Data-driven model for divertor plasma detachment prediction

Analytical Model and Data-driven Approach for Concrete Moisture Prediction

The advent of smart sensing technologies has opened up new avenues for addressing the billion dollar problem in the wastewater industry of H2S corrosion in concrete sewer pipes, where there is a growing interest in monitoring the environmental properties that govern the rate of corrosion. In this context, this paper proposes a methodology to predict the moisture content of concretes through dat...

A Data-driven Method for Crowd Simulation using a Holonification Model

In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it is. For this reason, we use simple rules for holonification. Using real-world data, we model the...

Understanding divertor detachment through CRETIN modeling — a work in progress

A Data-Driven Approach for Event Prediction

When given a single static picture, humans can not only interpret the instantaneous content captured by the image, but also they are able to infer the chain of dynamic events that are likely to happen in the near future. Similarly, when a human observes a short video, it is easy to decide if the event taking place in the video is normal or unexpected, even if the video depicts a an unfamiliar p...

Data-Driven Mortality Prediction for Trauma Patients

Trauma is the leading cause of death between the ages of 1 to 44. A large number of these deaths occur within days of the arrival of the patient at the hospital. Accurate prediction of the outcomes of trauma patients and the identification of a few key predictors would be highly valuable. In this paper we focus on (1) the prediction of mortality within any given time frame after arrival, and (2...