7,297 research outputs found
PRESS: A Novel Framework of Trajectory Compression in Road Networks
Location data becomes more and more important. In this paper, we focus on the
trajectory data, and propose a new framework, namely PRESS (Paralleled
Road-Network-Based Trajectory Compression), to effectively compress trajectory
data under road network constraints. Different from existing work, PRESS
proposes a novel representation for trajectories to separate the spatial
representation of a trajectory from the temporal representation, and proposes a
Hybrid Spatial Compression (HSC) algorithm and error Bounded Temporal
Compression (BTC) algorithm to compress the spatial and temporal information of
trajectories respectively. PRESS also supports common spatial-temporal queries
without fully decompressing the data. Through an extensive experimental study
on real trajectory dataset, PRESS significantly outperforms existing approaches
in terms of saving storage cost of trajectory data with bounded errors.Comment: 27 pages, 17 figure
Algorithms for the Analysis of Spatio-Temporal Data from Team Sports
Modern object tracking systems are able to simultaneously record trajectories—sequences of time-stamped location points—for large numbers of objects with high frequency and accuracy. The availability of trajectory datasets has resulted in a consequent demand for algorithms and tools to extract information from these data. In this thesis, we present several contributions intended to do this, and in particular, to extract information from trajectories tracking football (soccer) players during matches. Football player trajectories have particular properties that both facilitate and present challenges for the algorithmic approaches to information extraction. The key property that we look to exploit is that the movement of the players reveals information about their objectives through cooperative and adversarial coordinated behaviour, and this, in turn, reveals the tactics and strategies employed to achieve the objectives. While the approaches presented here naturally deal with the application-specific properties of football player trajectories, they also apply to other domains where objects are tracked, for example behavioural ecology, traffic and urban planning
A passivity based control methodology for flexible joint robots with application to a simplified shuttle RMS arm
The main goal is to develop a general theory for the control of flexible robots, including flexible joint robots, flexible link robots, rigid bodies with flexible appendages, etc. As part of the validation, the theory is applied to the control law development for a test example which consists of a three-link arm modeled after the shoulder yaw joint of the space shuttle remote manipulator system (RMS). The performance of the closed loop control system is then compared with the performance of the existing RMS controller to demonstrate the effectiveness of the proposed approach. The theoretical foundation of this new approach to the control of flexible robots is presented and its efficacy is demonstrated through simulation results on the three-link test arm
A high accuracy Leray-deconvolution model of turbulence and its limiting behavior
In 1934 J. Leray proposed a regularization of the Navier-Stokes equations
whose limits were weak solutions of the NSE. Recently, a modification of the
Leray model, called the Leray-alpha model, has atracted study for turbulent
flow simulation. One common drawback of Leray type regularizations is their low
accuracy. Increasing the accuracy of a simulation based on a Leray
regularization requires cutting the averaging radius, i.e., remeshing and
resolving on finer meshes. This report analyzes a family of Leray type models
of arbitrarily high orders of accuracy for fixed averaging radius. We establish
the basic theory of the entire family including limiting behavior as the
averaging radius decreases to zero, (a simple extension of results known for
the Leray model). We also give a more technically interesting result on the
limit as the order of the models increases with fixed averaging radius. Because
of this property, increasing accuracy of the model is potentially cheaper than
decreasing the averaging radius (or meshwidth) and high order models are doubly
interesting
WKB Approximation to the Power Wall
We present a semiclassical analysis of the quantum propagator of a particle
confined on one side by a steeply, monotonically rising potential. The models
studied in detail have potentials proportional to for ; the
limit would reproduce a perfectly reflecting boundary, but at
present we concentrate on the cases and 2, for which exact
solutions in terms of well known functions are available for comparison. We
classify the classical paths in this system by their qualitative nature and
calculate the contributions of the various classes to the leading-order
semiclassical approximation: For each classical path we find the action ,
the amplitude function and the Laplacian of . (The Laplacian is of
interest because it gives an estimate of the error in the approximation and is
needed for computing higher-order approximations.) The resulting semiclassical
propagator can be used to rewrite the exact problem as a Volterra integral
equation, whose formal solution by iteration (Neumann series) is a
semiclassical, not perturbative, expansion. We thereby test, in the context of
a concrete problem, the validity of the two technical hypotheses in a previous
proof of the convergence of such a Neumann series in the more abstract setting
of an arbitrary smooth potential. Not surprisingly, we find that the hypotheses
are violated when caustics develop in the classical dynamics; this opens up the
interesting future project of extending the methods to momentum space.Comment: 30 pages, 8 figures. Minor corrections in v.
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