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FAT-based adaptive backstepping control of an electromechanical system with an unknown input coefficient
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This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used as a strong approximator for estimation of uncertainty. The designed control law includes three terms: a feedforward term, a feedback term and a robust term for compensation of modeling error. Lyapunov stability is used to prove the validity of the proposed controller and to derive the update laws for the weighting vectors of orthogonal Chebyshev approximators. A case study of a geared DC motor in connection with a rotating output load is simulated to prove the effectiveness of the proposed controller structure.

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Publication Date
Sat Oct 10 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Color Stability of Different Aesthetic Archwires (An In vitro study)
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Background: Coated aesthetic archwires are currently the existing solutions for the esthetic problem, but the color of these archwires tends to change overtime. This study was aimed to evaluate the color stability of different types of esthetic archwires from four different companies at different time periods after immersion of two different staining drinks which are tea and Pepsi cola. Materials and methods: 48 specimens were prepared, each specimen contains 10 aesthetic archwires; and were divided according to type of solution into two groups: A (tea) &B (Pepsi cola); each group contained 24 specimens (12 specimens were immersed in the staining solution as 4 specimens for each time intervals and 12 specimens were immersed in distilled wa

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Publication Date
Thu Dec 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Evaluation of Solid-Solid Mixing in an Air Fluidized Bed
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Publication Date
Wed Jan 01 2025
Journal Name
Smart Innovation, Systems And Technologies
An Exploration of Current Trends for Enhancing Multimedia Transfer Efficiency
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This report explores emerging techniques to boost multimedia transfer effectiveness, given the escalating need for improved quality and performance in multimedia interactions. The analysis involves a thorough literature assessment and comparison of present strategies to pinpoint key tendencies and propose novel approaches. The methodology involves examining recent technological enhance ments in video coding standards, quality appraisal methods, and compression tech niques. Specific domains investigated comprise firmware component architectures, 4D indexing structures, and iterative filtering frameworks. The study in addition weighs tradeoffs between video quality, encoding intricacy, and bitrate demands. Key determinations consist of

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to t

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Geological Journal
Construction of Comprehensive Geological Model for an Iraqi Oil Reservoir
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The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie

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Publication Date
Sun Feb 01 2026
Journal Name
Applied Acoustics
Development of an acoustic vacuum gauge for low-pressure measurement
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Fri Apr 01 2016
Journal Name
Nurse Education Today
Diabetes knowledge of nurses in different countries: An integrative review
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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
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      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of an education program for Caregivers Knowledge Related to Management of Children with Growth Hormone Deficiency in Outpatient Endocrine Clinics
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Objectives: The study aims to assess and evaluate the caregivers  knowledge  about management of the children with growth hormone deficiency and to find out the relationship between caregivers kowledge and caregivers age, gender, number of individual in house hold, Date of treatment started ,Caregivers level education and economic status Methodology: Quazi expermental study design was carried out at (Child's Central Teaching Hospital, Medical City of Al Imamian Al Khadhmain Teaching Hospital, and National Centre for Treatment and Research of Diabetes,Specialized Center for Endocrine Diseases and Diabetes, and Department of Medical City Children Welfare Teaching Hospital started  from 

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