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Zhao, Yue. "Biopsy needles localization and tracking methods in 3d medical ultrasound with ROI-RANSAC-KALMAN." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0015/document.
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Dans les examens médicaux et les actes de thérapie, les techniques minimalement invasives sont de plus en plus utilisées. Des instruments comme des aiguilles de biopsie, ou des électrodes sont utilisés pour extraire des échantillons de cellules ou pour effectuer des traitements. Afin de réduire les traumatismes et de faciliter le suivi visuelle de ces interventions, des systèmes d’assistance par imagerie médicale, comme par exemple, par l’échographie 2D, sont utilisés dans la procédure chirurgicale. Nous proposons d’utiliser l’échographie 3D pour faciliter la visualisation de l’aiguille, mais en raison de l’aspect bruité de l’image ultrasonore (US) et la grande quantité de données d’un volume 3D, il est difficile de trouver l’aiguille de biopsie avec précision et de suivre sa position en temps réel. Afin de résoudre les deux principaux problèmes ci-dessus, nous avons proposé une méthode basée sur un algorithme RANSAC et un filtre de Kalman. De même l’étude est limitée à une région d’intérêt (ROI) pour obtenir une localisation robuste et le suivi de la position de l’aiguille de biopsie en temps réel. La méthode ROI-RK se compose de deux étapes: l’étape d’initialisation et l’étape de suivi. Dans la première étape, une stratégie d’initialisation d’une ROI en utilisant le filtrage de ligne à base de matrice de Hesse est mise en œuvre. Cette étape permet de réduire efficacement le bruit de granularité du volume US, et de renforcer les structures linéaires telles que des aiguilles de biopsie. Dans la deuxième étape, après l’initialisation de la ROI, un cycle de suivi commence. L’algorithme RK localise et suit l’aiguille de biopsie dans une situation dynamique. L’algorithme RANSAC est utilisé pour estimer la position des micro-outils et le filtrage de Kalman permet de mettre à jour la région d’intérêt et de corriger la localisation de l’aiguille. Une stratégie d’estimation de mouvement est également appliquée pour estimer la vitesse d’insertion de l’aiguille de biopsie. Des volumes 3D US avec un fond inhomogène ont été simulés pour vérifier les performances de la méthode ROI-RK. La méthode a été testée dans des conditions variables, telles que l’orientation d’insertion de l’aiguille par rapport à l’axe de la sonde et le niveau de contraste (CR). La précision de la localisation est de moins de 1 mm, quelle que soit la direction d’insertion de l’aiguille. Ce n’est que lorsque le CR est très faible que la méthode proposée peut échouer dans le suivi d’une structure incomplète de l’aiguille. Une autre méthode, utilisant l’algorithme RANSAC avec apprentissage automatique a été proposée. Cette méthode vise à classer les voxels en se basant non seulement sur l’intensité, mais aussi sur les caractéristiques de la structure de l’aiguille de biopsie. Les résultats des simulations montrent que l’algorithme RANSAC avec apprentissage automatique peut séparer les voxels de l’aiguille et les voxels de tissu de fond avec un CR faibleIn medical examinations and surgeries, minimally invasive technologies are getting used more and more often. Some specially designed surgical instruments, like biopsy needles, or electrodes are operated by radiologists or robotic systems and inserted in human’s body for extracting cell samples or delivering radiation therapy. To reduce the risk of tissue injury and facilitate the visual tracking, some medical vision assistance systems, as for example, ultrasound (US) systems can be used during the surgical procedure. We have proposed to use the 3D US to facilitate the visualization of the biopsy needle, however, due to the strong speckle noise of US images and the large calculation load involved as soon as 3D data are involved, it is a challenge to locate the biopsy needle accurately and to track its position in real time in 3D US. In order to solve the two main problems above, we propose a method based on the RANSAC algorithm and Kalman filter. In this method, a region of interest (ROI) has been limited to robustly localize and track the position of the biopsy needle in real time. The ROI-RK method consists of two steps: the initialization step and the tracking step. In the first step, a ROI initialization strategy using Hessian based line filter measurement is implemented. This step can efficiently reduce the speckle noise of the ultrasound volume, and enhance line-like structures as biopsy needles. In the second step, after the ROI is initialized, a tracking loop begins. The RK algorithm can robustly localize and track the biopsy needles in a dynamic situation. The RANSAC algorithm is used to estimate the position of the micro-tools and the Kalman filter helps to update the ROI and auto-correct the needle localization result. Because the ROI-RK method is involved in a dynamic situation, a motion estimation strategy is also implemented to estimate the insertion speed of the biopsy needle. 3D US volumes with inhomogeneous background have been simulated to evaluate the performance of the ROI-RK method. The method has been tested under different conditions, such as insertion orientations angles, and contrast ratio (CR). The localization accuracy is within 1 mm no matter what the insertion direction is. Only when the CR is very low, the proposed method could fail to track because of an incomplete ultrasound imaging of the needle. Another methodology, i.e. RANSAC with machine learning (ML) algorithm has been presented. This method aims at classifying the voxels not only depending on their intensities, but also using some structure features of the biopsy needle. The simulation results show that the RANSAC with ML algorithm can separate the needle voxels and background tissue voxels with low CR
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Čevorová, Nina. "Problematika ROI v oblasti získávání a výběru zaměstnanců." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-77881.
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The paper brings answers on the the question whether it is possible to measure the field of recruitment. Via quantifying the administrative process of recrutment, the paper reflects the savings of time and costs by using e-recruitment application (applicant tracking system ATS) and it searchs for the relationship between quality of hire and increase of company value and its profit.
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Öberg, Andreas, and Martin Hulterström. "Semantic segmentation using convolutional neural networks to facilitate motion tracking of feet : For real-time analysis of perioperative microcirculation images in patients with critical limb thretening ischemia." Thesis, Linköpings universitet, Avdelningen för medicinsk teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176795.
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This thesis investigates the use of Convolutional Neural Networks (CNNs) toperform semantic segmentation of feet during endovascular surgery in patientswith Critical Limb Threatening Ischemia (CLTI). It is currently being investigatedwhether objective assessment of perfusion can aid surgeons during endovascularsurgery. By segmenting feet, it is possible to perform automatic analysis of perfusion data which could give information about the impact of the surgery in specificRegions of Interest (ROIs). The CNN was developed in Python with a U-net architecture which has shownto be state of the art when it comes to medical image segmentation. An imageset containing approximately 78 000 images of feet and their ground truth segmentation was manually created from 11 videos taken during surgery, and onevideo taken on three healthy test subjects. All videos were captured with a MultiExposure Laser Speckle Contrast Imaging (MELSCI) camera developed by Hultman et al. [1]. The best performing CNN was an ensemble model consisting of10 sub-models, each trained with different sets of training data. An ROI tracking algorithm was developed based on the Unet output, by takingadvantage of the simplicity of edge detection in binary images. The algorithmconverts images into point clouds and calculates a transformation between twopoint clouds with the use of the Iterative Closest Point (ICP) algorithm. The resultis a system that perform automatic tracking of manually selected ROIs whichenables continuous measurement of perfusion in the ROIs during endovascularsurgery.
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Rubino, Vincenzo. "Studio della dinamica di perfusione per la valutazione della endometriosi ureterale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23018/.
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L’endometriosi è una patologia provocata dalla disseminazione o dalla crescita di tessuto endometriale in sedi anomale o dall’insorgenza del tessuto endometriale, per un processo di metaplasia, al di fuori della sede abituale. Le manifestazioni cliniche dell’endometriosi possono essere molto differenti. Accanto a pazienti prive di sintomi, si ritrovano pazienti con una sintomatologia dolorosa estremamente invalidante.
L’endometriosi rappresenta una delle patologie ginecologiche più controverse: infatti, nonostante il particolare interesse riservatole negli ultimi decenni dall’intera comunità scientifica e la notevole esperienza clinica acquisita in materia, resta ad oggi, un enigma da risolvere nella quasi totalità delle sue radici ed implicazioni fisiopatologiche.
Nella seguente tesi verrà analizzato l’uso endovenoso del verde indocianina per consentire la visualizzazione in tempo reale della perfusione intestinale nelle donne con endometriosi retto-sigmoidea. Tale metodica ci consentirà di valutare la buona riuscita dell’intervento, focalizzandoci soprattutto sulla perfusione ematica intestinale della neo-anastomosi, al fine di escludere la possibile complicanza più temuta nell’ambito chirurgico, ovvero la deiscenza anastomotica (AL). Vista anche la scarsità in letteratura di metodiche consolidate per la quantificazione della perfusione in un contesto chirurgico, che non richiedano una strumentazione di altissimo livello tecnologico, (quali per esempio bracci robotici), si punterà alla implementazione di un algoritmo automatizzato, che potrà fornire i parametri di interesse insieme anche ai relativi grafici. Il tutto in uno scenario di tempistica relativamente breve, che a fronte dell’utilizzo di un hardware di elevate prestazioni, possa puntare anche al real-time, e quindi trovare applicazione direttamente durante la seduta operatoria.
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Colson, Chelsea M. "Eye Gaze and Cortisol Levels in Socially Anxious Young Adults During an Interactive Real World Task." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/honors_theses/101.
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Social anxiety is a disorder where people fear social interactions and is associated with physiological changes. Eye tracking studies have shown that people with social anxiety spent more time gazing at emotional faces presented on a computer screen and spent more time gazing at the eye region. There has been limited studies on tracking eye gaze in a real-life setting interacting with another person. We used a wearable eye tracker during a brief one-on-one interview about participants’ challenges faced at work or school. Along with self-report psychological measures about social anxiety and shyness, we also measured participants’ salivary cortisol as a metric for physiological stress. We hypothesized that socially anxious individuals would have higher cortisol levels and spent more time gazing at the face. However, there was no change in cortisol levels before and after the interview. In addition, socially anxious individuals had lower cortisol levels than less anxious people. Furthermore, the time spent fixating on the region of interest (ROI), which was the face, was not correlated with social anxiety, anxiety or shyness. Paradoxically, the more socially anxious participants seem to have had a lower physiological stress response than less socially anxious participants.
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Nguyen, Anthony Ngoc. "Importance Prioritised Image Coding in JPEG 2000." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16005/.
