A5027616764- Probabilistic and Robust Engineering Design
- Model Reduction and Neural Networks
- Statistical Methods and Inference
- Distributed and Parallel Computing Systems
- Parallel Computing and Optimization Techniques
- Numerical methods in inverse problems
- Context-Aware Activity Recognition Systems
- Structural Health Monitoring Techniques
- Nuclear reactor physics and engineering
- Technology Use by Older Adults
- Ultrasonics and Acoustic Wave Propagation
- Statistical Distribution Estimation and Applications
- Frailty in Older Adults
- Advanced Data Storage Technologies
- Interconnection Networks and Systems
Università della Svizzera italiana
2021-2024
This paper describes CAREUP, a novel older adult healthy aging support platform based on Intrinsic Capacity (IC) monitoring. Besides standard functionalities like storing health measurement data or providing users with personalized recommendations, the includes intrinsic capacity assessment and prediction algorithms. Older adults’ performance is continuously monitored in all five IC domains—locomotion, psychology, cognition, vitality, sensory capacity—based results answers to questionnaires...
We present a novel approach aimed at high-performance uncertainty quantification for time-dependent problems governed by partial differential equations. In particular, we consider input uncertainties described Karhunen-Loève expansion and compute statistics of high-dimensional quantities-of-interest, such as the cardiac activation potential. Our methodology relies on close integration multilevel Monte Carlo methods, parallel iterative solvers, space-time discretization. This combination...
We present a novel approach which aims at high-performance uncertainty quantification for cardiac electrophysiology simulations. Employing the monodomain equation to model transmembrane potential inside cells, we evaluate effect of spatially correlated perturbations heart fibers on statistics resulting quantities interest. Our methodology relies close integration multilevel quadrature methods, parallel iterative solvers, and space-time finite element discretizations, allowing fully...
We present a novel approach aimed at high-performance uncertainty quantification for time-dependent problems governed by partial differential equations. In particular, we consider input uncertainties described Karhunen-Loeeve expansion and compute statistics of high-dimensional quantities-of-interest, such as the cardiac activation potential. Our methodology relies on close integration multilevel Monte Carlo methods, parallel iterative solvers, space-time discretization. This combination...
Sorting is a fundamental task in computing and plays central role information technology. The advent of rack-scale warehouse-size data processing shaped the architecture analysis platforms towards supercomputing. In turn, established techniques on supercomputers have become relevant to wider range application domains. This work concerned with multi-way mergesort exact splitting distributed memory architectures. At its core, our approach leverages novel parallel algorithm for selection...