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    Fault Detection and Identification in Robotic Systems

    , M.Sc. Thesis Sharif University of Technology Baghbahari, Masoud (Author) ; Namvar, Mehrzad (Supervisor)
    Abstract
    Fault detection and identification is one of the major issues and challenges in the field of engineering and currently is considered as an active field of research. As the replacement of human in dangerous or inaccessible environments, robotic mechanical systems can be used which exposes to a variety of stresses and actions that causes faults in the actuators or sensors. Accordingly, detection of fault at the earliest possible time after the fault accurence and its identification such that real flaw waveform is being extracted, can prevent more damage to the system without any need to human immediate interference. Model based approach in recent decades has shown their ability to detection... 

    , M.Sc. Thesis Sharif University of Technology Tasdighi, Alireza (Author) ; Zohuri Zangeneh, Bijan (Supervisor) ; Foroush Bastani, Ali (Supervisor)
    Abstract
    Modeling and simulating accurate patterns which are adapted to our real world is a hard and complicated task. The most important thing for these models is finding any explicite solution, or, finding any solution that is precise as much as possible. The knowledge of financial mathematics by gathering several sciences such as: probabilities, stochastic analysis, numerical analysis, and stochastic differential equations, attempt to determine such exact solutions, or, try to appoximate the explicit answers as precise as possible; in the world of financial trades and contracts. Moreover; one of the most important requirements to control the risk of these financial cotracts, and, then to optimize... 

    Visual tracking using D2-clustering and particle filter

    , Article 2012 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2012 ; 2012 , Pages 230-235 ; 9781467356060 (ISBN) Raziperchikolaei, R ; Jamzad, M ; Sharif University of Technology
    2012
    Abstract
    Since tracking algorithms should be robust with respect to appearance changes, online algorithms has been investigated recently instead of offline ones which has shown an acceptable performance in controlled environments. The most challenging issue in online algorithms is updating of the model causing tracking failure because of introducing small errors in each update and disturbing the appearance model (drift). in this paper, we propose an online generative tracking algorithm in order to overcome the challenges such as occlusion, object shape changes, and illumination variations. In each frame, color distribution of target candidates is obtained and the candidate having the lowest distance... 

    Adaptive and non-adaptive ISI sparse channel estimation based on SL0 and its application in ML sequence-by-sequence equalization

    , Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 27 September 2010 through 30 September 2010 ; Volume 6365 LNCS , September , 2010 , Pages 579-587 ; 03029743 (ISSN) ; 9783642159947 (ISBN) Niazadeh, R ; Hamidi Ghalehjegh, S ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
    2010
    Abstract
    In this paper, we firstly propose an adaptive method based on the idea of Least Mean Square (LMS) algorithm and the concept of smoothed l 0 (SL0) norm presented in [1] for estimation of sparse Inter Symbol Interface (ISI) channels which will appear in wireless and acoustic underwater transmissions. Afterwards, a new non-adaptive fast channel estimation method based on SL0 sparse signal representation is proposed. ISI channel estimation will have a direct effect on the performance of the ISI equalizer at the receiver. So, in this paper we investigate this effect in the case of optimal Maximum Likelihood Sequence-by-sequence Equalizer (MLSE) [2]. In order to implement this equalizer, we... 

    Cluster-based adaptive SVM: a latent subdomains discovery method for domain adaptation problems

    , Article Computer Vision and Image Understanding ; Volume 162 , 2017 , Pages 116-134 ; 10773142 (ISSN) Sadat Mozafari, A ; Jamzad, M ; Sharif University of Technology
    Abstract
    Machine learning algorithms often suffer from good generalization in testing domains especially when the training (source) and test (target) domains do not have similar distributions. To address this problem, several domain adaptation techniques have been proposed to improve the performance of the learning algorithms when they face accuracy degradation caused by the domain shift problem. In this paper, we focus on the non-homogeneous distributed target domains and propose a new latent subdomain discovery model to divide the target domain into subdomains while adapting them. It is expected that applying adaptation on subdomains increase the rate of detection in comparing with the situation... 

