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    Sound source localization in wide-range outdoor environment using distributed sensor network

    , Article IEEE Sensors Journal ; Volume 20, Issue 4 , 2020 , Pages 2234-2246 Faraji, M. M ; Shouraki, S. B ; Iranmehr, E ; Linares Barranco, B ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    Sound source localization has always been one of the most challenging subjects in different fields of engineering, one of the most important of which being tracking of flying objects. This article focuses on sound source localization using fuzzy fusion and a beamforming method. It proposes a new fuzzy-based algorithm for localizing a sound source using distributed sensor nodes. Eight low-cost sensor nodes have been constructed in this study each of which consists of a microphone array to capture sound waves. Each node is able to record audio signals synchronously on an SD card to evaluate different algorithms offline. However, the sensor nodes are designed to be able to estimate the location... 

    Multi-GNSS constellation fusion based on statistical features of positioning error

    , Article 26th Iranian Conference on Electrical Engineering, ICEE 2018, 8 May 2018 through 10 May 2018 ; 2018 , Pages 725-730 ; 9781538649169 (ISBN) Abolfathi Momtaz, A ; Behnia, F ; Marvasti, F ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    With the advent of new positioning services, one can reach more satellites these days to find his position. Using a combination of satellites which belong to different constellations needs some considerations like addressing biases between their time references. Each constellation has progressed to the point that they have enough satellites to provide accurate position separately. According to this fact, we propose to find the position in each constellation and fusion their results in a way that final position has the minimum possible variance instead of combining the constellations in a satellite level and dealing with inter system biases. Experimental studies are conducted based on IGS... 

    Performance comparison of the neyman-pearson fusion rule with counting rules for spectrum sensing in cognitive radio

    , Article Iranian Journal of Science and Technology - Transactions of Electrical Engineering ; Volume 36, Issue E1 , 2012 , Pages 1-17 ; 22286179 (ISSN) Mosleh, S ; Tadaion, A. A ; Derakhtian, M ; Aref, M. R ; Sharif University of Technology
    2012
    Abstract
    Distributed spectrum sensing (DSS) is of great importance in Cognitive Radio, especially under fading or shadowing effects. In order to evaluate the performance of a distributed system, it is commonly compared with the centralized system as an upper performance bound. Now the question is whether or not one can obtain a distributed strategy serving as an upper bound to benchmark any distributed strategy, tighter than that of the centralized scheme. Here, we suggest employing the Neyman-Pearson (NP) fusion rule to achieve an upper bound. Furthermore, the analysis of a randomized fusion rule has been provided, which is a long-existing problem in this field. For this purpose, theoretical... 

    Asynchronous track-to-track fusion by direct estimation of time of sample in sensor networks

    , Article IEEE Sensors Journal ; Vol. 14, issue. 1 , Jan , 2014 , p. 210-217 ; 1530437X Talebi, H ; Hemmatyar, A. M. A ; Sharif University of Technology
    Abstract
    Asynchronous data fusion is inevitable in track-to-track fusion for tracking high-speed targets. For low-speed targets, e.g., the movement of clouds, synchronization is insignificant and, depending on the application, may be disregarded. Real-time asynchronous fusion is a demanding task in sensor networks when the sensors are not synchronous in sampling-rate or in sampling-phase. In the method proposed in this paper, an estimator in the fusion center estimates the actual time of the sample with respect to the time-reference of the fusion center upon receiving the data from a sensor. Then, the computer of the fusion center uses predictions to transfer all the received data to the data... 

    Distibuted human tracking in smart camera networks by adaptive particle filtering and data fusion

    , Article 2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012, 30 October 2012 through 2 November 2012 ; November , 2012 ; 9781450317726 (ISBN) Rezaei, F ; Khalaj, B. H ; Sharif University of Technology
    2012
    Abstract
    Human tracking is an essential step in many computer vision-based applications. As single view tracking may not be sufficiently robust and accurate, tracking based on multiple cameras has been widely considered in recent years. This paper presents a distributed human tracking method in a smart camera network and introduces a particle filter design based on Histogram of Oriented Gradients (HOG) and color histogram. The proposed adaptive motion model also estimates the target speed from the history of its latest displacement and improves the robustness of the tracker by decreasing the probability of missing targets. In addition, a distributed data fusion method is proposed which fuses the... 

