Heavy metals especially lead (Pb), cadmium (Cd), chromium (Cr) and copper (Cu) are noxious pollutants with immense health hazards on living organisms, these pollutants enter aquatic environment in Iraq mainly Tigris and Euphrates rivers via waste water came from different anthropological activities, This study investigated capacity of dried and ground root of water hyacinth (Eichhornia crassipes) in removing the heavy metals from their aqueous solutions. Effects of initial concentrations of the heavy metals and pH of their aqueous solutions were studied. Results of this study revealed excellent biosorption capacity of water hyacinth root in general, removal of Pb was the highest and Cr was lowest. The results showed that the Pb, Cu and Cr removal increased as their initial concentrations increased, with maximum removal of Pb and Cu was in 1000 ppm 99.66% and 96.63% respectively and 85% was the maximum removal of Cr in 750 ppm, in contrast Cd maximum removal was in 250 ppm and the adsorption decreased as initial concentrations increased. Removal of Pb, Cu and Cr was maximum with pH 4 and 5, while Cd removal was maximum with pH 8. This study paves the way to use water hyacinth in many applications to remove the heavy metals especially in waste water treatment plants.
This paper proposes a novel method for generating True Random Numbers (TRNs) using electromechanical switches. The proposed generator is implemented using an FPGA board. The system utilizes the phenomenon of electromechanical switch bounce to produce a randomly fluctuated signal that is used to trigger a counter to generate a binary random number. Compared to other true random number generation methods, the proposed approach features a high degree of randomness using a simple circuit that can be easily built using off-the-shelf components. The proposed system is implemented using a commercial relay circuit connected to an FPGA board that is used to process and record the generated random sequences. Applying statistical testing on the exp
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In this paper Volterra Runge-Kutta methods which include: method of order two and four will be applied to general nonlinear Volterra integral equations of the second kind. Moreover we study the convergent of the algorithms of Volterra Runge-Kutta methods. Finally, programs for each method are written in MATLAB language and a comparison between the two types has been made depending on the least square errors.
* Khalifa E. Sharquie1, Hayder Al-Hamamy2, Adil A. Noaimi1, Mohammed A. Al-Marsomy3, Husam Ali Salman4, American Journal of Dermatology and Venereology, 2014 - Cited by 2
Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks
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This paper addresses the use of adaptive sliding mode control for the servo actuator system with friction. The adaptive sliding mode control has several advantages over traditional sliding mode control method. Firstly, the magnitude of control effort is reduced to the minimal admissible level defined by the conditions for the sliding mode to exist. Secondly, the upper bounds of uncertainties are not required to be known in advance. Therefore, adaptive sliding mode control method can be effectively implemented. The numerical simulation via MATLAB 2014a for servo actuator system with friction is investigated to confirm the effectiveness of the proposed robust adaptive sliding mode control scheme. The results clarify, after
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An automatic text summarization system mimics how humans summarize by picking the most significant sentences in a source text. However, the complexities of the Arabic language have become challenging to obtain information quickly and effectively. The main disadvantage of the traditional approaches is that they are strictly constrained (especially for the Arabic language) by the accuracy of sentence feature functions, weighting schemes, and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha
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