1,931 research outputs found

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    Digital Government: Knowledge Management Over Time-Varying Geospatial Datasets

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    Spatially-related data is collected by many government agencies in various formats and for various uses. This project seeks to facilitate the integration of these data, thus providing new uses. This will require the development of a knowledge management framework to provide syntax, context, and semantics, as well as exploring the introduction of time-varying data into the framework. Education and outreach will be part of the project through the development of an on-line short courses related to data integration in the area of geographical information systems. The grantees will be working with government partners (National Imagery and Mapping Agency, the National Agricultural Statistics Service, and the US Army Topographic Engineering Center), as well as an industrial organization, Base Systems, and the non-profit OpenGIS Consortium, which works closely with vendors of GIS products

    Categorical structure of continuation passing style

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    Laboratory for Foundations of Computer ScienceThis thesis attempts to make precise the structure inherent in Continuation Passing Style (CPS). We emphasize that CPS translates lambda-calculus into a very basic calculus that does not have functions as primitive. We give an abstract categorical presentation of continuation semantics by taking the continuation type constructor (cont in Standard ML of New Jersey) as primitive. This constructor on types extends to a contravariant functor on terms which is adjoint to itself on the left; restricted to the subcategory of those programs that do not manipulate the current continuation, it is adjoint to itself on the right. The motivating example of such a category is built from (equivalence classes of typing judgements for) continuation passing style (CPS) terms. The categorical approach suggests a notion of effect-free term as well as some operators for manipulating continuations. We use these for writing programs that illustrate our categorical approach and refute some conjectures about control effects. A call-by-value lambda-calculus with the control operator callcc can be interpreted. Arrow types are broken down into continuation types for argument/result-continuations pairs, reflecting the fact that CPS compiles functions into a special case of continuations. Variant translations are possible, among them lazy call-by-name, which can be derived by way of argument thunking, and a genuinely call-by-name transform. Specialising the semantics to the CPS term model allows a rational reconstruction of various CPS transforms

    Drawing off the page: How new 3D technologies provide insight into cognitive and pedagogical assumptions about mathematics

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    Mathematics has a history of being a two-dimensional inscribing practice. We describe the potential evolution in doing, thinking, and learning mathematics with the emergence of a technological innovation that enables real-time 3D virtual and material interactions. Using the 3D drawing pen as a simple and recently available technology, we highlight how it helps re-think long-standing assumptions and dichotomies in mathematics education including, for example, the material distinction between diagram and manipulative, the semiotic distinction between icon and index, and the developmental progression of action-icon-symbol. We then speculate on the future possibilities of the shift in technological infrastructure that 3D pens and similar technology may give rise to

    Model-Based Environmental Visual Perception for Humanoid Robots

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    The visual perception of a robot should answer two fundamental questions: What? and Where? In order to properly and efficiently reply to these questions, it is essential to establish a bidirectional coupling between the external stimuli and the internal representations. This coupling links the physical world with the inner abstraction models by sensor transformation, recognition, matching and optimization algorithms. The objective of this PhD is to establish this sensor-model coupling

    SNIF TOOL - Sniffing for Patterns in Continuous Streams

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    Recent technological advances in sensor networks and mobile devices give rise to new challenges in processing of live streams. In particular, time-series sequence matching, namely, the similarity matching of live streams against a set of predefined pattern sequence queries, is an important technology for a broad range of domains that include monitoring the spread of hazardous waste and administering network traffic. In this thesis, I use the time critical application of monitoring of fire growth in an intelligent building as my motivating example. Various measures and algorithms have been established in the current literature for similarity of static time-series data. Matching continuous data poses the following new challenges: 1) fluctuations in stream characteristics, 2) real-time requirements of the application, 3) limited system resources, and, 4) noisy data. Thus the matching techniques proposed for static time-series are mostly not applicable for live stream matching. In this thesis, I propose a new generic framework, henceforth referred to as the n-Snippet Indices Framework (in short, SNIF), for discovering the similarity between a live stream and pattern sequences. The framework is composed of two key phases: (1.) Off-line preprocessing phase: where the pattern sequences are processed offline and stored into an approximate 2-level index structure; and (2.) On-line live stream matching phase: streaming time-series (or the live stream) is on-the-fly matched against the indexed pattern sequences. I introduce the concept of n-Snippets for numeric data as the unit for matching. The insight is to match small snippets of the live stream against prefixes of the patterns and maintain them in succession. Longer the pattern prefixes identified to be similar to the live stream, better the confirmation of the match. Thus, the live stream matching is performed in two levels of matching: bag matching for matching snippets and order checking for maintaining the lengths of the match. I propose four variations of matching algorithms that allow the user the capability to choose between the two conflicting characteristics of result accuracy versus response time. The effectiveness of SNIF to detect patterns has been thoroughly tested through extensive experimental evaluations using the continuous query engine CAPE as platform. The evaluations made use of real datasets from multiple domains, including fire monitoring, chlorine monitoring and sensor networks. Moreover, SNIF is demonstrated to be tolerant to noisy datasets

    The Powers of Monodromy

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    Flux couplings to string theory axions yield super-Planckian field ranges along which the axion potential energy grows. At the same time, other aspects of the physics remain essentially unchanged along these large displacements, respecting a discrete shift symmetry with a sub-Planckian period. After a general overview of this monodromy effect and its application to large-field inflation, we present new classes of specific models of monodromy inflation, with monomial potentials μ4−pϕp\mu^{4-p}\phi^p. A key simplification in these models is that the inflaton potential energy plays a leading role in moduli stabilization during inflation. The resulting inflaton-dependent shifts in the moduli fields lead to an effective flattening of the inflaton potential, i.e. a reduction of the exponent from a fiducial value p0p_0 to p<p0p<p_0. We focus on examples arising in compactifications of type IIB string theory on products of tori or Riemann surfaces, where the inflaton descends from the NS-NS two-form potential B2B_2, with monodromy induced by a coupling to the R-R field strength F1F_1. In this setting we exhibit models with p=2/3,4/3,2,p=2/3,4/3,2, and 33, corresponding to predictions for the tensor-to-scalar ratio of r≈0.04,0.09,0.13,r\approx 0.04, 0.09, 0.13, and 0.20.2, respectively. Using mirror symmetry, we also motivate a second class of examples with the role of the axions played by the real parts of complex structure moduli, with fluxes inducing monodromy.Comment: 36 pages; v2: fixed typos, added reference
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