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    Design and Analysis of a Parallel TKR Simulator for Prosthesis Design Evaluation

    , M.Sc. Thesis Sharif University of Technology Daei Nejad, Fatemeh Sadat (Author) ; Farahmand, Farzam (Supervisor) ; Durali, Mohammad (Supervisor)
    Abstract
    In this project a knee prostheses wear testing simulator based on a parallel mechanism for applying forces and torques, is designed. First according to ISO 14243 standard required degrees of freedom and design constraints are determined and also regarding simulator requirements some considerations in design are outlined. Considering all of these parameters, literature has been searched for proper parallel mechanism and because no suitable parallel mechanism, which is a 3 DoF 2T1R paralle mechanism with rotational degree about z axis, has been found; several new designs of proper mechanism have been presented. Scoring different mechanisms according to outcomed parameters from standard and... 

    Studying and Comparing Agile and Lean Supply Chain Models and Determining the Optimum Model Using Genetic Algorithm

    , M.Sc. Thesis Sharif University of Technology Daei, Mohammad (Author) ; Ghasemi, Farhad (Supervisor)
    Abstract
    As you know in lean supply chains, it is tried to: reduce the wastes of resources and achieve more production with lower consumption of resources. This system is very well suited for many supply chains in which the final determinant factors are price and quality. In contrast, recently, the concept of agile supply chain has been introduced, insisting on flexibility and high service level. Opposite to lean supply chain, agile supply chain needs safety stock to be able to respond to market’s changes.
    Regarding the dissimilarities of these models –including the disagreement in the allocation of safety stock to nodes– In this thesis, in addition to studying and comparing these two approaches,... 

    Improved recovery of analysis sparse vectors in presence of prior information

    , Article IEEE Signal Processing Letters ; Volume 26, Issue 2 , 2019 , Pages 222-226 ; 10709908 (ISSN) Daei, S ; Haddadi, F ; Amini, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    In this letter, we consider the problem of recovering analysis-sparse signals from under-sampled measurements when some prior information about the support is available. We incorporate such information in the recovery stage by suitably tuning the weights in a weighted ℓ1-analysis optimization problem. Indeed, we try to set the weights such that the method succeeds with minimum number of measurements. For this purpose, we exploit the upper-bound on the statistical dimension of a certain cone to determine the weights. Our numerical simulations confirm that the introduced method with tuned weights outperforms the standard ℓ1-analysis technique. © 1994-2012 IEEE  

    Distribution-aware block-sparse recovery via convex optimization

    , Article IEEE Signal Processing Letters ; Volume 26, Issue 4 , 2019 , Pages 528-532 ; 10709908 (ISSN) Daei, S ; Haddadi, F ; Amini, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    We study the problem of reconstructing a block-sparse signal from compressively sampled measurements. In certain applications, in addition to the inherent block-sparse structure of the signal, some prior information about the block support, i.e., blocks containing non-zero elements, might be available. Although many block-sparse recovery algorithms have been investigated in the Bayesian framework, it is still unclear how to incorporate the information about the probability of occurrence into regularization-based block-sparse recovery in an optimal sense. In this letter, we bridge between these fields by the aid of a new concept in conic integral geometry. Specifically, we solve a weighted... 

    Living near the edge: A lower-bound on the phase transition of total variation minimization

    , Article IEEE Transactions on Information Theory ; Volume 66, Issue 5 , 2020 , Pages 3261-3267 Daei, S ; Haddadi, F ; Amini, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    This work is about the total variation (TV) minimization which is used for recovering gradient-sparse signals from compressed measurements. Recent studies indicate that TV minimization exhibits a phase transition behavior from failure to success as the number of measurements increases. In fact, in large dimensions, TV minimization succeeds in recovering the gradient-sparse signal with high probability when the number of measurements exceeds a certain threshold; otherwise, it fails almost certainly. Obtaining a closed-form expression that approximates this threshold is a major challenge in this field and has not been appropriately addressed yet. In this work, we derive a tight lower-bound on... 

    Sample complexity of total variation minimization

    , Article IEEE Signal Processing Letters ; Volume 25, Issue 8 , 2018 , Pages 1151-1155 ; 10709908 (ISSN) Daei, S ; Haddadi, F ; Amini, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    This letter considers the use of total variation (TV) minimization in the recovery of a given gradient sparse vector from Gaussian linear measurements. It has been shown in recent studies that there exists a sharp phase transition behavior in TV minimization for the number of measurements necessary to recover the signal in asymptotic regimes. The phase-transition curve specifies the boundary of success and failure of TV minimization for large number of measurements. It is a challenging task to obtain a theoretical bound that reflects this curve. In this letter, we present a novel upper bound that suitably approximates this curve and is asymptotically sharp. Numerical results show that our... 

    Reconstruction of binary shapes from blurred images via hankel-structured low-rank matrix recovery

    , Article IEEE Transactions on Image Processing ; Volume 29 , 2020 , Pages 2452-2462 Razavikia, S ; Amini, A ; Daei, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    With the dominance of digital imaging systems, we are often dealing with discrete-domain samples of an analog image. Due to physical limitations, all imaging devices apply a blurring kernel on the input image before taking samples to form the output pixels. In this paper, we focus on the reconstruction of binary shape images from few blurred samples. This problem has applications in medical imaging, shape processing, and image segmentation. Our method relies on representing the analog shape image in a discrete grid much finer than the sampling grid. We formulate the problem as the recovery of a rank $r$ matrix that is formed by a Hankel structure on the pixels. We further propose efficient... 

