4,446 research outputs found

    Deep-Inelastic Final States in a Space-Time Description of Shower Development and Hadronization

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    We extend a quantum kinetic approach to the description of hadronic showers in space, time and momentum space to deep-inelastic epep collisions, with particular reference to experiments at HERA. We follow the history of hard scattering events back to the initial hadronic state and forward to the formation of colour-singlet pre-hadronic clusters and their decays into hadrons. The time evolution of the space-like initial-state shower and the time-like secondary partons are treated similarly, and cluster formation is treated using a spatial criterion motivated by confinement and a non-perturbative model for hadronization. We calculate the time evolution of particle distributions in rapidity, transverse and longitudinal space. We also compare the transverse hadronic energy flow and the distribution of observed hadronic masses with experimental data from HERA, and find encouraging results. The techniques developed in this paper may be applied in the future to more complicated processes such as eA, pp, pA and AA collisions.Comment: 44 pages plus 14 postscript figure

    Space-Time Diffusion Visualization using Bayesian Inference

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    Retail marketing geography has traditionally employed static gravity models for location analytics based on probabilistic locational consumer demand. However, such retail trade area models provide little insight into the dynamic space-time hierarchical diffusionary processes that aggregate to an eventual market structure equilibrium (Mason et. al., 1994), which gravity models attempt to predict for retail trade areas. In addition, most attempts to display the aggregating dynamic space-time hierarchical diffusionary processes of space, time and attributes of interest, in a geographical information system (GIS), produce visualizations that are overly complex and typically displayed utilizing unfamiliar paradigms. Further, these attempts fail to take into account the extensive body of literature in psychology and brain science that stress the importance of perceptual elements and design in achieving optimum visualization comprehension. In other words, simplicity (three-way factor analysis) and visual familiarity (cognitive fit theory (Vessey, 2006), mere-exposure effect in psychology (Dajonc, 1968). This will provide faster perception and better visuospatial and temporal understanding of objects and trends. In this study we incorporate these elements in our visualization object that we refer to as “Avatar”. A Huff inspired, Bayesian framework of inference for spatial allocation and hypothesis testing allows the Avatar object to display the spatial allocation of the Bass model’s innovators and imitators for sales forecasts of new product diffusion (e.g. a mathematical version of Everett Roger’s adoption concept), thus enabling and supporting faster and improved visuospatial understanding of very large data repositories of unbounded and/or “countably infinite” sized geo-big-data (referred to throughout the rest of this paper as GBD). We then introduce the three steps necessary to create an Avatar object (i.e. a 3-D semaphoric, space-time diffusion visualization object). The Avatar object is designed specifically to visualize determinant attributes (e.g. demographics) for the Bass, Bayes, Berry and Huff integrated ensemble model forming part of an ancillary paper to this study. In this way we display the timed hierarchical diffusion of new innovative products throughout store trade areas and across the ensuing and evolving store networks. In addition, by calculating Bayesian conjugate priors and posterior spatial allocation probabilities for the “smallest units of human settlement” (Christaller, 1966) or in our case statistical demographic units (i.e. Census Blocks), we establish customer (innovator and imitator) spatial distributions for the Bass temporal-only model for the case of the aggregating store level trade area (SLTA) scenario. Our approach is empirically supported by five years of new product diffusion geocoded panel data from the Southern California market. We conclude that our cognitive fit theory validated Avatar space-time diffusion visualization strengthens “location analytics” and “location intelligence” and provides a simple and familiar tool for displaying GBD across a growing domain of varying applications and end-user knowledge and needs

    Kinematic interpolation of movement data

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    Mobile tracking technologies are facilitating the collection of increasingly large and detailed data sets on object movement. Movement data are collected by recording an object’s location at discrete time intervals. Often, of interest is to estimate the unknown position of the object at unrecorded time points to increase the temporal resolution of the data, to correct erroneous or missing data points, or to match the recorded times between multiple data sets. Estimating an object’s unknown location between known locations is termed path interpolation. This paper introduces a new method for path interpolation termed kinematic interpolation. Kinematic interpolation incorporates object kinematics (i.e. velocity and acceleration) into the interpolation process. Six empirical data sets (two types of correlated random walks, caribou, cyclist, hurricane and athlete tracking data) are used to compare kinematic interpolation to other interpolation algorithms. Results showed kinematic interpolation to be a suitable interpolation method with fast-moving objects (e.g. the cyclist, hurricane and athlete tracking data), while other algorithms performed best with the correlated random walk and caribou data. Several issues associated with path interpolation tasks are discussed along with potential applications where kinematic interpolation can be useful. Finally, code for performing path interpolation is provided (for each method compared within) using the statistical software R.PostprintPeer reviewe

    Does Time Smoothen Space? Implications for Space-Time Representation

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    The continuous nature of space and time is a fundamental tenet of many scientific endeavors. That digital representation imposes granularity is well recognized, but whether it is possible to address space completely remains unanswered. This paper argues Hales' proof of Kepler's conjecture on the packing of hard spheres suggests the answer to be "no", providing examples of why this matters in GIS generally and considering implications for spatio-temporal GIS in particular. It seeks to resolve the dichotomy between continuous and granular space by showing how a continuous space may be emergent over a random graph. However, the projection of this latent space into 3D/4D imposes granularity. Perhaps surprisingly, representing space and time as locally conjugate may be key to addressing a "smooth" spatial continuum. This insight leads to the suggestion of Face Centered Cubic Packing as a space-time topology but also raises further questions for spatio-temporal representation

    Multiversality

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    Valid ideas that physical reality is vastly larger than human perception of it, and that the perceived part may not be representative of the whole, exist on many levels and have a long history. After a brief general inventory of those ideas and their implications, I consider the cosmological "multiverse" much discussed in recent scientific literature. I review its theoretical and (broadly) empirical motivations, and its disruptive implications for the traditional program of fundamental physics. I discuss the inflationary axion cosmology, which provides an example where firmly rooted, plausible ideas from microphysics lead to a well-characterized "mini-multiverse" scenario, with testable phenomenological consequences.Comment: 23 pages. Solicited review for Classical and Quantum Gravit

    Planning of PEVs Parking Lots in Conjunction With Renewable Energy Resources and Battery Energy Storage Systems

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    The last few decades have seen growing concerns about climate change caused by global warming, which is cause primarily by CO2 emissions. Thus, the reduction of these emissions has become critically important. One of the effective methods for achieving this goal is to shift towards green electricity energy resources and green vehicles in transportation. For these reasons, the goal of the work presented in this thesis was to address the challenges associated with the planning of plug-in electric vehicles (PEVs) parking lots in combination with renewable energy sources (RES) and battery energy storage systems (BESS) in power distribution networks. This thesis introduces a new planning technique that aims to minimize the overall capital and operational costs, taking into consideration the operational aspects of distribution networks, such as 1) coordinated PEV charging, 2) smart inverter control of renewable distributed generation (DG) units, and 3) smart scheduling of BESS. Moreover, a new model for the PEV coordinated charging demand is introduced in this work. Due to the complexity of the proposed planning approach, a combination between metaheuristic technique and deterministic optimization techniques have been utilized to manage both the planning and operational aspects respectively

    Climate Change and Sea Level Rise Projections for Boston

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    While the broad outlines of how climate change would impact Boston have been known for some time, it is only recently that we have developed a more definitive understanding of what lies ahead. That understanding was advanced considerably with the publication of Climate Change and Sea Level Rise Projections for Boston by the Boston Research Advisory Group (BRAG).The BRAG report is the first major product of "Climate Ready Boston," a project led by the City of Boston in partnership with the Green Ribbon Commission and funded in part by the Barr Foundation. The BRAG team includes 20 leading experts from the region's major universities on subjects ranging from sea level rise to temperature extremes. University of Massachusetts Boston professors Ellen Douglas and Paul Kirshen headed the research.The BRAG report validates earlier studies, concluding Boston will get hotter, wetter, and saltier in the decades ahead (see figures below). But the group has produced a much more definitive set of projections than existed previously, especially for the problem of sea level rise. BRAG also concluded that some of the effects of climate change will come sooner than expected, accelerating the urgency of planning and action
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