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This report presents challenges, opportunities, and directions for computational science and engineering (CSE) research and education for the next decade. Over the past two decades the field of CSE has penetrated both basic and applied research in academia ...
There is a growing need for unbiased clustering algorithms, ideally automated to analyze complex data sets. Topological data analysis (TDA) has been used to approach this problem. This recent field of mathematics discerns characteristic features of a space ...
WEEE is Waste Electrical and Electronic Equipment and its proper treatment is one of the challenges Europe is facing, because of economically essential materials recovery and of proper treatment of environmentally critical components they contain (CFC, PCB ...
Paul Scherrer Institute, World Resources Forum2019
The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and t ...
In 1902, a contributor to Popular Science affirmed that “The era of the amateur scientist is passing; science must now be advanced by the professional expert.” Throughout the twentieth century, amateurs have been increasingly excluded from the production o ...
Location Privacy-Preserving Mechanisms (LPPMs) in the literature largely consider that users' data available for training wholly characterizes their mobility patterns. Thus, they hardwire this information in their designs and evaluate their privacy propert ...
Deep neural networks are highly effective tools for human and animal pose estimation. However, robustness to out-of-domain data remains a challenge. Here, we probe the transfer and generalization ability for pose estimation with two architecture classes (M ...
In order to investigate hydraulic connections between the Brenta river and its groundwater aquifers, this work performs a stochastic analysis of measured groundwater temperature timeseries. The aim is to compare their trends to verify their mutual influenc ...
Speech Emotion Recognition (SER) has been shown to benefit from many of the recent advances in deep learning, including recurrent based and attention based neural network architectures as well. Nevertheless, performance still falls short of that of humans. ...
Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction ...