This research presents a study for precipitating phosphorus (as phosphate ion) from simulated wastewater (5ppm initial concentration of phosphorus) using calcium hydroxide Ca(OH)₂ solution. The removal of phosphorus by Ca (OH)₂ solution is expected to be very effective since the chemical reaction is of acid-base type but Ca(OH)₂ forms complex compound with phosphate ions called. Hydroxyapatite Ca₅ (PO₄)₃OH. hydroxyapatite is slightly soluble in water. This research was directed towards sustainable elements as phosphorus. Kinetics of the dissolution reaction of hydroxyapatite was investigated to find the best factors to recover phosphorus. The effect of con

This study aims to assess the removal efficiency andestablish the BOD5 and COD statisticalcorrelation of the sewage flowing in Al-Diwaniyah wastewater treatment plant in Iraq during the study period (2005-2016). The strength of the influent wastewater entering the plant varied from medium to high in strength. High concentrations of BOD5 and COD in the effluent were obtained due to the poor performance of the plant. This was observed from the BOD5 /COD ratios that did not confirm with the typical ratios for the treated sewage. To improve the performance of this plant, regression equations for BOD5 and COD removal percentages were suggested which can be used to facilitate evaluation of liquid waste and optimal control process. The equations

   In the present work, tetracycline (TC) was removed from a simulated wastewater through a new photo-anodic oxidation process with a rotating graphite cylinder anode. The effects of current density, pH, rotation speed, and NaCl addition were evaluated. The results confirmed that increasing the current density results in improving the removal of TC. However, increasing the current density beyond 5 mA/cm2 had little effect on TC removal. Results revealed that TC removal using photoanodic oxidation can be achieved at high performance with an initial pH of 5. Increasing or decreasing pH beyond this value has a negative effect on TC removal. Increasing rotation speed gave better performance for TC removal due to the increase in mass t

Electromechanical actuators are used in a wide variety of aerospace applications such as missiles, aircrafts and spy-fly etc. In this work a linear and nonlinear fin actuator mathematical model has been developed and its response is investigated by developing an algorithm for the system using MATLAB. The algorithm used to the linear model is the state space algorithm while the algorithm used to the nonlinear model is the discrete algorithm. The huge moment constant is varied from (-3000 to 3000) and the damping ratio is varied from (0.4 to 0.8).        

 The comparison between linear and nonlinear fin actuator response results shows that for linear model, the maximum overshoot is about 10%,

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work presents the full details of design for vertical axis wind turbine (VAWT) and how to find the optimal values of necessary factors. Additionally, the results shed light on the efficiency and performance of the VAWT under different working conditions. It was taken into consideration the variety of surrounding environmental conditions (such as density and viscosity of fluid, number of elements of the blade, etc.) to simulate the working of vertical wind turbines under di