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Waste Water Treatment by Liquid-Solid Adsorption Using Calcined Sand-Clay Mixture Adsorbent
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Effluent from incompetent wastewater treatment plants (WWTPs) contains a great variety of pollutants so support water treatments are essential. The present work studies the removal of phosphate species from aqueous solutions by adsorption on to spherical Calcined Sand -Clay mixture (CSCM) used a natural, local and low-cost adsorbent. Batch experiments were performed to estimate removal efficiency of phosphate. The adsorption experiments were carried out as function of pH, dose of adsorbent, initial concentration, temperature and time of adsorption. The efficient removal was accomplished for pH between 10 and 12. The experimental results also showed that the removal of phosphate by (CSCM) was rapid (the % removal 98.9%, 92%, 90%, 89% in 60 min) when the initial phosphate concentrations were at  5, 10, 15, 20 mg/l, respectively at optimum PH 10-12 and optimum dose was 5 gm/200ml.   The adsorption process is time dependent. Thermodynamic studies showed that phosphate adsorption was exothermic. The effect of temperature range of 15-30 °C has been investigated. The results indicated that the temperature significantly affected phosphate adsorption on (CSCM)  adsorbent. Langmuir and Freundlich  isotherms models indicated that both isotherms were proper to describe the adsorption characteristics of (CSCM), with Langmuir being more fit.  Adsorption capacity of phosphate had equal to 0.835 mg phosphorous/g adsorbent. The study reveal that calcined sand-clay mixture is an excellent low cost material for phosphate removal in wastewater treatment process .

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Determination of Reservoir Hydraulic Flow Units and Permeability Estimation Using Flow Zone Indicator Method
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   Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
Cadmium removal using a spiral-wound woven wire meshes packed bed rotating cylinder electrode
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The effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or

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Publication Date
Wed Aug 25 2021
Journal Name
Caai Transactions On Intelligence Technology
Shoulder girdle recognition using electrophysiological and low frequency anatomical contraction signals for prosthesis control
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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Semiparametric Bayesian Method with Classical Method for Estimating Systems Reliability using Simulation Procedure
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               In this research, the semiparametric Bayesian method is compared with the classical  method to  estimate reliability function of three  systems :  k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has be

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Publication Date
Wed Mar 01 2017
Journal Name
Journal Of Craniofacial Surgery
Lateral Ridge Splitting (Expansion) With Immediate Placement of Endosseous Dental Implant Using Piezoelectric Device
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Assessment of image quality of cervical spine complications using Three Magnetic Resonance Imaging Sequences
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Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Comparative Study of Image Denoising Using Wavelet Transforms and Optimal Threshold and Neighbouring Window
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NeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among

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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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