4,629 research outputs found

    Navigation-by-music for pedestrians: an initial prototype and evaluation

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    Digital mobile music devices are phenomenally popular. The devices are becoming increasingly powerful with sophisticated interaction controls, powerful processors, vast onboard storage and network connectivity. While there are ‘obvious’ ways to exploit these advanced capabilities (such as wireless music download), here we consider a rather different application—pedestrian navigation. We report on a system (ONTRACK) that aims to guide listeners to their destinations by continuously adapting the spatial qualities of the music they are enjoying. Our field-trials indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes

    Mr. Stewart and Mr. Colbert Go to Washington: Television Satirists Outside the Box

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    The political satirists Jon Stewart and Stephen Colbert are largely celebrated for their nightly television programs, which use humor to offer useful political information, provide important forums for deliberation and debate, and serve as sites for alternative interpretations of political reality. Yet, when the two satirists more directly intervene in the field of politics—which they increasingly do—they are often met by a chorus of criticism that suggests they have improperly crossed normative boundaries. This article explores Stewart and Colbert’s “out of the box” political performances, which include, among others, the 2010 Rally to Restore Sanity, Colbert’s testimony before Congress in the same year, and his on-going efforts to run an actual Super PAC that raises and spends money to influence (and critique) the political process. Examining these and other examples of non-traditional, and clearly border-crossing political satire, we consider the ways in which such multi-modal performances--in and off the television screen--work together to provide information, critique, and commentary, as well as a significant form of moral voice and ethical imperative. In turn, we examine the responses from the political and journalistic establishment, which more often than not, constitutes a form of boundary maintenance that seeks to delegitimize such alternative modes of political engagement. Finally, we discuss the significance of the developing relationship between television entertainment and political performance for our understanding of contemporary political practice

    What is Business History? Why it is important?

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    This contribution discusses the intellectual and institutional development of the discipline of business history, whichwas created at the Harvard Business School in 1927. It explores the shifting research agenda of the subject, which has transitionedfrom looking at large capital-intensive manufacturing industries in the United States and Europe to research onbusiness groups, family business, societal and cultural impact, and Latin America and on other emerging markets. Theessay highlights the importance of business history in management education.Keywords: history, management education, Harvard, globalizatio

    A Block Minorization--Maximization Algorithm for Heteroscedastic Regression

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    The computation of the maximum likelihood (ML) estimator for heteroscedastic regression models is considered. The traditional Newton algorithms for the problem require matrix multiplications and inversions, which are bottlenecks in modern Big Data contexts. A new Big Data-appropriate minorization--maximization (MM) algorithm is considered for the computation of the ML estimator. The MM algorithm is proved to generate monotonically increasing sequences of likelihood values and to be convergent to a stationary point of the log-likelihood function. A distributed and parallel implementation of the MM algorithm is presented and the MM algorithm is shown to have differing time complexity to the Newton algorithm. Simulation studies demonstrate that the MM algorithm improves upon the computation time of the Newton algorithm in some practical scenarios where the number of observations is large

    Computational Multispectral Endoscopy

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    Minimal Access Surgery (MAS) is increasingly regarded as the de-facto approach in interventional medicine for conducting many procedures this is due to the reduced patient trauma and consequently reduced recovery times, complications and costs. However, there are many challenges in MAS that come as a result of viewing the surgical site through an endoscope and interacting with tissue remotely via tools, such as lack of haptic feedback; limited field of view; and variation in imaging hardware. As such, it is important best utilise the imaging data available to provide a clinician with rich data corresponding to the surgical site. Measuring tissue haemoglobin concentrations can give vital information, such as perfusion assessment after transplantation; visualisation of the health of blood supply to organ; and to detect ischaemia. In the area of transplant and bypass procedures measurements of the tissue tissue perfusion/total haemoglobin (THb) and oxygen saturation (SO2) are used as indicators of organ viability, these measurements are often acquired at multiple discrete points across the tissue using with a specialist probe. To acquire measurements across the whole surface of an organ one can use a specialist camera to perform multispectral imaging (MSI), which optically acquires sequential spectrally band limited images of the same scene. This data can be processed to provide maps of the THb and SO2 variation across the tissue surface which could be useful for intra operative evaluation. When capturing MSI data, a trade off often has to be made between spectral sensitivity and capture speed. The work in thesis first explores post processing blurry MSI data from long exposure imaging devices. It is of interest to be able to use these MSI data because the large number of spectral bands that can be captured, the long capture times, however, limit the potential real time uses for clinicians. Recognising the importance to clinicians of real-time data, the main body of this thesis develops methods around estimating oxy- and deoxy-haemoglobin concentrations in tissue using only monocular and stereo RGB imaging data
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