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Proxy-based sliding mode vibration control with an adaptive approximation compensator for euler-bernoulli smart beams
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Proxy-based sliding mode control PSMC is an improved version of PID control that combines the features of PID and sliding mode control SMC with continuously dynamic behaviour. However, the stability of the control architecture maybe not well addressed. Consequently, this work is focused on modification of the original version of the proxy-based sliding mode control PSMC by adding an adaptive approximation compensator AAC term for vibration control of an Euler-Bernoulli beam. The role of the AAC term is to compensate for unmodelled dynamics and make the stability proof more easily. The stability of the proposed control algorithm is systematically proved using Lyapunov theory. Multi-modal equation of motion is derived using the Galerkin method. The state variables of the multi-modal equation are expressed in terms of modal amplitudes that should be regulated via the proposed control system. The proposed control structure is implemented on a simply supported beam with two piezo-patches. The simulation experiments are performed using MATLAB/SIMULINK package. The locations of piezo-transducers are optimally placed on the beam. A detailed comparison study is implemented including three scenarios. Scenario 1 includes disturbing the smart beam while no feedback loop is established (open-loop system). In scenario 2, a PD controller is applied on the vibrating beam. Whereas, scenario 3 includes implementation of the PSMC+AAC. For all previously mentioned scenarios, two types of disturbances are applied separately: 1) an impulse force of 1 N peak and 1 s pulse width, and 2) a sinusoidal disturbance with 0.5 N amplitude and 20 Hz frequency. For impulse disturbance signals, the results show the superiority of the PSMC+AAC in comparison with the conventional PD control. Whereas, both the PSMC+ACC and the PD control work well in the case of a sinusoidal disturbance signal and the superiority of the PSMC is not clear.

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Publication Date
Sun Mar 01 2015
Journal Name
Craniomaxillofacial Trauma & Reconstruction
Mandibular Fractures in Iraq: An Epidemiological Study
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The purpose of this study was to evaluate the epidemiological characteristics of the mandibular fractures relating to gender, age, the etiology of injury, and the rendered treatment modalities and complications. The data of the patients who sustained mandibular fractures were retrieved and were analyzed retrospectively, and based on these data a descriptive analysis was conducted. A total of 112 patients were included in this study; the most common cause was road traffic accidents (RTAs) followed by assaults and missile injuries. The most frequently involved age group was 11 to 20 years, treatment modalities included conservative, closed reduction and indirect fixation, and open reduction and internal fixation (ORIF) in 11.6, 79.5, and 8.9%

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
CVOTING: An Anonymous Ballot E-Voting System
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One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

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Publication Date
Thu Sep 16 2021
Journal Name
International Journal Of Clinical Practice
An overview of post‐COVID‐19 complications
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Tue Sep 14 2021
Journal Name
Nature Reviews Microbiology
Towards an integrative view of virus phenotypes
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Publication Date
Sun Sep 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Rhabdomyolysis; is it an overlooked DKA complication
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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Electrofacies Characterization of an Iraqi Carbonate Reservoir
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

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Publication Date
Mon Apr 01 2024
Journal Name
Materials Science In Semiconductor Processing
Rational design of novel 0D/0D Bi2Sn2O7/CeO2 in the core-shell nanostructure for boosting the photocatalytic decomposition of antibiotics in wastewater: S-type-based mechanism
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Publication Date
Wed Dec 20 2023
Journal Name
Migration Letters
Women's Image in Arabic Songs (An Analytical Study of how Women Appear in the Most Viewed Songs on YouTube for the Year 2021)
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Publication Date
Sun Jan 17 2021
Journal Name
Academic Journal Of Interdisciplinary Studies
Employees Retention Strategy and its Impact on Organizational Memory: An Exploratory Research for the opinion of Faculty Members at Private Colleges on Baghdad
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The research aims to determine the impact of employees’ retention strategy on organizational memory. This research is historical, descriptive, and analytical. The sample consists of 158 faculty members in five private colleges in Baghdad. The technique used to analyze the data is SEM (Structural Equation Modeling), and SPSS (Statistical Package for the Social Sciences). The research concludes that the employees retaining strategy plays a vital role in retaining employees and hence maintains organizational memory. The findings and recommendations of this research assure the administrations of private colleges that employees retention strategy play a vital role in retaining its employee and hence maintains organizational memory. T

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