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    Performance analysis of EEG seizure detection features

    , Article Epilepsy Research ; Volume 167 , 2020 Niknazar, H ; Mousavi, S. R ; Niknazar, M ; Mardanlou, V ; Coelho, B. N ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    Automatic detection of epileptic seizures can serve as a valuable clinical tool which involves a more objective and computationally efficient method for the analysis of EEG data in order to generate increasingly accurate and reliable results. Automatic seizure detection is also an important component of closed-loop responsive cortical stimulation systems. The goal of this study is to evaluate EEG-based features recently proposed for seizure detection to discover the optimum ones for a reliable seizure detection system. We extracted seizure detection features from intracranial EEG signals that were recorded during invasive pre-surgical epilepsy monitoring of people with drug resistant focal... 

    Analysis of Epileptic Rats' EEG and Detection and Prediction of Epileptic Seizures

    , M.Sc. Thesis Sharif University of Technology Niknazar, Mohammad (Author) ; Vosoughi Vahdat, Bijan (Supervisor) ; Shamsollahi, Mohammad Bagher (Supervisor)
    Abstract
    Epilepsy is one of the most significant neurological disorders that about one percent of people suffer from it. Epilepsy can only be controlled, and so far no cure for it has been provided. Despite the many advances in the treatment of diseases, for a quarter of patients there is no medical treatment solution for controlling epileptic seizures. In the studies of medical groups on the epilepsy, one approach is employment of some models for each type of epilepsy. These types may be created in the animals to allow studying of the mechanism of epilepsy and also finding drugs of treatment or controlling seizures for each type of epilepsy. There is a type of epilepsy that is called absence... 

    Detection of characteristic points of ecg using quadratic spline wavelet transfrom

    , Article 3rd International Conference on Signals, Circuits and Systems, SCS 2009, 6 November 2009 through 8 November 2009, Medenine ; 2009 ; 9781424443987 (ISBN) Niknazar, M ; Vahdat, B. V ; Mousavi, S. R ; Sharif University of Technology
    2009
    Abstract
    This paper presents a method for ECG characteristic points detection based on Wavelet Transform (WT). Wavelet Transform leads to more accurate results in analyzing nonstationary signals such as ECG. The selected wavelet is quadratic spline wavelet. Using quadratic spline mother wavelet, a method for detection of QRS complex and T and P waves is presented and evaluated with the help of MIT-BIH Arrhythmia database. Experimental results show excellent performance of the proposed method. © 2009 IEEE  

    Volumetric behavior quantification to characterize trajectory in phase space

    , Article Chaos, Solitons and Fractals ; Volume 103 , 2017 , Pages 294-306 ; 09600779 (ISSN) Niknazar, H ; Nasrabadi, A. M ; Shamsollahi, M. B ; Sharif University of Technology
    2017
    Abstract
    This paper presents a methodology to extract a number of quantifier features to characterize volumetric behavior of trajectories in phase space. These features quantify expanding and contracting behaviors and complexity that can be used in nonlinear and chaotic signals classification or clustering problems. One of the features is directly extracted from the distance matrix and seven features are extracted from a matrix that is subsequently obtained from the distance matrix. To illustrate the proposed quantifiers, Mackey–Glass time series and Lorenz system were employed and feature evaluation was performed. It is shown that the proposed quantifier features are robust to different... 

    A new similarity index for nonlinear signal analysis based on local extrema patterns

    , Article Physics Letters, Section A: General, Atomic and Solid State Physics ; Volume 382, Issue 5 , February , 2018 , Pages 288-299 ; 03759601 (ISSN) Niknazar, H ; Motie Nasrabadi, A ; Shamsollahi, M. B ; Sharif University of Technology
    Elsevier B.V  2018
    Abstract
    Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By... 

    A new blind source separation approach based on dynamical similarity and its application on epileptic seizure prediction

    , Article Signal Processing ; Volume 183 , 2021 ; 01651684 (ISSN) Niknazar, H ; Nasrabadi, A. M ; Shamsollahi, M. B ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Blind source separation is an important field of study in signal processing, in which the goal is to estimate source signals by having mixed observations. There are some conventional methods in this field that aim to estimate source signals by considering certain assumptions on sources. One of the most popular assumptions is the non-Gaussianity of sources which is the basis of many popular blind source separation methods. These methods may fail to estimate sources when the distribution of two or more sources is Gaussian. Hence, this study aims to introduce a new approach in blind source separation for nonlinear and chaotic signals by using a dynamical similarity measure and relaxing... 

    A new framework based on recurrence quantification analysis for epileptic seizure detection

    , Article IEEE Journal of Biomedical and Health Informatics ; Volume 17, Issue 3 , 2013 , Pages 572-578 ; 21682194 (ISSN) Niknazar, M ; Mousavi, S. R ; Vosoughi Vahdat, B ; Sayyah, M ; Sharif University of Technology
    2013
    Abstract
    This study presents applying recurrence quantification analysis (RQA) on EEG recordings and their subbands: delta, theta, alpha, beta, and gamma for epileptic seizure detection. RQA is adopted since it does not require assumptions about stationarity, length of signal, and noise. The decomposition of the original EEG into its five constituent subbands helps better identification of the dynamical system of EEG signal. This leads to better classification of the database into three groups: Healthy subjects, epileptic subjects during a seizure-free interval (Interictal) and epileptic subjects during a seizure course (Ictal). The proposed algorithm is applied to an epileptic EEG dataset provided... 

    Application of Bhattacharyya distance as a dissimilarity index for automated prediction of epileptic seizures in rats

    , Article 2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010, 15 June 2010 through 17 June 2010 ; 2010 ; 9781424466238 (ISBN) Niknazar, M ; Vosoughi Vahdat, B ; Shamsollahi, M. B ; Sayyah, M ; Sharif University of Technology
    2010
    Abstract
    Seizures are defined as manifest of excessive and hypersynchronous activity of neurons in the cerebral cortex and represent a frequent malfunction of the human central nervous system. Therefore, the search for precursors and predictors of a seizure is of utmost clinical relevance and may even guide us to a deep understanding of the seizure generating mechanisms. In this study we analyzed invasive electroencephalogram (EEG) recordings in rats with experimentally induced generalized epilepsy with a nonlinear method called, dissimilarity index. In order to predict epileptic seizures automatically, Bhattacharyya distance between trajectory matrix of reference window, during an interval quite... 

    A new dissimilarity index of EEG signals for epileptic seizure detection

    , Article Final Program and Abstract Book - 4th International Symposium on Communications, Control, and Signal Processing, ISCCSP 2010, 3 March 2010 through 5 March 2010 ; March , 2010 ; 9781424462858 (ISBN) Niknazar, M ; Mousavi, S. R ; Vosoughi Vahdat, B ; Shamsollahi, M. B ; Sayyah, M ; Sharif University of Technology
    2010
    Abstract
    Epileptic seizures are generated by an abnormal synchronization of neurons. Since epileptic seizures are unforeseeable for the patients, epileptic seizures detection is an interesting issue in epileptology, that novel approaches to understand the mechanism of epileptic seizures. In this study we analyzed invasive electroencephalogram (EEG) recordings in patients suffering from medically intractable focal epilepsy with a nonlinear method called, dissimilarity index. In order to detect epileptic seizures Bhattacharyya distance between trajectory matrix of reference window during an interval quite distant in time from any seizure and trajectory matrix of present window is employed to measure... 

    Application of a dissimilarity index of EEG and its sub-bands on prediction of induced epileptic seizures from rat's EEG signals

    , Article IRBM ; Volume 33, Issue 5-6 , December , 2012 , Pages 298-307 ; 19590318 (ISSN) Niknazar, M ; Mousavi, S. R ; Shamsollahi, M. B ; Vosoughi Vahdat, B ; Sayyah, M ; Motaghi, S ; Dehghani, A ; Noorbakhsh, S. M ; Sharif University of Technology
    2012
    Abstract
    Objective: Epileptic seizures are defined as manifest of excessive and hyper-synchronous activity of neurons in the cerebral cortex that cause frequent malfunction of the human central nervous system. Therefore, finding precursors and predictors of epileptic seizure is of utmost clinical relevance to reduce the epileptic seizure induced nervous system malfunction consequences. Researchers for this purpose may even guide us to a deep understanding of the seizure generating mechanisms. The goal of this paper is to predict epileptic seizures in epileptic rats. Methods: Seizures were induced in rats using pentylenetetrazole (PTZ) model. EEG signals in interictal, preictal, ictal and postictal... 

    A unified approach for detection of induced epileptic seizures in rats using ECoG signals

    , Article Epilepsy and Behavior ; Volume 27, Issue 2 , 2013 , Pages 355-364 ; 15255050 (ISSN) Niknazar, M ; Mousavi, S. R ; Motaghi, S ; Dehghani, A ; Vosoughi Vahdat, B ; Shamsollahi, M. B ; Sayyah, M ; Noorbakhsh, S. M ; Sharif University of Technology
    2013
    Abstract
    Objective: Epileptic seizure detection is a key step for epilepsy assessment. In this work, using the pentylenetetrazole (PTZ) model, seizures were induced in rats, and ECoG signals in interictal, preictal, ictal, and postictal periods were recorded. The recorded ECoG signals were then analyzed to detect epileptic seizures in the epileptic rats. Methods: Two different approaches were considered in this work: thresholding and classification. In the thresholding approach, a feature is calculated in consecutive windows, and the resulted index is tracked over time and compared with a threshold. The moment the index crosses the threshold is considered as the moment of seizure onset. In the... 

    Construction of an Experimental Device for Foaming Agent and an Experimental Study of the Properties of Foaming Agent

    , M.Sc. Thesis Sharif University of Technology Mohammad Karami (Author) ; Bazargan, Mohammad (Supervisor)
    Abstract
    The primary purpose of acidizing operations in the oil and gas industry is to enhance hydrocarbon production. Acidizing has been a common and conventional method for years, especially when production engineers face issues like declining reservoir pressure leading to reduced production rates. Initially, the treatment solution is referred to as matrix acidizing. In acidizing operations, different additives are combined with the acid to control its behavior in the reservoir. These additives may include iron control agents, corrosion inhibitors, friction reducers, and more. Incompatibility among these additives, the acid, and reservoir fluids can lead to severe damage to the reservoir.... 

    Numerical Analysis of An Annular Gas Turbine Combustor

    , M.Sc. Thesis Sharif University of Technology Gandomi, Mohammad Hossein (Author) ; Farshchi, Mohammad (Supervisor)
    Abstract
    The goal of this research is the simulation of the annular combustion chamber of the turbine engine utilized by liquid fuel. The achievement to this goal will lead to create numerical tools for parametric study, analysis and combustion chamber designing.For this reason simple geometry has been considered. This simplicity of geometry causes to facilitate in parametric study and decrease in saving time for modeling and meshing. This combustion chamber is a simplified model of engine CF6. In recent study, the k – ε realizable model has been used for turbulence modeling. For non-adiabatic condition, chemical reaction is dissolved by utilizing probability density function along with laminar... 

    A misbehavior‐tolerant multipath routing protocol for wireless Ad hoc networks [electronic resource]

    , Article International Journal of Research in Wireless Systems (IJRWS) ; Vol. 2, Issue 9, pp. , Sep. 2013 Sedghi, H. (Haniyeh) ; Pakravan, Mohammad Reza ; Aref, Mohammad Reza ; Sharif University of Technology
    Abstract
    Secure routing is a major key to service maintenance in ad hoc networks. Ad hoc nature exposes the network to several types of node misbehavior or attacks. As a result of the resource limitations in such networks nodes may have a tendency to behave selfishly. Selfish behavior can have drastic impacts on network performance. We have proposed a Misbehavior-Tolerant Multipath Routing protocol (MTMR) which detects and punishes all types of misbehavior such as selfish behavior, wormhole, sinkhole and grey-hole attacks. The protocol utilizes a proactive approach to enforce cooperation. In addition, it uses a novel data redirection method to mitigate the impact of node misbehavior on network... 

    Theoretical and Experimental Study to Conversion of AUC to UO2 by Microwave Heating

    , Ph.D. Dissertation Sharif University of Technology Labbaf, Mohammad Hossein (Author) ; Otukesh, Mohammad (Supervisor) ; Ghannadi Maragheh, Mohammad (Co-Advisor) ; Ghasemi, Mohammad Reza (Co-Advisor)

    SAR Imaging Using the TomoSAR Technique to Resolve Multiple Scatterers

    , M.Sc. Thesis Sharif University of Technology Omati, Mohammad Mahdi (Author) ; Bastani, Mohammad Hassan (Supervisor) ; Karbasi, Mohammad (Co-Supervisor)
    Abstract
    During the last few years, the study of urban environment structures is considered as a research field of interest in remote sensing. In satellite observations of the earth's surface, continuous imaging in terms of time and space has caused the remote sensing technique to be proposed as a useful and efficient tool for the analysis of urban areas. Obtaining quantitative spatial information from the urban environment in fields such as determining the height of buildings plays an essential role in urban planning, monitoring damage to buildings, establishing communication bases and digital cities. During the last two decades, the use of Tomosar approach in order to reconstruct the structures of... 

    Estimating Possible Effects of Subsidies in Competition and Development of Fixed Broadband Internet

    , M.Sc. Thesis Sharif University of Technology Mohammadi, Mohammad Ali (Author) ; Vesal, Mohammad (Supervisor) ; Rahmati, Mohammad Hossein (Supervisor)
    Abstract
    In this work, the dynamic competition between firms providing internet services is studied. The framework is Markov equilibrium whereby structural parameters are obtained using two-step estimations, allowing for analyzing the situation in case of subsidies for service upgrade. The results show that such subsidy has little effect on the number of firms while increasing the number of fast firms  

    Estimating Price Elasticity of Natural Gas Demand in Iran's Residential Sector: A Regression Discontinuity Approach

    , M.Sc. Thesis Sharif University of Technology Makhsousi, Mohammad Hossein (Author) ; Rahmati, Mohammad Hossein (Supervisor) ; Vesal, Mohammad (Supervisor)
    Abstract
    Estimating the price elasticity of gas demand involves complexities depending on the gas market structure and pricing mechanisms in different countries. Distinguishing between supply and demand shocks and block pricing are among the main challenges that can cause endogeneity in elasticity estimates. Iran's domestic gas network, one of the largest and most extensive household gas markets, is divided into five climatic zones based on weather conditions. The pricing steps for these five climates during the five cold months are such that a customer in a warmer climate pays higher prices. Conversely, the pricing steps for the seven warm months are the same for all climates. This policy creates a... 

    Estimate the Effect of Religiosity on Voter Turnout

    , M.Sc. Thesis Sharif University of Technology Jarrahi, Mohammad Mahdi (Author) ; Rahmati, Mohammad Hossein (Supervisor) ; Vesal, Mohammad (Supervisor)
    Abstract
    The correlation between religious adherence and voter turnout is widely studied. However, whether the relation is causal is an open question. We use Household Expenditures and Income Survey (HEIS) data in Iran, which encompasses nine distinct religious expenditures. These expenditures have low correlation with each other and represent different aspects of religious adherence. We use Imamzadeh (some historical holy shrines) as Instruments to estimate the causal effect of religious expenditures on voter turnout. The results reveal that religious expenditures influence both presidential and parliamentary voter turnout, with a notably stronger impact on presidential elections  

    Joint Optimization of Computation Offloading and Resource Allocation in Mobile Edge Computing Networks

    , M.Sc. Thesis Sharif University of Technology Shokouhi, Mohammad Hossein (Author) ; Pakravan, Mohammad Reza (Supervisor) ; Hadi, Mohammad (Co-Supervisor)
    Abstract
    Mobile edge computing (MEC) is a promising technology that aims to resolve cloud computing’s issues by deploying computation resources at the edge of mobile network and in the proximity of users. The advantages of MEC include reduced latency, energy consumption, and load on access and mobile core networks, to name but a few. Despite all the aforementioned advantages, the mobility of mobile network users causes the traditional MEC architecture to suffer from several issues, such as decreased efficiency and frequent service interruption. One of the methods to manage users’ mobility is virtual machine (VM) migration, where the VM containing the user’s task is migrated to somewhere closer to...