    Trunk motion system (TMS) using printed body worn sensor (BWS) via data fusion approach

    , Article Sensors (Switzerland) ; Volume 17, Issue 1 , 2017 ; 14248220 (ISSN) Mokhlespour Esfahani, M. I ; Zobeiri, O ; Moshiri, B ; Narimani, R ; Mehravar, M ; Rashedi, E ; Parnianpour, M ; Sharif University of Technology
    MDPI AG  2017
    Abstract
    Human movement analysis is an important part of biomechanics and rehabilitation, for which many measurement systems are introduced. Among these, wearable devices have substantial biomedical applications, primarily since they can be implemented both in indoor and outdoor applications. In this study, a Trunk Motion System (TMS) using printed Body‐Worn Sensors (BWS) is designed and developed. TMS can measure three‐dimensional (3D) trunk motions, is lightweight, and is a portable and non‐invasive system. After the recognition of sensor locations, twelve BWSs were printed on stretchable clothing with the purpose of measuring the 3D trunk movements. To integrate BWSs data, a neural network data... 

    Human arm motion tracking by inertial/magnetic sensors using unscented Kalman filter and relative motion constraint

    , Article Journal of Intelligent and Robotic Systems: Theory and Applications ; Volume 90, Issue 1-2 , May , 2018 , Pages 161-170 ; 09210296 (ISSN) Atrsaei, A ; Salarieh, H ; Alasty, A ; Abediny, M ; Sharif University of Technology
    Springer Netherlands  2018
    Abstract
    Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the... 

    Improvements of image-steganalysis using boosted combinatorial classifiers and gaussian high pass filtering

    , Article 2008 4th International Conference on Intelligent Information Hiding and Multiedia Signal Processing, IIH-MSP 2008, Harbin, 15 August 2008 through 17 August 2008 ; 2008 , Pages 1508-1511 ; 9780769532783 (ISBN) Asadi, N ; Jamzad, M ; Sajedi, H ; Sharif University of Technology
    2008
    Abstract
    Powerful universal steganalyzers were proposed in the literature during the past few years. In addition some studies have been conducted on improvements of current steganalysis results using information fusion techniques, merging available feature vectors, etc. This paper presents two independent ideas, which can be used together, to obtain higher accuracy in detecting stego images. First, we propose the use of boosted fusion methods to aggregate outputs of multiple steganalyzers. Second, we investigate how passing high frequencies through filtering can enhance the results of steganalysis techniques. In this work, it is shown that, through different tests over the state-of-the-art... 

    Secure consensus averaging for secure information fusion in sensor networks

    , Article 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Sharjah, 12 February 2007 through 15 February 2007 ; 2007 ; 1424407796 (ISBN); 9781424407798 (ISBN) Kefayati, M ; Talebi, M. S ; Rabiee, H. R ; Khalaj, B. H ; Sharif University of Technology
    2007
    Abstract
    In this work, we have examined the problem of distributed consensus averaging over senor networks from a novel point of view considering the need for security. We have proposed a method for incorporating privacy into the scalable average consensus mechanisms. Our proposed method, Random Projections Method (RPM), is lightweight and transparent since it is not based on cryptography and does not require any change in the fusion system. RPM is based on introducing a simple, yet effective pre-fusion algorithm. We mathematically derived the correctness of RPM and analyzed its effect on convergence of the system through simulation. Robustness of RPM against honest-but-curious adversaries is... 

    Human arm motion tracking by inertial/magnetic sensors using unscented kalman filter and relative motion constraint

    , Article Journal of Intelligent and Robotic Systems: Theory and Applications ; 2017 , Pages 1-10 ; 09210296 (ISSN) Atrsaei, A ; Salarieh, H ; Alasty, A ; Abediny, M ; Sharif University of Technology
    Abstract
    Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the... 

    Abnormality detection and monitoring in multi-sensor molecular communication

    , Article IEEE Transactions on Molecular, Biological, and Multi-Scale Communications ; Volume 5, Issue 2 , 2019 , Pages 68-83 ; 23327804 (ISSN) Ghoroghchian, N ; Mirmohseni, M ; Nasiri Kenari, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    In this paper, we investigate the problem of detecting and monitoring changes (abnormality) in molecular communication (MC), using the quickest change detection (QCD) schemes. The objective is to watch an environment using a sensor network and make decisions on the time and location of changes based on the received signals from sensors in the fusion center (FC). Such assumptions call for considering spatial and temporal correlations among sensors' transmitting signals. We use the framework of Partially Observable Markov Decision Processes (POMDPs) based on non-homogeneous Markov models. The metric in detection (stopping-time) scenario is to minimize the delay of announcing an abnormality... 

    Distributed Tracking in Smart Camera Networks

    , M.Sc. Thesis Sharif University of Technology Rezaei Hosseinabadi, Fatemeh (Author) ; Hossein Khalaj, Babak (Supervisor)
    Abstract
    Human tracking is an essential step in many computer vision-based applications. As single view tracking may not be sufficiently robust and accurate, tracking based on multiple cameras has been widely considered in recent years. This thesis presents a distributed human tracking method in a smart camera network and introduces a particle filter design based on Histogram of Oriented Gradients (HOG) and color histogram. The proposed adaptive motion model also estimates the target speed from the history of its latest displacement and improves the robustness of the tracker by decreasing the probability of missing targets. In addition, a distributed data fusion method is proposed which fuses the... 

    Design and Manufacturing a Wearable Measuring System for Trunk Movements

    , M.Sc. Thesis Sharif University of Technology Mokhlespour Esfahani, Mohammad Iman (Author) ; Parnianpour, Mohamad (Supervisor) ; Narimani, Roya (Supervisor) ; Moshiri, Behzad (Co-Advisor) ; Hoviattalab, Maryam (Co-Advisor)
    Abstract
    Measurement of human movement during work, sport as daily activities has important effects for rehabilitation and biomechanics experts.
    Recently, several researches are concentrated on this technology significantly because of new progress in sensors and fusion sensors. In the near future, wearable and ambulatory devices will be used considerably in biomedical applications. In this study, we reviewed some methods about wearable measuring system then introduced and designed innovative wearable clothing for this purpose. Some specifications and advantages of our system in comparison with relevant researches are; using textile sensors that are manufactured through nano electro active polymer... 

    Body Orientation Measurement by Multisensor Data Fusion

    , M.Sc. Thesis Sharif University of Technology Akbari, Ali (Author) ; Vosoughi Vahdat, Bijan (Supervisor) ; Parnianpour, Mohammad (Supervisor)
    Abstract
    The importance of the motion measurement systems is obvious due to survey the number of people who have joint pains through wrong movements. Considering the medical device’s trend toward wearable systems, the necessity of portable measurement instruments which are independent from experimental setup, is undeniable. Motion measurement systems based on MEMS Inertial sensors are widely used these days because they are cheap and portable. However these systems have some defects such as error accumulation and increasing error due to magnetic disturbance or high acceleration motions. Multisensory data fusion along with compensator filters is the best solution in order to reduce these errors.... 

    IMU and Kinect Data Fusion for Human Arm Motion Tracking Using Unscented Kalman Filter

    , M.Sc. Thesis Sharif University of Technology Atrsaei, Arash (Author) ; Salarieh, Hassan (Supervisor) ; Alasti, Aria (Co-Advisor)
    Abstract
    Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in non-laboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g. home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the... 

