14.d Contributo in Atti di Convegno

14.d Contributo in Atti di Convegno: [31935] Home page macrotipologia

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14.d.1 Abstract in Atti di convegno 22337
14.d.3 Contributi in extenso in Atti di convegno 8980
14.d.4 Poster 618

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A Scalable LoRaWAN-Based Environmental Sensing System for Cultural Heritage Sites

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Predicting Lithium-Ion Battery Degradation Modes Using a Machine Learning Approach Based on EIS Measurements

This study presents a machine learning (ML) framework that is able to predict the degradation modes of a lithium-ion battery. Leveraging on some analytical models recently proposed in literature, the proposed algorithm estimates three main ageing indicators (Conductivity Loss (CL), Loss of Active Material (LAM) and Loss of Lithium Inventory (LLI)), using ML models based on battery-related features, i.e., Electrochemical Impedance Spectroscopy (EIS), State of Charge (SoC), Open Circuit Voltage...

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As the transition to a low-carbon economy accelerates, firms are under increasing pressure to demonstrate meaningful commitments to decarbonization and circularity. Nonetheless, the influence of internationalization on corporate sustainability initiatives remains mainly unexamined and somewhat unclear. This paper delves into how the varied international exposure of firms affects their dedication to decarbonization and the implementation of emission reduction strategies, with a special focus o...

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