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Creating a LabVIEW Sub VI for the INA219 Sensor for Detecting Extremely Low-Level Electrical Quantities
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An impressed current cathodic protection system (ICCP) requires measurements of extremely low-level quantities of its electrical characteristics. The current experimental work utilized the Adafruit INA219 sensor module for acquiring the values for voltage, current, and power of a default load, which consumes quite low power and simulates an ICCP system. The main problem is the adaptation of the INA219 sensor to the LabVIEW environment due to the absence of the library of this sensor. This work is devoted to the adaptation of the Adafruit INA219 sensor module in the LabVIEW environment through creating, developing, and successfully testing a Sub VI to be ready for employment in an ICCP system. The sensor output was monitored with an Arduino Uno microcontroller and the LabVIEW Linx firmware toolkit. Pulse Width Modulation (PWM) technique, which ranges from 0% to 100%, was applied by the Arduino to supply the l298N voltage driver in order to regulate the voltage input to the load. A moving average filter was employed to measure the ripple voltage averaging, and a median filter was utilized to stabilize the readings. A passive low-pass filter circuit smoothed the PWM voltage before supplying the load. The results from the MATLAB-Simulink environment showed a cut-off frequency of 2.33 Hz, ripple voltage peak to peak was 41.1 mV and a settling time of 0.157 seconds. The calibrated results of the INA219 module sensor showed an absolute voltage inaccuracy of around 2.3% at full scale. In addition, an absolute error in the current of 2.2% at 25 mA shows a gradual increase as the current increases to 7% at 43 mA, while the highest absolute error for the full scale of power was at 5.8%. The obtained measurements were highly precise, and the values of the coefficient of variation were 0.36 %, 0.28% and 0.17% for the voltage, current, and power, respectively.

 

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
Robust Adaptive Sliding Mode Controller for a Nonholonomic Mobile Platform
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In this paper, a robust adaptive sliding mode controller is designed for a mobile platform trajectory tracking.  The mobile platform is an example of a nonholonomic mechanical system. The presence of holonomic constraints reduces the number of degree of freedom that represents the system model, while the nonholonomic constraints reduce the differentiable degree of freedom. The mathematical model was derived here for the mobile platform, considering the existence of one holonomic and two nonholonomic constraints imposed on system dynamics. The partial feedback linearization method was used to get the input-output relation, where the output is the error functions between the position of a certain point on the platform

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Publication Date
Sun Jan 01 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
A reliable numerical simulation technique for solving COVID-19 model
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Publication Date
Sat Dec 01 2018
Journal Name
Ain Shams Engineering Journal
A semi-analytical iterative method for solving differential algebraic equations
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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
A New Operational Matrix of Derivative for Orthonormal Bernstein Polynomial's
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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Phase Behavior Compositional Model for Jambour Cretaceous Oil Reservoir
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Publication Date
Mon Jul 01 2019
Journal Name
2019 International Joint Conference On Neural Networks (ijcnn)
A Fast Feature Extraction Algorithm for Image and Video Processing
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Publication Date
Wed Oct 01 2008
Journal Name
2008 First International Conference On Distributed Framework And Applications
A strategy for Grid based t-way test data generation
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Publication Date
Tue Nov 01 2022
Journal Name
Japanese Dental Science Review
Pathogenesis of periodontitis – A potential role for epithelial-mesenchymal transition
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Epithelial mesenchymal transition (EMT) is a process comprising cellular and molecular events which result in cells shifting from an epithelial to a mesenchymal phenotype. Periodontitis is a destructive chronic disease of the periodontium initiated in response to a dysbiotic microbiome, and dominated by Gram-negative bacteria in the subgingival niches accompanied by an aberrant immune response in susceptible subjects. Both EMT and periodontitis share common risk factors and drivers, including Gram-negative bacteria, excess inflammatory cytokine production, smoking, oxidative stress and diabetes mellitus. In addition, periodontitis is characterized by down-regulation of key epithelial markers such as E-cadherin together with up-regulation of

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimator a Smoothing Technique for Estimating Regression Function
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    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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