The effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or

This paper deals with a method called Statistical Energy Analysis that can be applied to the mechanical and acoustical systems like buildings, bridges and aircrafts …etc. S.E.A as a tool can be applied to the resonant systems in the circumstances of high frequency or/and complex structure». The parameters of S.E.A such as coupling loss factor, internal loss factor, modal density and input power are clarified in this work ; coupled plate sub-systems and explanations are presented for these parameters. The developed system is assumed to be resonant, conservative, linear and there is an equipartition of energy between all the resonant modes within a given frequency band in a given sub-system. The aim of th

Lead remediation was achieved using simple cost, effective and eco-friendly way from industrial wastewater. Phragmitesaustralis (P.a) (Iraqi plant), was used as anovel biomaterial to remove lead ions from synthesized waste water. Different parameters which affected on adsorption processes were investigated like adsorbent dose, pH, contact time, and adsorbent particle size, to reach the optimized conditions (maximum adsorption). The adsorption of Pb (?) on (P.a) involved fast and slow process as a mechanism steps according to obey two theoretical adsorption isotherms; Langmuir and Freundlich. The thermos dynamic adsorption parameters were evaluated also. The (?H) obtained positive value that meanes adsorption of lead ions was an endothermic

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

This paper deals with the modeling of a preventive maintenance strategy applied to a single-unit system subject to random failures.

According to this policy, the system is subjected to imperfect periodic preventive maintenance restoring it to ‘as good as new’ with probability

p and leaving it at state ‘as bad as old’ with probability q. Imperfect repairs are performed following failures occurring between consecutive

preventive maintenance actions, i.e the times between failures follow a decreasing quasi-renewal process with parameter a. Considering the

average durations of the preventive and corrective maintenance actions a

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of