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Bioglass Coating on 316L Stainless Steel
, M.Sc. Thesis Sharif University of Technology ; Afshar, Abdollah (Supervisor)
Abstract
Bioactive glasses are able to bond to soft and hard tissues in living body and their application as coating on metallic implants like 316L stainless steel has two important effects: (1) intimate link between bone and materials and (2) corrosion protection of metallic implant in body fluid and protection from tissues in front of corrosion products. Therefore, in this research, 45S5 bioactive glass prepared via sol- gel method was dip coated on 316L stainless steel substrates and its characteristics was investigated.Results of phase analysis showed that by sintering 45S5 bioglass at 600 ˚C for 5 h, an amorph sample with small amount of Na2Ca2Si3O9 was obtained. So, the bioglass coated samples...
Double layer bioglass-silica coatings on 316L stainless steel by sol-gel method
, Article Ceramics International ; Volume 40, Issue 1, Part A , January 2014 , Pages 993–1000 ; Afshar, A ; Sharif University of Technology
January 2014
Abstract
The application of bioglass coatings on metallic implants provides link between bone and materials and prevents corrosion of metallic implants in body fluid. Therefore, in this research, 45S5 bioglass-silica coatings on 316L stainless steel were prepared by the sol-gel method and were characterized by different techniques. According to X-ray diffraction (XRD) results, by sintering 45S5 bioglass at 600 C for 5 h, coatings containing both amorphous phase and Na2Ca2Si3O9 crystalline phase were obtained. Scanning electron microscopy (SEM) results showed that coatings prepared via appropriate sol aging and substrate preparations are crack-free. Potentiodynamic polarization tests in simulated body...
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,...
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....
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...
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...
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...
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...