The rapid adoption of the internet has occurred despite the lack of a ubiquitous identity meta-system. The status quo is a patchwork of proprietary security systems. A number of security issues have arisen as a result which threaten to lead to a loss of trust in the internet, and may limit the scope of applications built on it; effectively constraining the potential of the internet as a platform for business and services. Current initiatives by a broad consortium of industry leaders promise a vastly improved landscape with a set of interoperable protocols and systems, built on open specifications, and guided by a set of core identity principles, enabling a more secure online experience. Simultaneously there have arisen a large number of location aware web application and services which detect and use a user’s location to enhance their application experience. These advances, although useful, present new security and privacy issues. This paper investigates the operation of one of the new identity technologies, information cards, and proposes extensions to the existing supported schemas to incorporate recent advances in geo-location technology. The proposal is supported by reference to existing o pen source implementations.

Thesis (Ph. D.)--Universität Bielefeld, 1999. / "13 April 1999." Postscript file reader required. Includes bibliographical references (p. 72-76) and index.

Thesis (M.Sc.) - Carleton University, 2002. / Includes bibliographical references (p. 85-87). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 280-283). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 280-283). Also available on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 120-127). Also available in electronic format on the Internet.

The formal definition of network coding by Ahlswede et al. in 2000 has led to several breakthroughs in information theory, for example solving the bottleneck problem in butterfly networks and breaking the min-cut max-flow theorem for multicast communication. Especially promising is the usage of network coding as a packet-level Forward Error Correction (FEC) scheme to increase the robustness of a data stream against packet loss, also known as intra-session coding. Yet, despite these benefits, network coding-based FEC is still rarely deployed in real-world networks. To bridge this gap between information theory and real-world usage, this cumulative thesis will present our contributions to the integration, evaluation, and optimization of network coding-based FEC. The first set of contributions introduces and evaluates efficient ways to integrate coding into UDP-based IoT protocols to speed up bulk data transfers in lossy scenarios. This includes a packet-level FEC extension for the Constrained Application Protocol (CoAP) [P1] and one for MQTT for Sensor Networks (MQTT-SN), which levels the underlying publish-subscribe architecture [P2]. The second set of contributions addresses the development of novel evaluation tools and methods to better quantify possible coding gains. This includes link ’em, our award-winning link emulation bridge for reproducible networking research [P3], and also SPQER, a word recognition-based metric to evaluate the impact of packet loss on the Quality of Experience of Voice over IP applications [P5]. Finally, we highlight the impact of padding overhead for applications with heterogeneous packet lengths [P6] and introduce a novel packet-preserving coding scheme to significantly reduce this problem [P4]. Because many of the shown contributions can be applied to other areas of network coding research as well, this thesis does not only make meaningful contributions to specific network coding challenges, but also paves the way for future work to further close the gap between information theory and real-world usage.

Orientador: Luís Geraldo Pedroso Meloni / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-21T21:07:48Z (GMT). No. of bitstreams: 1 Chanquini_JuliaJacobsenDornelles_M.pdf: 2607975 bytes, checksum: f9b57a1325c9977a5bfd0cdb69a56661 (MD5) Previous issue date: 2012 / Resumo: Este trabalho apresenta a adequação de um codificador de áudio padrão MPEG-4 AAC para aderência à norma brasileira do SBTVD. Também apresenta um estudo dos conceitos envolvidos em codificadores de áudio perceptuais com enfoque no codificador MPEG-4 AAC e também inclui a parte de multiplexação e sincronia do MPEG-4. Para o desenvolvimento do projeto foram estudados alguns códigos abertos de codificadores AAC: FAAD, 3GPP e o código de referência do padrão MPEG-4, especialmente a parte referente ao LATM/LOAS. O decodificador de áudio padrão MPEG-4 AAC que foi modificado para suportar a camada LATM/ LOAS foi o FAAD. Foi calculado o tempo adicional que o decodificador modificado leva para decodificar o áudio com a camada LATM/LOAS, sem ser notado um aumento significativo que não permite a decodificação em tempo real do áudio / Abstract: This work presents an adaptation of a standard MPEG-4 AAC audio coder to conform to the Brazilian digital TV standard SBTVD. It also presents a study of the concepts involved in perceptual audio coders focusing on MPEG-4 AAC and also including the multiplexing and synchronization part of the MPEG-4 standard. To develop this project, open source AAC coders were studied: FAAD, 3GPP and the MPEG-4 reference software code specially the part concerning LATM/LOAS. The AAC audio decoder which was modified to support the LATM / LOAS layer was FAAD. The additional time that the modified decoder needs to decode a sample audio with LATM / LOAS was calculated, and it did not introduce a large enough delay that would restrict real time audio decoding / Mestrado / Telecomunicações e Telemática / Mestra em Engenharia Elétrica

