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DTSTART;TZID=America/Los_Angeles:20230131T121500
DTEND;TZID=America/Los_Angeles:20230131T131000
DTSTAMP:20260426T191214
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UID:3021-1675167300-1675170600@colleges.claremont.edu
SUMMARY:Biquandle arrow weights (Sam Nelson\, CMC)
DESCRIPTION:Many knot invariants are defined from features of knot projections such as arcs or crossings. Gauss diagrams provide an alternative combinatorial scheme for representing knots. In this talk we will use Gauss diagrams to enhance the biquandle counting invariant for classical and virual knots using biquandle arrow weights\, a new algebraic structure without a clear geometric interpretation. This is joint work with Migiwa Sakurai (Shibaura Institute of Technology\, Tokyo).
URL:https://colleges.claremont.edu/ccms/event/antc-talk-sam-nelson-cmc-3/
LOCATION:Davidson Lecture Hall\, CMC\, 340 E 9th St\, Claremont\, CA\, 91711\, United States
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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DTSTART;TZID=America/Los_Angeles:20230201T161500
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SUMMARY:Building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City (Prof. Joan Ponce\, Arizona State University)
DESCRIPTION:Title: Building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City\n\n\n\nSpeaker: Joan Ponce\, Department of Mathematics\, Arizona State University\n\nAbstract: Epidemiological models can provide the dynamic evolution of a pandemic but they are based on many assumptions and parameters that have to be adjusted over the time the pandemic lasts. However\, often the available data are not sufficient to identify the model parameters and hence infer the unobserved dynamics. We develop a general framework for building a trustworthy data-driven epidemiological model\, consisting of a workflow that integrates data acquisition and event timeline\, model development\, identifiability analysis\, sensitivity analysis\, model calibration\, model robustness analysis\, and projection with uncertainties in different scenarios.  In particular\, we apply this framework to propose a modified susceptible–exposed–infectious–recovered (SEIR) model\, including new compartments and model vaccination in order to project the transmission dynamics of COVID-19 in New York City (NYC). We find that we can uniquely estimate the model parameters and accurately project the daily new infection cases\, hospitalizations\, and deaths\, in agreement with the available data from NYC’s government’s website. In addition\, we employ the calibrated data-driven model to study the effects of vaccination and timing of reopening indoor dining in NYC.
URL:https://colleges.claremont.edu/ccms/event/prof-joan-ponce/
LOCATION:Argue Auditorium\, Pomona College\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Colloquium
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DTSTART;TZID=America/Los_Angeles:20230204T100000
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CREATED:20230123T180832Z
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UID:3050-1675504800-1675512000@colleges.claremont.edu
SUMMARY:GEMS February 4th Session
DESCRIPTION:
URL:https://colleges.claremont.edu/ccms/event/gems-february-4th-session/
LOCATION:Harvey Mudd College at the Shanahan Teaching and Learning Center\, 301 Platt Blvd.\, Claremont\, CA\, 91711\, United States
CATEGORIES:GEMS
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