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One-dimensional chemotaxis kinetic model
, Article Nonlinear Differential Equations and Applications ; Volume 18, Issue 2 , 2011 , Pages 139-172 ; 10219722 (ISSN) ; Sharif University of Technology
Abstract
In this paper, we study a variation of the equations of a chemotaxis kinetic model and investigate it in one dimension. In fact, we use fractional diffusion for the chemoattractant in the Othmar-Dunbar-Alt system (Othmer in J Math Biol 26(3):263-298, 1988). This version was exhibited in Calvez in Amer Math Soc, pp 45-62, 2007 for the macroscopic well-known Keller-Segel model in all space dimensions. These two macroscopic and kinetic models are related as mentioned in Bournaveas, Ann Inst H Poincaré Anal Non Linéaire, 26(5):1871-1895, 2009, Chalub, Math Models Methods Appl Sci, 16(7 suppl):1173-1197, 2006, Chalub, Monatsh Math, 142(1-2):123-141, 2004, Chalub, Port Math (NS), 63(2):227-250,...
Blow-up For Chemotaxis Models
, Ph.D. Dissertation Sharif University of Technology ; Hesaaraki, Mahmoud (Supervisor)
Abstract
Moving of living organisms appears in many interesting problems, e.g. the growth of bacteria colonies, tumor growth, wound healing, color patterns of animals and etc. There are many ways to model such problems and PDE theory is widely used to investigate these problems. In this thesis, we study two well-known classic models. First, macroscopic “Keller–Segel” model and then kinetic “Othmer–Dunbar–Alt” System. Since these models have a nice behavior in two dimensions that they don’t have in other dimensions, we propose a way to alter them such that they behave in this way in all dimensions. Also none of the known models have the suitable dynamics in one dimension, so our model has the property...
WT-SOBI Method Towards Blind System Identification of Structures
, M.Sc. Thesis Sharif University of Technology ; Kazemi , Mohammad Taghi (Supervisor)
Abstract
Blind source separation methods such as independent component analysis (ICA) and second order blind identification (SOBI) have shown considerable potential in the area of ambient vibration system identification. The objective of these methods is to separate the modal responses, or sources, from the measured output responses, without the knowledge of excitation. Several frequency domain and time domain methods have been proposed and successfully implemented in the literature. Whereas frequency-domain methods pose several challenges typical of dealing with signals in the frequency-domain, popular time domain methods such as NExT/ERA and SSI pose limitations in dealing with noise, low sensor...
Cross-flow vortex induced vibrations of inclined helically straked circular cylinders: An experimental study
, Article Journal of Fluids and Structures ; Volume 59 , November , 2015 , Pages 178-201 ; 08899746 (ISSN) ; Farhangmehr, A ; Seif, M. S ; Zandi, A. P ; Sharif University of Technology
Academic Press
2015
Abstract
Effects of suppression devices on the vortex induced vibration (VIV) of inclined cylinders appear not to have received previous due attentions. The current paper reports the results of some towing tank experiments on the vortex induced cross-flow vibrations of bare and helically straked cylinders in vertical and inclined arrangements. Rigid test cylinders were mounted on a single degree of freedom elastic support. The inclination angles examined were θ=0°, ±20° and ±45°. The Reynolds number ranged from 4000 to 45. 000 and the reduced velocity from 1 to 16. With all tests the mass ratio and the mass-damping parameters were kept constant.Test results on "inclined bare" and "inclined helically...
Analysis of partial discharge by eavelet-hilbert transform
, Article European Transactions on Electrical Power ; Volume 19, Issue 8 , 2009 , Pages 1140-1152 ; 1430144X (ISSN) ; Reihani, E ; Nabizadeh, N ; Hooshmand, A ; Davodi, M ; Sharif University of Technology
2009
Abstract
Time-frequency and time-scale transforms are one of the powerful mathematical methods for feature extraction of non-stationary signals such as partial discharge (PD) signals. Modified Fourier-based transforms and Wavelet transforms are well known among them. PD signals can be analyzed by these influential methods but normally with some serious limitations and inadequacies. This paper proposes a new approach based on Wavelet-Hilbert transform for the analysis of electrical PD signals. The mathematical model of a Wavelet-Hilbert transform is described. Contemplating of natural behavior of PD, that is, stochastic and non-stationary an artificial multi-source of PD is simulated in a Detail model...
