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Robust Continuous Sliding Mode Controller for Uncertain Canonical Brunovsky Systems Using Reduced Order Extended State Observer
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A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its estimation error. Finally, the tracking performance is examined by carrying out several simulations on robotic systems with compliant actuators as an application example of the high order systems. In addition, the comparative study is conducted between the proposed SMC method with RESO and a feedback linearization control (FLC) with a full-order ESO to confirm the estimation and tracking performance of the proposed scheme.

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Publication Date
Tue Jun 24 2025
Journal Name
Food And Bioprocess Technology
Classification of Apple Slices Treated by Atmospheric Plasma Jet for Post-harvest Processes Using Image Processing and Convolutional Neural Networks
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Abstract<p>Apple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin</p> ... Show More
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Publication Date
Tue Feb 22 2022
Journal Name
Watre
Subsurface Flow Phytoremediation Using Barley Plants for Water Recovery from Kerosene-Contaminated Water: Effect of Kerosene Concentration and Removal Kinetics
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A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu

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Publication Date
Thu Jun 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Investigation of evaluated temperature oxidation for IN-738 LC superalloy turbine blade thermally coated by AL2O3 using slurry coating process
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The study aims to investigate the effect of Al2O3 and Al additions to Nickel-base superalloys as a coating layer on oxidation resistance, and structural behavior of nickel superalloys such as IN 738 LC. Nickel-base superalloys are popular as base materials for hot components in industrial gas turbines such as blades due to their superior mechanical performance and high-temperature oxidation resistance, but the combustion gases' existence generates hot oxidation at high temperatures for long durations of time, resulting in corrosion of turbine blades which lead to massive economic losses. Turbine blades used in Iraqi electrical gas power stations require costly maintenance using traditional processes regularly. These blades are made

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation the annual dose for residents in the area around the berms of Al-Tuwaitha nuclear site using RESRAD software
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RESRAD is a computer model designed to estimate risks and radiation doses from residual radioactive materials in soil. Thirty seven soil samples were collected from the area around the berms of Al-Tuwaitha site and two samples as background taken from an area about 3 km north of the site. The samples were measured by gamma-ray spectrometry system using high purity germanium (HPGe) detector. The results of samples measurements showed that three contaminated area with 238U and 235U found in the study area. Two scenarios were applied for each contaminated area to estimate the dose using RESRAD (onsite) version 7.0 code. The total dose of resident farmer scenario for area A, B and C are 0.854, 0.033 and 2.15×10-3 mSv.yr-1, respectively. Whi

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Publication Date
Mon Aug 05 2024
Journal Name
Pharmacia
A validated spectrophotometric analysis for simultaneous estimation of vincristine sulfate and bovine serum albumin in pure preparations using Vierordt’s method
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The novel Vierordt’s approach, or simultaneous equation method, was created and validated for the concurrent determination of vincristine sulfate (VCS) and bovine serum albumin (BSA) in pure solutions utilizing UV spectrophotometry. It is simple, precise, economical, rapid, reliable, and accurate. This method depends on measuring absorbance at two wavelengths, 296 nm and 278 nm, which correspond to the λmax of VCS and BSA in deionized water, respectively. The calibration curves of VCS and BSA are linear at concentration ranges of 10–60 μg/mL and 200–1600 μg/mL, with correlation coefficient values (R2) of 1 and 0.999, respectively. The limits of detection (LOD) and quantification (LO

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Ocular Pharmacology And Therapeutics
Formulation and<i>In Vitro</i>Evaluation of Cyclosporine-A Inserts Prepared Using Hydroxypropyl Methylcellulose for Treating Dry Eye Disease
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Publication Date
Wed Sep 21 2022
Journal Name
Journal Of Thermoplastic Composite Materials
Enhancement of thermal characteristics of flexible poly(vinyl chloride) for automotive applications by using environmentally friendly heavy metal-free modifier
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This work intends to develop an effective heavy metal-free modifier having properties comparable to traditional stabilizers and flame retardants, simultaneously being environmentally friendly and may be superior in many aspects. The important requirement focused on is: how to increase thermal stability and flame retardancy of flexible poly(vinyl chloride). Due to the typical materials now used with poly(vinyl chloride), which increases health and environmental concerns, utilizing a novel heavy metal-free additive will make poly(vinyl chloride) substantially safer. We have used an artificial silicate for this aim, which proved to be an efficient flame retardant and surprisingly showed excellent heat stabilizing effect. Thermal stabi

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Sat Nov 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Optimizing Irrigation Water Quality Index Along the Tigris River Using Gravitational Search Algorithm: A Novel Approach for Sustainable Water Management
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Abstract<p>The Tigris River, a vital water resource for Iraq, faces significant challenges due to urbanization, agricultural runoff, industrial discharges, and climate change, leading to deteriorating water quality. Traditional methods for assessing irrigation water quality, such as laboratory testing and statistical modeling, are often insufficient for capturing dynamic and nonlinear relationships between parameters. This study proposes a novel application of the Gravitational Search Algorithm (GSA) to estimate the Irrigation Water Quality Index (IWQI) along the Tigris River. Using data from multiple stations, the study evaluates spatial variability in water quality, focusing on key paramete</p> ... Show More
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