2 Contributo in Volume

2 Contributo in Volume: [17533] Home page macrotipologia

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2.1 Contributo in volume (Capitolo o Saggio) 16479
2.2 Prefazione/Postfazione 224
2.3 Breve introduzione 129
2.4 Voce (in dizionario o enciclopedia) 383
2.5 Traduzione in volume 31
2.6 Recensione in volume 10
2.7 Schede di catalogo,repertorio o corpus 277

Prodotti recenti

Renewable Energy Sources and Ecosystem Services: Measuring the Impacts of Ground-Mounted Photovoltaic Panels

Europe is facing complex challenges related to rising natural gas prices and the need for energy independence due to the energy crisis of 2022. To address these challenges, the European Commission presented the REPowerEU plan, which aims to accelerate the deployment of renewable energy sources (RESs), achieve greater energy autonomy, accelerate the green transition, and facilitate investments in renewable energies by 2027. Among the different RESs, the potential of ground-mounted photovoltaic...

Prefazione

Il volume presenta gli esiti di una sperimentazione didattica che ha avuto l’obiettivo di sviluppare modelli tridimensionali di nodi tecnologici a partire dall’esplorazione di materiali e prodotti a “costo zero”. Si tratta di una selezione dei lavori realizzati dagli studenti del primo anno del corso di laurea in Architettura del Politecnico di Torino, nell’ambito del corso Cultura e Fondamenti di Tecnologia dell’Architettura, negli anni accademici 2019/20, 2020/21, 2021/22. L’esperienza dei...

The digitalization of physical reality: Theoretical lenses to incorporate digitalization into management research

The management literature has recently witnessed a considerable escalation of research around the implications of digitalization for firms and their environment. Yet, the conceptualization of the construct of digitalization remains elusive at best. In this chapter, we develop a taxonomy of the outcomes of the digitalization of physical reality, and of the interaction amongst digitalized units of physical reality. We maintain that these taxonomies may enhance the scope for combining extant res...

Gaussian Class-Conditional Training for Secure and Robust Deep Neural Networks

This chapter presents a Gaussian Class-Conditional (GCC) training strategy for deep neural networks. The approach is based on a novel loss that maps the input data onto Gaussian target distributions in the latent space, where the parameters of the target distributions can be optimized for the specific task. For multiclass classification, the mean values of the learned distributions are centered on the vertices of a simplex such that each class is at the same distance from every other class. F...

Model dependency of memristor circuit dynamics

Pickett's model is one of the few memristor models based upon experimental observations. Despite its high degree of accuracy, it is fairly complex and its use in large circuits is problematic. A number of simpler memristor models, specifically Biolek's model, the generalized Boundary Condition Memristor model and the ThrEshold Adaptive Memristor model are capable to track the dynamics of Pickett's model after undergoing a proper optimization process. However, since the parameter values ...

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