Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach
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The problem of control synthesis to maximize the probability of satisfying automata specifications for systems with uncertainty is addressed. Two types of uncertainty are considered; stochasticity in the dynamical system and in the sets defining the specif ...
With ever greater computational resources and more accessible software, deep neural networks have become ubiquitous across industry and academia.
Their remarkable ability to generalize to new samples defies the conventional view, which holds that complex, ...
Electric vehicles (EV) as an alternative to fossil fuel based cars play an important role for a more sustainable development of the transport sector. Traction batteries such as Lithium-ion Batteries (LIB) represent the vital part of this technology and cou ...
A World Resources Forum Production, PSI2017
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Simulating the most external plasma region of a tokamak, the scrape-off layer (SOL), is of crucial importance in the way towards a fusion reactor as heat load on the vessel wall, impurity generation, and overall plasma confinement, all depend on the plasma ...
2016
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Accurate models capable to predict the dynamic behavior and the State-of-Charge (SoC) of Battery Energy Storage Systems (BESSs) is a key aspect for the definition of model-based controls in electric vehicles and in power grid applications of these energy s ...
2017
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As a promising cathode inheritor for lithium-ion batteries, the sulfur cathode exhibits very high theoretical volumetric capacity and energy density. In its practical applications, one has to solve the insulating properties of sulfur and the shuttle effect ...
A family of 2D transition metal carbides and nitrides known as MXenes has received increasing attention since the discovery of Ti3C2 in 2011. To date, about 30 different MXenes with well-defined structures and properties have been synthesized, and many mor ...
2020
Humans have a remarkable way of learning, adapting and mastering new manipulation
tasks. With the current advances in Machine Learning (ML), the promise of having
robots with such capabilities seems to be on the cusp of reality. Transferring human-level
sk ...
Thanks to the digital preservation of cultural heritage materials, multimedia tools (e.g., based on automatic visual processing) considerably ease the work of scholars in the humanities and help them to perform quantitative analysis of their data. In this ...
In this work we propose an Uncertainty Quantification methodology for sedimentary basins evolution under mechanical and geochemical compaction processes, which we model as a coupled, time-dependent, non-linear, monodimensional (depth-only) system of PDEs w ...
