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sepideh-atrbar-mohammadi
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Total 897 records
Utilizing Artificial Intelligence Technique in Acidizing Process of Asphaltenic Oil Wells
, M.Sc. Thesis Sharif University of Technology ; Ayatollahi, Shahaboddin (Supervisor) ; Pishvaie, Mahmoud Reza (Supervisor)
Abstract
The Oil wells are usually damaged because of the drilling process and production scenarios or fluid injection during EOR processes. These damages would critically affect the rate of production and injectivity of the well in the form of plugging damage. Different methods are used to fix these damages and increase the production flow from the oil wells. One of the most widely used well-stimulation methods to remediate this challenge is well acidizing. Although this method has very high efficiency in improving the ability of wells, if it is not designed and implemented correctly and optimally, it can cause induced damage and even lead to the well shutting. This challenge is especially reported...
Seizure Detection in Generalized and Focal Seizure from EEG Signals
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so...
Emotion Recognition from EEG Signals using Tensor based Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
The brain electrical signal (EEG) has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion, which, in turn, indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration.In the emotion recognition problem,...
Evaluation Auditory Attention Using Eeg Signals when Performing Motion and Visual Tasks
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Attention is one of the important aspects of brain cognitive activities, which has been widely discussed in psychology and neuroscience and is one of the main fields of research in the education field. The human sense of hearing is very complex, impactful and crucial in many processes such as learning. Human body always does several tasks and uses different senses simultaneously. For example, a student who listens to his/her teacher in the class, at the same time pays attention to the teacher, looks at a text or image, and sometimes writes a note.Using the electroencephalogram (EEG) signal for attention assessment and other cognitive activities is considered because of its facile recording,...
Studying Time Perception in Musician and Non-musician Using Auditory Stimuli
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Time perception is a concept that describes how a person interprets the duration of an event. Depending on the circumstances, people may feel that time passes quickly or slowly. So far, the understanding, comparison, and estimation of the time interval have been described using a simple model, a pacemaker accumulator, that is powerful in explaining behavioral and biological data. Also, the role of the frequency band, Contingent Negative Variation (CNV), and Event-Related Potential (ERP) components have been investigated in the passage of time and the perception of time duration. Still, the stimuli used in these studies were not melodic. Predicting is one of the main behaviors of the brain....
Diagnosis of Depressive Disorder using Classification of Graphs Obtained from Electroencephalogram Signals
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Depression is a type of mental disorder that is characterized by the continuous occurrence of bad moods in the affected person. Studies by the World Health Organization (WHO) show that depression is the second disease that threatens human life, and eight hundred thousand people die due to suicide every year. In order to reduce the damage caused by depression, it is necessary to have an accurate method for diagnosing depression and its rapid treatment, in which electroencephalogram (EEG) signals are considered as one of the best methods for diagnosing depression. Until now, various researches have been conducted to diagnose depression using electroencephalogram signals, most of which were...
Extraction of Event Related Potentials (ERP) from EEG Signals using Semi-blind Approaches
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor)
Abstract
Nowadays, Electroencephalogram (EEG) is the most common method for brain activity measurement. Event Related Potentials (ERP) which are recorded through EEG, have many applications. Detecting ERP signals is an important task since their amplitudes are quite small compared to the background EEG. The usual way to address this problem is to repeat the process of EEG recording several times and use the average signal. Though averaging can be helpful, there is a need for more complicated filtering. Blind source separation methods are frequently used for ERP denoising. These methods don’t use prior information for extracting sources and their use is limited to 2D problems only. To address these...
Design and Implementation of a P300 Speller System by Using Auditory and Visual Paradigm
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor)
Abstract
The use of brain signals in controlling devices and communication with the external environment has been very much considered recently. The Brain-Computer Interface (BCI) systems enable people to easily handle most of their daily physical activity using the brain signal, without any need for movement. One of the most common BCI systems is P300 speller. In this type of BCI systems, the user can spell words without the need for typing with hands. In these systems, the electrical potential of the user's brain signals is distorted by visual, auditory, or tactile stimuli from his/her normal state. An essential principle in these systems is to exploit appropriate feature extraction methods which...
An Investigation of Resting-State Eeg Biomarkers Derived from Graph of Brain Connectivity for Diagnosis of Depressive Disorder
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Among the most costly diseases that affect a person's quality of life throughout his or her life, mental disorders (excluding sleep disorders) affect up to 25 percent of people in any community. One of the most common types of these disorders in Iran is depressive disorder, which according to official statistics, 13% of Iranians have some symptoms of it. Until now, the diagnosis of this disease has been traditionally done in clinics with interviews and questionnaires tests based on behavioral psychology and using symptom assessment. Therefore, there is a relatively low accuracy in the treatment process. Nowadays, with the help of functional brain imaging such as electroencephalogram (EEG)...
