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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
Mon Dec 02 2013
Journal Name
Iraqi Medical Journal
Etiology and Antibiotic Sensitivity for Otitis Media in A Central Pediatric Teaching Hospital.
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Publication Date
Sat Dec 30 2023
Journal Name
Traitement Du Signal
Optimizing Acoustic Feature Selection for Estimating Speaker Traits: A Novel Threshold-Based Approach
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Mon Jan 01 2018
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Image And Video Technology: 8th Pacific-rim Symposium
A New Scheme for QoE Management of Live Video Streaming in Cloud Environment
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Publication Date
Fri Aug 10 2018
Journal Name
In Book: Challenges In Mechanics Of Time-dependent Materials, Volume 2edition: 1stchapter: 11
A Case Study to Evaluate Live Load Distributions for Pre-stressed RC Bridge
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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Environmental Management
Induced electro-fenton process with a new electrochemical reactor design for tetracycline degradation
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Publication Date
Sat Jul 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Polyacrylonitrile Nanofiber Composites as Efficient Removal of Pollutants for Wastewater: A Review Article
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Polyacrylonitrile nanofiber (PANFS), a well-known polymers, has been extensively employed in the manufacturing of carbon nanofibers (CNFS), which have recently gained substantial attention due to their excellent features, such as spinnability, environmental friendliness, and commercial feasibility. Because of their high carbon yield and versatility in tailoring the final CNFS structure, In addition to the simple formation of ladder structures through nitrile polymerization to yield stable products, CNFS and PAN have been the focus of extensive research as potential production precursors. For instance, the development of biomedical and high-performance composites has now become achievable. PAN homopolymer or PAN-based precursor copolymer can

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Publication Date
Mon Apr 07 2025
Journal Name
The Peerian Journal
Plant-Bacterial Interactions: A latent Alliance for Growth promotion and Environmental Stress Tolerance
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This encapsulates the general relationship between plant and bacteria in the natural and agricultural ecosystem. It is based on the activities of useful bacteria, such as plant growth-promoting bacteria (PGPRs) and nitrogen-fixing bacteria, in promoting plant growth and plant tolerance to stressful situations regarding pollution, salinity, and drought. The article also mentions that the bacteria maintain plant health by secretion of phytohormones, nitrogen fixation, solubilization of phosphate, and production of antibiotics against pathogenic bacteria. The article also mentions the existing applications of the interaction in sustainable agriculture and bioremediation of contaminated soils.

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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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 Jun 19 2023
Journal Name
Journal Of Polymer Research
Design, and synthesis of a plasticizer- Schiff’s bases complexes as additive for polystyrene
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This work involved the successful synthesis of three new Schiff base complexes, including Ni(II), Mn(II), and Cu(II) complexes. The Schiff base ligand was created by reacting the malonyldihydrazide molecule with naphthaldehyde, and the final step involved reacting the ligand with the corresponding metallic chloride yielding pure target complexes. FTIR, 1 H NMR, 13 C NMR, mass, and UV/Vis spectroscopies were used to comprehensively characterize the produced complexes. These substances have been employed in this study to photo-stabilize polystyrene (PS) and lessen the photo-degradation of its polymeric chains. Several methods, including FTIR, weight loss, viscosity average molecular weight, light and atomic force microscopy, and energy disper

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