    Optimal Retrofitting of the Steel Moment Resisting Frames Using Friction Dampers

    , M.Sc. Thesis Sharif University of Technology Afzalinia, Farshad (Author) ; Moghaddam, Hassan (Supervisor)
    Abstract
    The purpose of this thesis is the optimal retrofitting of the moment resisting frames with friction dampers, using the adaptive approach. In this regard, numerical modeling of the frictional behavior has been presented firstly. Also a 6-story moment resisting frame has been modeled in the OpenSees environment and the time history analysis has been carried out under a specific earthquake record. It is shown that inter-story drifts of the frame exceeds the acceptance criteria which has been assumed 2.5% according to the Life Safety limit. Then, the optimal retrofitting of the frame has been done. It is demonstrated that the maximum inter-story drift of all stories is 2.5% or less, while the... 

    Seismic Rehabilitation of Irregular Steel Structures Using Friction Dampers

    , M.Sc. Thesis Sharif University of Technology Babaei, Hossein (Author) ; Moghaddam, Hassan (Supervisor)
    Abstract
    The purpose of this study was to find the optimal position and slip force of friction dampers, for improving the seismic performance of regular and irregular steel structures and comparison of dampers final pattern of these buildings.In this regard, one to six floor regular and irregular buildings were designed. These buildings were modeled three-dimensionally in the OpenSees Software, and were subjected to horizontal components of seven far field accelerogram in order to investigate the need for their rehabilitation. The results of the time history analysis of these buildings showed that inter-story drifts exceeds the acceptance criteria which has been assumed 2.5% according to the Life... 

    Domain Adaptation Using Source Classifier for Object Detection

    , Ph.D. Dissertation Sharif University of Technology Mozafari, Azadeh Sadat (Author) ; Jamzad, Mansour (Supervisor)
    Abstract
    Detection degradation caused by distribution discrepancy between the training and testing domains is a common problem in object detection systems. The difference between training and testing domains’ distribution mainly happenes because of the different ways of collecting and gathering data. For instance, datasets which have images with different illumination, view point, resolution, background and are obtained by different acquisition systems, have variance in distribution. The solution toward improving the detection rate of the classifier trained on training (source) domain when it is applied on testing (target) domain is to use Domain Adaptation (DA) techniques. One of important branches... 

    A Sample Selection Method for Cost Reduction in Crowd Computing

    , Ph.D. Dissertation Sharif University of Technology Mohammadi, Jafar (Author) ; Rabiee, Hamid Reza (Supervisor)
    Abstract
    The goal of crowd labeling is to find labels of given samples using humans’ mind power.Since crowds are not necessarily experts, their provided labels are rather noisy and erroneous.This challenge is usually resolved by collecting multiple labels for each sample and aggregating them to estimate its true label. Although this mechanism leads to high-quality labels, it is not actually cost effective. Adaptive methods consider that only some samples are challenging and require more labels. They spend the budget more wisely, and iteratively collect the required labels. Using adaptive methods approach, we utilize statistical latent models to model and analyze the collected labels and low-rank... 

    Foreign Exchange Rate Forecasting In Global Money Markets Using Adaptive Methods

    , M.Sc. Thesis Sharif University of Technology Nafarieh, Mohammad (Author) ; Kianfar, Farhad (Supervisor)
    Abstract
    The traders exchange currencies in an online foreign exchange market (Forex), so they need to know ways help them to predict trend of market. There are some methods to forecast exchange rate based on experiment. However they can submit good signals, they are too late for exchange. Two things are important, they should be correct and on time. In this research, we try to submit a prediction by Adaptive Methods in which provides both of them. In first approach, we test 468 models of Artificial Neural Network to achieve the best; and in second approach, Genetic Algorithm and Swarm Intelligence are applied to training Artificial Neural Network. Finally, in addition to forecasting exchange rate,... 

