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    The Investigation of PTC Effects of Barium Titanate Prepared from Nano-Structural BaTiO3 by Two Step Sintering Method

    , M.Sc. Thesis Sharif University of Technology Esmaeili Rad, Ahmad (Author) ; Nemati, Ali (Supervisor)
    Abstract
    The PTC effect which is one of the most important properties of electroceramics is being used in lots of electrical devices. This effect is observed in ceramics based on Barium Titanate. In the present study, the effects of grain size and two-step sintering method on PTC effect of Barium Titanate were investigated and La2O3 was used as an additive to improve the PTC effect and sintering behaviors of BaTiO3. Characterization analysis showed that the BaTiO3 powders had Cubic structure up to 700°C and Tetragonal structure at 1150°C. The FE-SEM analysis and density analysis showed that the samples which were two-step sintered at T1 less than 1200°C only reached 90% of relative density. Under... 

    Heat transfer enhancement in shell-and-tube heat exchangers using porous media

    , Article Heat Transfer Engineering ; Volume 36, Issue 3 , 2015 , Pages 262-277 ; 01457632 (ISSN) Esmaeili Rad, S ; Afshin, H ; Farhanieh, B ; Sharif University of Technology
    Taylor and Francis Ltd  2015
    Abstract
    A numerical simulation has been carried out to investigate the heat transfer enhancement in a shell-and-tube heat exchanger using a porous medium inside its shell and tubes, separately. A three-dimensional geometry with k-ε turbulent model is used to predict the heat transfer and pressure drop characteristics of the flow. The effects of porosity and dimensions of these media on the heat exchanger's thermal performance and pressure drop are analyzed. Inside the shell, the entire tube bundle is wrapped by the porous medium, whereas inside the tubes the porous media are located in two different ways: (1) at the center of the tubes, and (2) attached to the inner wall of the tubes. The results... 

    Heat Transfer Enhancement in Shell-and-Tube Heat Exchangers Using Porous Media

    , M.Sc. Thesis Sharif University of Technology Esmaeili Rad, Sepideh (Author) ; Farhanieh, Bijan (Supervisor) ; Afshin, Hossein (Supervisor)
    Abstract
    Heat transfer enhancement in heat transfer equipment, such as heat exchangers, has been widely studied. There are plenty of techniques to increase heat transfer in tubular heat exchangers. One of these techniques is applying a porous medium. These media have a great interface with fluids which can enhance the heat transfer rate. Meanwhile, the thermal conductivity of these media is usually greater than that of the studied fluid. Thus, by adding a kind of highly conductive porous insert to a heat exchanger, we are able to save the material used to construct the device and the space occupied by it.
    Shell-and-tube heat exchangers are one of the most widely-used types of exchangers in... 

    Experimental Study on the Efficiency of Moving Bed Biofilm Reactor in Treating Ethylene Glycol

    , M.Sc. Thesis Sharif University of Technology Esmaeili Rad, Nasim (Author) ; Borghei, Mehdi (Supervisor) ; Vossoughi, Manoochehr (Supervisor)
    Abstract
    The removal of ethylene glycol, one of the most widely used antifreez, with moving bed biofilm reactor (MBBR) was studied. Beside of ethylene glycol, the synthetic wastewater contained molasses and other salts as nutrient source. The packings were composed of polyethylene and shaped like small cylinders with a surface area of 500 m2 per m3 bulk volume of carriers(KMT). The COD of the feed was adjusted by varying the ratio of ethylene glycol to molasses. The total COD was 1252.5, 1345 and 1500 mg/L. The resulted showed that when the biofilm grows on the packings and its thickness is good enough, the removal efficiency increased. The increase was attributed to higher concentration of biomass... 

    Empirical Study of Minimum Miscibility Pressure Determination of CO2 and Associate Gas in Iranian Off-shore Oil

    , M.Sc. Thesis Sharif University of Technology Esmaeili Rad, Farnaz (Author) ; Tghikhani, Vahid (Supervisor) ; Ghotbi, Cyrus (Supervisor) ; Badakhshan, Amir (Supervisor)
    Abstract
    The main EOR method after heat recovery is gas injection. Minimum miscibility pressure is one of the parameters that affect gas injection. This project includes computational and laboratory sections to estimate the MMP. The MMP were estimated during the injection of CO2, Ga, Gb and methane gases into two oil samples. In the computational part of the project, MMP is estimated through cell to cell simulation and using Peng_Robinson equation of state. Also, the MMP is measured by using slim tube apparatus which is used so widely in the industry. According to the results, CO2 has the lowest miscibility pressure among other gases. It was miscible into oil even at pressures near the bubble... 

    Seizure Detection in Generalized and Focal Seizure from EEG Signals

    , M.Sc. Thesis Sharif University of Technology Mozafari, Mohsen (Author) ; 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... 

    Studying Time Perception in Musician and Non-musician Using Auditory Stimuli

    , M.Sc. Thesis Sharif University of Technology Niroomand, Niavash (Author) ; 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.... 

    Evaluation Auditory Attention Using Eeg Signals when Performing Motion and Visual Tasks

    , M.Sc. Thesis Sharif University of Technology Bagheri, Sara (Author) ; 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,... 

    Emotion Recognition from EEG Signals using Tensor based Algorithms

    , M.Sc. Thesis Sharif University of Technology Einizadeh, Aref (Author) ; 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,... 