<div>Many important scientific, engineering, and societal challenges involve large systems of individual agents or components interacting in complex ways. For example, to understand the emergence of consciousness, we study the dendritic integration in neurons; to prevent disease and rumor outbreaks, we trace the dynamics of social networks; to perform complicated scientific experiments, we separate and control the independent variables. Collectively, the interactions between individual neurons/agents/variables are often non-linear, i.e., a subset of the agents jointly behave in a manner unlike the marginal behaviors of the individuals.</div><div><br></div><div>The goal of this thesis is to construct a theoretical framework for measuring, comparing, and representing complex interactions in stochastic systems. Specifically, tools from information theory, differential geometry, lattice theory, and linear algebra are used to identify and characterize higher-order interactions among random variables.</div><div><br></div><div>We first propose measures of unique, redundant, and synergistic interactions for small stochastic systems using information projections for the exponential family. Their magnitudes are endowed with information theoretical meanings naturally, since they are measured by the Kullback-Leibler divergence. We prove that these quantities satisfy various desired properties.</div><div><br></div><div>We next apply these measures to hypothesis testing and network communication. We interpret the unique information as the two types of error components in a hypothesis testing problem. We analytically show that there is a duality between the synergistic and redundant information in Gaussian Multiple Access Channels (MAC) and Broadcast Channels (BC). We establish a novel duality between the partial information decomposition components for MAC and BC in the general case.</div><div><br></div><div>We lastly propose a new concept of representing the partial information decomposition framework with random variables. We give necessary and sufficient conditions for the representation under the assumption of Gaussianity and develop a construction method.</div><div><br></div><div>This research has the potential to advance the fields of information theory, statistics, and machine learning by contributing novel ideas, implementing these ideas with innovative tools, and constructing new simulation methods.</div>

Neurons can respond to input by firing isolated action potentials or spikes. Sequences of spikes have been linked to the encoding of neuron input. However, many neurons also fire bursts; mechanistically distinct responses consisting of brief high-frequency spike firing. Bursts form separate response symbols but historically have not been thought to encode input. However, recent experimental evidence suggests that bursts can encode input in parallel with tonic spikes. The recognition of bursts as distinct encoding symbols raises important questions; these form the basic aims of this thesis: (1) What inputs do bursts encode? (2) Does burst structure provide extra information about different inputs. (3) Is burst coding robust against the presence of noise; an inherent property of all neural systems? (4) What mechanisms are responsible for burst input encoding? (5) How does burst coding manifest in in-vivo neurons. To answer these questions, bursting is studied using a combination of neuron models and in-vivo hippocampal neuron recordings. Models ranged from neuron-specific cell models to models belonging to three fundamentally different burst dynamic classes (unspecific to any neural region). These classes are defined using concepts from non-linear system theory. Together, analysing these model types with in-vivo recordings provides a specific and general analysis of burst encoding. For neuron-specific and unspecific models, a number of model types expressing different levels of biological realism are analysed. For the study of thalamic encoding, two models containing either a single simplified burst-generating current or multiple currents are used. For models simulating three burst dynamic classes, three further models of different biological complexity are used. The bursts generated by models and real neurons were analysed by assessing the input they encode using methods such as information theory, and reverse correlation. Modelled bursts were also analysed for their resilience to simulated neural noise. In all cases, inputs evoking bursts and tonic spikes were distinct. The structure of burst-evoking input depended on burst dynamic class rather than the biological complexity of models. Different n-spike bursts encoded different inputs that, if read by downstream cells, could discriminate complex input structure. In the thalamus, this n-spike burst code explains informative responses that were not due to tonic spikes. In-vivo hippocampal neurons and a pyramidal cell model both use the n-spike code to mark different LFP features. This n-spike burst may therefore be a general feature of bursting relevant to both model and in-vivo neurons. Bursts can also encode input corrupted by neural noise, often outperforming the encoding of single spikes. Both burst timing and internal structure are informative even when driven by strongly noise-corrupted input. Also, bursts induce input-dependent spike correlations that remain informative despite strong added noise. As a result, bursts endow their constituent spikes with extra information that would be lost if tonic spikes were considered the only informative responses.