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Exploring electromembrane extraction and liquid membrane for efficient removal of heavy metals from aqueous solutions: An overview
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Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutants and environmental conditions remains uncharted. Future research must expand EME's applicability, assess its environmental impact versus other methods, and boost scalability, cost-effectiveness, and energy efficiency in industry. Advances in novel liquid membrane materials can enhance extraction efficiency and selectivity, aiming to provide efficient, sustainable industrial pollutant treatment. This research provides a review of the existing practices in the field of liquid membranes when coupled with the application of an electric field.

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Publication Date
Tue May 15 2018
Pre‐low noise amplifier (LNA) filtering linearisation method for low‐power ultra‐wideband complementary metal oxide semiconductor LNA
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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Polyvinyl Alcohol – Sodium Nitrite Water Soluble Composite as a Corrosion Inhibitor for Mild Steel in Simulated Cooling Water
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The inhibitive action of polyvinyl alcohol –sodium nitrite (PVASN) composite on the corrosion of mild steel in simulated cooling water (SCW) has been investigated by weight loss and potentiodynamic polarization. The effect of composite concentration (PVA/SN) , pH, and exposure time on corrosion rate of mild steel were verified using 2 levels factorial design and surface response analysis through weight loss approach, while the electrochemical measurements were used to study the behavior of mild steel in (SCW) with pH between 6 and 8 and in absence and presence of (PVA) in solution containing different concentration of NaNO2. It was verified that all three main variables studied were statistically significant while their interaction is

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Determination the Relationship between Some genetic Aspects with the Capsule Formation for Pathogenic Klebsiella pneumoniae Serotypes K1 &K2
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A total of 47 samples were collected from different clinical specimens (urine, wounds, burns, sputum, blood, stools) during the period from November 2013 to
January 2014, only 18 isolates (38.29%) were identified as Klebsiella pneumoniae ,11isolates (23.4%) as E. coli , 9 isolates (19.1%) as S. aureus, 3isolates (6.3%) as Psedomonase spp., 2 isolates (4.2 %) as K. terrigena and 4 isolates (8.5%) as K. oxytoca. The results were shown the elevation of K. pneumoniae percentage among the bacterial isolates depending on cultural, microscopically, biochemically characteristics and confirmed by using the API 20E and VITEK 2 system . Also K. pneumoniae isolates were more frequently in sputum samples then burns, stools , urine, wounds ,and blo

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Sliding mode control based on high-order extended state observer for flexible joint robot under time-varying disturbance
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Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

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Publication Date
Tue Mar 01 2022
Journal Name
Materials Today Communications
Fe2O3-SiO2 nanocomposite film-induced high nonlinear effect for multiwavelength mode-locked generation in ytterbium-doped fiber laser
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In this work, the possibility of a multiwavelength mode-locked fiber laser generation based on Four-Wave Mixing (FWM) induced by Fe2O3-SiO2 nanocomposite material is investigated for the first time. A multiwavelength mode-locked pulses fiber laser are generated from Ytterbium–doped fiber laser (YDFL) due to the combined action of high nonlinear absorption and high refractive coefficients of Fe2O3-SiO2 nanocomposite incorporated inside YDFL ring cavity. Up to more than 20 lasing lines in the 1040–1070 nm band with an equally lines separation of ~0.6 nm have been observed by just simple variation of passive modulation of the state of the polarization and the pump power altogether. Moreover, a passively mode-locked operation of YDFL laser

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Publication Date
Fri Oct 01 2021
Journal Name
International Journal Of Mechanical Engineering And Robotics Research
Proportional-Derivative PD Vibration Control with Adaptive Approximation Compensator for a Nonlinear Smart Thin Beam Interacting with Fluid
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This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

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Publication Date
Thu Oct 01 2020
Journal Name
Bulletin Of Electrical Engineering And Informatics
Lightweight hamming product code based multiple bit error correction coding scheme using shared resources for on chip interconnects
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In this paper, we present multiple bit error correction coding scheme based on extended Hamming product code combined with type II HARQ using shared resources for on chip interconnect. The shared resources reduce the hardware complexity of the encoder and decoder compared to the existing three stages iterative decoding method for on chip interconnects. The proposed method of decoding achieves 20% and 28% reduction in area and power consumption respectively, with only small increase in decoder delay compared to the existing three stage iterative decoding scheme for multiple bit error correction. The proposed code also achieves excellent improvement in residual flit error rate and up to 58% of total power consumption compared to the other err

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Publication Date
Tue Jan 01 2019
Wide-range tunable subwavelength band-stop filter for the far-infrared wavelengths based on single-layer graphene sheet
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