Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

Background: Mental health is integrated into PHC as a strategy of WHO to fill the gap in mental health treatment. Part of this strategy needs a level of task shifting so that mental health care is provided by different level of PHC workers and not only specialists such as psychiatrists and psychologists.

Objectives: To assess the knowledge and attitudes of family doctors regarding the provision of psychological health in PHCC and if there is an association between the certificates of these family doctors and their Knowledge and attitudes to psychological health.

Subjects and Methods:  A cross-sectional descriptive study with analytic elements was conducted in 8 famil

The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) process for treatment of heavy metals wastewater contains zinc. In this research, the salt of heavy metals were zinc chloride (ZnCl2) used as feed solution.Nanofiltration and reverse osmosis membranes are made from polyamide as spiral wound module. The parameters studied were: operating time (0 – 70 min), feed concentrations for zinc ions (10 – 300 mg/l), operating pressure (1 – 4 bar).The theoretical results showed, flux of water through membrane decline from 19 to 10.85 LMH with time. Flux decrease from 25.84 to 10.88 LMH with the increment of feed concentration. The raise of pressure, the flux increase for NF and RO membranes.The maximum

In this study, hexadecyltrimethylammonium bromide (HDMAB) - bentonite was synthesized by placing alkylammonium cation onto bentonite. Adsorption of textile dye such as direct Yellow 50 on natural bentonite and HDMAB -bentonite was investigated. The effects of pH, contact time,dosage clay and temperature were investigated experimentally .The Langmuir and Freundlish isotherms equations were applied to the data and values of parameters of these isotherm equations were evaluated. The study indicated that using 0.2 g of HDMAB (hexadecyltrimethylammonium bromide) lead to increase the percentage removal(R%) from 78% for pure bentonite to 99 %. The optimum pH value for the adsorption experiments was found to be pH=3 and therefore all the experim

An agricultural waste (walnut shell) was undertaken to remove Cu(II) from aqueous solutions in batch and continuous fluidized bed processes. Walnut shell was found to be effective in batch reaching 75.55% at 20 and 200 rpm, when pH of the solution adjusted to 7. The equilibrium was achieved after 6 h of contacting time. The maximum uptake was 11.94mg/g. The isotherm models indicated that the highest determination coefficient belongs to Langmuir model. Cu (II) uptake process in kinetic rate model followed the pseudo-second-order with determination coefficient of 0.9972. More than 95% of the Cu(II) were adsorbed on the walnut shells within 6 h at optimum agitation speed of 800 rpm. The main functional groups responsible for biosorption of

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

     The main parameters and methods influencing the removal of Gentian Violet (GV) dye from aqueous media were investigated using a stachy plant in this study. The surface of the stachy plant was determined using FTIR spectra. Adsorption is influenced by the adsorbent's characteristic groups. The research took into account the usual conditions for GV dye adsorption by the stachy plant, such as the impact of contact time. Mass dosage , after 0.3 g the amount of adsorbed dye declines. Study pH and ionic strength, the results obtained showed that at pH 3 the largest adsorption of (GV) was seen, while at pH 9, the lowest adsorption was observed  at 298 K, the adsorption kinetics and equilibrium constants were achieved, and the equilibr

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