Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Messier, Geoffrey"'
Autor:
Taib, Musa, Messier, Geoffrey G.
Machine learning models benefit when allowed to learn from temporal trends in time-stamped administrative data. These trends can be represented by dividing a model's observation window into time segments or bins. Model training time and performance c
Externí odkaz:
http://arxiv.org/abs/2401.16537
On any night in Canada, at least 35,000 individuals experience homelessness. These individuals use emergency shelters to transition out of homelessness and into permanent housing. We designed and deployed a technology to support front-line staff at t
Externí odkaz:
http://arxiv.org/abs/2310.13795
Autor:
Messier, Geoffrey G.
This paper investigates how COVID-19 disrupted emergency housing shelter access patterns in Calgary, Canada and what aspects of these changes persist to the present day. This analysis will utilize aggregated shelter access data for over 40,000 indivi
Externí odkaz:
http://arxiv.org/abs/2308.08028
Background: Mental illness can lead to adverse outcomes such as homelessness and police interaction and understanding of the events leading up to these adverse outcomes is important. Predictive models may help identify individuals at risk of such adv
Externí odkaz:
http://arxiv.org/abs/2307.11211
Autor:
Messier, Geoffrey G.
The Simplified Access Metric (SAM) is a new approach for characterizing emergency shelter access patterns as a measure of shelter client vulnerability. The goal of SAM is to provide shelter operators with an intuitive way to understand access pattern
Externí odkaz:
http://arxiv.org/abs/2210.13619
Autor:
John, Caleb, Messier, Geoffrey G.
This paper uses rule search techniques for the early identification of emergency homeless shelter clients who are at risk of becoming long term or chronic shelter users. Using a data set from a major North American shelter containing 12 years of serv
Externí odkaz:
http://arxiv.org/abs/2205.09883
This paper investigates how to best compare algorithms for predicting chronic homelessness for the purpose of identifying good candidates for housing programs. Predictive methods can rapidly refer potentially chronic shelter users to housing but also
Externí odkaz:
http://arxiv.org/abs/2105.15080
This paper explores how to best identify clients for housing services based on their homeless shelter access patterns. We focus on counting the number of shelter stays and episodes of shelter use for a client within a time window. Thresholds are then
Externí odkaz:
http://arxiv.org/abs/2105.01042
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Autor:
Gaafar, Mohamed, Messier, Geoffrey G
This paper presents the results of the first multi- antenna propagation measurement campaign to be conducted at an operating petroleum refining facility. The measurement equipment transmits pseudo-random noise test signals from two antennas at a 2.47
Externí odkaz:
http://arxiv.org/abs/1611.00289