Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant

This study deals with the elimination of methyl orange (MO) from an aqueous solution by utilizing the 3D electroFenton process in a batch reactor with an anode of porous graphite and a cathode of copper foam in the presence of granular activated carbon (GAC) as a third pole, besides, employing response surface methodology (RSM) in combination with Box-Behnk Design (BBD) for studying the effects of operational conditions, such as current density (3–8 mA/cm2), electrolysis time (10–20 min), and the amount of GAC (1–3 g) on the removal efficiency beside to their interaction. The model was veiled since the value of R2 was high (>0.98) and the current density had the greatest influence on the response. The best removal efficiency (MO Re%)

The main objective of this study is to experimentally investigate the effect of the CMC polymeric drag reducer on the pressure drop occurred along the annulus of the wellbore in drilling operation and investigate the optimum polymer concentration that give the minimum pressure drop. A flow loop was designed for this purpose consist from 14 m long with transparent test section and differential pressure transmitter that allows to sense and measure the pressure losses along the test section. The results from the experimental work show that increasing in polymer concentration help to reduce the pressure drop in annulus and the optimum polymer concentration with the maximum drag reducing is 0.8 kg/m³. Also increasing in flow rate a

This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

لاهمية التوزيع المختلط في التعبيرعن التوزيعات الاحتمالية للمتغيرات العشوائية المختلطة من النوعين المتقطع والمستمر ، حيث انها تاخذ قيم أحتمالية موجبة عن نقاط معرفة لقيم x

وتاخذ دالة او قيم اخرى عندما تقع    x ضمن مجال معين                            .(Interval)

وحاول

Acceptable Bit Error rate can be maintained by adapting some of the design parameters such as modulation, symbol rate, constellation size, and transmit power according to the channel state.

An estimate of HF propagation effects can be used to design an adaptive data transmission system over HF link. The proposed system combines the well known Automatic Link Establishment (ALE) together with variable rate transmission system. The standard ALE is modified to suite the required goal of selecting the best carrier frequency (channel) for a given transmission. This is based on measuring SINAD (Signal plus Noise plus Distortion to Noise plus Distortion), RSL (Received Signal Level), multipath phase distortion and BER (Bit Error Rate) fo

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt