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eslami--mahdi
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A Systematic Approach for Biomarker Identification in Autism Spectrum Disorder based on Machine learning
, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor) ; Kavousi, Kaveh (Co-Supervisor) ; Ohadi, Mina (Co-Supervisor)
Abstract
Autism spectrum disorder (ASD) is a strong genetic perturbation that encompasses a wide range of clinical symptoms, including functional at different regions of the brain, repetitive behaviors, and interests, weaknesses in social relationships, some sensitivities to environmental factors and etc. Genetic complexity and the impact of environmental factors put the disease in the category of Level 1 complex developmental disorders.We proposed a pilot, combined, and highly effective structure to identify biomarkers in the autism spectrum disorder that could be extended to other diseases that have a similar genetic architecture with autism. We also develop a Gene-tissue interaction network to...
Modified Gravity; From Theory to Observation
, M.Sc. Thesis Sharif University of Technology ; Baghram, Shant (Supervisor) ; Khosravi, Nima (Co-Advisor)
Abstract
The observations of the cosmic background radiation and large-scale structures show that the standard cosmological model is in good agreement with observational data. The standard model is based on the cosmological constant, dark matter, and Gaussian, nearly scale-invariant, adiabatic, and isotropic initial conditions. Although this model has been phenomenologically successful, but the problems of dark energy, dark matter, missing baryons and early universe remain unresolved. One of the most important theoretical questions in cosmology is whether the cosmological constant is the reason for accelerated cosmic expansion. In other words, is Einsteinian gravity the correct theory on the cosmic...
Control of the Concurrency and Consistency Problem in Readable/Writable Virtual Machine Introspection
, M.Sc. Thesis Sharif University of Technology ; Kharrazi, Mahdi (Supervisor)
Abstract
Over the last years, research about writable virtual machine introspection has been started. This approach has the benefits of readonly virtual machine introspection. Additionally, it has more applications, such as automated defense against malware programs, than the read-only approach. In the read-only VMI, data is gathered from virtual machine hardware states and then analysis in virtual machine monitor. In writable one, hypervisor can modify virtual machine kernel state. Consistency issue is an essential challenge for out-vm writable VMI. In the best of our knowledge, only one implementation try to solve this consistency issue. However it cannot resolve this issue completely. Other VMI...
Data-Assisted Control in Aerial Systems
, Ph.D. Dissertation Sharif University of Technology ; Banazadeh, Afshin (Supervisor)
Abstract
The role of data in the advancement of science and engineering has been emphasized due to the abundance and verity of data, the improvement in online computing speed, the enhancement of quality of life in the era of cyber-physical systems, human aspirations for new discoveries, and the need for real-time decision-making in autonomy. Furthermore, the emergence of new computing capabilities has created additional demands for data. Utilizing data-based methods has become a necessity, as the system model is not always available or cannot be represented as a comprehensive mathematics. System modeling can be extremely challenging and complex, which can hinder controller performance or even render...
Nonlinear Bilateral Adaptive Impedance Control with Applications in Medical Robotics
, Ph.D. Dissertation Sharif University of Technology ; Salarieh, Hassan (Supervisor) ; Behzadipour, Saeed (Supervisor) ; Tavakoli, Mahdi (Co-Advisor)
Abstract
In recent years, teleoperation systems have been widely used in bio-medical applications such as minimally invasive telesurgery, telerehabilitation and telesonography, and also for outer space exploration and radioactive material management. In bilateral teleoperation systems, the human operator applies force on the master robot to control the position of the slave robot in order to perform a task in a remote environment. A nonlinear robust adaptive bilateral impedance control strategy is proposed in this research to provide the absolute stability of multi-DOF teleoperation systems with communication delays. Using this controller, instead of conventional position tracking (synchronization)...
Application of Magnetorheological Damper for Control of Vibration in Marine's Seat
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mahdi (Supervisor) ; Mahdigholi, Hamid (Supervisor)
Abstract
Suspension system is one of the most influential components of vehicle in the area of stability and comfort. The suspension system is designed based on the use of the vehicle and stable characteristics. Obviously, being distant from the designed spots and applying various gates, its optimized performance is lost. Semi-active suspensions by changing their features get floating designed spots to be created and suspension system is always in optimum conditions through a suitable control. This research covers the efficacy of using damper Magneto Rheological which is called damper (MR) on the performance of seat suspension system in reducing vibrations. This damper is considered as a device in...
Inference and Analysis of Hidden Structures of Financial Networks Using Diffusion Models on Complex Network
, M.Sc. Thesis Sharif University of Technology ; Jalili, Mahdi (Supervisor) ; Habibi, Jafar (Supervisor)
Abstract
For along time, analysis of financial markets is an interesting topic for mankind. There are different statistical methods to analyze financial time series. In this manuscript, financial markets are analyzed from network view point. Inference of hidden structures between companies of a market is merit information so we introduce different methods to infer
hidden network structure of financial markets. In addition, we will show that dynamic of network structure can provide important information about external sources of influence on financial markets. Actually, we show affect of political events on financial market of Iran. At last, we generalize diffusion concept at financial networks...
hidden network structure of financial markets. In addition, we will show that dynamic of network structure can provide important information about external sources of influence on financial markets. Actually, we show affect of political events on financial market of Iran. At last, we generalize diffusion concept at financial networks...
Elasticity of DNA Molecule The Role of Anisotropy, Asymmetry and Nonlocal Interactions
, Ph.D. Dissertation Sharif University of Technology ; Ejtehadi, Mohammad Reza (Supervisor)
Abstract
The DNA Molecule carries genetic information in almost all living organisms. The information coded on DNA is an instruction which organizes and conducts all living activities of the living organism. The role of DNA in biological processes is so fundamental that life, as we know, is not possible without DNA. Therefore, studying the biological properties of DNA is crucial for understanding the nature of life. In biological conditions, DNA molecule can be found in highly packed configurations. Since the DNA is a rather stiff molecule, the formation of these configurations cost a considerable amount of energy. The elasticity of DNA plays an important role here. The important question is: how...
Multi Dimensional Dictionary Based Sparse Coding in ISAR Image Reconstruction
, Ph.D. Dissertation Sharif University of Technology ; Nayebi, Mohammad Mahdi (Supervisor) ; Karbasi, Mohammad (Co-Supervisor)
Abstract
By generalizing dictionary learning (DL) algorithms to Multidimensional (MD) mode and using them in applications where signals are inherently multidimensional, such as in three-dimensional (3D) Inverse Synthetic Aperture Radar (ISAR) imaging, it is possible to achieve much higher speed and less computational complexity. In this thesis, the formulation of the Multidimensional Dictionary Learning (MDDL) problem is expressed and six algorithms are proposed to solve it. The first one is based on the method of optimum directions (MOD) algorithm for 1D dictionary learning (1DDL), which uses alternating minimization and gradient projection approach. As the MDDL problem is non-convex, the second...
Drag Reduction by Blowing and Creating a Film of a Secondary Lower Viscosity Fluid-Large Eddy Simulation
, M.Sc. Thesis Sharif University of Technology ; Taeibi Rahni, Mohammad (Supervisor) ; Ramezanizadeh, Mahdi (Supervisor)
Abstract
Drag reduction is one of the most important topics in aerodynamics. Several techniques have been represented to reduce this force, such as surface roughness reduction, blowing, suction, cooling the fluid, etc. Blowing and creating a film of a secondary lower viscosity fluid is the technique used here. In our computations, we used large eddy simulation approach considering viscosity ratio variations effects. Investigations were performed for multiple squared cross sectional jets inclined normally into a turbulent cross flow. Each jet generates a pair of counter rotating vortex pair (CRVP) at its downstream while entering the cross flow. Two horseshoe vortices and a couple of wake vortices...
Operation of Internal Capital Market through Dividend Payout: Evidence from Iranian Business Groups
, M.Sc. Thesis Sharif University of Technology ; Ebrahimnejad, Ali (Supervisor) ; Heidari, Mahdi (Supervisor)
Abstract
Studies of the ownership structure of companies in different countries demonstrates that pyramidal ownership structures and business groups are present and even dominant in many countries. This type of structure allows the ultimate owners to leverage their capital and control more capital in the economy. Studies related to this type of ownership structure, scrutinize various motivations that have caused the formation of this type of ownership structure. Some studies emphasize the destructive role of business groups, such as tunneling and creating monopolies through common ownership in competing companies, and as a result, consumers and small shareholders are expropriated. Others, relying on...
The Application of Deep Learning on Network Traffic Classification
, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor)
Abstract
Almost all of the network traffic classification systems use pre-defined extracted features by the experts in computer network. These features include regular expressions, port number, information in the header of different layers and statistical feature of the flow. The main problem of the traffic analysis and anomaly detection system lies in finding appropriate features. The feature extraction is a time consuming process which needs an expert to be done. It is notable that the classification of special kinds of traffic like encrypted traffic is impossible using some subset of mentioned features.The lack of integration in feature detection and classification is also another important issue...