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Importance prioritised coding is a principle aimed at improving the interpretability (or image content recognition) versus bit-rate performance of image coding systems. This can be achieved by (1) detecting and tracking image content or regions of interest (ROI) that are crucial to the interpretation of an image, and (2)compressing them in such a manner that enables ROIs to be encoded with higher fidelity and prioritised for dissemination or transmission. Traditional image coding systems prioritise image data according to an objective measure of distortion and this measure does not correlate well with image quality or interpretability. Importance prioritised coding, on the other hand, aims to prioritise image contents according to an 'importance map', which provides a means for modelling and quantifying the relative importance of parts of an image. In such a coding scheme the importance in parts of an image containing ROIs would be higher than other parts of the image. The encoding and prioritisation of ROIs means that the interpretability in these regions would be improved at low bit-rates. An importance prioritised image coder incorporated within the JPEG 2000 international standard for image coding, called IMP-J2K, is proposed to encode and prioritise ROIs according to an 'importance map'. The map can be automatically generated using image processing algorithms that result in a limited number of ROIs, or manually constructed by hand-marking OIs using a priori knowledge. The proposed importance prioritised coder coder provides a user of the encoder with great flexibility in defining single or multiple ROIs with arbitrary degrees of importance and prioritising them using IMP-J2K. Furthermore, IMP-J2K codestreams can be reconstructed by generic JPEG 2000 decoders, which is important for interoperability between imaging systems and processes. The interpretability performance of IMP-J2K was quantitatively assessed using the subjective National Imagery Interpretability Rating Scale (NIIRS). The effect of importance prioritisation on image interpretability was investigated, and a methodology to relate the NIIRS ratings, ROI importance scores and bit-rates was proposed to facilitate NIIRS specifications for importance prioritised coding. In addition, a technique is proposed to construct an importance map by allowing a user of the encoder to use gaze patterns to automatically determine and assign importance to fixated regions (or ROIs) in an image. The importance map can be used by IMP-J2K to bias the encoding of the image to these ROIs, and subsequently to allow a user at the receiver to reconstruct the image as desired by the user of the encoder. Ultimately, with the advancement of automated importance mapping techniques that can reliably predict regions of visual attention, IMP-J2K may play a significant role in matching an image coding scheme to the human visual system.
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Dong, Weizhen. "Time Blanking for GBT Data with RADAR RFI." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd468.pdf.
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Abbasi, Hoseini Afshin. "Experimental study of turbulent flow with dispersed rod-like particles through optical measurements." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for energi- og prosessteknikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-24956.
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The knowledge of the behavior of non-spherical particles suspended in turbulent flows covers a wide range of applications in engineering and science. Dispersed two-phase flows and turbulence are the most challenging subjects in engineering, and when combined it gives rise to more complexities as the result of the inherent stochastic nature of the turbulence of the carrier-phase together with the random distribution of the dispersed phase. Moreover, for anisotropic particles the coupling between the translation and rotation of particle increases the complication. Because of the practical importance of prolate particleladen turbulent flows, the plenty of numerical and experimental works have been conducted to study such suspensions. Numerical approaches have given valuable insight of turbulent suspension flows, although the computation has been only carried out at the macro scale and models, not including flow distortion around the particle, comprise the detail of the flow in the order of a particle size. In addition, the model of the forces imposed on the particle by the fluid and mass point treatment are strictly valid for infinitely small particle having size less than all scales of the fluid turbulence. Fully resolved solution at the scale of the dispersed phase in turbulent flows for high Reynolds number has been recently performed but is still a challenge. On the other hand, the presence of particle as the dispersed phase makes experimental measurements much more complicated than those with single phase as a result of particles interference. The area of considerable difficulty with this type of experiments is the measurement of the fluid-phase velocity remarkably close to the particle surface. Generally, experimental researches have been concentrated on measuring the mean velocity and Reynolds stresses of the carrier-phase, and the mean velocity, fluctuations, orientation and accumulation of the non-spherical particles. Higher-order quantities, including Lagrangian particle velocity correlations, the carrier-phase turbulence modulation, and two-particle and particlefluid velocity correlations are also of interest. It has been found that the rotational and translational movements of the fibershaped particle depend on the nature of carrier-phase field and fiber characteristics such as aspect ratio, fiber Stokes number, fiber Reynolds number, and the ratio of fiber to flow length scale. With the development of PIV (Particle Image Velocimetry) and PTV (Particle Tracking Velocimetry) techniques, it has been appeared that combined PIV/PTV will be the best available choice for the experimental study of dispersed two-phase flows. The purpose of combined PIV/PTV measurement of two-phase systems is simultaneous measurements of fluid and suspended objects, where the PIV measurement of the fluid phase are combined with PTV measurement of the dispersed phase. The objective of this doctoral thesis is to study the behavior of rod-like particles suspended in wall-bounded turbulent flow through simultaneous PIV/PTV measurements of the velocity of the flow field and particle motion. As a representative of rod-like particles, I have employed cellulose acetate fibers with the length to diameter ratio (aspect ratio) larger than one. Here, It has been considered only dilute suspensions with no flocculation; thus fiber-fiber interaction is negligible. The measurements have been conducted within the parallel planes (2D view) illuminated by laser in the streamwise direction in thin film suspension flowing on the water table setup at Linné FLOW Centre, KTH Mechanics Lab. It is shown that this setup is a well-behaved experimental model of half channel flows often used in Direct Numerical Simulation (DNS) investigations. Therefore, the experimental results are comparable to their DNS counterpart where it is convenient. A single camera PIV technique has been used to measure flowing suspension. Therefore, it has been needed to preprocess images using a spatial median filter to separate images of two phases, tracer particles as representative of fluid and fibers suspended. The well-known PIV processing algorithms have been applied to the phase of fluid. I have also introduced a novel algorithm to recognize and match fibers in consecutive images to track fibers and estimate their velocity. It is not feasible to study all relevant aspects of particle-laden turbulent flows in a single study. In this study, I present the statistics of the rotational and translational motion of fiber-like particles and the surrounding fluid velocity. To the author’s knowledge, remarkably little experimental work has been published to date on simultaneous measurement of fiber motion and turbulence field in a turbulent fiber suspension flow to reveal dynamics of fibers in this regime. Therefore, the results of this work will be profitable in better understanding of such multiphase flows. The statistical analysis of the translational motion of fibers shows that the size of fiber is a significant factor for the dynamical behavior of the fiber near the wall. It has been observed that, in the region near the wall, the probability of presence of the long fibers is high in both the high-speed and low-speed streaks of flow, and the mean velocity of fibers almost conforms to the mean velocity of flow; whereas the short fibers are mostly present in the low-speed areas, and the fiber mean velocity obey the dominant flow velocity in these areas. In the far-wall regions, the translation of fibers is practically unaffected by the aspect ratio, whereas it depends crucially on the wall-normal distance. Moreover, it was found that in the case of long fibers near the wall, the low speed fibers mostly are orientated in streamwise direction. On the other hand, there is no preferential orientation for fast long fibers. Although wall-normal velocities were not measured in this study, it is hypothesized that this behavior is a result of fibers being affected by the sweep and ejection events known to occur in wall-bounded turbulent flow. The fast fibers are in sweep environment and comes from the upper layer. The low speed fibers are into ejection areas in the vicinity of the wall, and the wall has a stabilizing effect on them. The short fibers are still oriented mostly in streamwise direction for a certain range of low velocity. Furthermore, since a considerable change of the fiber behavior is observed in a certain ratio of the fiber length to the fiber distance from the solid wall, it is supposed that this ratio is also a prominent parameter for the behavior of fiber near the wall. The results presented are in terms of viscous wall units wherever are denoted by superscript “+”.
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Couceiro, Mariana Afonso Abade. "Dinâmica de sedimentos coesivos em um estuário altamente estratificado: rio Araranguá, SC." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/21/21136/tde-24062015-145812/.
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O objetivo deste estudo é compreender a dinâmica das partículas no estuário do rio Araranguá (SC) em termos de transporte em suspensão, deposição e exportação, em diferentes condições físico-químicas da água, com pH baixo (<4,5) e normal (>=7), e sob condições de regime transiente da descarga fluvial. O estuário do rio Araranguá é classificado como altamente estratificado e dominado pela descarga fluvial. Um aspecto fundamental nos processos que controlam a dinâmica de materiais em suspensão no estuário é a atividade de lavra e beneficiamento do carvão, que gera uma drenagem ácida no rio Mãe Luzia. O seu pH baixo (˜3) indica que o processo de floculação é intensificado no interior do estuário. Com o objetivo de melhor entender a hidrodinâmica do estuário, um modelo tridimensional foi implementado para a região. O modelo foi calibrado e validado com dados observados. Simulações com diferentes picos de descarga fluvial (100, 400, 700 e 1000 m3.s-1) e baixa descarga (30 m3.s-1) foram realizadas. Para calcular o transporte do material particulado em suspensão foi desenvolvido um modelo Lagrangeano da trajetória da partícula. O modelo da trajetória utiliza os resultados do modelo hidrodinâmico e a velocidade de decantação das partículas. O estuário respondeu rapidamente às variações da descarga fluvial. A cunha salina foi transportada para fora do estuário durante os picos de 700 e 1000 m3.s-1. A descarga fluvial é o fator dominante no controle da intrusão da salinidade no estuário e, em condições de baixa descarga, o transporte advectivo de sal é dominado pelo termo dispersivo da circulação gravitacional. O tempo de residência médio das partículas no estuário foi menor em condições de pH baixo. A exportação das partículas aumentou com o aumento da descarga fluvial (pico de 1000 m3.s-1), sendo que 27% e 30% foram exportadas para a plataforma interna durante os experimentos com pH baixo e pH normal, respectivamente. A região de deposição das partículas indica que com a diminuição do pH, as partículas passam a depositar mais à jusante no estuário. O evento de descarga de 1000 m3.s-1 não foi capaz de remover a grande maioria das partículas do estuário, mas foi responsável por redistribuir as partículas ao longo do médio estuário, onde se depositaram em condições favoráveis com baixas velocidades e ausência de salinidade. O trabalho demonstra que apesar da alta estratificação do estuário, a acidez de suas águas, seu padrão de circulação, com baixas velocidades e a presença da cunha salina, possuem um papel fundamental no transporte das partículas, resultando em maior potencial de retenção do material em suspensão no estuário do rio Araranguá.The present study assessed the dynamics of particles of the Araranguá (SC) river estuary in terns of suspended transport, deposition and exportation in different conditions of physical-chemical of water, with low (<4,5) and normal pH (>=7), and transient of river discharge conditions. The Araranguá river estuary is a highly stratified flash-flood dominated. The river basin of the Mãe Luzia river, one of the main tributaries of the Araranguá river, is performed the activity of mining and coal processing, wich generates an acidic drainage. Its low pH indicates that flocculation process is intensified in estuary inner. With the objective of better understanding the estuarine processes, a three-dimensional hydrodynamics model was implemented. The model was calibrated and verified using observational data. Simulations were conducted with freshet peak ranged over 100, 400, 700 and 1000 m3.s-1. Lagrangian particle tracking algorithms was developed to represent the suspended particle transport at estuary. The particle tracking used the montion resulting from hydrodynamics model and the particle settling velocity. The estuary responded quickly the river discharge variations. During the pulse event the velocities at water column were unidirectional down-estuary is shown the barotropic dominates over baroclinic component. During the highest flash flood event (700 and 1000 m3.s-1) the salt water was pushed out of the estuary. The river discharge is a dominating factor affecting the salinity intrusion in the estuarine system and under low discharge conditions the advective salt transport is dominated by dispersive term of gravitational circulation. The mean residence time of the particles was lowest in pH low conditions. The particles export is great as the river discharge is rising (1000 m3.s-1) with 27% and 30% exported to inner shelf during the experiments with low and normal pH, respectively. The particles deposition local indicates that with the pH decrease the particles become to be deposited further downstream. The discharge event of 1000 m3.s-1 was not able to remove all particles out, but was response to redistribute the particles along of the meddle estuary, where settling in favorable conditions at low velocities and absence of salinity. The study shows that although high stratification of estuary, the acidity of water, the pattern of circulation, at low velocities, and the salt wedge presence play a fundamental role in the transport of particle matter resulting in increased the potential retention of suspended matter in the Araranguá river estuary.
