Combining Multiple Results of a Reverse Engineering Algorithm: Application to the DREAM Five Gene Network Challenge
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Prediction in environmental systems, such as hydrological streamflow prediction, is a challenging task. Although on a small scale, many of the physical processes are well described, accurate predictions of macroscopical (e.g. catchment scale) behavior with ...
This paper introduces a method to predict and analyse students' mathematical performance by detecting distinguishable subgroups of children who share similar learning patterns. We employ pairwise clustering to analyse a comprehensive dataset of user intera ...
The so-called rotating-stall (RS) is an undesired hydrodynamic phenomenon affecting the regular function of Francis-type pump-turbines. Stronger noise and vibration increase the risk of catastrophic failures and economic loses. In the past, such phenomenon ...
This study analyses the use of neural networks to produce accurate forecasts of total bookings and cancellations before departure, of a major European rail operator. Effective forecasting models, can improve revenue performance of transportation companies ...
The pressure drops of external flow over enhanced tube bundles were experimentally obtained at both adiabatic and diabatic conditions using R-134a and R-236fa as test fluids. The tests were carried out at saturation temperatures of 5 and 15 degrees C, mass ...
A new method to predict the void fraction in annular two-phase flow in macroscale and microscale channels is presented. The underlying experimental database contains 2673 data points collected from 29 different literature studies for 8 different gas-liquid ...
Discrete-time mobile adaptive networks have been successfully used to model self-organization in biological networks. We recently introduced a continuous-time adaptive diffusion strategy with the goal of better modeling physical phenomena governed by conti ...
Networks are central in the modeling and analysis of many large-scale human and technical systems, and they have applications in diverse fields such as computer science, biology, social sciences, and economics. Recently, network mining has been an active a ...
Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which ignores the dependencies between human joints, or model these dependencies via a ...
Mobility is a central aspect of our life; the locations we visit reflect our tastes and lifestyle and shape our social relationships. The ability to foresee the places a user will visit is therefore beneficial to numerous applications, ranging from forecas ...