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    Graph Learning from Incomplete and Noisy Graph Signals

    , M.Sc. Thesis Sharif University of Technology Daghestani, Amir Hossein (Author) ; Babaiezadeh, Masoud (Supervisor)
    Abstract
    The problem of inferring a graph from a set of graph signals over it plays a crucial role in the field of Graph Signal Processing (GSP). When provided with a graph that best models the structure of data, the GSP algorithms can offer high data processing capability. However, a meaningful graph of data is not always available, hence in some applications, the graph needs to be learned from the data itself. When the data is corrupted and missing, this task becomes even more challenging. In this paper, we present a graph learning algorithm that is capable of learning the underlying structure of data from an incomplete and noisy dataset of graph signals. We propose an algorithm that jointly... 

    Incremental Discovery of Representative Sample Sets in Networks

    , M.Sc. Thesis Sharif University of Technology Salehe, Mohammad (Author) ; Ghodsi, Mohammad (Supervisor)
    Abstract
    In many network which relationships between nodes are defined based on the similarity of attributes (Such as the World Wide Web and social networks), extracting information about networks object’s attributes may be difficult or even in many cases impossible.In these cases, predicting unknown attributes based on other objects attributes according to network structure can be extremely useful.Even more, finding a representative sample set of objects and trying to obtain their attributes in order to predict other object’s attributes with this obtained data can be an interesting problem. Finding such a set of objects with minimum size while giving maximizing accuracy in predicting other object’s... 

    General Reinforcement Learning

    , M.Sc. Thesis Sharif University of Technology Makiabadi, Nima (Author) ; Alishahi, Kasra (Supervisor)
    Abstract
    Reinforcement learning (RL) is a subfield of machine learning that expresses how to learn optimal actions in a wide range of unknown environments. Reinforcement learning problems are often phrased in terms of Markov decision processes (MDPs). However, being restricted to Markov environments to solve problems with limited state space is not an unreasonable assumption, but the main challenge is to consider these problems in as large a class of environments as possible, which includes any challenges that an agent may face in real world. Such agents are able to learn to play chess, wash dishes, invest in financial markets, and do many tasks that an intelligent human being can learn and do. In... 

    Magnetic Resonance Imaging Scan Time Reduction

    , M.Sc. Thesis Sharif University of Technology Alviri, Mohammad Reza (Author) ; Vosoughi, Naser (Supervisor) ; Vosoughi Vahdat, Bijan (Supervisor)
    Abstract
    Magnetic resonance imaging (MRI) is a highly efficient method that can provide acceptable contrast between soft tissues. But the big disadvantage of this method is that its acquisition is slow. To find the reason of being time-consuming should the procedure be surveyed. In the magnetic resonance imaging, location information obtained using phase and frequency encoding gradients. So the output is matrix of image data in the frequency domain, which is called k space. For the formation of the k space phase, need to apply gradients several times and this is the main reason of dullness of the system. Therefore, in this project using software methods try to reduce the scan time as possible. Among... 

    Compressed Sensing in SAR

    , M.Sc. Thesis Sharif University of Technology Kamjoo, Mohammad Mahdi (Author) ; Marvasti, Farokh (Supervisor)
    Abstract
    The remote sensing is the knowledge of gaining information about an event without having direct access to it, and synthetic aperture radars (SAR) have gained spectacular attention in this filed due to their wide applications and high efficiency. The performance of SAR, which are classified in the space-borne or space-borne radars is similar to that of pulse radars. The transmitted signals in SAR are generally chirp signals, and the received signal is two-dimensional which is scattered in two dimensions of range and azimuth called as raw data. Due to relative movement between the radar base and the target point, the distance between the radar base and the target point would not be fixed along... 

    Probabilistic Framework for Seismic Risk Analysis of Industrial Plants of the Oil Infrastructure

    , M.Sc. Thesis Sharif University of Technology Kamali Shakib, Mohammad Javad (Author) ; Mahsouli, Mojtaba (Supervisor)
    Abstract
    This research proposes a probabilistic framework for seismic risk analysis of industrial plants of oil infrastructure using reliability methods. The proposed approach integrates multiple probabilistic models and system reliability to quantify the seismic risk of the process plants. A chain of probabilistic seismic hazard and risk models is utilized for the risk analysis. The Monte Carlo sampling method is used to propagate the significant uncertainty in the hazard event, damage to components and its consequences, and the potential losses incurred by process plant. In each sample of the analysis, hazard models simulate the occurrence, magnitude, and rupture area and location of earthquake... 

    An Interior Needle Electropolymerized Pyrrole-Based Coating for Headspace Solid-Phase Dynamic Extraction of Chlorophenols

    , M.Sc. Thesis Sharif University of Technology Kamal Abyaneh, Zahra (Author) ; Bagheri, Habib (Supervisor)
    Abstract
    Nowadays, the inside needle capillary adsorption trap (INCAT) technique as a solventless sample preparation approach and alternative extraction method derived from SPME is gaining rising attentions. The INCAT and needle-trap devices are inexpensive, robust, reusable, and are applicable for sampling and analyzing suitable organic compounds from many different sample matrices. Compared to the fragile silica-based SPME fiber, the needle device is nearly impossible to break mechanically. In addition, the extraction medium possesses quite a large extraction phase volume and a powerful preconcentration capability. Similar to SPME, needle-like devices are particularly convenient for automation and... 