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Li, Tai-Kuang, and 李泰廣. "ROI Tracking and Enhancement in Low-Quality Video Sequences." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/84420821010600950479.
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碩士淡江大學
資訊工程學系碩士班
97
Due to the cost consideration, most of surveillance systems adopt the low resolution format to record the video sequences. However, the low resolution image quality often results the interested object too vague to be identified. We propose a two folds algorithm- tracking and enhancement- to solve this problem. First, the block-based motion estimation is used for object tracking. Next, a novel image enhancement scheme is used to reconstruct an initial high resolution image acquired from the region of interested (ROI). The error back-projection is further used to improve the quality of the reconstructed high resolution image. The proposed algorithm has been tested on surveillance video sequences and some common video sequences. The tracking results are satisfying that it demonstrated the proposed algorithm is illumination invariant and robust to complex background. The image enhancement scheme is also tested. The test results on synthetic images showed that the quality of enlarged images has been improved.
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Chien, Jui-Chen, and 簡瑞辰. "Accurate and Robust ROI Localization in CAMSHIFT Tracking Application." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/71918913979137437303.
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碩士淡江大學
資訊工程學系碩士班
100
In this paper, we present an improved version of CAMSHIFT algorithm. We use a 2D histogram including hue and brightness to describe the color feature of the target. In this way, videos with poor quality or achromatic points can be better characterized. The Flooding process and contribution evaluation are used to obtain a precise target histogram which reflects true color information and discrimination ability. To be adaptive to the foreground/background variation, formula for updating ROI size and target histogram are proposed. The proposed method is compared with existing methods and shows steady and satisfactory results.
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"Continuous Spatio Temporal Tracking of Mobile Targets." Master's thesis, 2014. http://hdl.handle.net/2286/R.I.27520.
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abstract: There has been extensive study of the target tracking problems in the recent years. Very little work has been done in the problem of continuous monitoring of all the mobile targets using the fewest number of mobile trackers, when the trajectories of all the targets are known in advance. Almost all the existing research discretized time (and/or space), or assume infinite tracker velocity. In this thesis, I consider the problem of covering (tracking) target nodes using a network of Unmanned Airborne Vehicles (UAV's) for the entire period of observation by adding the constraint of fixed velocity on the trackers and observing the targets in continuous time and space. I also show that the problem is NP-complete and provide algorithms for handling cases when targets are static and dynamic.Dissertation/Thesis
Masters Thesis Computer Science 2014
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"Smart Phones and Dietary Tracking: A Feasibility Study." Master's thesis, 2012. http://hdl.handle.net/2286/R.I.9316.
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abstract: Dietary self-monitoring has been shown to be a predictor of weight loss success and is a prevalent part of behavioral weight control programs. As more weight loss applications have become available on smartphones, this feasibility study investigated whether the use of a smartphone application, or a smartphone memo feature would improve dietary self-monitoring over the traditional paper-and-pencil method. The study also looked at whether the difference in methods would affect weight loss. Forty-seven adults (BMI 25 to 40 kg/m2) completed an 8-week study focused on tracking the difference in adherence to a self-monitoring protocol and subsequent weight loss. Participants owning iPhones (n=17) used the 'Lose It' application (AP) for diet and exercise tracking and were compared to smartphone participants who recorded dietary intake using a memo (ME) feature (n=15) on their phone and participants using the traditional paper-and-pencil (PA) method (n=15). There was no significant difference in completion rates between groups with an overall completion rate of 85.5%. The overall mean adherence to self-monitoring for the 8-week period was better in the AP group than the PA group (p = .024). No significant difference was found between the AP group and ME group (p = .148), or the ME group and the PA group (p = .457). Weight loss for the 8 week study was significant for all groups (p = .028). There was no significant difference in weight loss between groups. Number of days recorded regardless of group assignment showed a weak correlation to weight loss success (p = .068). Smartphone owners seeking to lose weight should be encouraged by the potential success associated with dietary tracking using a smartphone app as opposed to the traditional paper-and-pencil method.Dissertation/Thesis
M.S. Nutrition 2012
15
"Empowering Apprentice Teachers: Tracking Instructional Practices with MyiLOGS." Doctoral diss., 2013. http://hdl.handle.net/2286/R.I.18163.
Full textAbstract:
abstract: Growing popularity of alternatively certifying teachers has created challenges for teacher preparation programs. Many non-traditional routes into classroom include no full-time mentor teacher. Absence of a mentor teacher in the classroom leaves teachers with a deficit. This study follows ten teachers on the intern certificate enrolled in both an alternative certification teacher preparation program and the Teach for America organization as they pursue a master's degree in education and state teaching certification from a large southwestern university. The five randomly chosen for the treatment group and the control group contained 1 male and 4 female teachers, some of whom teach at public schools and others at charter schools. All were secondary education language arts teachers ranging in age from 22- 29. The treatment used in this study is a job-embedded, professional development, software tool designed to help teachers track their classroom practices called MyiLOGS. The purpose of this action research project was to study the effect using MyiLOGS had on six of the nine areas evaluated by a modified version of the Teacher Advancement Program evaluation rubric, alignment with Opportunity To Learn constructs, and the tool's influence on the efficacy of these first year teachers. The data generated from this study indicate that the MyiLOGS tool did have a positive effect on the teachers' TAP evaluation performances. Also, the MyiLOGS tool had a large impact on the teachers' instruction as measured by the constructs of Opportunity to Learn and their teaching self-efficacy. Implications suggested the tool was an asset to these teachers because they tracked their data, became more reflective, and self-sufficient.Dissertation/Thesis
Ed.D. Educational Leadership and Policy Studies 2013
16
"Target Tracking in Environments of Rapidly Changing Clutter." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.29894.
Full textAbstract:
abstract: Tracking targets in the presence of clutter is inevitable, and presents many challenges. Additionally, rapid, drastic changes in clutter density between different environments or scenarios can make it even more difficult for tracking algorithms to adapt. A novel approach to target tracking in such dynamic clutter environments is proposed using a particle filter (PF) integrated with Interacting Multiple Models (IMMs) to compensate and adapt to the transition between different clutter densities. This model was implemented for the case of a monostatic sensor tracking a single target moving with constant velocity along a two-dimensional trajectory, which crossed between regions of drastically different clutter densities. Multiple combinations of clutter density transitions were considered, using up to three different clutter densities. It was shown that the integrated IMM PF algorithm outperforms traditional approaches such as the PF in terms of tracking results and performance. The minimal additional computational expense of including the IMM more than warrants the benefits of having it supplement and amplify the advantages of the PF.Dissertation/Thesis
Masters Thesis Electrical Engineering 2015
17
Li, Min-Da, and 李岷達. "Design of Focusing and Tracking Controllers for DVD-ROM." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/68t5qg.
Full textAbstract:
碩士國立臺北科技大學
電機工程系所
93
In the DVD-ROM, there are many complicated servo systems. The focusing and tracking servo systems are more important than other servo systems in DVD-ROM. The lead-lag compensator is employed as the focusing and tracking controller. Toady’s DVD-ROM manufactures still use the bilinear transformation to design servo controller in w-plane. In the special purpose servo chip for the DVD-ROM, because of the effect of the structure of the controller and the limits of the chip, the result of the controllers may not be implemented in the chip after designing, and redesigning is regained again and again. In this paper, the transfer function of DVD-ROM controlled system is evaluated by the method of system identification. To design for genetic algorithm, the known transfer function is used to make the genetic algorithm demonstrates its powerful searching capability can achieve the aim to automatic adjustment of controller parameters and let the controller work in the best performance level. Meanwhile, the above proposed method can significantly decrease lots of inconvenience and increase more design efficiency when engineers design the controller of DVD-ROM. Concerning about the uncertainty of both focusing and tracing controlled system, Quantitative Feedback Theory (QFT) is considered as an effective method for uncertain plants to satisfy the assigned specifications. In this paper, a methodology using the genetic algorithm is proposed to improve the design accuracy, The methodology has also been applied to the design of focus and tracking servo controllers for the DVD-ROM, to reduce the work of tedious trial and error process and to enable automatic design procedure.
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"Multiple Detection and Tracking in Complex Time-Varying Environments." Doctoral diss., 2014. http://hdl.handle.net/2286/R.I.27551.
