Ph.D. Thesis - Online Status Tracking System
.For the realization of his practice project and the following bachelor thesis he A subject was quickly found: „Resistant Auto-ID system for product tracking“.The particle filter tracking system utilizes a map (known environment) to assist the in AAAI Workshop on Challenges in Game AI, Pittsburgh, PA, USA, 2004.
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Natacha I, Natacha Vsindilok, declare that this thesis, submitted in fulfilment of the requirements for the award of New automated case tracking system of the Federal Court of.
students to knowFreehand three-dimensional ultrasound (3D US) imaging is commonly used for This thesis presents a low-cost camera-based system for tracking the.
PTZ Auto Tracking - Thermal 2 - PureTech Systems
Mohammad Jafari (2013-2014), BSc. thesis: Stability and tracking of noiselessnonlinear Lipschitz systems over digital communication channelsAli Khodabandehlo(2013-2014), MSc. thesis: Distributed model predictivecontrol and its application in automated irrigation networks()
Shayan Mashadi Najafi(2013-2014), MSc. thesis: Stability and tracking of linearGaussian systems over AWGN channel with noisy feedback channel
Nabil Ettehadi(2013-2014), BSc. thesis: Stability of noiseless nonlinear dynamic systemsover AWGN channel using describing function
Amir-reza Sedaghat(2013-2014), BSc. thesis: Stability and tracking of noiselessnonlinear dynamic systems over the packet erasure channel usinglinearization method ()
Kimia Chavoshi(2014-2015), BSc. thesis: Stability and tracking of noisy nonlineardynamic systems over AWGN channel using linearization method (, )
Reza Ghorbani(2013-2015), MSc. thesis: Stability and tracking of noisy nonlinearLipschitz dynamic systems over the packet erasure channel()
Shahab Sarmashghi(2013-2015), MSc. thesis: Control over noisy channel (jointlysupervised by Prof. Khalaj, me and Prof. Motahari )
Kiarash Aryankia(2013-2015), MSc. thesis: Distributed optimal control basedon efficient methods for decomposition ()
Ali Karbasi(2013-2015), MSc. thesis: Distributed optimal control based on anefficient method for communication: Application in smart building
Vahid Ahmadi(2013-2015), MSc. thesis: Model predictive control based on integerprogramming: Application in smart oil well
Pegah Ebrahimi(2014-2015), BSc. thesis: Control of electricvehicle ()
Sajjad Easapour(2014-2016), MSc. thesis: Recursive feasibilityfor distributed model predictive control: Application in automated irrigationnetwork()
Maliheh Mahloji(2014-2016), Automated elimination system ofstick-slip oscillation of drilling string using tele-metery and predictiveestimator (jointy supervised by Prof. Khalaj and me).
MSc. thesis: Design and development of automatedirrigation canal pilot()
(2015-2017), MSc. thesis: Design and development of flow meter foropen irrigation channels
2016-2017), BSc. thesis: Design and development of the pilot of automated oil drillingsystem and the associated Scada software
(2015-2017), MSc. thesis: Predictive controlin the presence of model uncertainty and communication imperfections: Applications in automated irrigation network ()
PureTech Systems Video Library PTZ Auto Tracking - Thermal 2
Tracking Systems provide an important analysis technique that can be used in many different areas of science. A Tracking System can be defined as the estimation of the dynamic state of moving objects based on 'inaccurate’ measurements taken by sensors. The area encompasses a wide range of subjects, although the two most essential elements are estimation and data association. Tracking systems are applicable to relatively simple as well as more complex applications. These include air traffic control, ocean surveillance and control sonar tracking, military surveillance, missile guidance, physics particle experiments, global positioning systems and aerospace. This thesis describes an investigation into state-of-the-art tracking algorithms and distributed memory architectures (Multiple Instructions Multiple Data systems - “MIMD”) for parallel processing of tracking systems. The first algorithm investigated is the Interacting Multiple Model (IMM) which has been shown recently to be one of the most cost-effective in its class. IMM scalability is investigated for tracking single targets in a clean environment. Next, the IMM is coupled with a well-established Bayesian data association technique known as Probabilistic Data Association (PDA) to permit the tracking of a target in different clutter environments (IMMPDA). As in the previous case, IMMPDA scalability is investigated for tracking a single target in different clutter environments. In order to evaluate the effectiveness of these new parallel techniques, standard languages and parallel software systems (to provide message-passing facilities) have been used. The main objective is to demonstrate how these complex algorithms can benefit in the general case from being implemented using parallel architectures.