Design and Implementing an Evaluator Platforn for Cochlear Implent Devices
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor) ; Molaei, Behnam (Co-Supervisor)
Abstract
The auditory system with its unique features has been considered by researchers in the past and its various parts from the outside of the body to its internal parts have been studied. The auditory nervous system, as the most important part of the auditory system, is responsible for receiving and processing information from the ear. The auditory system has different anatomical and physiological characteristics. The result of these characteristics is processing power in the field of time and frequency, which has received more attention in this dissertation. This processing power is most evident in the central auditory nervous system. This section includes nerve neurons and synapses from the...
Detection of High Frequency Oscillations from ECoG Recordings in Epileptic Patients
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor) ; Sinaei, Farnaz (Co-Supervisor)
Abstract
The processing of brain signals, including the electrocorticogram (ECoG) signal, is widely used in the investigation of neurological diseases. Conventionally, the ECoG signal has frequency components up to the range of 80 Hz. Studies have proven that in some conditions, such as epilepsy, the brain signal includes frequency components higher than 80 Hz, which are called high-frequency oscillations (HFO). Therefore, HFOs are recognized as a biomarker for epilepsy. The aim of this thesis is to review the previous methods of detecting HFOs and to present new methods with greater efficiency in the direction of diagnosis or treatment of epileptic patients. For this purpose, we used the ECoG data...
Improving CCA Based Methods for SSVEP Classification using Graph Signal Processing
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor) ; Einizadeh, Aref (Co-Supervisor)
Abstract
The Brain Computer Interface (BCI) translates brain signals into a series of commands, enabling individuals to fulfill many of their basic needs without physical activity. Electroencephalogram (EEG) signals are commonly used as input for BCI systems, because the recording of this signal is non-invasive, inexpensive, and also have an acceptable time resolution. One of the most prevalent methods in BCI systems is the brain-computer interface based on Steady State Visual Evoked Potentials (SSVEP). These systems provide high response speed and Information Transfer Rate (ITR) as well as a good signal-to-noise ratio (SNR). The main purpose of these systems is to detect the frequency of SSVEP in...
Multimodal Brain Source Localization
, Ph.D. Dissertation Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor) ; Hajipour Sardouei, Sepideh (Supervisor)
Abstract
In most of brain studies, the primary objective is to find dipole activities, an underdetermined problem that requires additional constraints. Adequate constraints can be added by using information from other modalities. This research aims to develop a platform that combines various noninvasive modalities to improve localization accuracy. To accomplish this, two novel general approaches to combining modalities are proposed. In the first approach, the result of localizing by different methods and in different modalities are processed and combined in intervals by Dempster Shaffer's combination law. The final amount of bipolar activity is obtained by cumulating the activities obtained at...
Subspace Identification and Brain Connectivity Estimation of Electroencephalogram Signals Using Graph Signal Processing
, Ph.D. Dissertation Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor) ; Shamsollahi, Mohammad Bagher (Supervisor)
Abstract
EEG brain signals have gained particular attention among researchers in the field of brain signal processing due to their easy and cheap recording, high temporal resolution, and non-invasiveness. On the other hand, defects such as high vulnerability to various types of noise and artifacts have caused the main challenge before processing them to improve the signal-to-noise ratio and the interpretability of brain connectivity obtained from them. In order to solve these challenges, two important problems of "separation of desired and undesired signal subspace" and "functional and effective connectivity analysis" have been raised, respectively. In solving both problems, EEG signals are usually...
3D distributed modeling of trolling-mode AFM during 2D manipulation of a spherical cell
, Article Journal of Nanoparticle Research ; Volume 23, Issue 4 , 2021 ; 13880764 (ISSN) ; Nejat Pishkenari, H ; Mohammadi Moghaddam, M ; Sharif University of Technology
Springer Science and Business Media B.V
2021
Abstract
In this study, a general 3D distributed modeling of Trolling-Mode AFM (TR-AFM) as a nanorobot is presented to analyze the 2D manipulation process of a spherical cell. To this aim, the analysis is categorized into 3 sections. In the first section, 6 deformations of TR-AFM are taken into account, and the standard model of the system is obtained. Moreover, the system is simulated in ANSYS Workbench. The results of modal and transient analyses of the system from both analytical and software methods reveal high agreement, which confirms the accuracy of the presented analytical model. In the second section, by utilizing the 3D derived model, displacement of a spherical yeast single cell (W303)...