Full textAbstract:
abstract: This work considers the problem of multiple detection and tracking in two complex time-varying environments, urban terrain and underwater. Tracking multiple radar targets in urban environments is rst investigated by exploiting multipath signal returns, wideband underwater acoustic (UWA) communications channels are estimated using adaptive learning methods, and multiple UWA communications users are detected by designing the transmit signal to match the environment. For the urban environment, a multi-target tracking algorithm is proposed that integrates multipath-to-measurement association and the probability hypothesis density method implemented using particle filtering. The algorithm is designed to track an unknown time-varying number of targets by extracting information from multiple measurements due to multipath returns in the urban terrain. The path likelihood probability is calculated by considering associations between measurements and multipath returns, and an adaptive clustering algorithm is used to estimate the number of target and their corresponding parameters. The performance of the proposed algorithm is demonstrated for different multiple target scenarios and evaluated using the optimal subpattern assignment metric. The underwater environment provides a very challenging communication channel due to its highly time-varying nature, resulting in large distortions due to multipath and Doppler-scaling, and frequency-dependent path loss. A model-based wideband UWA channel estimation algorithm is first proposed to estimate the channel support and the wideband spreading function coefficients. A nonlinear frequency modulated signaling scheme is proposed that is matched to the wideband characteristics of the underwater environment. Constraints on the signal parameters are derived to optimally reduce multiple access interference and the UWA channel effects. The signaling scheme is compared to a code division multiple access (CDMA) scheme to demonstrate its improved bit error rate performance. The overall multi-user communication system performance is finally analyzed by first estimating the UWA channel and then designing the signaling scheme for multiple communications users.Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2014
19
"Tracking the Humoral Immune Response In Type 1 Diabetes." Doctoral diss., 2015. http://hdl.handle.net/2286/R.I.29782.
Full textAbstract:
abstract: Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by progressive autoimmune destruction of insulin-producing pancreatic β-cells. Genetic, immunological and environmental factors contribute to T1D development. The focus of this dissertation is to track the humoral immune response in T1D by profiling autoantibodies (AAbs) and anti-viral antibodies using an innovative protein array platform called Nucleic Acid Programmable Protein Array (NAPPA).
AAbs provide value in identifying individuals at risk, stratifying patients with different clinical courses, improving our understanding of autoimmune destructions, identifying antigens for cellular immune response and providing candidates for prevention trials in T1D. A two-stage serological AAb screening against 6,000 human proteins was performed. A dual specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) was validated with 36% sensitivity at 98% specificity by an orthogonal immunoassay. This is the first systematic screening for novel AAbs against large number of human proteins by protein arrays in T1D. A more comprehensive search for novel AAbs was performed using a knowledge-based approach by ELISA and a screening-based approach against 10,000 human proteins by NAPPA. Six AAbs were identified and validated with sensitivities ranged from 16% to 27% at 95% specificity. These two studies enriched the T1D “autoantigenome” and provided insights into T1D pathophysiology in an unprecedented breadth and width.
The rapid rise of T1D incidence suggests the potential involvement of environmental factors including viral infections. Sero-reactivity to 646 viral antigens was assessed in new-onset T1D patients. Antibody positive rate of EBV was significantly higher in cases than controls that suggested a potential role of EBV in T1D development. A high density-NAPPA platform was demonstrated with high reproducibility and sensitivity in profiling anti-viral antibodies.
This dissertation shows the power of a protein-array based immunoproteomics approach to characterize humoral immunoprofile against human and viral proteomes. The identification of novel T1D-specific AAbs and T1D-associated viruses will help to connect the nodes in T1D etiology and provide better understanding of T1D pathophysiology.Dissertation/Thesis
Doctoral Dissertation Biological Design 2015
20
"The Evaluation of Information Visualization Techniques Using Eye Tracking." Doctoral diss., 2015. http://hdl.handle.net/2286/R.I.34899.
Full textAbstract:
abstract: Node-link diagrams are widely used to visualize the relational structure of real world datasets. As identical data can be visualized in infinite ways by simply changing the spatial arrangement of the nodes, one of the important research topics of the graph drawing community is to visualize the data in the way that can facilitate people's comprehension. The last three decades have witnessed the growth of algorithms for automatic visualization. However, despite the popularity of node-link diagrams and the enthusiasm in improving computational efficiency, little is known about how people read these graphs and what factors (layout, size, density, etc.) have impact on their effectiveness (the usability aspect of the graph, e.g., are they easy to understand?). This thesis is comprehensive research to investigate the factors that affect people's understanding of node-link diagrams using eye-tracking methods. Three experiments were conducted, including 1) a pilot study with 22 participants to explore the layout and size effect; 2) an eye tracking experiment with 43 participants to investigate the layout, size and density effect on people's graph comprehension using abstract node-link diagram and generic tasks; and 3) an eye tracking experiment with the same participants to investigate the same effects using a real visualization analytic application. Results showed that participants' spatial reasoning ability had significant impact on people's graph reading performance. Layout, size, and density were all found to be significant effects under different task circumstances. The applicability of the eye tracking methods on visualization evaluation has been confirmed by providing detailed evidence that demonstrates the cognitive process of participants' graph reading behavior.Dissertation/Thesis
Doctoral Dissertation Engineering 2015
21
"Efficient Implementation of a Low Cost Object Tracking System." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.36403.
Full textAbstract:
abstract: Object tracking is an important topic in multimedia, particularly in applications such as teleconferencing, surveillance and human-computer interface. Its goal is to determine the position of objects in images continuously and reliably. The key steps involved in object tracking are foreground detection to detect moving objects, clustering to enable representation of an object by its centroid, and tracking the centroids to determine the motion parameters.
In this thesis, a low cost object tracking system is implemented on a hardware accelerator that is a warp based processor for SIMD/Vector style computations. First, the different foreground detection techniques are explored to figure out the best technique that involves the least number of computations without compromising on the performance. It is found that the Gaussian Mixture Model proposed by Zivkovic gives the best performance with respect to both accuracy and number of computations. Pixel level parallelization is applied to this algorithm and it is mapped onto the hardware accelerator.
Next, the different clustering algorithms are studied and it is found that while DBSCAN is highly accurate and robust to outliers, it is very computationally intensive. In contrast, K-means is computationally simple, but it requires that the number of means to be specified beforehand. So, a new clustering algorithm is proposed that uses a combination of both DBSCAN and K-means algorithm along with a diagnostic algorithm on K-means to estimate the right number of centroids. The proposed hybrid algorithm is shown to be faster than the DBSCAN algorithm by ~2.5x with minimal loss in accuracy. Also, the 1D Kalman filter is implemented assuming constant acceleration model. Since the computations involved in Kalman filter is just a set of recursive equations, the sequential model in itself exhibits good performance, thereby alleviating the need for parallelization. The tracking performance of the low cost implementation is evaluated against the sequential version. It is found that the proposed hybrid algorithm performs very close to the reference algorithm based on the DBSCAN algorithm.Dissertation/Thesis
Masters Thesis Electrical Engineering 2015
22
"Robust Human Motion Tracking using Low-Cost Inertial Sensors." Master's thesis, 2016. http://hdl.handle.net/2286/R.I.40826.
Full textAbstract:
abstract: The advancements in the technology of MEMS fabrication has been phenomenal in recent years. In no mean measure this has been the result of continued demand from the consumer electronics market to make devices smaller and better. MEMS inertial measuring units (IMUs) have found revolutionary applications in a wide array of fields like medical instrumentation, navigation, attitude stabilization and virtual reality. It has to be noted though that for advanced applications of motion tracking, navigation and guidance the cost of the IMUs is still pretty high. This is mainly because the process of calibration and signal processing used to get highly stable results from MEMS IMU is an expensive and time-consuming process. Also to be noted is the inevitability of using external sensors like GPS or camera for aiding the IMU data due to the error propagation in IMU measurements adds to the complexity of the system.
First an efficient technique is proposed to acquire clean and stable data from unaided IMU measurements and then proceed to use that system for tracking human motion. First part of this report details the design and development of the low-cost inertial measuring system ‘yIMU’. This thesis intends to bring together seemingly independent techniques that were highly application specific into one monolithic algorithm that is computationally efficient for generating reliable orientation estimates. Second part, systematically deals with development of a tracking routine for human limb movements. The validity of the system has then been verified.
The central idea is that in most cases the use of expensive MEMS IMUs is not warranted if robust smart algorithms can be deployed to gather data at a fraction of the cost. A low-cost prototype has been developed comparable to tactical grade performance for under $15 hardware. In order to further the practicability of this device we have applied it to human motion tracking with excellent results. The commerciality of device has hence been thoroughly established.Dissertation/Thesis
Masters Thesis Mechanical Engineering 2016
23
"Rapid Antimicrobial Susceptibility Testing Based on Bacterial Motion Tracking." Doctoral diss., 2017. http://hdl.handle.net/2286/R.I.44980.
Full textAbstract:
abstract: Antibiotic resistant bacteria are a worldwide epidemic threatening human survival. Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Current ASTs are based on bacterial culturing, which take 2-14 days to complete depending on the microbial growth rate. Considering the high mortality and morbidity rates for most acute infections, such long time frames are clinically impractical and pose a huge risk to a patient's life. A faster AST will reduce morbidity and mortality rates, as well as help healthcare providers, administer narrow spectrum antibiotics at the earliest possible treatment stage.
In this dissertation, I developed a nonculture-based AST using an imaging and cell tracking technology. I track individual Escherichia coli O157:H7 (E. coli O157:H7) Uropathogenic Escherichia Coli (UPEC) cells, widely implicated in food-poisoning outbreaks and urinary tract infections respectively. Cells tethered to a surface are tracked on the nanometer scale, and phenotypic motion is correlated with bacterial metabolism. Antibiotic action significantly slows down motion of tethered bacterial cells, which is used to perform antibiotic susceptibility testing. Using this technology, the clinical minimum bactericidal concentration of an antibiotic against UPEC pathogens was calculated within 2 hours directly in urine samples as compared to 3 days using current gold standard tools.