    Deterministic Compressed Sensing

    , Ph.D. Dissertation Sharif University of Technology Amini, Arash (Author) ; Marvasti, Farrokh (Supervisor)
    Abstract
    The emerging field of compressed sensing deals with the techniques of combining the two blocks of sampling and compression into a single unit without compromising the performance. Clearly, this is not feasible for any general signal; however, if we restrict the signal to be sparse, it becomes possible. There are two main challenges in compressed sensing, namely the sampling process and the reconstruction methods. In this thesis, we will focus only on the deterministic sampling process as opposed to the random sampling. The sampling methods discussed in the literature are mainly linear, i.e., a matrix is used as the sampling operator. Here, we first consider linear sampling methods and... 

    Sampling in Large-Scale Complex Networks

    , Ph.D. Dissertation Sharif University of Technology Salehi, Mostafa (Author) ; Rabiei, Hamid Reza (Supervisor)
    Abstract
    Many real-world communication systems such as Internet, online social networks, and brain networks can be modeled as a complex network of interacting dynamical nodes. These networks have non-trivial topological features, i.e., features that do not occur in simple networks such as lattices or random networks. The tremendous growth of Internet and its applications in recent years has resulted in creation of large-scale complex networks involving tens or hundreds of millions of nodes and links. Thus, it may be impossible or costly to obtain a complete picture of these large networks, and sampling methods are essential for practical estimation of network properties. Therefore, in this thesis, we... 

    Sampling of Complex-Networks by Considering Activity-Level of Node

    , M.Sc. Thesis Sharif University of Technology Khodadadi, Ali (Author) ; Manzuri Shalmani, Mohammad Taghi (Supervisor)
    Abstract
    Many studies has been focused on extracting structural and behavioral properties of complex networks in recent decade. Online Social Networks (OSNs) are one example of complex networks. Nowadays with rapid growth of OSNs such as Facebook and Twitter, the study of OSNs has become an interesting research area. Many of recent OSN studies studied friendship networks. Friendship network is a binary unweighted network, and all of its links have the same importance. But, in reality not only all friendship links are not representative of social interactions, but also the social links have a variety of intimacy, intensity, and etc. So, all links should not be considered equal. Recently researchers... 

    RF Signal Sampling using Compress Sensing and its Implementation on FPGA

    , M.Sc. Thesis Sharif University of Technology Talebi Tabar Monfared, Homayoon (Author) ; Pezeshk, Amir Mansour (Supervisor)
    Abstract
    Analog-to-digital conversion and signal processing has been increasing due to its many advantages. So that mostly we prefer to convert signal from analog area to digital samples, then they are processed and finaly put the result signal at the system output. How ever because the restriction of the sampling rate, Prevent the spread of digital processing for the high-frequency signal (RF). In recent years, ADCs sampling rate rise up to several GHz (for example ADC with 4 GSPS and 12 bits for TI) that output of the these ADCs by powerful and fast FPGAs are processed but According to Shannon theorem band width of these ADCs is not desirable.the goal of this thesis uses of the compressed sensing... 

    Sparse Representation with Application to Image Inpainting

    , M.Sc. Thesis Sharif University of Technology Javaheri, Amir Hossein (Author) ; Marvasti, Farrokh (Supervisor)
    Abstract
    The emerging field of compressed sensing has found wide-spread applications in signal processing. Exploiting the sparsity of natural image signals on basis of a set of atoms called dictionary, one can find numerous examples for applications of compressed sensing in the field of image processing. One of these interesting applications is to help recover missing samples of a damaged or lossy image signal which is also known as image inpainting. There are dozens of reasons why an image may get damaged, for instance, during data transmission, some blocks of an image (or frames of a video ) may get lost due to error in the telecommunication channel (this is known as block-loss). In this case image... 

    Source Localization by Analysis the Response of Detectors Using Inverse Methods

    , M.Sc. Thesis Sharif University of Technology Mechershavi, Fatemeh (Author) ; Vosoughi, Naser (Supervisor)
    Abstract
    Localization of a neutron point source using a designed computer program namely “MCMC-MATURE” is performed. The computer program analyses several detector responses in some certain media by Markov Chain Monte Carlo (MCMC) method and a new iteration algorithm. Identification of the possible regions of source position would be found by analyzing the initial fluxes generated by mesh tally of MCNPX computer code. The designed computer program is capable to generate the flux between detectors. “Regular-Sequential”, “Irregular-Sequential” and “Non-Sequential” are three methods used for sampling the generated random number in two dimensions. Each sample multiplied by a sampling function and lead to... 

    Comparison and Evaluation of Flood Simulation Under Different Scenarios in Kashkan River and Missouri Basins Using Hec-Ras and Lisflood-Fp, and Development of a Method for Downscaling of Flood Discharge

    , M.Sc. Thesis Sharif University of Technology Ahmadi, Mohammad (Author) ; Moghim, Sanaz (Supervisor)
    Abstract
    This study consists of two parts. In the first part, the performance of the LISFLOOD-FP model, which is raster-based, and the HEC-RAS model, are compared and evaluated. This work studied different scenarios under various digital models in two study areas, the Kashkan study basin with mountainous topography and the basin in Nebraska, which has a plain surface. The flood events are among the most severe floods in both study areas that occurred in March and April 2019. This study showed that in mountain topography, the performance of both models is good even with the 30 m high digital models. Although two models perform well, in the Nebraska basin, the performance of the two models in the... 

    Study on the Performance of Magnetic Nanoparticles in Hyper-thermic Treatment of Cancerous Tumors, by Heating an MRI Apparatus

    , M.Sc. Thesis Sharif University of Technology Payami Golhin, Zahra (Author) ; Outokesh, Mohammad (Supervisor) ; Nourani, Mohammad Reza (Supervisor)
    Abstract
    The aim of this study was to investigate the rate of increase in temperature of a phantom equivalent to body tissue by different groups of magnetic iron nanoparticles in the external magnetic field to kill cancer cells based on the hyperthermia method. To achieve this goal, three groups of dextran magnetic nanoparticles with different properties and reduced iron oxide-graphene oxide magnetic nanoparticles by M-rGO supercritical synthesis method were used. After XRD, FTIR, SEM, FESEM, VSM, TEM characterization tests, these materials were placed in a phantom made of agarose gel and with the same properties, in a magnetic field with fixed characteristics for all groups and during the process of... 

    The Inverse Electromagnetic Scattering Problem

    , M.Sc. Thesis Sharif University of Technology Sajedi, Masoumeh (Author) ; Hesaaraki, Mahmoud (Supervisor)

    Modeling and Control of Hybrid Systems Including Multirate Sampling

    , M.Sc. Thesis Sharif University of Technology Samadi, Sediqeh (Author) ; Bozorgmehry Boozarjomehry, Ramin (Supervisor)
    Abstract
    Whenever continuous and discrete dynamics interact, hybrid systems arise. Basically, models of such systems consisted of differential or difference equations to represent continuous dynamics and automata or other discrete variables to describe behavioral mode of the systems. Our main concern is focused on two types of hybrid systems: Discrete controllers which are combined with continuous physical process like biological systems can often be well described by hybrid systems. Our approach in this thesis deals with optimal multiple daily insulin injections which are introduced as an offline control approach on a simulated patient with type I diabetes. Simulated patient is provided via GlucoSim... 

    Destination Choice Modeling For Shopping Trips; Case Study For The City of Shiraz

    , M.Sc. Thesis Sharif University of Technology Rahimi, Ehsan (Author) ; Samimi, Amir (Supervisor)
    Abstract
    The fratar model that is one of the most common models of travel distribution has some weak points. Due to its strong tendency to existing distribution and disregarding the zonal characteristics, this model is unable to consider sudden changes in plan on the horizon. In order to identify the variables affecting the distribution of travel, using the behavioral approach is vital. For this purpose, Multinomial Logit model is used for distribution of shopping trips in the city of Shiraz. The city of Shiraz is divided into 156 zones. If all zones be considered as the choice set for each traveler, the results of model won't be efficient. To address this problem, sampling should be done based on... 

    Secure Communication via Cooperation and Cooperative Jamming

    , M.Sc. Thesis Sharif University of Technology Hatami, Mohammad (Author) ; Behroozi, Hamid (Supervisor)
    Abstract
    The broadcast nature of wireless communications makes the propagation medium vulnerable to security attacks such as eavesdropping and jamming from adversarial or unauthorized users. Applying physical layer secrecy approaches will enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers, without using any secret keys. However, physical layer security approaches are typically feasible only when the source-eavesdropper channel is weaker than the source-destination channel. Cooperative jamming can be used to overcome this challenge and increase the secrecy rate. In this thesis, the security of two-phase relaying system with multiple... 

    The Information Theory Approach to Communication over Deletion Channel with Hidden Markov Codebook

    , M.Sc. Thesis Sharif University of Technology Molavipour, Sina (Author) ; Aminzadeh Gohari, Amin (Supervisor)
    Abstract
    One of the main challenges in data transmission is synchronization error. In practice there are solutions to this issue, but this incurs a cost that can not be neglected. Synchronization error consists of deletion, insertion and substitution. Investigation of such errors in a communication channel has been of a great concern in information theory. Furthermore, in many applications such as biology and data storage on disks, we observe synchronization errors. Deletion channel is defined as a channel in which input symbols are deleted with a probability d independently of each other, such that the order of symbols remains unchanged. In spite of attempts to find a closed form for the capacity of...