    Diagnosis of Depressive Disorder using Classification of Graphs Obtained from Electroencephalogram Signals

    , M.Sc. Thesis Sharif University of Technology Moradi, Amir (Author) ; 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... 

    Inverse design of supersonic diffuser with flexible walls using a Genetic Algorithm

    , Article Journal of Fluids and Structures ; Volume 22, Issue 4 , 2006 , Pages 529-540 ; 08899746 (ISSN) Ziaei-Rad, S ; Ziaei-Rad, M ; Sharif University of Technology
    2006
    Abstract
    An efficient algorithm for the design optimization of the compressible fluid flow problem through a flexible structure is presented. The methodology has three essential parts: first the behavior of compressible flow in a supersonic diffuser was studied numerically in quasi-one-dimensional form using a flux splitting method. Second, a fully coupled sequential iterative procedure was used to solve the steady state aeroelastic problem of a flexible wall diffuser. Finally, a robust Genetic Algorithm was implemented and used to calculate the optimum shape of the flexible wall diffuser for a prescribed pressure distribution. © 2006 Elsevier Ltd. All rights reserved  

    EEG-based Emotion Recognition Using Graph Learning

    , M.Sc. Thesis Sharif University of Technology Talaie, Sharareh (Author) ; Hajipour Sardouie, Sepideh (Supervisor)
    Abstract
    The field of emotion recognition is a growing area with multiple interdisciplinary applications, and processing and analyzing electroencephalogram signals (EEG) is one of its standard methods. In most articles, emotional elicitation methods for EEG signal recording involve visual-auditory stimulation; however, the use of virtual reality methods for recording signals with more realistic information is suggested. Therefore, in the present study, the VREED dataset, whose emotional elicitation is virtual reality, has been used to classify positive and negative emotions. The best classification accuracy in the VREED dataset article is 73.77% ± 2.01, achieved by combining features of relative... 

    Detection of High Frequency Oscillations from Brain Electrical Signals Using Time Series and Trajectory Analysis

    , M.Sc. Thesis Sharif University of Technology Gharabaghi, Ali (Author) ; Hajipour Sardouie, Sepideh (Supervisor)
    Abstract
    The analysis of cerebral signals, encompassing both invasive and non-invasive electroencephalogram recordings, is extensively utilized in the exploration of neural systems and the examination of neurological disorders. Empirical research has indicated that under certain conditions, such as epileptic episodes, cerebral signals exhibit frequency components exceeding 80 Hz, which are designated as high frequency oscillations. Consequently, high frequency oscillations are recognized as a promising biomarker for epilepsy and the delineation of epileptic foci. The objective of this dissertation is to evaluate the existing methodologies for the detection of high frequency oscillations and to... 

    High Frequency Oscillation Detection in Brain Electrical Signals Using Tensor Decomposition

    , M.Sc. Thesis Sharif University of Technology Yousefi Mashhoor, Reza (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    High-frequency oscillations (HFOs) in brain electrical signals are activities within the 80–500 Hz frequency range that are distinct from the baseline and include at least four oscillatory cycles. Research indicates that HFOs could serve as potential biomarkers for neurological disorders. Manual detection of HFOs is time-consuming and prone to human error, making automated HFO detection methods increasingly necessary. These automated methods typically rely on the signal's energy within the HFO frequency band. Tensor decompositions are mathematical models capable of extracting hidden information from multidimensional data. Due to the multidimensional nature of brain electrical signals, tensor... 

    Extraction of Event Related Potentials (ERP) from EEG Signals using Semi-blind Approaches

    , M.Sc. Thesis Sharif University of Technology Jalilpour Monesi, Mohammad (Author) ; 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 Jalilpour, Shayan (Author) ; 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 Arabpour, Mohammad Reza (Author) ; 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 Asadian, Saeed (Author) ; 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... 

    Comparison of several sparse recovery methods for low rank matrices with random samples

    , Article 2016 8th International Symposium on Telecommunications, IST 2016, 27 September 2016 through 29 September 2016 ; 2017 , Pages 191-195 ; 9781509034345 (ISBN) Esmaeili, A ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2017
    Abstract
    In this paper, we will investigate the efficacy of IMAT (Iterative Method of Adaptive Thresholding) in recovering the sparse signal (parameters) for linear models with random missing data. Sparse recovery rises in compressed sensing and machine learning problems and has various applications necessitating viable reconstruction methods specifically when we work with big data. This paper will mainly focus on comparing the power of Iterative Method of Adaptive Thresholding (IMAT) in reconstruction of the desired sparse signal with that of LASSO. Additionally, we will assume the model has random missing information. Missing data has been recently of interest in big data and machine learning... 

    A novel approach to quantized matrix completion using huber loss measure

    , Article IEEE Signal Processing Letters ; Volume 26, Issue 2 , 2019 , Pages 337-341 ; 10709908 (ISSN) Esmaeili, A ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    In this paper, we introduce a novel and robust approach to quantized matrix completion. First, we propose a rank minimization problem with constraints induced by quantization bounds. Next, we form an unconstrained optimization problem by regularizing the rank function with Huber loss. Huber loss is leveraged to control the violation from quantization bounds due to two properties: first, it is differentiable; and second, it is less sensitive to outliers than the quadratic loss. A smooth rank approximation is utilized to endorse lower rank on the genuine data matrix. Thus, an unconstrained optimization problem with differentiable objective function is obtained allowing us to advantage from...