Such technologies can make a tremendous impact to improve the efficacy and efficiency of infectious disease treatment. This has the potential to reduce the antibiotic mis-prescription steeply, which can drastically decrease the annual 2M+ hospitalizations and 23,000+ deaths caused due to antibiotic resistance bacteria along with saving billions of dollars to payers, patients, and hospitals.Dissertation/Thesis
Doctoral Dissertation Bioengineering 2017
24
"Bayesian Nonparametric Modeling and Inference for Multiple Object Tracking." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.54996.
Full textAbstract:
abstract: The problem of multiple object tracking seeks to jointly estimate the time-varying cardinality and trajectory of each object. There are numerous challenges that are encountered in tracking multiple objects including a time-varying number of measurements, under varying constraints, and environmental conditions. In this thesis, the proposed statistical methods integrate the use of physical-based models with Bayesian nonparametric methods to address the main challenges in a tracking problem. In particular, Bayesian nonparametric methods are exploited to efficiently and robustly infer object identity and learn time-dependent cardinality; together with Bayesian inference methods, they are also used to associate measurements to objects and estimate the trajectory of objects. These methods differ from the current methods to the core as the existing methods are mainly based on random finite set theory.
The first contribution proposes dependent nonparametric models such as the dependent Dirichlet process and the dependent Pitman-Yor process to capture the inherent time-dependency in the problem at hand. These processes are used as priors for object state distributions to learn dependent information between previous and current time steps. Markov chain Monte Carlo sampling methods exploit the learned information to sample from posterior distributions and update the estimated object parameters.
The second contribution proposes a novel, robust, and fast nonparametric approach based on a diffusion process over infinite random trees to infer information on object cardinality and trajectory. This method follows the hierarchy induced by objects entering and leaving a scene and the time-dependency between unknown object parameters. Markov chain Monte Carlo sampling methods integrate the prior distributions over the infinite random trees with time-dependent diffusion processes to update object states.
The third contribution develops the use of hierarchical models to form a prior for statistically dependent measurements in a single object tracking setup. Dependency among the sensor measurements provides extra information which is incorporated to achieve the optimal tracking performance. The hierarchical Dirichlet process as a prior provides the required flexibility to do inference. Bayesian tracker is integrated with the hierarchical Dirichlet process prior to accurately estimate the object trajectory.
The fourth contribution proposes an approach to model both the multiple dependent objects and multiple dependent measurements. This approach integrates the dependent Dirichlet process modeling over the dependent object with the hierarchical Dirichlet process modeling of the measurements to fully capture the dependency among both object and measurements. Bayesian nonparametric models can successfully associate each measurement to the corresponding object and exploit dependency among them to more accurately infer the trajectory of objects. Markov chain Monte Carlo methods amalgamate the dependent Dirichlet process with the hierarchical Dirichlet process to infer the object identity and object cardinality.
Simulations are exploited to demonstrate the improvement in multiple object tracking performance when compared to approaches that are developed based on random finite set theory.Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2019
25
"Automatic Tracking of Linguistic Changes for Monitoring Cognitive-Linguistic Health." Master's thesis, 2016. http://hdl.handle.net/2286/R.I.38607.
Full textAbstract:
abstract: Many neurological disorders, especially those that result in dementia, impact speech and language production. A number of studies have shown that there exist subtle changes in linguistic complexity in these individuals that precede disease onset. However, these studies are conducted on controlled speech samples from a specific task. This thesis explores the possibility of using natural language processing in order to detect declining linguistic complexity from more natural discourse. We use existing data from public figures suspected (or at risk) of suffering from cognitive-linguistic decline, downloaded from the Internet, to detect changes in linguistic complexity. In particular, we focus on two case studies. The first case study analyzes President Ronald Reagan’s transcribed spontaneous speech samples during his presidency. President Reagan was diagnosed with Alzheimer’s disease in 1994, however my results showed declining linguistic complexity during the span of the 8 years he was in office. President George Herbert Walker Bush, who has no known diagnosis of Alzheimer’s disease, shows no decline in the same measures. In the second case study, we analyze transcribed spontaneous speech samples from the news conferences of 10 current NFL players and 18 non-player personnel since 2007. The non-player personnel have never played professional football. Longitudinal analysis of linguistic complexity showed contrasting patterns in the two groups. The majority (6 of 10) of current players showed decline in at least one measure of linguistic complexity over time. In contrast, the majority (11 out of 18) of non-player personnel showed an increase in at least one linguistic complexity measure.Dissertation/Thesis
Masters Thesis Computer Science 2016
26
"Validating the STOM Model Using MATB II and Eye-tracking." Master's thesis, 2020. http://hdl.handle.net/2286/R.I.62734.
Full textAbstract:
abstract: The choices of an operator under heavy cognitive load are potentially critical to overall safety and performance. Such conditions are common when technological failures arise, and the operator is forced into multi-task situations. Task switching choice was examined in an effort to both validate previous work concerning a model of task overload management and address unresolved matters related to visual sampling. Using the Multi-Attribute Task Battery and eye tracking, the experiment studied any influence of task priority and difficulty. Continuous visual attention measurements captured attentional switches that do not manifest into behaviors but may provide insight into task switching choice. Difficulty was found to have an influence on task switching behavior; however, priority was not. Instead, priority may affect time spent on a task rather than strictly choice. Eye measures revealed some moderate connections between time spent dwelling on a task and subjective interest. The implication of this, as well as eye tracking used to validate a model of task overload management as a whole, is discussed.Dissertation/Thesis
Masters Thesis Human Systems Engineering 2020
27
"Utilization of automated location tracking for clinical workflow analytics and visualization." Doctoral diss., 2018. http://hdl.handle.net/2286/R.I.51634.
Full textAbstract:
abstract: The analysis of clinical workflow offers many challenges to clinical stakeholders and researchers, especially in environments characterized by dynamic and concurrent processes. Workflow analysis in such environments is essential for monitoring performance and finding bottlenecks and sources of error. Clinical workflow analysis has been enhanced with the inclusion of modern technologies. One such intervention is automated location tracking which is a system that detects the movement of clinicians and equipment. Utilizing the data produced from automated location tracking technologies can lead to the development of novel workflow analytics that can be used to complement more traditional approaches such as ethnography and grounded-theory based qualitative methods. The goals of this research are to: (i) develop a series of analytic techniques to derive deeper workflow-related insight in an emergency department setting, (ii) overlay data from disparate sources (quantitative and qualitative) to develop strategies that facilitate workflow redesign, and (iii) incorporate visual analytics methods to improve the targeted visual feedback received by providers based on the findings. The overarching purpose is to create a framework to demonstrate the utility of automated location tracking data used in conjunction with clinical data like EHR logs and its vital role in the future of clinical workflow analysis/analytics. This document is categorized based on two primary aims of the research. The first aim deals with the use of automated location tracking data to develop a novel methodological/exploratory framework for clinical workflow. The second aim is to overlay the quantitative data generated from the previous aim on data from qualitative observation and shadowing studies (mixed methods) to develop a deeper view of clinical workflow that can be used to facilitate workflow redesign. The final sections of the document speculate on the direction of this work where the potential of this research in the creation of fully integrated clinical environments i.e. environments with state-of-the-art location tracking and other data collection mechanisms, is discussed. The main purpose of this research is to demonstrate ways by which clinical processes can be continuously monitored allowing for proactive adaptations in the face of technological and process changes to minimize any negative impact on the quality of patient care and provider satisfaction.Dissertation/Thesis
Doctoral Dissertation Biomedical Informatics 2018
28
"Multiple Radar Target Tracking in Environments with High Noise and Clutter." Doctoral diss., 2015. http://hdl.handle.net/2286/R.I.29684.
Full textAbstract:
abstract: Tracking a time-varying number of targets is a challenging
dynamic state estimation problem whose complexity is intensified
under low signal-to-noise ratio (SNR) or high clutter conditions.
This is important, for example, when tracking
multiple, closely spaced targets moving in the same direction such as a
convoy of low observable vehicles moving through a forest or multiple
targets moving in a crisscross pattern. The SNR in
these applications is usually low as the reflected signals from
the targets are weak or the noise level is very high.
An effective approach for detecting and tracking a single target
under low SNR conditions is the track-before-detect filter (TBDF)
that uses unthresholded measurements. However, the TBDF has only been used to
track a small fixed number of targets at low SNR.
This work proposes a new multiple target TBDF approach to track a
dynamically varying number of targets under the recursive Bayesian framework.
For a given maximum number of
targets, the state estimates are obtained by estimating the joint
multiple target posterior probability density function under all possible
target
existence combinations. The estimation of the corresponding target existence
combination probabilities and the target existence probabilities are also
derived. A feasible sequential Monte Carlo (SMC) based implementation
algorithm is proposed. The approximation accuracy of the SMC
method with a reduced number of particles is improved by an efficient
proposal density function that partitions the multiple target space into a
single target space.
The proposed multiple target TBDF method is extended to track targets in sea
clutter using highly time-varying radar measurements. A generalized
likelihood function for closely spaced multiple targets in compound Gaussian
sea clutter is derived together with the maximum likelihood estimate of
the model parameters using an iterative fixed point algorithm.
The TBDF performance is improved by proposing a computationally feasible
method to estimate the space-time covariance matrix of rapidly-varying sea
clutter. The method applies the Kronecker product approximation to the
covariance matrix and uses particle filtering to solve the resulting dynamic
state space model formulation.Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2015
29
"Image Reconstruction, Classification, and Tracking for Compressed Sensing Imaging and Video." Doctoral diss., 2016. http://hdl.handle.net/2286/R.I.40835.
Full textAbstract:
abstract: Compressed sensing (CS) is a novel approach to collecting and analyzing data of all types. By exploiting prior knowledge of the compressibility of many naturally-occurring signals, specially designed sensors can dramatically undersample the data of interest and still achieve high performance. However, the generated data are pseudorandomly mixed and must be processed before use. In this work, a model of a single-pixel compressive video camera is used to explore the problems of performing inference based on these undersampled measurements. Three broad types of inference from CS measurements are considered: recovery of video frames, target tracking, and object classification/detection. Potential applications include automated surveillance, autonomous navigation, and medical imaging and diagnosis.
Recovery of CS video frames is far more complex than still images, which are known to be (approximately) sparse in a linear basis such as the discrete cosine transform. By combining sparsity of individual frames with an optical flow-based model of inter-frame dependence, the perceptual quality and peak signal to noise ratio (PSNR) of reconstructed frames is improved. The efficacy of this approach is demonstrated for the cases of \textit{a priori} known image motion and unknown but constant image-wide motion.
Although video sequences can be reconstructed from CS measurements, the process is computationally costly. In autonomous systems, this reconstruction step is unnecessary if higher-level conclusions can be drawn directly from the CS data. A tracking algorithm is described and evaluated which can hold target vehicles at very high levels of compression where reconstruction of video frames fails. The algorithm performs tracking by detection using a particle filter with likelihood given by a maximum average correlation height (MACH) target template model.
Motivated by possible improvements over the MACH filter-based likelihood estimation of the tracking algorithm, the application of deep learning models to detection and classification of compressively sensed images is explored. In tests, a Deep Boltzmann Machine trained on CS measurements outperforms a naive reconstruct-first approach.
Taken together, progress in these three areas of CS inference has the potential to lower system cost and improve performance, opening up new applications of CS video cameras.Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2016
30
"Tracking Chemical Indicators of Public Health in the Urban Water Environment." Doctoral diss., 2018. http://hdl.handle.net/2286/R.I.49018.
Full textAbstract:
abstract: This dissertation focuses on the application of urban metabolism metrology (UMM) to process streams of the natural and built water environment to gauge public health concerning exposure to carcinogenic N-nitrosamines and abuse of narcotics. A survey of sources of exposure to N-nitrosamines in the U.S. population identified contaminated food products (1,900 ± 380 ng/day) as important drivers of attributable cancer risk (Chapter 2). Freshwater sediments in the proximity of U.S. municipal wastewater treatment plants were shown for the first time to harbor carcinogenic N-nitrosamine congeners, including N-nitrosodibutylamine (0.2-3.3 ng/g dw), N-nitrosodiphenylamine (0.2-4.7 ng/g dw), and N-nitrosopyrrolidine (3.4-19.6 ng/g dw) were, with treated wastewater discharge representing one potential factor contributing to the observed contamination (p=0.42) (Chapter 3). Opioid abuse rates in two small midwestern communities were estimated through the application of wastewater-based epidemiology (WBE). Average concentrations of opioids (City 1; City 2) were highest for morphine (713 ± 38, 306 ± 29 ng/L) and varied by for the remainder of the screened analytes. Furthermore, concentrations of the powerful opioid fentanyl (1.7 ± 0.2, 1.0 ± 0.5 ng/L) in wastewater were reported for the first time in the literature for the U.S. (Chapter 4). To gauge narcotic consumption within college-aged adults the WBE process used in Chapter 4 was applied to wastewater collected from a large university in the Southwestern U.S. Estimated narcotics consumption, in units of mg/day/1,000 persons showed the following rank order: cocaine (470 ± 42), heroin (474 ± 32), amphetamine (302 ± 14) and methylphenidate (236 ± 28). Most parental drugs and their respective metabolites showed detection frequencies in campus wastewater of 80% or more, with the notable exception of fentanyl, norfentanyl, buprenorphine, and norbuprenorphine. Estimated consumption of all narcotics, aside from attention-deficit/hyperactivity disorder medication, were higher than values reported in previous U.S. WBE studies for U.S. campuses (Chapter 5). The analyses presented here have identified variation in narcotic consumption habits across different U.S. communities, which can be gauged through UMM. Application of these techniques should be implemented throughout U.S. communities to provide insight into ongoing substance abuse and health issues within a community.Dissertation/Thesis
Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018
31
"Hybrid Envelope Tracking Supply Modulator Analysis and Design for Wideband Applications." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.55465.
Full textAbstract:
abstract: A wideband hybrid envelope tracking modulator utilizing a hysteretic-controlled three-level switching converter and a slew-rate enhanced linear amplifierer is presented. In addition to smaller ripple and lower losses of three-level switching converters, employing the proposed hysteresis control loop results in a higher speed loop and wider bandwidth converter, enabling over 80MHz of switching frequency. A concurrent sensor circuit monitors and regulates the flying capacitor voltage VCF and eliminates conventional required calibration loop to control it. The hysteretic-controlled three-level switching converter provides a high percentage of power amplifier supply load current with lower ripple, reducing the linear amplifier high-frequency current and ripple cancellation current, improving the overall system efficiency. A slew-rate enhancement (SRE) circuit is employed in the linear amplifier resulting in slew-rate of
over 307V/us and bandwidth of over 275MHz for the linear amplifier. The slew-rate enhancement circuit provides a parallel auxiliary current path directly to the gate of the class-AB output stage transistors, speeding-up the charging or discharging of out-
put without modifying the operating point of the remaining linear amplifier, while maintaining the quiescent current of the class-AB stage. The supply modulator is fabricated in 65nm CMOS process. The measurement results show the tracking of LTE-40MHz envelope with 93% peak efficiency at 1W output power, while the SRE is disabled. Enabling the SRE it can track LTE-80MHz envelope with peak efficiency of 91%.Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2019
32
"Head Rotation Detection in Marmoset Monkeys." Master's thesis, 2014. http://hdl.handle.net/2286/R.I.25880.
Full textAbstract:
abstract: Head movement is known to have the benefit of improving the accuracy of sound localization for humans and animals. Marmoset is a small bodied New World monkey species and it has become an emerging model for studying the auditory functions. This thesis aims to detect the horizontal and vertical rotation of head movement in marmoset monkeys.
Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses in marmoset monkeys.Dissertation/Thesis
Masters Thesis Electrical Engineering 2014
33
Reyes, Denny L. "Three-Dimensional Velocity Measurement Reconstruction for a Rod Bundle Array using Matched Refractive Index Particle Tracking Velocimetry." Thesis, 2013. http://hdl.handle.net/1969.1/151280.
Full textAbstract:
In a pressurized water reactor (PWR), pressurized water flows over fuel rods containing radioactive uranium. Potential failure of these nuclear fuel rods is a primary concern, as fuel rod failure typically results in power generation losses and reactor downtime. Thermal parameters such as critical heat flux have traditionally been utilized as performance metrics to ensure that the reactor core remains stable even during failure events. Recently, fuel leaking events have occurred which have resulted in excess debris buildup on fuel rods and fuel grid array mixing devices. Understanding the flow field surrounding these nuclear fuel rods is critical in predicting where crud could deposit. Although CFD simulations have been conducted to characterize the fluid flow around fuel rod bundles, limited experimental data characterizing the mechanics of this fluid flow exists in the current literature.
This study will present experimental data collected detailing the fluid flow around a rod bundle geometry using a novel matched refractive index particle tracking velocimetry (PTV) technique over a 3D volume cross section of a prototypical nuclear fuel rod bundle. Velocimetry tracking will be performed in order to characterize the mechanics of the fluid flow. Using optical distortion mitigation techniques and various image processing methods, data from multiple cameras was used to assemble 3-dimensional velocity information of a turbulent fluid region. Results are compared to the solution of a k-epsilon unsteady RANS numerical simulation.
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"Urban Terrain Multiple Target Tracking Using the Probability Hypothesis Density Particle Filter." Master's thesis, 2011. http://hdl.handle.net/2286/R.I.9471.
Full textAbstract:
abstract: The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban terrain environments is traditionally implemented using sequential Monte Carlo filtering algorithms and data association techniques. However, data association techniques can be computationally intensive and require very strict conditions for efficient performance. This thesis investigates the probability hypothesis density (PHD) method for tracking multiple targets in urban environments. The PHD is based on the theory of random finite sets and it is implemented using the particle filter. Unlike data association methods, it can be used to estimate the number of targets as well as their corresponding tracks. A modified maximum-likelihood version of the PHD (MPHD) is proposed to automatically and adaptively estimate the measurement types available at each time step. Specifically, the MPHD allows measurement-to-nonlinearity associations such that the best matched measurement can be used at each time step, resulting in improved radar coverage and scene visibility. Numerical simulations demonstrate the effectiveness of the MPHD in improving tracking performance, both for tracking multiple targets and targets in clutter.Dissertation/Thesis
M.S. Electrical Engineering 2011
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"Tracking Climate-Driven Changes in Neandertal Subsistence Behaviors and Prey Mobility Patterns." Doctoral diss., 2012. http://hdl.handle.net/2286/R.I.16049.
Full textAbstract:
abstract: The ability of Neandertals to cope with the oscillating climate of the late Pleistocene and the extent to which these climate changes affected local Neandertal habitats remain unanswered anthropological topics of considerable scientific interest. Understanding the impact of climatic instability on Neandertals is critical for reconstructing the behaviors of our closest fossil relatives and possibly identifying factors that contributed to their extinction. My work aimed to test the hypotheses that 1) cold climates stressed Neandertal populations, and 2) that global climate changes affected local Neandertal habitats. An analysis of Neandertal butchering on Cervus elaphus, Rangifer tarandus, and Capreolus capreolus skeletal material deposited during global warm and cold phases from two French sites - Pech de l'Azé IV and Roc de Marsal - was conducted to assess the impact of climate change on butchering strategies and resource extraction. Results from a statistical analysis of surface modification on all marrow yielding long bones, including the 1st phalanx, demonstrated that specimens excavated from the cold levels at each cave have more cut marks (Wald χ2= 51.33, p= <0.001) and percussion marks (Wald χ2= 4.92, p= 0.02) than specimens from the warm levels after controlling for fragment size. These results support the hypothesis that Neandertals were nutritionally stressed during glacial cycles. The hypothesis that global climates affected local habitats was tested through radiogenic strontium isotopic reconstruction of large herbivore mobility patterns (e.g., Bison, Equus, Cervus and Rangifer), because it is known that in the northern hemisphere, mammals migrate less in warm, well-vegetated environments, but more in cold, open environments. Identifying isotopic variation in mammalian fossils enables mobility patterns to be inferred, providing an indication of whether environments at Pech de l'Azé IV and Roc de Marsal tracked global climates. Results from this study indicate that Neandertal prey species within the Dordogne Valley of France did not undertake long distance round-trip migrations in glacial or interglacial cycles, maintaining the possibility that local habitats did not change in differing climatic cycles. However, because Neandertals were nutritionally stressed the most likely conclusion is that glacial cycles decreased herbivore populations, thus stressing Neandertals.Dissertation/Thesis
Ph.D. Anthropology 2012
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"Contextual Computing: Tracking Healthcare Providers in the Emergency Department via Bluetooth Beacons." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.34786.