Sol-gel nanostructured titanium dioxide: Controlling the crystal structure, crystallite size, phase transformation, packing and ordering
, Article Microporous and Mesoporous Materials ; Volume 112, Issue 1-3 , 2008 , Pages 392-402 ; 13871811 (ISSN) ; Fray, D. J ; Mohammadi, A ; Sharif University of Technology
2008
Abstract
The anatase phase of titania was stabilised with physically modifying particulate sol-gel process. Two major parameters, peptisation temperature and drying temperature, were identified which were responsible for retarding the anatase to rutile phase transformation, crystal growth and packing of primary particles. The critical nucleus size of transformation was controlled by natural (at 25 °C) and artificial (at 50 and 70 °C) peptisation techniques. Moreover, sintering of primary particles was controlled by cool (at 0 and 5 °C) and normal (at 25 °C) drying techniques. Fourier transform infrared spectroscopy (FT-IR) analysis confirmed that a full conversion of titanium isopropoxide is obtained...
Electrokinetic mixing and displacement of charged droplets in hydrogels
, Article Transport in Porous Media ; Vol. 104, Issue. 3 , Jun , 2014 , pp. 469-499 ; ISSN: 01693913 ; Sharif University of Technology
2014
Abstract
Mixing in droplets is an essential task in a variety of microfluidic systems. Inspired by electrokinetic mixing, electric field-induced hydrodynamic flow inside a charged droplet embedded in an unbounded polyelectrolyte hydrogel is investigated theoretically. In this study, the polyelectrolyte hydrogel is modeled as a soft, and electrically charged porous solid saturated with a salted Newtonian fluid, and the droplet is considered an incompressible Newtonian fluid. The droplet-hydrogel interface is modeled as a surface, which is located at the plane of shear, with the electrostatic potential ζ. The fluid inside the droplet attains a finite velocity owing to hydrodynamic coupling with the...
Electric-field-induced response of a droplet embedded in a polyelectrolyte gel
, Article Physics of Fluids ; Volume 25, Issue 8 , 2013 ; 10706631 (ISSN) ; Sharif University of Technology
2013
Abstract
The electric-field induced response of a droplet embedded in a quenched polyelectrolyte gel is calculated theoretically. The response comprises the droplet translation and the electric-field induced flow fields within the droplet. The gel is modeled as a soft, and electrically charged porous solid saturated with a salted Newtonian fluid. The droplet is considered an incompressible Newtonian fluid with no free charge. An analytical solution, using the perturbation methodology and linear superposition, is obtained for the leading-order steady response to a DC electric-field. The fluid within the droplet is driven due to hydrodynamic coupling with the electroosmotic flow. The fluid velocity...
Oscillatory response of charged droplets in hydrogels
, Article Journal of Non-Newtonian Fluid Mechanics ; Volume 234 , 2016 , Pages 215-235 ; 03770257 (ISSN) ; Sharif University of Technology
Elsevier
2016
Abstract
Characterization of droplet-hydrogel interfaces is of crucial importance to engineer droplet-hydrogel composites for a variety of applications. In order to develop electrokinetic diagnostic tools for probing droplet-hydrogel interfaces, the displacement of a charged droplet embedded in a polyelectrolyte hydrogel exposed to an oscillating electric field is determined theoretically. The polyelectrolyte hydrogel is modeled as an incompressible, charged, porous, and elastic solid saturated with a salted Newtonian fluid. The droplet is considered an incompressible Newtonian fluid with no charges within the droplet. The droplet-hydrogel interface is modeled as a surface with the thickness of zero...
Transport in droplet-hydrogel composites: response to external stimuli
, Article Colloid and Polymer Science ; Volume 293, Issue 3 , March , 2015 , Pages 941-962 ; 0303402X (ISSN) ; Sharif University of Technology
Springer Verlag
2015
Abstract
Determination of effective transport properties of droplet-hydrogel composites is essential for various applications. The transport of ions through a droplet-hydrogel composite subjected to an electric field is theoretically studied as an initial step toward quantifying the effective transport properties of droplet-hydrogel composites. A three-phase electrokinetic model is used to derive the microscale characteristics of the polyelectrolyte hydrogel, and the droplet is considered an incompressible Newtonian fluid. The droplet-hydrogel interface is modeled as a surface, which encloses the interior fluid. The surface has the thickness of zero and the electrostatic potential ζ. Standard...