Design and analysis of adaptive noise subspace estimation algorithms

Ph.DDOCTOR OF PHILOSOPH

Mirror Activity in the Macaque Motor System

Mirror neurons (MirNs) within ventral premotor cortex (PMv) and primary motor cortex (M1), including pyramidal tract neurons (PTNs) projecting to the spinal cord, modulate their activity during both the execution and observation of motor acts. However, movement is not produced in the latter condition, and mirror responses cannot be explained by lowlevel muscle activity. Relatively reduced activity in M1 during observation may help to suppress movement. Here, we examined the extent to which activity at different stages of action observation reflects grasp representation and suppression of movement across multiple levels of the mirror system in monkeys and humans. We recorded MirNs in M1 and F5 (rostral PMv), including identified PTNs, in two macaque monkeys as they performed, observed, and withheld reach-to-grasp actions. Time-varying population activity was more distinct between execution and observation in M1 than in F5, and M1 activity in the lead-up to the observation of movement onset shared parallels with movement withholding activity. In separate experiments, modulation of short-latency responses evoked in hand muscles by pyramidal tract stimulation revealed modest grasp-specific facilitation at the spinal level during grasp observation. This contrasted with a relative suppression of excitability prior to observed movement onset or when monkeys simply withheld movement. Additional cortical recording experiments examined how contextual factors, such as observing to imitate, observing while engaged in action, or observation with reduced visual information, modulated mirror activity in M1 and F5. Finally, single-pulse transcranial magnetic stimulation (TMS) in healthy human volunteers was used to examine changes in corticospinal excitability (CSE) during action observation and withholding. Overall, the results reveal distinctions in the profile of mirror activity across premotor and motor areas. While F5 maintains a more abstract representation of grasp independent of the acting agent, a balance of excitation and inhibition in motor cortex and spinal circuitry during action observation may support a flexible dissociation between initiation of grasping actions and representation of observed grasp

Observable signatures of general relativistic dynamics in compact binaries

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 217-237).The effects of general relativity (GR) in astrophysical systems are often difficult to calculate, but they can have important consequences for observables. This thesis considers the impact of previously-ignored GR effects in two different types of compact binary systems. The first is the coalescence of massive black holes in high-redshift galaxies. The gravitational waves (GWs) from these systems can be detected by the proposed low-frequency gravitational wave detector LISA and used to determine the various parameters which characterize the binary. Most studies of LISA's parameter estimation capability have ignored a significant piece of physics: the relativistic precession of the binary's angular momentum vectors. In the first two-thirds of this thesis, we show how including precession effects in the waveform model helps to break various degeneracies and improve the expected parameter errors. We give special attention to the localization parameters, sky position and distance. When distance is converted to an approximate redshift, these parameters define a "pixel" on the sky in which astronomers can search for an electromagnetic counterpart to the GW event. The final third of this thesis focuses on stellar -mass compact binaries in which at least one member is a neutron star. The measurement of tidal effects in these systems may shed some light on the poorly understood high-density equation of state. We first calculate the point at which a neutron star tidally disrupts in the field of a black hole. Previous calculations of this effect have used Newtonian self-gravity, which is inappropriate for a neutron star; we correct this by using relativistic perturbation theory.(cont.) We then turn to small tidal distortions of neutron stars, which can be characterized by a quantity known as the Love number. We calculate relativistic Love numbers for a wide variety of equations of state and investigate their impact on the GWs from neutron star-neutron star binaries.by Ryan Nathan Lang.Ph.D

Developing integrated data fusion algorithms for a portable cargo screening detection system

Towards having a one size fits all solution to cocaine detection at borders; this thesis proposes a systematic cocaine detection methodology that can use raw data output from a fibre optic sensor to produce a set of unique features whose decisions can be combined to lead to reliable output. This multidisciplinary research makes use of real data sourced from cocaine analyte detecting fibre optic sensor developed by one of the collaborators - City University, London. This research advocates a two-step approach: For the first step, the raw sensor data are collected and stored. Level one fusion i.e. analyses, pre-processing and feature extraction is performed at this stage. In step two, using experimentally pre-determined thresholds, each feature decides on detection of cocaine or otherwise with a corresponding posterior probability. High level sensor fusion is then performed on this output locally to combine these decisions and their probabilities at time intervals. Output from every time interval is stored in the database and used as prior data for the next time interval. The final output is a decision on detection of cocaine. The key contributions of this thesis includes investigating the use of data fusion techniques as a solution for overcoming challenges in the real time detection of cocaine using fibre optic sensor technology together with an innovative user interface design. A generalizable sensor fusion architecture is suggested and implemented using the Bayesian and Dempster-Shafer techniques. The results from implemented experiments show great promise with this architecture especially in overcoming sensor limitations. A 5-fold cross validation system using a 12 13 - 1 Neural Network was used in validating the feature selection process. This validation step yielded 89.5% and 10.5% true positive and false alarm rates with 0.8 correlation coefficient. Using the Bayesian Technique, it is possible to achieve 100% detection whilst the Dempster Shafer technique achieves a 95% detection using the same features as inputs to the DF system

Saliency for Image Description and Retrieval

We live in a world where we are surrounded by ever increasing numbers of images. More often than not, these images have very little metadata by which they can be indexed and searched. In order to avoid information overload, techniques need to be developed to enable these image collections to be searched by their content. Much of the previous work on image retrieval has used global features such as colour and texture to describe the content of the image. However, these global features are insufficient to accurately describe the image content when different parts of the image have different characteristics. This thesis initially discusses how this problem can be circumvented by using salient interest regions to select the areas of the image that are most interesting and generate local descriptors to describe the image characteristics in that region. The thesis discusses a number of different saliency detectors that are suitable for robust retrieval purposes and performs a comparison between a number of these region detectors. The thesis then discusses how salient regions can be used for image retrieval using a number of techniques, but most importantly, two techniques inspired from the field of textual information retrieval. Using these robust retrieval techniques, a new paradigm in image retrieval is discussed, whereby the retrieval takes place on a mobile device using a query image captured by a built-in camera. This paradigm is demonstrated in the context of an art gallery, in which the device can be used to find more information about particular images. The final chapter of the thesis discusses some approaches to bridging the semantic gap in image retrieval. The chapter explores ways in which un-annotated image collections can be searched by keyword. Two techniques are discussed; the first explicitly attempts to automatically annotate the un-annotated images so that the automatically applied annotations can be used for searching. The second approach does not try to explicitly annotate images, but rather, through the use of linear algebra, it attempts to create a semantic space in which images and keywords are positioned such that images are close to the keywords that represent them within the space

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks