Searched for: subject%3A%22machine%255C%252Blearning%22
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Brosinsky, Christoph (author), Karaçelebi, M. (author), Cremer, Jochen (author)
The reader of the chapter will be able to connect techniques from machine learning (ML) and digital twins (DTs) to gain insights for monitoring and control of (dynamic) security for electrical power systems. DTs are validated and verified high-fidelity (hf) models providing high simulation accuracy. DTs can be used for simulation of the...
book chapter 2023
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Pacheco-López, Adrián (author), Prifti, Kristiano (author), Manenti, Flavio (author), Somoza Tornos, A. (author), Graells, Moisès (author), Espuña, Antonio (author)
The constant development of new alternatives to treat waste aids in closing material loops towards the circular economy and improving sustainability through the use of new renewable materials and energy. This fact leads to the increasing need for decision-making tools for process synthesis and assessment, which can be addressed with an...
book chapter 2023
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Nadeem, A. (author), Verwer, S.E. (author), Yang, Shanchieh Jay (author)
The evolving nature of the tactics, techniques, and procedures used by cyber adversaries have made signature and template based methods of modeling adversary behavior almost infeasible. We are moving into an era of data-driven autonomous cyber defense agents that learn contextually meaningful adversary behaviors from observables. In this chapter...
book chapter 2023
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Coraddu, A. (author), Kalikatzarakis, Miltiadis (author), Walker, J.M. (author), Ilardi, Davide (author), Oneto, Luca (author)
The purpose of this chapter is to provide an overview of the state-of-the-art and future perspectives of Data Science and Advanced Analytics for Shipping Energy Systems. Specifically, we will start by listing the different static and dynamic data sources and knowledge base available in this particular context. Then we will review the Data...
book chapter 2022
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Averta, Giuseppe (author), Arapi, Visar (author), Bicchi, Antonio (author), Della Santina, C. (author), Bianchi, Matteo (author)
The need for users’ safety and technology acceptability has incredibly increased with the deployment of co-bots physically interacting with humans in industrial settings, and for people assistance. A well-studied approach to meet these requirements is to ensure human-like robot motions and interactions. In this manuscript, we present a...
book chapter 2021
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Liem, C.C.S. (author), Langer, Markus (author), Demetriou, A.M. (author), Hiemstra, Annemarie M.F. (author), Achmadnoer Sukma Wicaksana, Sukma (author), Born, Marise Ph. (author), König, Cornelis J. (author)
In a rapidly digitizing world, machine learning algorithms are increasingly employed in scenarios that directly impact humans. This also is seen in job candidate screening. Data-driven candidate assessment is gaining interest, due to high scalability and more systematic assessment mechanisms. However, it will only be truly accepted and trusted...
book chapter 2018
Searched for: subject%3A%22machine%255C%252Blearning%22
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