    A MAP-Based order estimation procedure for Sparse channel estimation

    , Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 25 2015 through 28 August 2015 ; Volume 9237 , August , 2015 , Pages 344-351 ; 03029743 (ISSN) ; 9783319224817 (ISBN) Daei, S ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
    Springer Verlag  2015
    Abstract
    Recently, there has been a growing interest in estimation of sparse channels as they are observed in underwater acoustic and ultrawideband channels. In this paper we present a new Bayesian sparse channel estimation (SCE) algorithm that, unlike traditional SCE methods, exploits noise statistical information to improve the estimates. The proposed method uses approximate maximum a posteriori probability (MAP) to detect the non-zero channel tap locations while least square estimation is used to determine the values of the channel taps. Computer simulations shows that the proposed algorithm outperforms the existing algorithms in terms of normalized mean squared error (NMSE) and approaches... 

    On the error in phase transition computations for compressed sensing

    , Article IEEE Transactions on Information Theory ; Volume 65, Issue 10 , 2019 , Pages 6620-6632 ; 00189448 (ISSN) Daei, S ; Haddadi, F ; Amini, A ; Lotz, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    Evaluating the statistical dimension is a common tool to determine the asymptotic phase transition in compressed sensing problems with Gaussian ensemble. Unfortunately, the exact evaluation of the statistical dimension is very difficult and it has become standard to replace it with an upper-bound. To ensure that this technique is suitable, [1] has introduced an upper-bound on the gap between the statistical dimension and its approximation. In this work, we first show that the error bound in [1] in some low-dimensional models such as total variation and ell _{1} analysis minimization becomes poorly large. Next, we develop a new error bound which significantly improves the estimation gap... 

    Algorithms for Sparse Channel Estimation

    , M.Sc. Thesis Sharif University of Technology Daei Omshi, Sajjad (Author) ; Babaei Zadeh, Masoud (Supervisor)
    Abstract
    Recently, there has been much interest in sparse channel estimation, i.e. recovering a channel which has much less non zero tabs than its length. These channels have been observed in underwater and broadband wireless channels. In the last few years methods available to estimate these channels have used sparse structure information to improve the estimates. However, these methods are vulnerable to noise and interference. In other words, these methods do not use channel posterior information obtained from the received signal and this is detrimental to the estimator performance. In order to solve these problems in this thesis, motivated by CoSAMP algorithm which is a sparse signal processing... 

    Investigating the Amplitude of the Kinematic Dipole and Clustering in Cosmic Large-Scale Structure and the Effects of the Long Mode in the Early Universe

    , M.Sc. Thesis Sharif University of Technology Daei Rasouli, Arefeh (Author) ; Baghram, Shant (Supervisor) ; Rahvar, Sohrab (Supervisor)
    Abstract
    The standard ΛCDM model is built upon the cosmological principle, which states that the universe is homogeneous and isotropic on large scales (greater than 100 Mpc). A crucial test of this principle involves analyzing the Cosmic Microwave Background (CMB) radiation, which exhibits a dipole anisotropy on the order of ΔT/T∼10^−3. This dipole is commonly interpreted as owing to our motion with respect to the CMB rest frame. A model-independent approach to validate this kinematic hypothesis is to determine the dipole moment in the angular distribution of large-scale structures. According to the cosmological principle, the rest frame of the large-scale structure distribution should align with the... 

    Investigation and Simulation of Compton-Positron Emission Tomography Imaging System to Improve Image Quality

    , M.Sc. Thesis Sharif University of Technology Daei Ghafur Basir, Fatemeh (Author) ; Hosseini, Abolfazl (Supervisor) ; Niknami, Mostafa (Co-Supervisor)
    Abstract
    The combination of Compton imaging and positron emission tomography, also known as Compton-PET, has gained attention due to its improved spatial resolution and imaging sensitivity compared to PET imaging alone. Compton-PET simulated system consists of two concentric detector rings. The inner ring with a smaller diameter is called the Compton scattering detector, the scatterer, and the outer ring, which has the dual applications of Compton scattering detection and PET detector, is called the absorber. Improving the images is possible by increasing resolution, contrast, and reducing noise, and the quality of nuclear medicine images also depends on these three characteristics. Considering the... 

    Estimating Stopping Time Using Function Approximation Algorithms in Reinforcement Learning

    , M.Sc. Thesis Sharif University of Technology Daei Naby, Ali (Author) ; Alishahi, Kasra (Supervisor) ; Haji Mirsadeghi, Mir omid (Supervisor)
    Abstract
    We study the expected value of stopping times in stochastic processes. Since there is no rigorous solution for computing stopping times in many processes, our approach is based on estimation using well-known methods in the Reinforcement Learning literature. The primary method in this research is the temporal difference algorithm. With some modifications, we can study the role of some state features in determining the stopping time. Moreover, without a complicated mathematical analysis, we can find functions closely enough to the goal function.Furthermore, we compare our proposed algorithm to the well-known regression methods and show our algorithm's advantages and disadvantages. The primary... 

    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...