier transform infrared (FT-IR) spectroscopy calibration standards for measuring water contamination in used or in-service engine oil, in an attempt to strengthen the specific guidelines of ASTM International standards for sample preparation. By using different emulsification techniques and readily available laboratory equipment, this work is an attempt to establish the ideal sample preparation technique for reliability, repeatability, and reproducibility for FT-IR analysis while still considering t
... Show MoreIn this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.
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Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the
... Show Moreيهدف البحث الحالي إلى اختبار العلاقة بين نوعية حياة العمل والإبداع التنظيمي في ديوان وزارة التخطيط ، ولبلوغ الهدف المذكور وبناء على معطيات البحث الاستطلاعي للباحث بني ألانموذج الفرضي للبحث الذي ضم المتغير المستقل والمعتمد، واعتماداً على حركية الأنموذج صيغت فرضيتان، ولاختبار صحة الفرضيات وجمع المعلومات من عينة البحث البالغة (100) مدير يمثلون مرك
... Show MoreMalaysia has been supported by one of the high-speed fiber internet connections called TM UniFi. TM UniFi is very familiar to be used as a medium to apply Small Office Home Office (SOHO) concept due to the COVID-19 pandemic. Most of the communication vendors offer varieties of network services to fulfill customers' needs and satisfaction during the pandemic. Quality of Services is queried by most users by the fact of increased on users from time to time. Therefore, it is crucial to know the network performance contrary to the number of devices connected to the TM UniFi network. The main objective of this research is to analyze TM UniFi performance with the impact of multiple device connections or users' services. The study was conducted
... Show MoreIn this manuscript, the effect of substituting strontium with barium on the structural properties of Tl0.8Ni0.2Sr2-xBrxCa2Cu3O9-δcompound with x= 0, 0.2, 0.4, have been studied. Samples were prepared using solid state reaction technique, suitable oxides alternatives of Pb2O3, CaO, BaO and CuO with 99.99% purity as raw materials and then mixed. They were prepared in the form of discs with a diameter of 1.5 cm and a thickness of (0.2-0.3) cm under pressures 7 tons / cm2, and the samples were sintered at a constant temperature o
... Show MoreIncreased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
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