    Implementation of RUL Estimation Approaches on Software Platform, Concentrated on Confidence Level Determination in Rolling Element Bearings

    , M.Sc. Thesis Sharif University of Technology Mirfarah, Motahareh (Author) ; Behzad, Mehdi (Supervisor)
    Abstract
    Estimating the remaining useful life (RUL) of critical assets is an essential task in system health management. It also has a crucial role in the optimization of maintenance scheduling and decision making about the future of the asset. On the other hand, since the rolling element bearings are widely used in the rotating machinery, estimation of their RUL is considered as remarkable progress in improving the reliability of the whole system. In this way, various models have been introduced to predict the RUL of rolling element bearings, which their proper functionality is affected by the underlying assumptions in the model structure. Because of the presence of several uncertainties and... 

    Improving the Performance of Distributed Fusion for PHD Filter in Multi-Object Tracking

    , M.Sc. Thesis Sharif University of Technology Khazaei, Mohammad (Author) ; Jamzad, Mansour (Supervisor)
    Abstract
    The Gaussian mixture (cardinalized) probability hypothesis density (GM-(C)PHD) filter is a closed form approximation of multi-target Bayes filter which can overcome most of multi-target tracking problems. Limited field of view, decreasing cost of cameras and its advances induce us to use large-scale camera networks. Increasing the size of camera networks make centralized networks practically inefficient. On the other hand, scalability, simplicity and low data transmission cost has made distributed networks a good replacement for centralized networks. However, data fusion in distributed network is sub-optimal due to unavailable cross-correlation.Among data fusion algorithms which deal with... 

    Elicitation and Aggregation of Experts’ Knowledge for Event Outcome Prediction

    , M.Sc. Thesis Sharif University of Technology Ghazimatin, Azin (Author) ; Habibi, Jafar (Supervisor) ; Movaghar Rahim Abadi, Ali ($item.subfieldsMap.e)
    Abstract
    Given an event O and a set of experts E, we describe a method for finding a subset of experts S whose aggregated opinions best predict the outcome of O. Therefor, the problem can be regarded as team formation for performing a prediction task. In order to estimate competency of each team we propose measure Sum Squared Error which uses experts’ records of predictions during past k days. For simplicity, opinion pooling is selected as the method of information aggregation. we prove in case of simple averaging of opinions,finding best team is NP-hard. we suggest some rounding and heuristic algorithms for finding near optimal solutions. Simulation results show that a variation of tabu search used... 

    Data fusion in MIMO DVB-T-based passive coherent location

    , Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 49, Issue 3 , 2013 , Pages 1725-1737 ; 00189251 (ISSN) Radmard, M ; Karbasi, S. M ; Nayebi, M. M ; Sharif University of Technology
    2013
    Abstract
    Efficient combination of MIMO (multiple-input multiple-output) and PCL (passive coherent location) ideas is expected to improve performance of localization schemes. While, in general, adding the number of transmit and receive antennas provides spatial diversity, it is possible to obtain similar effects by using multiple transmitters that are already transmitting standard signals (such as digital TV (DTV) transmission) in the environment (also known as illuminators of opportunity). However, in the case of passive schemes, it is not always possible to ensure that signals of different transmitters are orthogonal to each other. In such cases in which nonorthogonal transmitter signals are to be... 

    Secure consensus averaging in sensor networks using random offsets

    , Article 2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications, ICT-MICC 2007, Penang, 14 May 2007 through 17 May 2007 ; 2007 , Pages 556-560 ; 1424410940 (ISBN); 9781424410941 (ISBN) Kefayati, M ; Talebi, M. S ; Hossein Khalaj, B ; Rabiee, H. R ; Sharif University of Technology
    2007
    Abstract
    In this work, we have examined the distributed consensus averaging problem from a novel point of view considering the need for privacy and anonymity. We have proposed a method for incorporating security into the scalable average consensus mechanisms proposed in the literature. Random Offsets Method (ROM) is lightweight, transparent and flexible since it is not based on cryptography, does not require any change in the fusion system and can be used optionally by some nodes who care about their privacy. In this method, which is based on noisiflcation of nodes' information, we achieve robustness against n - 1 colluding adversaries in a network of n nodes, which is maximum level of robustness...