Receiver Placement in Passive MIMO Radar Systems
, M.Sc. Thesis Sharif University of Technology ; Nayebi, Mohammad Mahdi (Supervisor) ; Behnia, Fereidoon (Supervisor)
Abstract
There are a wide variety of radar systems that one of them is MIMO Radars. After a spark in communication in 1998 that developed MIMO communication, recently there has been a great attention towards MIMO radar systems. Researchers have studied this topic from several points of view. Generally, MIMO radar systems are divided into two categories: MIMO radars widely separated antennas and MIMO radars with collocated antennas. One of the important issues of widely separated MIMO radars, is the placement manner of receivers in the geometrical area. This radar’s performance is very dependent to placement of the antennas, because the performance is dependent to relative position of...
Link Prediction using Dynamic Graph Neural Network with Application to Call Data
, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor)
Abstract
In network science, link prediction is one of the essential tasks that has been neglected. One important application of link prediction in telecommunication networks is analyzing the user's consumption pattern to provide better service. This project aims to predict future links with applications to call data using the users' call history. In previous research, there are two main approaches: 1) heuristic-based approach, and 2) deep-learning-based approach, such as graph neural networks. These methods are mainly used for processing static graphs, and therefore, we cannot generalize them to dynamic graphs. But there are many graphs which are dynamic in nature. For instance, call data records...
Using Electronic Payment Data to Nowcast GDP Growth Rate and Private Consumption Growth rate of Iran
, M.Sc. Thesis Sharif University of Technology ; Barkchian, Mahdi (Supervisor)
Abstract
This research uses the Comovement between electronic payment data with GDP growth rate and private consumption growth rate to nowcast these two important macroeconomics variables. We use point of sale data set from the beginning of 1392 to the end of autumn of 1395 in monthly frequency in mixed data sampling model to use the Comovement for Nowcasting. Besides, we use two other data set, sale of industrial electricity and sale of agricultural electricity. All of this data set gives a real time sense of macroeconomics. They are also free of mistake. We show that using of this data set in the frame of MIDAS can decrease the root mean square forecast error (RMSFE) relative to auto regressive...
A New Approach in Value-at-Risk (VaR) Estimation by Forecast Combination Methods
, M.Sc. Thesis Sharif University of Technology ; Barakchian, Mahdi (Supervisor)
Abstract
Value-at-Risk (VaR) is the most commontool for risk management. This tool is used to measure market risk and also used as a basis in determining financial standards for international financial institutions. VaR is the maximum loss of the asset portfolio at the specified confidence level and certain time horizon. Many parametric, nonparametric and semi parametric methods have been invented for VaR estimation. Each one of these methods has its advantages and disadvantages and different methods may perform better in differnet situations.When estimating VaR, we can choose one of these methods or we can combine the VaRs estimated by different methods. There are few researches conducted on VaR...
Short-term Load Forecasting
, M.Sc. Thesis Sharif University of Technology ; Fatemi Ardestani, Farshad (Supervisor) ; Barakchian, Mahdi (Supervisor)
Abstract
In this thesis we are going to forecast the hourly consumption of the electricity over the country with two models and then, combine them. The first model decomposes the consumption to a deterministic trend and a stochastic residual. The second one assumes that the trend part is also stochastic.Once the consumption is being predicted separately by the models, in the second part of the thesis, we will combine the results to get a final prediction. This prediction is going to be compared with the load forecast of the Dispatching Unit of the electricity network as a base model. We are going to answer two important questions: firstly, does combining the models give a better prediction or not,...
Fault Growth Forecasting of Rotatory Systems Using Wavelet Transform and Artificial Neural Network Algorithm
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mahdi (Supervisor) ; Mahdigholi, Hamid (Supervisor)
Abstract
Failure of mechanical parts in the industry lead to a larger system downtime and even imposing economic losses to the factory. For this Purpose, for many years, researchers have been trying to find ways to predict early failure and to prevent losses from occurring. Creation of new sciences like artificial intelligence, helped researchers in this field.In the current study, using experimental data of a set of bearings that have been tested and recorded in the Intelligent Systems Research Center, A new approach with sufficient accuracy is presented for the prediction algorithm. Among the features extracted, three features of entropy, root mean square and maximum are the most appropriate...
Multi-period Value-at-Risk Forecasting
, M.Sc. Thesis Sharif University of Technology ; Barakchian, Mahdi (Supervisor)
Abstract
Multi-period Value-at-Risk (VaR) forecasting is important for risk management. Financial institutions especially commercial banks according to Basel Committee regulations for capital adequacy in “Internal Approach”, should forecast their VaR for multi-period horizons (longer than one day). The most conventional approach for forecasting multi-period VaR is scaling one-day forecasted VaR that is called “square root of time rule”; therefore most works in this area have been focused on forecasting one-day VaR. In this study, we review performance of a wide range of different methods in forecasting multi-period VaR. The results of our study show that historical simulation performs weakly in...