This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p

 ABSTRICT:

  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

  This study aimed to obtain an isolate of a mold that has well characteristic for production of citric acid from raw materials available locally by solid-state fermentation and determination of the optimum conditions for production .Fourteen mold isolates producing acid were obtained from different sources, involved decayed fruits and soils. These isolates were subjected to initial qualitative screening followed by secondary quantitative screening In secondary screening a method combined between the submerged fermentation and solid-state fermentation was followed using a piece of sponge saturated by nutrients required for growth and production of acid. It was found that the isolate of A7 was the highest producer for citric acid tha

Mixed phase rutile/anatase of TiO2 was prepared and studied by a closed field DC magnetron sputtering configuration (CFDCMS). It was found that the contents of rutile increased from the ratio of 38% to 53% as the deposition time increased from 3.5 hours to 4.5 hours.
The photocatalytic activity of the mixed phase rutile/anatase TiO2 was measured by monitoring the degradation of the blue methylene dye in an aqueous solution, under exposure to UV-radiation, using UV-vis absorption spectroscopy. It was proven that the photocatalytic activity in the mixed phase (TiO2) is a function of rutile content reaching a maximum value at 53% rutile. Thus, the effect of synergy between anatase- TiO2 and rutile- TiO2 was observed. It was observed that

Ferric oxide nanoparticles Fe3O4NPs have been prepared by the coprecipitation method, which were used to functionalize the surface of electrospun nanofibers of polyacrylonitrile to increase their effectiveness in adsorption of Congo red (CR) dye from their aqueous solutions. The effect factors of adsorption were systematically investigated such as adsorbent mass, initial concentration, contact time, temperature, ionic strength and pH. The maximum adsorbed amount of the dye was at 0.003g of adsorbent. The adsorption of dye increased with increasing initial dye concentration and the system reaches to the equilibrium state at 150 min. The adsorbed dye capacity decreases with increasing temperature which indicates to the exothermic nature of ad

     The worldwide pandemic Coronavirus (Covid-19) is a new viral disease that spreads mostly through nasal discharge and saliva from the lips while coughing or sneezing. This highly infectious disease spreads quickly and can overwhelm healthcare systems if not controlled. However, the employment of machine learning algorithms to monitor analytical data has a substantial influence on the speed of decision-making in some government entities.        ML algorithms trained on labeled patients’ symptoms cannot discriminate between diverse types of diseases such as COVID-19. Cough, fever, headache, sore throat, and shortness of breath were common symptoms of many bacterial and viral diseases.

This research focused on the nu