    Development of an Adaptive Model for Coupling the Meshfree Peridynamics to the Finite Element Method

    , Ph.D. Dissertation Sharif University of Technology Nikpayam, Jaber (Author) ; Kouchakzadeh, Mohammad Ali (Supervisor)
    Abstract
    The presence of spatial partial derivatives in the equations of classical continuum mechanics has led to the fact that methods based on this theory are not valid in displacement discontinuities (such as cracks). The peridynamic theory is a nonlocal formulation of solid mechanics which is most suited to model discontinuities and dynamic fractures in continuous or discrete media. By substituting integral expressions instead of partial differentials in the equations of motion, peridynamics provides an integrated model that is valid and the same in continuous, discontinuous, and discrete media.The capability of the peridynamic theory in modeling discontinuities and cracks has been demonstrated... 

    An energy-efficient virtual channel power-gating mechanism for on-chip networks

    , Article Proceedings -Design, Automation and Test in Europe, DATE, 9 March 2015 through 13 March 2015 ; Volume 2015-April , March , 2015 , Pages 1527-1532 ; 15301591 (ISSN) ; 9783981537048 (ISBN) Mirhosseini, A ; Sadrosadati, M ; Fakhrzadehgan, A ; Modarressi, M ; Sarbazi Azad, H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Abstract
    Power-gating is a promising method for reducing the leakage power of digital systems. In this paper, we propose a novel power-gating scheme for virtual channels in on-chip networks that uses an adaptive method to dynamically adjust the number of active VCs based on the on-chip traffic characteristics. Since virtual channels are used to provide higher throughput under high traffic loads, our method sets the number of virtual channel at each port selectively based on the workload demand, thereby do not negatively affect performance. Evaluation results show that by using this scheme, about 40% average reduction in static power consumption can be achieved with negligible performance overhead  

    Towards the optimal tracking interval management for target tracking wireless sensor networks

    , Article ATC 2009 - Proceedings of the 2009 International Conference on Advanced Technologies for Communications, 12 October 2009 through 14 October 2009 ; 2009 , Pages 161-166 ; 9781424451395 (ISBN) Jamali Rad, H ; Abolhassani, B ; Abdizadeh, M ; Sharif University of Technology
    Abstract
    We consider the minimization of power consumption in target tracking wireless sensor networks (WSNs) using dynamic modification of tracking interval. In this context, we first analyze the performance of such networks, using a quantitative mathematical analysis. Then we calculate an upper bound for the achievable improvement in total power consumption, when using an adaptive time interval modification algorithm for tracking moving objects with acceleration. Towards this optimum functionality, we propose a novel adaptive algorithm (AHC) to adapt the tracking interval such that it minimizes power consumption while keeping an acceptable accuracy. Simulation results show that using the proposed... 

    A new adaptive prediction-based tracking scheme for wireless sensor networks

    , Article Proceedings of the 7th Annual Communication Networks and Services Research Conference, CNSR 2009, 11 May 2009 through 13 May 2009, Moncton, NB ; 2009 , Pages 335-341 ; 9780769536491 (ISBN) Jamali Rad, H ; Abolhassani, B ; Abdizadeh, M. T ; Sharif University of Technology
    2009
    Abstract
    The accuracy of the object tracking is dependent on the tracking time interval. Smaller tracking time interval increases the accuracy of tracking a moving object. However, this increases the power consumption significantly. This paper proposes a new adaptive algorithm (AEC) to adapt tracking time interval such that it minimizes power consumption while keeping the required accuracy. Simulation results show that using the proposed algorithm, the tracking network has a good performance with the added advantage of reducing the power consumption significantly when compared with existing nonadaptive methods (like PATES). Moreover, simulation results show that the performance of the proposed... 

    Adaptive exploitation of pre-trained deep convolutional neural networks for robust visual tracking

    , Article Multimedia Tools and Applications ; Volume 80, Issue 14 , 2021 , Pages 22027-22076 ; 13807501 (ISSN) Marvasti-Zadeh, S.M ; Ghanei Yakhdan, H ; Kasaei, S ; Sharif University of Technology
    Springer  2021
    Abstract
    Due to the automatic feature extraction procedure via multi-layer nonlinear transformations, the deep learning-based visual trackers have recently achieved a great success in challenging scenarios for visual tracking purposes. Although many of those trackers utilize the feature maps from pre-trained convolutional neural networks (CNNs), the effects of selecting different models and exploiting various combinations of their feature maps are still not compared completely. To the best of our knowledge, all those methods use a fixed number of convolutional feature maps without considering the scene attributes (e.g., occlusion, deformation, and fast motion) that might occur during tracking. As a... 

