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Design and Simulation of L1-Adaptive Controller for Position Control of DC Servomotor
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This paper presents L1-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L1-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L1-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L1-adaptive controller ensured uniformly bounded transient and asymptotic tracking for both system's input and output signals, simultaneously with asymptotic tracking. Simulations of a DC servomotor with time-varying friction and disturbance are presented to verify the theoretical findings.

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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering & Science (iconmeas 2019)
A kinetic model for prodigiosin production by Serratia marcescens as a bio-colorant in bioreactor
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Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Modis Satellite Data Evaluation for Detecting the Dust Storm Using Remote Sensing Techniques Over Iraq
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Abstract<p>The phenomena of Dust storm take place in barren and dry regions all over the world. It may cause by intense ground winds which excite the dust and sand from soft, arid land surfaces resulting it to rise up in the air. These phenomena may cause harmful influences upon health, climate, infrastructure, and transportation. GIS and remote sensing have played a key role in studying dust detection. This study was conducted in Iraq with the objective of validating dust detection. These techniques have been used to derive dust indices using Normalized Difference Dust Index (NDDI) and Middle East Dust Index (MEDI), which are based on images from MODIS and in-situ observation based on hourly wi</p> ... Show More
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Publication Date
Fri Feb 24 2023
Journal Name
Membranes
Enhanced Antifouling in Flat-Sheet Polyphenylsulfone Membranes Incorporating Graphene Oxide–Tungsten Oxide for Ultrafiltration Applications
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In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f

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Publication Date
Thu Oct 21 2021
Journal Name
Physical Review E
Lattice Boltzmann method with moment-based boundary conditions for rarefied flow in the slip regime
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Publication Date
Mon Nov 28 2022
Journal Name
F1000research
In vitro apical microleakage evaluation for different endodontic sealers by spectrophotometric analysis: an observational study
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Background: It has been established that several filling techniques can affect apical leakage, which is responsible for 59% of endodontic failures. The primary goal of endodontic therapy is to create a tight seal that aids in repairing the periapical tissues, prevents apical periodontitis, and shields against root canal infection. The study aims to compare the apical sealing ability of epoxy resin based sealer  (AH plus), which is an epoxy-resin-based root canal sealer, GuttaFlow 2, which is a silicone-based root canal sealer, GuttaFlow bioseal is a bioactive glass-based root canal sealer, TotalFill HiFlow bioceramic (BC) sealer is a silicate-based root canal sealer (bioceramic sealer) using a single cone techn

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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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