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Corrosion Inhibition of Medium Carbon Steel in the Acidic Medium Using Alcoholic and Aqueous Extract of Kujarat Tea Plant
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This study deals with the corrosion inhibition of metal corrosion process of medium carbon steel using 1M HCl for kinetic studies and rate reaction determination. The weight loss method is applied to pieces of Medium carbon steel divided to Cubans with dimensions (0.4*2*2.4) cm , and use Tafel Extrapolation Method, the samples were polished using carbide silicon paper with dimensions of (180,200,400,600,800,1000). The samples were immersed in the alcoholic medium ethanol at a temperature 293K for 3hr. Natural inhibitor Kujarat Tea (Hibiscus sabdarriffa L.) is used which is extracted in aqueous and alcoholic medium, different concentrations (1000،2000, 3000) ppm have been used ; The best concentration found through the results is a concentration found that is 1000 and 2000 ppm, the results indicate that the highest degree of inhibition for aqueous extract is 93.3% with the concentration of 2000 ppm and 90.5% with 1000 ppm at293K. While the alcoholic inhibitor shows the highest efficiency 92.4% with a concentration of 2000 ppm and 88.6% with a concentration of 1000 ppm respectively. The structure of the inhibitor was investigated using infrared spectroscopy (FTIR), and the surface morphology of the tested samples was investigated using a scanning electron microscope (SEM).

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Publication Date
Tue Feb 24 2015
Journal Name
Robotica
Multi-level control of zero-moment point-based humanoid biped robots: a review
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SUMMARY<p>Researchers dream of developing autonomous humanoid robots which behave/walk like a human being. Biped robots, although complex, have the greatest potential for use in human-centred environments such as the home or office. Studying biped robots is also important for understanding human locomotion and improving control strategies for prosthetic and orthotic limbs. Control systems of humans walking in cluttered environments are complex, however, and may involve multiple local controllers and commands from the cerebellum. Although biped robots have been of interest over the last four decades, no unified stability/balance criterion adopted for stabilization of miscellaneous walking/running modes of biped </p> ... Show More
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Publication Date
Wed Dec 04 2013
Journal Name
Proceedings Of Nuclei Of Seyfert Galaxies And Qsos - Central Engine &amp; Conditions Of Star Formation — Pos(seyfert 2012)
Are Narrow Line Seyfert 1 galaxies a special class of Active Galactic Nuclei?
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No. Due to their apparently extreme optical to X-ray properties, Narrow Line Seyfert 1s (NLSy1s) have been considered a special class of active galactic nuclei (AGN). Here, we summarize observational results from different groups to conclude that none of the characteristics that are typically used to define the NLSy1s as a distinct group – from the, nowadays called, Broad Line Seyfert 1s (BLSy1s) – is unique, nor ubiquitous of these particular sources, but shared by the whole Type 1 AGN. Historically, the NLSy1s have been distinguished from the BLSy1s by the narrow width of the broad Hb emission line. The upper limit on the full width at half maximum of this line is 2000kms−1 for NLSy1s, while in BLSy1s it can be of several thousands

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Medicine And Life
Nephroprotective effect of vitamin D Against Levofloxacin-induced renal injury: an observational study
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Efficiency of CFRP torsional strengthening technique for L-shaped spandrel reinforced concrete beams
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Abstract<p>The present study aims to get experimentally a deeper understanding of the efficiency of carbon fiber-reinforced polymer (CFRP) sheets applied to improve the torsional behavior of L-shaped reinforced concrete spandrel beams in which their ledges were loaded in two stages under monotonic loading. An experimental program was conducted on spandrel beams considering different key parameters including the cross-sectional aspect ratio (<italic>i.e.</italic>, web height/web thickness), and the availability of the CFRP strengthening system. The ledge of the spandrel beams was exposed during testing to a very high eccentric load, which was transferred to the web of the spandrel beam </p> ... Show More
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Publication Date
Sat Jan 09 2021
Journal Name
Journal Of Control, Automation And Electrical Systems
Design of an Adaptive Linear Quadratic Regulator for a Twin Rotor Aerodynamic System
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Publication Date
Thu Dec 01 2022
Journal Name
Environmental Nanotechnology, Monitoring & Management
Boosted visible-light-driven photocatalytic degradation of lomefloxacin over α-Ag2WO4/NiSx nanocomposites
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Publication Date
Thu Mar 01 2018
Journal Name
Materials Today Communications
Improved mechanical properties of sol-gel derived ITO thin films via Ag doping
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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Mon Sep 04 2017
Journal Name
International Journal Of Environmental Science And Technology
A review of permeable reactive barrier as passive sustainable technology for groundwater remediation
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