Geometric Cover with Outliers Removal

We study the problem of partial geometric cover, which asks to find the minimum number of geometric objects (unit squares and unit disks in this work) that cover at least (n-t) of n given planar points, where 0 ? t ? n/2. When t = 0, the problem is the classical geometric cover problem, for which many existing works adopt a general framework called the shifting strategy. The shifting strategy is a divide and conquer paradigm which partitions the plane into equal-width strips, applies a local algorithm on each strip and then merges the local solutions with only a small loss on the overall approximation ratio. A challenge to extend the shifting strategy to the case of outliers is to determine the number of outliers in each strip. We develop a shifting strategy incorporating the outlier distribution, which runs in O(tn log n) time. We also develop local algorithms on strips for the outliers case, improving the running time over previous algorithms, and consequently obtain approximation algorithms to the partial geometric cover

A Faster 4-Approximation Algorithm for the Unit Disk Cover Problem

Abstract Given a set P of n points in the plane, we consider the problem of covering P with a minimum number of unit disks. This problem is known to be NP-hard. We present a simple 4-approximation algorithm for this problem which runs in O(n log n)-time and uses the plane-sweep technique. Previous algorithms that achieve the same approximation ratio have a higher time complexity. We also show how to extend this algorithm to other metrics, and to three dimensions

Spatio-Temporal Reasoning About Agent Behavior

There are many applications where we wish to reason about spatio-temporal aspects of an agent's behavior. This dissertation examines several facets of this type of reasoning. First, given a model of past agent behavior, we wish to reason about the probability that an agent takes a given action at a certain time. Previous work combining temporal and probabilistic reasoning has made either independence or Markov assumptions. This work introduces Annotated Probabilistic Temporal (APT) logic which makes neither assumption. Statements in APT logic consist of rules of the form "Formula G becomes true with a probability [L,U] within T time units after formula F becomes true'' and can be written by experts or extracted automatically. We explore the problem of entailment - finding the probability that an agent performs a given action at a certain time based on such a model. We study this problem's complexity and develop a sound, but incomplete fixpoint operator as a heuristic - implementing it and testing it on automatically generated models from several datasets. Second, agent behavior often results in "observations'' at geospatial locations that imply the existence of other, unobserved, locations we wish to find ("partners"). In this dissertation, we formalize this notion with "geospatial abduction problems" (GAPs). GAPs try to infer a set of partner locations for a set of observations and a model representing the relationship between observations and partners for a given agent. This dissertation presents exact and approximate algorithms for solving GAPs as well as an implemented software package for addressing these problems called SCARE (the Spatio-Cultural Abductive Reasoning Engine). We tested SCARE on counter-insurgency data from Iraq and obtained good results. We then provide an adversarial extension to GAPs as follows: given a fixed set of observations, if an adversary has probabilistic knowledge of how an agent were to find a corresponding set of partners, he would place the partners in locations that minimize the expected number of partners found by the agent. We examine this problem, along with its complement by studying their computational complexity, developing algorithms, and implementing approximation schemes. We also introduce a class of problems called geospatial optimization problems (GOPs). Here the agent has a set of actions that modify attributes of a geospatial region and he wishes to select a limited number of such actions (with respect to some budget and other constraints) in a manner that maximizes a benefit function. We study the complexity of this problem and develop exact methods. We then develop an approximation algorithm with a guarantee. For some real-world applications, such as epidemiology, there is an underlying diffusion process that also affects geospatial proprieties. We address this with social network optimization problems (SNOPs) where given a weighted, labeled, directed graph we seek to find a set of vertices, that if given some initial property, optimize an aggregate study with respect to such diffusion. We develop and implement a heuristic that obtains a guarantee for a large class of such problems

The effect of wind turbulence on noise barrier performance

An investigation has been carried out into the effect of wind turbulence on the propagation of sound over open grassland both with, and without, a 2.4m high barrier present. Sound bursts, derived from a variety of original signals, were generated using a horn loudspeaker and the resulting levels were measured using two variably positioned microphones, the further of which was placed at distances of up to 24m from the source. Simultaneous measurements were made of a variety of meteorological parameters. A microcomputer-based system was developed to control the experiments-and store the measured data for subsequent retrieval and analysis. As one of the approaches adopted in a search for visible evidence of correlation between various acoustical and meteorological parameters, the measured level difference for each sound burst was displayed graphically against the corresponding value of a particular measure of wind turbulence. For many combinations of measurement geometry and acoustic signal type, the data points fell, with a noticeable degree of consistency, within an envelope of characteristic shape. The shape implied that when the instant of transmission of a sound burst coincided with a low value of the measure of local turbulence, the apparent level difference was subject to considerable statistical fluctuation. This was the case both with and without the barrier present. As the turbulence increased, however, the propagating medium appeared to behave as a progressively more uniform and stable one and the observed scatter correspondingly reduced. The origin of this behaviour remains unclear; however the presence of the barrier, it was concluded, did not appear to modify this effect. 1 to 16 laboratory scale model experiments have been carried out to investigate the replication of the above effects and the results are reported