Structural Health Monitoring based on Emprical Wavelet Transform and Fuzzy Logic
, M.Sc. Thesis Sharif University of Technology ; Bakhshi, Ali (Supervisor) ; Ghodrati Amiri, Gholamreza (Supervisor)
Abstract
Performance of civil infrastructures, such as high-rise buildings, bridges, tunnels, offshore platforms and other structures may be critically influenced by existence of structural damages or even lead to devastating consequences. Structural Health Monitoring(SHM) and damage detection denotes the ability to monitor the performance of structure, detect and assess any damage at the earliest stage in order to reduce the life-cycle cost of structure and improve its reliability and safety. Generally, damage is defined as some changes in the physical properties of a structure, such as stiffness matrix. On the other hand, presence of damage causes changes in structural dynamic characteristics, such...
Fault Detection of Rotary System with Signal Processing and Intelligent Systems
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor)
Abstract
Condition monitoring and fault detection is an important way to provide economy in both time and costs. Many methods are developed for this purpose. Vibration analysis is one of the most important ways in this field. In this thesis, fault detection of mechanical rotary systems with nonlinear and non-stationary nature has been developed by use of empirical mode decomposition (EMD) and Hilbert transform. Firstly the measured signal is transformed into some intrinsic mode functions (IMF’s) by EMD, and then the Hilbert transform is implemented on each IMF. With Hilbert transform, the instantaneous frequency of system and then the mean frequency are obtained. Mean frequency is a key definition...
Fetal R-wave detection from multichannel abdominal ECG recordings in low SNR
, Article Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, 2 September 2009 through 6 September 2009, Minneapolis, MN ; 2009 , Pages 344-347 ; 9781424432967 (ISBN) ; Shamsollahi, M. B ; Sameni, R ; Sharif University of Technology
Abstract
Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called πCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of πCA (after maternal ECG cancellation), had a very good performance. Also,...
An efficient real-time voice activity detection algorithm using teager energy to energy ratio
, Article 27th Iranian Conference on Electrical Engineering, ICEE 2019, 30 April 2019 through 2 May 2019 ; 2019 , Pages 1420-1424 ; 9781728115085 (ISBN) ; Pakravan, M. R ; Razavi, M. M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
We define a new feature called Teager Energy to Energy and mathematically show that it provides distinguished values for pure tone and white noise signals. We then employ the Teager Energy to Energy feature to propose an efficient procedure for voice activity detection and use simulation results to evaluate its performance in different noisy environments. Furthermore, we experimentally demonstrate the performance of the proposed voice activity detection technique in a real-time voice processing embedded system. Experimental and simulation results show that the introduced procedure provides more reliable results with a reasonable amount of computational complexity in comparison with its...
Online nonlinear structural damage detection using hilbert Huang transform and artificial neural networks
, Article Scientia Iranica ; Volume 26, Issue 3A , 2019 , Pages 1266-1279 ; 10263098 (ISSN) ; Bakhshi, A ; Bahar, O ; Sharif University of Technology
Sharif University of Technology
2019
Abstract
In order to implement a damage detection strategy and assess the condition of a structure, Structural Health Monitoring (SHM) as a process plays a key role in structural reliability. This paper aims to present a methodology for online detection of damages that may occur during a strong ground excitation. In this regard, Empirical Mode Decomposition (EMD) is superseded by Ensemble Empirical Mode Decomposition (EEMD) in the Hilbert Huang Transformation (HHT). Although analogous with EMD, EEMD brings about more appropriate Intrinsic Mode Functions (IMFs). IMFs are employed to assess the first-mode frequency and mode shape. Afterwards, Artificial Neural Network (ANN) is applied to predict story...
