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"Pere Boqué, a mathematician who works as an analyst for the Catalan Police Department, set out the problem of anticipating a burglar's movements using predictive models in the same way that mathematical models for fluid dynamics allow meteorologists to predict the weather.We found the topic fascinating." Their work is inspired by age-dependent population models, which study a population's evolution in time based on the physiological ages of its individuals.
After establishing these fundamentals, Saldaña et al.
modify their initial predator-prey system to account for active police response to criminal activity.
"Our model puts the emphasis on when -- rather than where -- the burglaries will take place and on the type of victimized houses, represented by their 'age,'" Avinyó said.
A burglar's age is the amount of time since his most recent offense, while a house's age is the amount of time since it was last burglarized.
In the authors' model, a lower house vulnerability leads to a higher degree of co-offending.
The aforementioned assumptions imply a predator-prey type relationship between burglars and vulnerable homes.
Although law enforcement is making concerted efforts to address and prevent burglary, frequent offenses in major metropolises continue to unsettle city-dwellers.
Existing mathematical models typically examine burglaries in residential, suburban environments, where similarly-structured houses with predictable lattice alignments are hotspots for repeated criminal activity.
"All of these aspects are linked to the age of a burglar in our formulation.
This allows us to implement different behavioral theories and use particular information obtained directly from offenders, like the so-called 'individual offending frequency' considered in criminology." Because behavioral hypotheses related to repeat and near-repeat victimization limit a model's customizability, Saldaña et al.