19,369 research outputs found

    Observer Placement for Source Localization: The Effect of Budgets and Transmission Variance

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    When an epidemic spreads in a network, a key question is where was its source, i.e., the node that started the epidemic. If we know the time at which various nodes were infected, we can attempt to use this information in order to identify the source. However, maintaining observer nodes that can provide their infection time may be costly, and we may have a budget kk on the number of observer nodes we can maintain. Moreover, some nodes are more informative than others due to their location in the network. Hence, a pertinent question arises: Which nodes should we select as observers in order to maximize the probability that we can accurately identify the source? Inspired by the simple setting in which the node-to-node delays in the transmission of the epidemic are deterministic, we develop a principled approach for addressing the problem even when transmission delays are random. We show that the optimal observer-placement differs depending on the variance of the transmission delays and propose approaches in both low- and high-variance settings. We validate our methods by comparing them against state-of-the-art observer-placements and show that, in both settings, our approach identifies the source with higher accuracy.Comment: Accepted for presentation at the 54th Annual Allerton Conference on Communication, Control, and Computin

    Sensor Deployment for Network-like Environments

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    This paper considers the problem of optimally deploying omnidirectional sensors, with potentially limited sensing radius, in a network-like environment. This model provides a compact and effective description of complex environments as well as a proper representation of road or river networks. We present a two-step procedure based on a discrete-time gradient ascent algorithm to find a local optimum for this problem. The first step performs a coarse optimization where sensors are allowed to move in the plane, to vary their sensing radius and to make use of a reduced model of the environment called collapsed network. It is made up of a finite discrete set of points, barycenters, produced by collapsing network edges. Sensors can be also clustered to reduce the complexity of this phase. The sensors' positions found in the first step are then projected on the network and used in the second finer optimization, where sensors are constrained to move only on the network. The second step can be performed on-line, in a distributed fashion, by sensors moving in the real environment, and can make use of the full network as well as of the collapsed one. The adoption of a less constrained initial optimization has the merit of reducing the negative impact of the presence of a large number of local optima. The effectiveness of the presented procedure is illustrated by a simulated deployment problem in an airport environment

    Median problems in networks

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    The P-median problem is a classical location model “par excellence”. In this paper we, first examine the early origins of the problem, formulated independently by Louis Hakimi and Charles ReVelle, two of the fathers of the burgeoning multidisciplinary field of research known today as Facility Location Theory and Modelling. We then examine some of the traditional heuristic and exact methods developed to solve the problem. In the third section we analyze the impact of the model in the field. We end the paper by proposing new lines of research related to such a classical problem.P-median, location modelling

    Analysis of antenna position measurements and weather station network data during the ALMA Long Baseline Campaign of 2015

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    In a radio interferometer, the determination of geometrical antenna positions relies on accurate calibration of the dry and wet delay of the atmosphere above each antenna. For the Atacama Large Millimeter/Submillimeter Array (ALMA), which has baseline lengths up to 16 kilometers, the geography of the site forces the height above mean sea level of the more distant antenna pads to be significantly lower than the central array. Thus, both the ground level meteorological values and the total water column can be quite different between antennas in the extended configurations. During 2015, a network of six additional weather stations was installed to monitor pressure, temperature, relative humidity and wind velocity, in order to test whether inclusion of these parameters could improve the repeatability of antenna position determinations in these configurations. We present an analysis of the data obtained during the ALMA Long Baseline Campaign of Oct. through Nov. 2015. The repeatability of antenna position measurements typically degrades as a function of antenna distance. Also, the scatter is more than three times worse in the vertical direction than in the local tangent plane, suggesting that a systematic effect is limiting the measurements. So far we have explored correcting the delay model for deviations from hydrostatic equilibrium in the measured air pressure and separating the partial pressure of water from the total pressure using water vapor radiometer (WVR) data. Correcting for these combined effects still does not provide a good match to the residual position errors in the vertical direction. One hypothesis is that the current model of water vapor may be too simple to fully remove the day-to-day variations in the wet delay. We describe possible avenues of improvement, including measuring and applying more accurate values of the sky coupling efficiency of the WVRs.Comment: 19 pages, 14 figures, 1 table; presented at SPIE Astronomical Telescopes + Instrumentation 2016, held in Edinburgh, UK on 26 June - 1 July 201

    IMPROVING QUALITY OF SERVICE IN EMS SYSTEMS BY REDUCING DISPARITIES BETWEEN SERVICE ZONES

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    Emergency medical service (EMS) systems respond to emergency or urgent calls so as to provide immediate care, such as pre-hospital care and/or transportation, to hospitals. Care must be provided in a timely manner; in fact quality of service is usually directly associated with response time. To reduce the response time, the number and location of vehicles within the service area are important variables. However with limited capacity, increasing the number of vehicles is often an infeasible alternative. Therefore, a critical design goal is to decide at which facilities stations should be located in order to serve as much demand as possible in a reasonable time, and at the same time maintain equitable service between customers. This study aims to focus on locating ambulances which respond to 911 calls in EMS systems. The goals are to find the optimal base station location for vehicles so that the number of calls or customers served is maximized while disparity between those customers is minimized, to consider the survival rate of patients directly in the model, and develop appropriate meta-heuristics for solving problems which cannot be solved optimally