Full textAbstract:
abstract: Hospital Emergency Departments (EDs) are frequently crowded. The Center for
Medicare and Medicaid Services (CMS) collects performance measurements from EDs
such as that of the door to clinician time. The door to clinician time is the time at which a
patient is first seen by a clinician. Current methods for documenting the door to clinician
time are in written form and may contain inaccuracies. The goal of this thesis is to
provide a method for automatic and accurate retrieval and documentation of the door to
clinician time. To automatically collect door to clinician times, single board computers
were installed in patient rooms that logged the time whenever they saw a specific
Bluetooth emission from a device that the clinician carried. The Bluetooth signal is used
to calculate the distance of the clinician from the single board computer. The logged time
and distance calculation is then sent to the server where it is determined if the clinician
was in the room seeing the patient at the time logged. The times automatically collected
were compared with the handwritten times recorded by clinicians and have shown that
they are justifiably accurate to the minute.Dissertation/Thesis
Masters Thesis Computer Science 2015
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"Stress and Strain Propagation in Soft Viscoelastic Tissue While Tracking Microscale Targets." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.36525.
Full textAbstract:
abstract: Tracking microscale targets in soft tissue using implantable probes is important in clinical applications such as neurosurgery, chemotherapy and in neurophysiological application such as brain monitoring. In most of these applications, such tracking is done with visual feedback involving some imaging modality that helps localization of the targets through images that are co-registered with stereotaxic coordinates. However, there are applications in brain monitoring where precision targeting of microscale targets such as single neurons need to be done in the absence of such visual feedback. In all of the above mentioned applications, it is important to understand the dynamics of mechanical stress and strain induced by the movement of implantable, often microscale probes in soft viscoelastic tissue. Propagation of such stresses and strains induce inaccuracies in positioning if they are not adequately compensated. The aim of this research is to quantitatively assess (a) the lateral propagation of stress and (b) the spatio-temporal distribution of strain induced by the movement of microscale probes in soft viscoelastic tissue. Using agarose hydrogel and a silicone derivative as two different bench-top models of brain tissue, we measured stress propagation during movement of microscale probes using a sensitive load cell. We further used a solution of microscale beads and the silicone derivative to quantitatively map the strain fields using video microscopy. The above measurements were done under two different types of microelectrode movement – first, a unidirectional movement and second, a bidirectional (inch-worm like) movement both of 30 μm step-size with 3min inter-movement interval. Results indicate movements of microscale probes can induce significant stresses as far as 500 μm laterally from the location of the probe. Strain fields indicate significantly high levels of displacements (in the order of 100 μm) within 100 μm laterally from the surface of the probes. The above measurements will allow us to build precise mechanical models of soft tissue and compensators that will enhance the accuracy of tracking microscale targets in soft tissue.Dissertation/Thesis
Masters Thesis Bioengineering 2015
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"Temporal Coding of Cortical Neural Signals and Camera Motion Estimation in Target Tracking." Doctoral diss., 2012. http://hdl.handle.net/2286/R.I.14715.
Full textAbstract:
abstract: This dissertation includes two parts. First it focuses on discussing robust signal processing algorithms, which lead to consistent performance under perturbation or uncertainty in video target tracking applications. Projective distortion plagues the quality of long sequence mosaicking which results in loosing important target information. Some correction techniques require prior information. A new algorithm is proposed in this dissertation to this very issue. Optimization and parameter tuning of a robust camera motion estimation as well as implementation details are discussed for a real-time application using an ordinary general-purpose computer. Performance evaluations on real-world unmanned air vehicle (UAV) videos demonstrate the robustness of the proposed algorithms. The second half of the dissertation addresses neural signal analysis and modeling. Neural waveforms were recorded from rats' motor cortical areas while rats performed a learning control task. Prior to analyzing and modeling based on the recorded neural signal, neural action potentials are processed to detect neural action potentials which are considered the basic computation unit in the brain. Most algorithms rely on simple thresholding, which can be subjective. This dissertation proposes a new detection algorithm, which is an automatic procedure based on signal-to-noise ratio (SNR) from the neural waveforms. For spike sorting, this dissertation proposes a classification algorithm based on spike features in the frequency domain and adaptive clustering method such as the self-organizing map (SOM). Another major contribution of the dissertation is the study of functional interconnectivity of neurons in an ensemble. These functional correlations among neurons reveal spatial and temporal statistical dependencies, which consequently contributes to the understanding of a neuronal substrate of meaningful behaviors. This dissertation proposes a new generalized yet simple method to study adaptation of neural ensemble activities of a rat's motor cortical areas during its cognitive learning process. Results reveal interesting temporal firing patterns underlying the behavioral learning process.Dissertation/Thesis
Ph.D. Electrical Engineering 2012
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"Radar Tracking Waveform Design in Continuous Space and Optimization Selection Using Differential Evolution." Master's thesis, 2014. http://hdl.handle.net/2286/R.I.25100.
Full textAbstract:
abstract: Waveform design that allows for a wide variety of frequency-modulation (FM) has proven benefits. However, dictionary based optimization is limited and gradient search methods are often intractable. A new method is proposed using differential evolution to design waveforms with instantaneous frequencies (IFs) with cubic FM functions whose coefficients are constrained to the surface of the three dimensional unit sphere. Cubic IF functions subsume well-known IF functions such as linear, quadratic monomial, and cubic monomial IF functions. In addition, all nonlinear IF functions sufficiently approximated by a third order Taylor series over the unit time sequence can be represented in this space. Analog methods for generating polynomial IF waveforms are well established allowing for practical implementation in real world systems. By sufficiently constraining the search space to these waveforms of interest, alternative optimization methods such as differential evolution can be used to optimize tracking performance in a variety of radar environments. While simplified tracking models and finite waveform dictionaries have information theoretic results, continuous waveform design in high SNR, narrowband, cluttered environments is explored.Dissertation/Thesis
M.S. Electrical Engineering 2014
40
"Radar Target Tracking with Varying Levels of Communications Interference for Shared Spectrum Access." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.29990.
Full textAbstract:
abstract: As the demand for spectrum sharing between radar and communications systems is steadily increasing, the coexistence between the two systems is a growing and very challenging problem. Radar tracking in the presence of strong communications interference can result in low probability of detection even when sequential Monte Carlo
tracking methods such as the particle filter (PF) are used that better match the target kinematic model. In particular, the tracking performance can fluctuate as the power level of the communications interference can vary dynamically and unpredictably.
This work proposes to integrate the interacting multiple model (IMM) selection approach with the PF tracker to allow for dynamic variations in the power spectral density of the communications interference. The model switching allows for a necessary transition between different communications interference power spectral density (CI-PSD) values in order to reduce prediction errors. Simulations demonstrate the high performance of the integrated approach with as many as six dynamic CI-PSD value changes during the target track. For low signal-to-interference-plus-noise ratios, the derivation for estimating the high power levels of the communications interference is provided; the estimated power levels would be dynamically used in the IMM when integrated with a track-before-detect filter that is better matched to low SINR tracking applications.Dissertation/Thesis
Masters Thesis Electrical Engineering 2015
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"Target Discrimination Against Clutter Based on Unsupervised Clustering and Sequential Monte Carlo Tracking." Master's thesis, 2016. http://hdl.handle.net/2286/R.I.41269.
Full textAbstract:
abstract: The radar performance of detecting a target and estimating its parameters can deteriorate rapidly in the presence of high clutter. This is because radar measurements due to clutter returns can be falsely detected as if originating from the actual target. Various data association methods and multiple hypothesis filtering approaches have been considered to solve this problem. Such methods, however, can be computationally intensive for real time radar processing. This work proposes a new approach that is based on the unsupervised clustering of target and clutter detections before target tracking using particle filtering. In particular, Gaussian mixture modeling is first used to separate detections into two Gaussian distinct mixtures. Using eigenvector analysis, the eccentricity of the covariance matrices of the Gaussian mixtures are computed and compared to threshold values that are obtained a priori. The thresholding allows only target detections to be used for target tracking. Simulations demonstrate the performance of the new algorithm and compare it with using k-means for clustering instead of Gaussian mixture modeling.Dissertation/Thesis
Masters Thesis Electrical Engineering 2016
42
"High Slew-Rate Adaptive Biasing Hybrid Envelope Tracking Supply Modulator for LTE Applications." Doctoral diss., 2017. http://hdl.handle.net/2286/R.I.45948.
Full textAbstract:
abstract: As wireless communication enters smartphone era, more complicated communication technologies are being used to transmit higher data rate. Power amplifier (PA) has to work in back-off region, while this inevitably reduces battery life for cellphones. Various techniques have been reported to increase PA efficiency, such as envelope elimination and restoration (EER) and envelope tracking (ET). However, state of the art ET supply modulators failed to address high efficiency, high slew rate, and accurate tracking concurrently.
In this dissertation, a linear-switch mode hybrid ET supply modulator utilizing adaptive biasing and gain enhanced current mirror operational transconductance amplifier (OTA) with class-AB output stage in parallel with a switching regulator is presented. In comparison to a conventional OTA design with similar quiescent current consumption, proposed approach improves positive and negative slew rate from 50 V/µs to 93.4 V/µs and -87 V/µs to -152.5 V/µs respectively, dc gain from 45 dB to 67 dB while consuming same amount of quiescent current. The proposed hybrid supply modulator achieves 83% peak efficiency, power added efficiency (PAE) of 42.3% at 26.2 dBm for a 10 MHz 7.24 dB peak-to-average power ratio (PAPR) LTE signal and improves PAE by 8% at 6 dB back off from 26.2 dBm power amplifier (PA) output power with respect to fixed supply. With a 10 MHz 7.24 dB PAPR QPSK LTE signal the ET PA system achieves adjacent channel leakage ratio (ACLR) of -37.7 dBc and error vector magnitude (EVM) of 4.5% at 26.2 dBm PA output power, while with a 10 MHz 8.15 dB PAPR 64QAM LTE signal the ET PA system achieves ACLR of -35.6 dBc and EVM of 6% at 26 dBm PA output power without digital pre-distortion (DPD). The proposed supply modulator core circuit occupies 1.1 mm2 die area, and is fabricated in a 0.18 µm CMOS technology.Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2017
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"Visual Behavior and Planning for Object Manipulation: Gaze Patterns for Altered Center of Mass." Master's thesis, 2017. http://hdl.handle.net/2286/R.I.45580.
