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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
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Tue Apr 25 2023
Journal Name
Journal Of Periodontal Research
Salivary E‐cadherin as a biomarker for diagnosis and predicting grade of periodontitis
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Abstract<sec><title>Objectives

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Background

E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.

Materials and Methods

A total of 63 patients with periodontitis (case) and 35

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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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Publication Date
Tue Oct 13 2015
Journal Name
Plos Medicine
P2RX7 Purinoceptor: A Therapeutic Target for Ameliorating the Symptoms of Duchenne Muscular Dystrophy
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Publication Date
Wed Feb 11 2026
Journal Name
Chemistryselect
Gelatin Nanoparticles as a Carrier for Acriflavine and Triethylenetetramine: Cytotoxicity and Antibacterial Activity
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ABSTRACT<p> Despite extensive investigation as biocompatible drug carriers, gelatin nanoparticles (GNPs) have not been thoroughly assessed for carrying chemically distinct cationic molecules such as acriflavine (ACF) and triethylenetetramine (TETA). In this study, we hypothesize that GNPs can effectively encapsulate ACF and TETA, forming stable delivery systems with distinct antibacterial and cytotoxic activities. ACF encapsulated in gelatin was prepared adapting desolvation technique. The procedure involved stirring of an aqueous solution of gelatin and ACF at room temperature, the pH was titrated to eight using NaOH followed by addition of ethanol. The resulting nanopart</p> ... Show More
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Publication Date
Mon Dec 02 2013
Journal Name
Iraqi Medical Journal
Etiology and Antibiotic Sensitivity for Otitis Media in A Central Pediatric Teaching Hospital.
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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
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
Tue Dec 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A Haptic feedback system based on leap motion controller for prosthetic hand application
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

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Publication Date
Sat Aug 01 2020
Journal Name
Computational Biology And Chemistry
A graph-based multi-sample test for identifying pathways associated with cancer progression
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Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

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