Online nonlinear structural damage detection using hilbert huang transform and artificial neural networks
, Article Scientia Iranica ; Volume 26, Issue 3A , 2019 , Pages 1266-1279 ; 10263098 (ISSN) ; Bakhshi, A ; Bahar, O ; Sharif University of Technology
Sharif University of Technology
2019
Abstract
In order to implement a damage detection strategy and assess the condition of a structure, Structural Health Monitoring (SHM) as a process plays a key role in structural reliability. This paper aims to present a methodology for online detection of damages that may occur during a strong ground excitation. In this regard, Empirical Mode Decomposition (EMD) is superseded by Ensemble Empirical Mode Decomposition (EEMD) in the Hilbert Huang Transformation (HHT). Although analogous with EMD, EEMD brings about more appropriate Intrinsic Mode Functions (IMFs). IMFs are employed to assess the first-mode frequency and mode shape. Afterwards, Artificial Neural Network (ANN) is applied to predict story...
Fetal R Detection from Mixed Maternal and Fetal MCG Signals
, M.Sc. Thesis Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor) ; Sameni, Reza (Supervisor)
Abstract
Analyzing cardiac function of the fetus during pregnancy is proved to be an important prenatal care procedure. Traditional methods like auscultation and ultrasonography could only lead to anatomical information about the fetal heart. So in the recent decades many researches on the abdominal electrical signals of the pregnant women have been done. Nowadays, it is possible to record the heart magnetic signals. With regard to the morphological similarity between the electrical and magnetical signals of the heart and the superiority of the magnetic ones, one could assume more diagnostic capacity for the fetal MCG. It should be mentioned that finding the location of the fetal R waves could help...
Structural Damage Detection by Using Signal-Based and Artificial Intelligence Methods; Case Study 'Moment-Resisting Frame Structure
, M.Sc. Thesis Sharif University of Technology ; Bakhshi, Amin (Supervisor) ; Bahar, Omid (Supervisor)
Abstract
Civil structures are on the verge of changing which leads energy dissipation capacity to decline. Structural Health Monitoring (SHM) as a process in order to implement a damage detection strategy and assess the condition of structure plays a key role in structural reliability. Earthquake is a recognized factor in variation of structures condition, inasmuch as inelastic behavior of a building subjected to design level earthquakes is plausible. In this study Hilbert Hunag Transformation (HHT) is superseded by Ensemble Empirical Mode decomposition (EEMD) and Hilbert Transform (HT) together. Albeit this method is closely resemble HHT, EEMD brings more appropriate Intrinsic Mode Functions (IMFs)....
Coordination variability during walking and running in individuals with and without patellofemoral pain part 1: lower limb intersegmental coordination variability
, Article Journal of Medical and Biological Engineering ; Volume 41, Issue 3 , 2021 , Pages 295-304 ; 16090985 (ISSN) ; Rezaie, M ; Ebrahimi, S ; Shokouhyan, S. M ; Motealleh, A ; Parnianpour, M ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2021
Abstract
Purpose: Although it has been proposed that individuals with patellofemoral pain show less lower limb intersegmental coordination variability, the evidence to support this hypothesis is rare. The purpose of this study was, therefore, to evaluate whether individuals with patellofemoral pain exhibit less intersegmental coordination variability compared with healthy individuals during walking and running. Also, it was hypothesized that increasing task demand would exacerbate group differences regarding coordination variability measures. Methods: Three-dimensional kinematics were collected while 17 females with patellofemoral pain and 17 healthy females walked at preferred speed, and ran at...
Behavior of olfactory-related frontal lobe oscillations in Alzheimer's disease and MCI: A pilot study
, Article International Journal of Psychophysiology ; Volume 175 , 2022 , Pages 43-53 ; 01678760 (ISSN) ; Aghajan, H ; Vahabi, Z ; Afzal, A ; Sedghizadeh, M. J ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Slow-gamma (35-45 Hz) phase synchronization and the coupling between slow-gamma and low-frequency theta oscillations (4–8 Hz) are closely related to memory retrieval and cognitive functions. In this pilot study, we assess the Phase Amplitude Coupling (PAC) between theta and slow-gamma oscillatory bands and the quality of synchronization in slow-gamma oscillations using Phase Locking Value (PLV) on EEG data from healthy individuals and patients diagnosed with amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD) during an oddball olfactory task. Our study indicates noticeable differences between the PLV and PAC values corresponding to olfactory stimulation in the three groups...