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Sliding Mode Vibration Suppression Control Design for a Smart Beam
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Active vibration control is the main problem in different structure. Smart material like piezoelectric make a structure smart, adaptive and self-controlling so, they are effective in active vibration control. In this paper piezoelectric elements are used as sensors and actuators in flexible structures for sensing and actuating purposes, and to control the vibration of a cantilever beam by using sliding mode control. The sliding mode controller (SMC) is designed to attenuate the vibration induced by initial tip displacement which is equal to 15 mm.  It is designed based on the balance realization reduction method where three states are selected for the reduced model from the 24th states that describe the cantilever beam according to the FEM. These states are most controllable and observable. The stability and control performance for the proposed SMC are proved using candidate Lyapunov function and the equivalent control concept. The control spillover, which is the sources of instability, is completely avoided as ensured within the control performance proof.

            Numerical simulations are preformed to test the vibration attenuation ability of the proposed SMC. For 15 mm initial tip displacement, the piezoelectric actuator was found able to reduce the tip displacement to about (0.2) mm within (2.5 s), while it is equal to (3.5) mm with the open loop case. Moreover, the induced chattering in system response, due to the discontinuous control action, is removed by approximating the signum function by a continuous arctan function. As a result  a smoother response are obtained with the same control performance as can be shown in the sliding variable, the control input voltage and the tip displacement plots.

 

 

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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
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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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
Tue Jan 01 2019
Journal Name
Energy Procedia
Quadrupole Moment & Deformation Parameter for Even-Even 38Sr (A=76-102) Nuclide
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Popular naming for goods and materials in the Iraqi slang "A Semantic Study"
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The current research is concerned with the prices of Goods and materials in the Iraqi slang a descriptive, lexicographic , and semantic study expressing the meanings of these names and their positions , as well as expressing the imaginations of Human mind , the popular mind in describing these goods with evaluating them besides the semantic of each word accordingly
The current research is divided into two parts , the first part is consisted of Vocalizations" words" That are arisen through cognitive naming that concentrate on the mental imaginations for the most important and sensitive such as colors , taste , shapes and forms impacts of Goods and materials according to users' ' taste for those words , on other hand, the second part of

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Using a New Modification on Wind Turbine Ventilator for Improving Indoor Air Quality
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This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Promoting Clinical Breast Examination as A screening Tool for Breast Cancer in Iraq
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Breast cancer constitutes about one fourth of the registered cancer cases among the Iraqi population (1)
and it is the leading cause of death among Iraqi women (2)
. Each year more women are exposed to the vicious
ramifications of this disease which include death if left unmanaged or the negative sequels that they would
experience, cosmetically and psychologically, after exposure to radical mastectomy.
The World Health Organization (WHO) documented that early detection and screening, when coped
with adequate therapy, could offer a reduction in breast cancer mortality; displaying that the low survival rates
in less developed countries, including Iraq, is mainly attributed to the lack of early detection programs couple

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Validity of Generalized Standard Addition Method for a Mixture of Amino Acid Analysis
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A Modified version of the Generlized standard addition method ( GSAM) was developed. This modified version was used for the quantitative determination of arginine   (Arg) and glycine ( Gly) in arginine  acetyl salicylate – glycine complex . According to this method two linear equations were solved to obtain the amounts of (Arg) and (Gly). The first equation was obtained by spectrophotometic measurement of the total absorbance of (Arg) and (Gly) colored complex with ninhydrin . The second equation was obtained by measuring the total acid consumed by total amino groups of (Arg) and ( Gly). The titration was carried out in non- aqueous media using perchloric acid in glacial acetic acid as a titrant. The developed metho

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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