Cold plasma is a relatively low temperature gas, so this feature enables us to use cold plasma to treat thermally sensitive materials including polymers and biologic tissues. In this research, the non-thermal plasma system is designed with diameter (3 mm, 10 mm) Argon at atmospheric pressure as well as to be suitable for use in medical and biotechnological applications.
The thermal description of this system was studied and we observed the effect of the diameter of the plasma needle on the plasma, when the plasma needle slot is increased the plasma temperature decrease, as well as the effect of the voltages applied to the temperature of the plasma, where the temperature increasing with increasing the applied voltage . Results showed t

Dielectric barrier discharges (DBD) can be described as the presence of contact with the discharge of one or more insulating layers located between two cylindrical or flat electrodes connected to an AC/pulse dc power supply. In this work, the properties of the plasma generated by dielectric barrier discharge (DBD) system without and with a glass insulator were studied. The plasma was generated at a constant voltage of 4 kV and fixed distance between the electrodes of 5 mm, and with a variable flow rate of argon gas (0.5, 1, 1.5, 2 and 2.5) L/min. The emission spectra of the DBD plasmas at different flow rates of argon gas have been recorded. Boltzmann plot method was used to calculate the plasma electron temperature (Te), and Stark broadeni

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

The research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatements. The researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is