Modern epidemiological forecasts of common illnesses, such as the flu, rely on both traditional surveillance sources as well as digital surveillance data. However, most published studies have been retrospective. Concurrently, the reports about flu activity generally lags by several weeks and even when published are revised for several weeks more. We posit that effectively handling this uncertainty is one of the key challenges for a real-time prediction system in this sphere. In this paper, we present a detailed prospective analysis on the generation of robust quantitative predictions about temporal trends of flu activity, using several surrogate data sources for 15 Latin American countries. We present our findings about the limitations and possible advantages of correcting the uncertainty associated with official flu estimates. We also compare the prediction accuracy between model-level fusion of different surrogate data sources against data-level fusion. Finally, we present a novel matrix factorization approach using neighborhood embedding to predict flu case counts. Comparing our proposed ensemble method against several baseline methods helps us demarcate the importance of different data sources for the countries under consideration.
Multi-constraint quality-of-service routing will become increasingly important as the Internet evolves to support real-time services. It is well known however, that optimum multi-constraint QoS routing is computationally complex, and for this reason various heuristics have been proposed for routing in practical situations. Among these methods, those that use a single mixed metric are the most popular. Although mixed metric routing discards potentially useful information, this is compensated for by significantly reduced complexity. Exploiting this tradeoff is becoming increasingly important where low complexity designs are desired, such as in battery operated wireless applications. In this paper, a novel single mixed metric multi-constraint routing algorithm is introduced. The proposed technique has similar complexity compared with existing low complexity methods. Simulation results are presented which show that it can obtain better performance than comparable techniques in terms of generating feasible multi-constraint QoS routes.
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