Full textAbstract:
abstract: The interaction between visual fixations during planning and performance in a
dexterous task was analyzed. An eye-tracking device was affixed to subjects during
sequences of null (salient center of mass) and weighted (non salient center of mass) trials
with unconstrained precision grasp. Subjects experienced both expected and unexpected
perturbations, with the task of minimizing object roll. Unexpected perturbations were
controlled by switching weights between trials, expected perturbations were controlled by
asking subjects to rotate the object themselves. In all cases subjects were able to
minimize the roll of the object within three trials. Eye fixations were correlated with
object weight for the initial context and for known shifts in center of mass. In subsequent
trials with unexpected weight shifts, subjects appeared to scan areas of interest from both
contexts even after learning present orientation.Dissertation/Thesis
Masters Thesis Biomedical Engineering 2017
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"Detect and Analyze the 3-D Head Movement Patterns in Marmoset Monkeys using Wireless Tracking System." Master's thesis, 2015. http://hdl.handle.net/2286/R.I.34913.
Full textAbstract:
abstract: Head movement is a natural orienting behavior for sensing environmental events around us. Head movement is particularly important for identifying through the sense of hearing the location of an out-of-sight, rear-approaching target to avoid danger or threat. This research aims to design a portable device for detecting the head movement patterns of common marmoset monkeys in laboratory environments. Marmoset is a new-world primate species and has become increasingly popular for neuroscience research. Understanding the unique patterns of their head movements will improve its values as a new primate model for uncovering the neurobiology of natural orienting behavior. Due to their relatively small head size (5 cm in diameter) and body weight (300-500 g), the device has to meet several unique design requirements with respect to accuracy and workability. A head-mount wireless tracking system was implemented based on inertial sensors that are capable of detecting motion in the Yaw, Pitch and Roll axes. The sensors were connected to the encoding station, which transmits wirelessly the 3-axis movement data to the decoding station at the sampling rate of ~175 Hz. The decoding station relays this information to the computer for real-time display and analysis. Different tracking systems, based on the accelerometer and Inertial Measurement Unit is implemented to track the head movement pattern of the marmoset head. Using these systems, translational and rotational information of head movement are collected, and the data analysis focuses on the rotational head movement in body-constrained marmosets. Three stimulus conditions were tested: 1) Alert, 2) Idle 3) Sound only. The head movement patterns were examined when the house light was turned on and off for each stimulus. Angular velocity, angular displacement and angular acceleration were analyzed in all three axes.
Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior.Dissertation/Thesis
Masters Thesis Bioengineering 2015
45
"Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets." Master's thesis, 2012. http://hdl.handle.net/2286/R.I.14953.
Full textAbstract:
abstract: In this thesis, an integrated waveform-agile multi-modal tracking-beforedetect sensing system is investigated and the performance is evaluated using an experimental platform. The sensing system of adapting asymmetric multi-modal sensing operation platforms using radio frequency (RF) radar and electro-optical (EO) sensors allows for integration of complementary information from different sensors. However, there are many challenges to overcome, including tracking low signal-to-noise ratio (SNR) targets, waveform configurations that can optimize tracking performance and statistically dependent measurements. Address some of these challenges, a particle filter (PF) based recursive waveformagile track-before-detect (TBD) algorithm is developed to avoid information loss caused by conventional detection under low SNR environments. Furthermore, a waveform-agile selection technique is integrated into the PF-TBD to allow for adaptive waveform configurations. The embedded exponential family (EEF) approach is used to approximate distributions of parameters of dependent RF and EO measurements and to further improve target detection rate and tracking performance. The performance of the integrated algorithm is evaluated using real data from three experimental scenarios.Dissertation/Thesis
M.S. Electrical Engineering 2012
46
"Effect of Incorporating Aerodynamic Drag Model on Trajectory Tracking Performance of DJI F330 Quadcopter." Master's thesis, 2020. http://hdl.handle.net/2286/R.I.57415.
Full textAbstract:
abstract: Control algorithm development for quadrotor is usually based solely on rigid body dynamics neglecting aerodynamics. Recent work has demonstrated that such a model is suited only when operating at or near hover conditions and low-speed flight. When operating in confined spaces or during aggressive maneuvers destabilizing forces and moments are induced due to aerodynamic effects. Studies indicate that blade flapping, induced drag, and propeller drag influence forward flight performance while other effects like vortex ring state, ground effect affect vertical flight performance. In this thesis, an offboard data-driven approach is used to derive models for parasitic (bare-airframe) drag and propeller drag. Moreover, thrust and torque coefficients are identified from static bench tests. Among the two, parasitic drag is compensated for in the position controller module in the PX4 firmware. 2-D circular, straight line, and minimum snap rectangular trajectories with corridor constraints are tested exploiting differential flatness property wherein altitude and yaw angle are constant. Flight tests are conducted at ASU Drone Studio and results of tracking performance with default controller and with drag compensated position controller are presented. Root mean squared tracking error in individual axes is used as a metric to evaluate the model performance. Results indicate that, for circular trajectory, the root mean squared error in the x-axis has reduced by 44.54% and in the y-axis by 39.47%. Compensation in turn degrades the tracking in both axis by a maximum under 12% when compared to the default controller for rectangular trajectory case. The x-axis tracking error for the straight-line case has improved by 44.96% with almost no observable change in the y-axis.Dissertation/Thesis
Real-time Flight Test of Circular Trajectories
Masters Thesis Aerospace Engineering 2020
47
"Quiet Eye Training and the Focus of Visual Attention in Golf Putting." Master's thesis, 2019. http://hdl.handle.net/2286/R.I.53829.
Full textAbstract:
abstract: Previous research has shown that training visual attention can improve golf putting performance. A technique called the Quiet Eye focuses on increasing a player’s length of fixation between the ball and the hole. When putting, the final fixation is made on the ball before executing the stroke leaving players to rely on their memory of the hole’s distance and location. The present study aimed to test the effectiveness of Quiet Eye training for final fixation on the hole. Twelve Arizona State University (ASU) students with minimal golf experience putted while wearing eye tracking glasses under the following conditions: from three feet with final fixation on the ball, from six feet with final fixation on the ball, from three feet with final fixation on the hole and from six feet with final fixation on the hole. Participant’s performance was measured before training, following quiet eye training, and under simulated pressure conditions. Putting performance was not significantly affected by final fixation for all conditions. The number of total putts made was significantly greater when putting from three feet for all conditions. Future research should test the effects of this training with expert golfers whose processes are more automatic compared to novices and can afford to look at the hole while putting.Dissertation/Thesis
Masters Thesis Human Systems Engineering 2019
48
"Comparison of SPR and Edge Tracking as a Measure of Binding Kinetics in Whole Cells." Master's thesis, 2018. http://hdl.handle.net/2286/R.I.51617.
Full textAbstract:
abstract: Most drugs work by binding to receptors on the cell surface. These receptors can then carry the message into the cell and have a wide array of results. However, studying how fast the binding is can be difficult. Current methods involve extracting the receptor and labeling them, but both these steps have issues. Previous works found that binding on the cell surface is accompanied with a small change in cell size, generally an increase. They have also developed an algorithm that can track these small changes without a label using a simple bright field microscope. Here, this relationship is further explored by comparing edge tracking results to a more widely used method, surface plasmon resonance. The kinetic constants found from the two methods are in agreement. No corrections or manipulations were needed to create agreement. The Bland-Altman plots shows that the error between the two methods is about 0.009 s-1. This is about the same error between cells, making it a non-dominant source of error.Dissertation/Thesis
Masters Thesis Biochemistry 2018
49
"Efficient Bayesian Tracking of Multiple Sources of Neural Activity: Algorithms and Real-Time FPGA Implementation." Doctoral diss., 2013. http://hdl.handle.net/2286/R.I.18146.
Full textAbstract:
abstract: Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.Dissertation/Thesis
Ph.D. Electrical Engineering 2013
50
"Using Swept Tones to Evoke Stimulus Frequency Otoacoustic Emissions with In-situ Calibration." Doctoral diss., 2012. http://hdl.handle.net/2286/R.I.14711.
Full textAbstract:
abstract: Otoacoustic emissions (OAEs) are soft sounds generated by the inner ear and can be recorded within the ear canal. Since OAEs can reflect the functional status of the inner ear, OAE measurements have been widely used for hearing loss screening in the clinic. However, there are limitations in current clinical OAE measurements, such as the restricted frequency range, low efficiency and inaccurate calibration. In this dissertation project, a new method of OAE measurement which used a swept tone to evoke the stimulus frequency OAEs (SFOAEs) was developed to overcome the limitations of current methods. In addition, an in-situ calibration was applied to equalize the spectral level of the swept-tone stimulus at the tympanic membrane (TM). With this method, SFOAEs could be recorded with high resolution over a wide frequency range within one or two minutes. Two experiments were conducted to verify the accuracy of the in-situ calibration and to test the performance of the swept-tone SFOAEs. In experiment I, the calibration of the TM sound pressure was verified in both acoustic cavities and real ears by using a second probe microphone. In addition, the benefits of the in-situ calibration were investigated by measuring OAEs under different calibration conditions. Results showed that the TM pressure could be predicted correctly, and the in-situ calibration provided the most reliable results in OAE measurements. In experiment II, a three-interval paradigm with a tracking-filter technique was used to record the swept-tone SFOAEs in 20 normal-hearing subjects. The test-retest reliability of the swept-tone SFOAEs was examined using a repeated-measure design under various stimulus levels and durations. The accuracy of the swept-tone method was evaluated by comparisons with a standard method using discrete pure tones. Results showed that SFOAEs could be reliably and accurately measured with the swept-tone method. Comparing with the pure-tone approach, the swept-tone method showed significantly improved efficiency. The swept-tone SFOAEs with in-situ calibration may be an alternative of current clinical OAE measurements for more detailed evaluation of inner ear function and accurate diagnosis.Dissertation/Thesis
Ph.D. Speech and Hearing Science 2012