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Past
Porjects
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Support Opportunities
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Awards
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Current
Projects / Past Projects
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Roundtables
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 CURA
Research Projects
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Publications
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NIMPRO Decision
Support for Infrastructure Management
Our
increasing reliance on networks of all types, coupled
with their increasing vulnerability to disruption,
makes it critical to better understand risks associated
with natural disasters, terrorist attacks, and other
incidents. However, choosing how to best protect,
reinforce, and improve a network given a limited
budget is a complex problem. We have developed an
integrated approach that examines the effects of
different network disruption scenarios for a variety
of performance measures. The developed decision
support methodology allows for comprehensive exploration
of disruption impacts, statistically and visually,
and facilitates examination of “what-if”planning
scenarios.
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Presentations
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Current
Projects
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Survey Research
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Urban
Disciplines
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GeoComputational
Approaches to Coverage Maximization in Service Facility
Siting
The
focus of the project is on sitingfacilities in continuous
space to maximally serve (cover) continuously distributed
demand. Most existing approaches use discrete representations
of space, but this can bias modeling results. We
relax the assumptions of discrete space and seek
to maximize coverage of continuously distributed
demand while sitingfacilities in continuous space.
We propose a geocomputationalapproach based on geometric
properties of a region for solving this problem.
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ITR
- Multi-level, Active Attention Surveillance
As
a part of automated surveillance systems, this project
focuses on developing optimization models satisfying
various surveillance concerns, such as coverage
maximization, overlapping coverage, or multi-types
sensor placement and developing solution approaches
for these location models. The project also examines
spatial representation issues in sitingsurveillance
sensors and evaluates how developed sensor location
models are sensitive to spatial representation.
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Maximal
Coverage Optimization for Regional Demand
Emergency
warning sirens are important to alert the public
of animpending danger. To efficiently utilize investment
for such service facilities, this project examined
and developed different model approaches. Instead
of representing the demand region as discrete points
of no dimension, we investigated the coverage with
respect to objects, including points, lines, and
polygons. Based on the demand object representation,
a general maximal coverage model PMP-MC (p-median
problem-multi-facility coverage) is developed and
applied to warning siren coverage evaluation in
Dublin, Ohio. The application results demonstrate
that representation issues are addressed using the
PMP-MC and efficiency can be achieved.
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GIS
Based Exploratory Spatial Analytical Methods for
Analyses of Paired Location Events
It
is often difficult to detect local or global patterns
of change in migration, home ownership, crime or
information exchange because of the complexity of
underlying processes. In this project, a GIS based
exploratory spatial data analysis approach is developed
to examine changes in home ownership. Specifically,
we propose a new visualization technique to summarize
local and global patterns.
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Maximal Covering for Survivable Network Design in Providing Citywide Wireless Broadband
Many local governments are now looking to municipal wireless broadband networks because of cheaper installation costs and easier deployment, instead of cable or fiber optic networks. For municipal wireless broadband networks, ubiquitous and reliable provision of services is an important consideration. However, it is often difficult to provide large covering and reliable broadband services simultaneously because of the tradeoff between those conflicting objectives. To deal with those considerations simultaneously, we introduce the maximum covering for survivable network design (MCSND) in providing citywide wireless broadband based on Wi-Fi mesh network topology. Specifically, we develop the integer linear formulation of the MCSND and solve the problem by the exact method (branch and bound) for a small problem.
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Path
Reduction for Network Interdiction Model
Identify
vulnerability in network infrastructure is necessary
in planning for enhanced network security. Network
infrastructure models are one approach for identifying
such vulnerabilities. Many modeling approaches are
often premised an identifying all paths of movement
between network origins to destinations. However
given the complexities associated to the real world
networks, identifying all possible O-D paths is
not generally possible. Thus, we propose a new model
formation which can reduce the number of paths of
the network and hence, the complexity associated
with searching for network vulnerabilities.
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Evaluating
Radar Systems: Backup Coverage and Spatial Representation
Weather
radar is a vital tool in forecasting and disseminating
warnings to people at risk of impending inclement
weather. The National Weather Service (NWS) has
been investigating the implementation of phased
array radar technology to improve the performance
of weather radar. With costs in the millions of
dollars, it behooves planners to assess facility
placement in a manner the maximizes coverage of
the population, establishes survivability (or redundance)
of coverage, and minimizes costs.
In this effort
we have built upon the Backup Coverage Location
Problem (Hogan and Revelle, 1986) to account for
complementary partial coverage of an area by multiple
radar. Our results show that implementation of this
model assesses coverage in a more realistic manner,
and suggests radar facility locations which provide
coverage and backup coverage to a greater population
than both other model formulation results and the
current NWS radar locations.
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Connectivity
Change in Habitat Networks
Habitat management is essential for safeguarding important flora and fauna. Further, habitat connectivity is a crucial component for maintaining biodiversity given that it is known to have implications for species persistence. However, damage to habitat due to natural and human induced hazards can alter spatial relationships between habitats, potentially impacting biodiversity. Therefore, the susceptibility of spatial relationships to patch loss and associated connectivity degradation is obviously an important factor in maintaining existing or planned biodiversity networks. Identifying patches vital to connectivity is critical both for effectively prioritizing protection (e.g., enhancing habitat connectivity) and establishing disaster mitigation measures (e.g., stemming the spread of habitat loss). This focus of this project is on developing methodologies for characterizing connectivity change associated with habitat systems. The ultimate goal of this research is to better understand how habitat connectivity can be impacted by site loss, to better inform biodiversity management planning. In particular, work has involved the development of new measurements of landscape connectivity as well as approaches for assessing the distributional aspects of connectivity given the loss of habitat sites.
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