The development of a new, cheap, efficient, and ecofriendly adsorbents has become an important demand for the treatment of waste water, so nano silica is considered a good choice. A sample of nanosilica (NS) was prepared from sodium silicate as precursor and the nonionic surfactant Tween 20 as a template. The prepared sample was characterized using various characterization techniques such as FT-IR, AFM, SEM and EDX analysis. The spectrum of FTIR confirms the presence of silica in the sample, while SEM analysis of sample shows nanostructures with pore ranging (2-100nm).The adsorptive properties of this sample were studied by removing Congo red dye (CR) from aqueous solution. Batch experimental methods were carried o

The current study was to examine the reliability and effectiveness of using most abundant, inexpensive waste in the form of scrap raw zero valent aluminum ZVAI and zero valent iron ZVI for the capture, retard, and removal of one of the most serious and hazardous heavy metals cadmium dissolved in water. Batch tests were conducted to examine contact time (0-250) min, sorbent dose (0.25-1 g ZVAI/100 mL and 2-8 g ZVI/100 mL), initial pH (3-6), pollutant concentration of 50mg/L initially, and speed of agitation (0-250) rpm . Maximum contaminant removal efficiency corresponding to (90 %) for cadmium at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed wer

This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in go

Removing of terasil yellow (W-6GS) dye it was studied by using Iraqi Siliceous Rocks Powder (SRP). The study included adsorption isotherms and some effects: temperature, salty medium and the acidity the study that the adsorption isotherms obeys to Temkin equation more than other equations the results showed that the adsorption increased with increasing temperature (Endothermic process. Based on the results, thermodynamic functions (˜H, ˜G, ˜S) were estimated. The amount of adsorbent on the surface increasing with increasing the acidity solution. The kinetics study of the adsorption treated according (Lagergren equation). The kinetic data of experiments properly correlated with the first order kinetic equation.

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

ان تصنيع رمال مطلية بأوكسيد الحديد من خلال ترسيب الجزيئات النانوية لذلك الاوكسيد على سطوح الرمال واستخدامها في الحاجز التفاعلي النفاذ لإزالة ايونات الكادميوم والنحاس من المياه الجوفية الملوثة الهدف الرئيسي للدراسة الحالية. تم توصيف بيانات الامتزاز نتيجة تفاعل المادة المازة مع المادة الممتزة قيد الدراسة بشكل جيد من خلال نموذج لانكمير والذي كان أفضل من نموذج فراندلش. لقد وجد ان اعلى قيم لقابلية الامتزاز با

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.