Performance of gas-solid spouted bed benefit from solids uniformity structure (UI).Therefore, the focus of this work is to maximize UI across the bed based on process variables. Hence, UI is to be considered as the objective of the optimization process .Three selected process variables are affecting the objective function. These decision variables are: gas velocity, particle density and particle diameter. Steady-state solids concentration measurements were carried out in a narrow 3-inch cylindrical spouted bed made of Plexiglas that used 60° conical shape base. Radial concentration of particles (glass and steel beads) at various bed heights and different flow patterns were measured using sophisticated optical probes. Stochastic Genetic Algorithm (GA) has been found better than deterministic search for study mutation of process variables of the non-linear bed. Spouted bed behaved as hybrid system. Global GA could provide confirmed data and selected best operating conditions. Optimization technique would guide the experimental work and reduce the risk and cost of operation. Optimum results could improve operating of the bed at high-performance and stable conditions. Maximum uniformity has been found at high-density, small size of solid beads and low gas velocity. Density of solids has been effective variable on UI.Velocity of gas and diameter of solid particles has been observed more sensitive decision variables with UI mutations. Uniformity of solid particles would enhance hydrodynamic parameters, heat and mass transfer in the bed because of improving of hold-up and voids distributions of solids. The results of the optimization have been compared with the experimental data using sophisticated optical probe and Computed Tomography technique.
In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption. No significant effect of initial Cd concentration on the removal efficie
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Treatment of a high strength acidic industrial wastewater was attempted by activated carbon
adsorption to evaluate the feasibility of yielding effluents of reusable qualities. The experimental
methods which were employed in this investigation included batch and column studies. The
former was used to evaluate the rate and equilibrium of carbon adsorption, while the latter was
used to determine treatment efficiencies and performance characteristics. Fixed bed and expanded
bed adsorbers were constructed in the column studies. In this study, the adsorption behavior of acetic acid onto activated carbon was examined as a function of the concentration of the adsorbate, contact time and adsorbent dosage. The adsorption data was mo
Cloud computing describes computer services provided through the internet and includes a wide range of virtualization resources. Because cloud computing is made up of a sizable number of heterogeneous autonomous systems with an adaptable computational architecture, it has been widely adopted by many businesses. The scheduling and management of resource utilization, however, have become more difficult as a result of cloud computing. Task scheduling is crucial, and this procedure must schedule tasks on the virtual machine while using the least amount of time possible. Utilizing an effective scheduling strategy enhances and expedites cloud computing services. Optimization techniques are used to resolve cloud scheduling problems.
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Nano- particles (Ag NPs) are synthesized by using plasma Jet argon gas. The prepared Ag NPs are characterized by Atomic Absorption Spectroscopy (AAS) The measure was performed for different time exposuring 15,30,45 and 60 sec. The results shows the low concentration of nano-silver time expose (15 sec) and very) and high concentration at 60 sec. The UV-VIS spectrometer for nano-silver different time exsposuring to plasma, shows the Surface Plasmon Resonance (SPR) appeared around 419 nm, and the energy gab is 4.1 eV for the 15 second exposure and 1.6eV for 60 second exposure. The Scanning Probe Microscope (SPM) is used to identify the characterization of silver nanoparticles, the average diameter of nano-silver for 15 second exp
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Nanosilica was extracted from rice husk, which was locally collected from the Iraqi mill at Al-Mishikhab district in Najaf Governorate, Iraq. The precipitation method was used to prepared Nanosilica powder from rice husk ash, after treating it thermally at 700°C, followed by dissolving the silica in the alkaline solution and getting a sodium silicate solution. Two samples of the final solution were collected to study the effect of filtration on the purity of the sample by X-ray fluorescence spectrometry (XRF). The result shows that the filtered samples have purity above while the non-filtered sample purity was around The structure analysis investigated by the X-ray diffraction (XRD), found that the Nanosilica powder has an amorphous
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The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w
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In this study some generic commercial products of Atorvastatin tablets were evaluated by dissolution test in acid medium by comparing with that of parent drug Lipitor of Pfizer Company. Some of solubilizing agents were studied in formulation of Atorvastatin tablet including; surface active agent and PEG 6000 .The most effective factor was the use of PEG6000 in formulation of Atorvastatin tablet which improved the dissolution and the results of dissolution profile of formulated tablet in this work was bioequivalent to that of Lipitor .The quantitative analysis of this work was performed by using reversed phase liquid chromatography and a proper mixture of  
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Many of the key stream generators which are used in practice are LFSR-based in the sense that they produce the key stream according to a rule y = C(L(x)), where L(x) denotes an internal linear bit stream, produced by small number of parallel linear feedback shift registers (LFSRs), and C denotes some nonlinear compression function. In this paper we combine between the output sequences from the linear feedback shift registers with the sequences out from non linear key generator to get the final very strong key sequence
A fuzzy valued diffusion term, which in a fuzzy stochastic differential equation refers to one-dimensional Brownian motion, is defined by the meaning of the stochastic integral of a fuzzy process. In this paper, the existence and uniqueness theorem of fuzzy stochastic ordinary differential equations, based on the mean square convergence of the mathematical induction approximations to the associated stochastic integral equation, are stated and demonstrated.
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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