Industrial wastewater containing nickel, lead, and copper can be produced by many industries. The reverse osmosis (RO) membrane technologies are very efficient for the treatment of industrial wastewater containing nickel, lead, and copper ions to reduce water consumption and preserving the environment. Synthetic industrial wastewater samples containing Ni(II), Pb(II), and Cu(II) ions at various concentrations (50 to 200 ppm), pressures (1 to 4 bar), temperatures (10 to 40 ^oC), pH (2 to 5.5), and flow rates (10 to 40 L/hr), were prepared and subjected to treatment by RO system in the laboratory. The results showed that high removal efficiency of the heavy metals could be achieved by RO process (98.5%, 97.5% and 96% for Ni(II),

The corrosion behavior of carbon steel at different temperatures 100,120,140 and 160 Cͦ under different pressures 7,10 and 13 bar in pure distilled water and after adding three types of oxygen scavengers Hydroquinone, Ascorbic acid and Monoethanolamine in different concentrations 40,60 and 80 ppm has been investigated using weight loss method. The carbon steel specimens were immersed in water containing 8.2 ppm dissolved oxygen (DO) by using autoclave. It was found that corrosion behavior of carbon steel was greatly influenced by temperature with high pressure. The corrosion rate decreases, when adding any one of oxygen scavengers. The best results were obtained at a concentration of 80 ppm of each scavenger. It was observed that 

Chlorinated volatile organic compounds (CVOCs) are toxic chemical entities emitted invariably from stationary thermal operations when a trace of chlorine is present. Replacing the high-temperature destruction operations of these compounds with catalytic oxidation has led to the formulation of various potent metal oxides catalysts; among them are ceria-based materials. Guided by recent experimental measurements, this study theoretically investigates the initial steps operating in the interactions of ceria surface CeO2(111) with three CVOC model compounds, namely chloroethene (CE), chloroethane (CA) and chlorobenzene (CB). We find that, the CeO2(111) surface mediates fission of the carbon–chlorine bonds in the CE, CA and CB molecules via mo

Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

BOOK REVIEW

 Thin films of tin disulphide SnS2 with different thicknesses (2500,4000,5000)A0 have been prepared by chemical spray pyrolises technique on substrate of glass with temperature (603)K .  The effect of thickness on the optical properties of SnS2 has been studied.the optical  study that includes the absorptance and transmittance spectra in the wavelength range (300900)nm demonstrated that the value of absorption coefficient (α) ) was greater than (104 cm-1) the  electronic transitions at the fundamental absorption edge were of the indirect kind whether allowed and forbidden . Absorption edge shift slightly towards higher wave  length.The value of energy gaps (Eg) for all the films prepared are decreased with inc

     This paper presents an IoT smart building platform with fog and cloud computing capable of performing near real-time predictive analytics in fog nodes. The researchers explained thoroughly the internet of things in smart buildings, the big data analytics, and the fog and cloud computing technologies. They then presented the smart platform, its requirements, and its components. The datasets on which the analytics will be run will be displayed. The linear regression and the support vector regression data mining techniques are presented. Those two machine learning models are implemented with the appropriate techniques, starting by cleaning and preparing the data visualization and uncovering hidden information about the behavior of