Predicting encounter and colocation events

Predicting encounter and colocation events in metropolitan areas

Despite an extensive literature has been devoted to mine and model mobility features, forecasting where, when and whom people will encounter/colocate still deserve further research efforts. Forecasting people’s encounter and colocation features is the key point for the success of many applications ranging from epidemiology to the design of new networking paradigms and services such as delay tol...

Predicting Encounter Rates for Zooplankton: A Model Assuming a Cylindrical Encounter Field

Nous delimitons un champ d9attaque cylindrique chez une larve de Chaoborus qui se nourrit de zooplancton, et nous proposons un mod2le mathematique qui pr6dit le taux de rencontre avec des proies pour ce p6dateur i l'dffit. Le modkle se base sur le processus de rencontre d'un cylindre stationnaire avec des sphkres qui se deplacent au hasard et h vitesse constante. Les prkdictions du modkle sont ...

Colocation as a Service

By colocating with other tenants of an Infrastructure as a Service (IaaS) offering, IaaS users could reap significant cost savings by judiciously sharing their use of the fixed-size instances offered by IaaS providers. This paper presents the blueprints of a Colocation as a Service (CaaS) framework. CaaS strategic services identify coalitions of selfinterested users that would benefit from colo...

Predicting Taste and Odor Events in Kansas

Obesity, risk factors, and predicting cardiovascular events.

APubMed search in March 2005 with the key word “metabolic syndrome” yielded 10 000 references. Past labels for this disorder include “syndrome X,” “deadly quartet,” and “cardiovascular dysmetabolic syndrome.”1–3 What is driving the current increased interest in the metabolic syndrome? Possibly the impetus comes from the dramatic increases in obesity in the United States and other developed coun...