    Adaptable Spatial Agent-Based Facility Location for Healthcare Coverage

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    Lack of access to healthcare is responsible for the world’s poverty, mortality and morbidity. Public healthcare facilities (HCFs) are expected to be located such that they can be reached within reasonable distances of the patients’ locations, while at the same time providing complete service coverage. However, complete service coverage is generally hampered by resource availability. Therefore, the Maximal Covering Location Problem (MCLP), seeks to locate HCFs such that as much population as possible is covered within a desired service distance. A consideration to the population not covered introduces a distance constraint that is greater than the desired service distance, beyond which no population should be. Existing approaches to the MCLP exogenously set the number of HCFs and the distance parameters, with further assumption of equal access to HCFs, infinite or equal capacity of HCFs and data availability. These models tackle the real-world system as static and do not address its intrinsic complexity that is characterised by unstable and diverse geographic, demographic and socio-economic factors that influence the spatial distribution of population and HCFs, resource management, the number of HCFs and proximity to HCFs. Static analysis incurs more expenditure in the analytical and decision-making process for every additional complexity and heterogeneity. This thesis is focused on addressing these limitations and simplifying the computationally intensive problems. A novel adaptable and flexible simulation-based meta-heuristic approach is employed to determine suitable locations for public HCFs by integrating Geographic Information Systems (GIS) with Agent-Based Models (ABM). Intelligent, adaptable and autonomous spatial and non-spatial agents are utilized to interact with each other and the geographic environment, while taking independent decisions governed by spatial rules, such as •containment, •adjacency, •proximity and •connectivity. Three concepts are introduced: assess the coverage of existing HCFs using travel-time along the road network and determine the different average values of the service distance; endogenously determine the number and suitable locations of HCFs by integrating capacity and locational suitability constraints for maximizing coverage within the prevailing service distance; endogenously determine the distance constraint as the maximum distance between the population not covered within the desired service distance and its closest facility. The models’ validations on existing algorithms produce comparable and better results. With confirmed transferability, the thesis is applied to Lagos State, Nigeria in a disaggregated analysis that reflects spatial heterogeneity, to provide improved service coverage for healthcare. The assessment of the existing health service coverage and spatial distribution reveals disparate accessibility and insufficiency of the HCFs whose locations do not factor in the spatial distribution of the population. Through the application of the simulation-based approach, a cost-effective complete health service coverage is achieved with new HCFs. The spatial pattern and autocorrelation analysis reveal the influence of population distribution and geographic phenomenon on HCF location. The relationship of selected HCFs with other spatial features indicates agents’ compliant with spatial association. This approach proves to be a better alternative in resource constrained systems. The adaptability and flexibility meet the global health coverage agenda, the desires of the decision maker and the population, in the support for public health service coverage. In addition, a general theory of the system for a better-informed decision and analytical knowledge is obtained

    Nonvolcanic tremor observed in the Mexican subduction zone

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    Nonvolcanic tremor (NVT) activity is revealed as episodes of higher spectral amplitude at 1–8 Hz in daily spectrograms from the continuous seismological records in Guerrero, Mexico. The analyzed data cover a period of 2001–2007 when in 2001–2002 a large slow slip event (SSE) had occurred in the Guerrero-Oaxaca region, and then a new large SSE occurred in 2006. The tremor burst is dominated by S-waves. More than 100 strong NVT bursts were recorded in the narrow band of ~40 × 150 km^2 to the south of Iguala City and parallel to the coastline. Depths of NVT hypocenters are mostly scattered in the continental crust between 5 and 40 km depth. Tremor activity is higher during the 2001–2002 and 2006 SSE compared with that for the “quiet” period of 2003–2005. While resistivity pattern in Guerrero does not correlate directly with the NVT distribution, gravity and magnetic anomaly modeling favors a hypothesis that the NVT is apparently related to the dehydration and serpentinization processes

    Testing for Non-Gaussianity in the Wilkinson Microwave Anisotropy Probe Data: Minkowski Functionals and the Length of the Skeleton

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    The three Minkowski functionals and the recently defined length of the skeleton are estimated for the co-added first-year Wilkinson Microwave Anisotropy Probe (WMAP) data and compared with 5000 Monte Carlo simulations, based on Gaussian fluctuations with the a-priori best-fit running-index power spectrum and WMAP-like beam and noise properties. Several power spectrum-dependent quantities, such as the number of stationary points, the total length of the skeleton, and a spectral parameter, gamma, are also estimated. While the area and length Minkowski functionals and the length of the skeleton show no evidence for departures from the Gaussian hypothesis, the northern hemisphere genus has a chi^2 that is large at the 95% level for all scales. For the particular smoothing scale of 3.40 degrees FWHM it is larger than that found in 99.5% of the simulations. In addition, the WMAP genus for negative thresholds in the northern hemisphere has an amplitude that is larger than in the simulations with a significance of more than 3 sigma. On the smallest angular scales considered, the number of extrema in the WMAP data is high at the 3 sigma level. However, this can probably be attributed to the effect of point sources. Finally, the spectral parameter gamma is high at the 99% level in the northern Galactic hemisphere, while perfectly acceptable in the southern hemisphere. The results provide strong evidence for the presence of both non-Gaussian behavior and an unexpected power asymmetry between the northern and southern hemispheres in the WMAP data.Comment: 17 pages, 10 figures, accepted for publication in Ap
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