    Application of Adaptive Method in Optimum Seismic Design of Steel Moment Resisting Frames and Dampers

    , Ph.D. Dissertation Sharif University of Technology Hosseini Gelekolai, Mojtaba (Author) ; Moghaddam, Hassan (Supervisor)
    Abstract
    The preliminary design of building structures is normally based on the equivalent lateral forces provided in seismic design guidelines. The height-wise distribution of these loads is predominantly based on elastic vibration modes. However, as structures exceed their elastic limits in severe earthquakes, these design load patterns may not necessarily lead to efficient distribution of strength within the structures. To address this issue, several alternative load patterns have been proposed for the seismic design of non-linear structures. However, due to the simplifications involved in the development of these design load patterns, their adequacy needs to be assessed for different structural... 

    Optimal Retrofitting of the Steel Moment Resisting Frames Using Telescopic Dampers

    , M.Sc. Thesis Sharif University of Technology Sakhdari, Sepideh (Author) ; Mofid, Masoud (Supervisor) ; Eskandari, Morteza (Co-Supervisor)
    Abstract
    The purpose of this thesis is the optimal retrofitting of the moment resisting frames with telescopic dampers, using the adaptive approach. In this regard, numerical modeling of the telescopic behavior has been presented firstly. Also, a 3,9,20 story (sac) moment resisting frame has been modeled in the OpenSees environment and the time history analysis has been carried out under a specific earthquake record. It is shown that inter-story drifts of the frame exceed the acceptance criteria which has been assumed 2.5% according to the Life Safety limit. Then, the optimal retrofitting of the frame has been done. It is demonstrated that the maximum inter-story drift of all stories is 2.5% or less,... 

    Zero-gravity emulation of satellites in present of uncalibrated sensors and model uncertainties

    , Article Proceedings of the IEEE International Conference on Control Applications, 8 July 2009 through 10 July 2009, Saint Petersburg ; 2009 , Pages 1063-1068 ; 9781424446025 (ISBN) Talebpour, M ; Namvar, M ; Sharif University of Technology
    Abstract
    Recently, an alternative to the standard passive zero gravity emulation testbeds is developed which uses robotic technology. It is comprised of a manipulator whose end-effector rigidly grasps a satellite mock up, a six-axis force/moment (F/M) sensor placed at the interface of the satellite and the manipulator, and a control system. Despite significant advantages of the approach there exist practical problems such as the existence of uncertainty in the robot dynamic model as well as uncalibrated force/moment sensor measurements. In this paper, new adaptive methods based on the Lyapunov theory are proposed to deal with the model uncertainty and imperfect sensor measurements. Simulations which... 

    An energy efficient target tracking scheme for distributed wireless sensor networks

    , Article Proceedings of the 2009 6th International Symposium on Wireless Communication Systems, ISWCS'09, 7 September through 10 September ; 2009 , Pages 136-140 ; 9781424435845 (ISBN) Jamali Rad, H ; Abolhassani, B ; Abdizadeh, M ; Sharif University of Technology
    Abstract
    We study the problem of power optimization for object tracking using distributed Wireless Sensor Networks (WSNs). The accuracy of the object tracking is dependent on the tracking time interval. Smaller tracking time interval increases the accuracy of tracking a moving object. However, this increases the power consumption significantly. This paper proposes a modified adaptive sleep time management scheme called Modified Predict and Mesh (MPaM) to adapt tracking time interval such that it minimizes power consumption while keeping an acceptable tracking accuracy. Also a quantitative analysis to compare the performances of the conventional PaM and proposed Modified PaM (MPaM) schemes is... 

    A complexity-based approach in image compression using neural networks

    , Article World Academy of Science, Engineering and Technology ; Volume 35 , 2009 , Pages 684-694 ; 2010376X (ISSN) Veisi, H ; Jamzad, M ; Sharif University of Technology
    2009
    Abstract
    In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation...