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3 results on '"Merolla, Davide"'

1. Automated Road Safety: Enhancing Sign and Surface Damage Detection with AI

Author

Merolla, Davide, Latorre, Vittorio, Salis, Antonio, and Boanelli, Gianluca

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence
Abstract

Public transportation plays a crucial role in our lives, and the road network is a vital component in the implementation of smart cities. Recent advancements in AI have enabled the development of advanced monitoring systems capable of detecting anomalies in road surfaces and road signs, which, if unaddressed, can lead to serious road accidents. This paper presents an innovative approach to enhance road safety through the detection and classification of traffic signs and road surface damage using advanced deep learning techniques. This integrated approach supports proactive maintenance strategies, improving road safety and resource allocation for the Molise region and the city of Campobasso. The resulting system, developed as part of the Casa delle Tecnologie Emergenti (House of Emergent Technologies) Molise (Molise CTE) research project funded by the Italian Minister of Economic Growth (MIMIT), leverages cutting-edge technologies such as Cloud Computing and High Performance Computing with GPU utilization. It serves as a valuable tool for municipalities, enabling quick detection of anomalies and the prompt organization of maintenance operations, Comment: 16 pages, 10 figures

Published
2024

3. A bilevel approach to ESG multi‑portfolio selection

Author

Francesco Cesarone, Lorenzo Lampariello, Davide Merolla, Jacopo Maria Ricci, Simone Sagratella, Valerio Giuseppe Sasso, Cesarone, Francesco, Lampariello, Lorenzo, Merolla, Davide, Ricci, Jacopo Maria, Sagratella, Simone, and Giuseppe Sasso, Valerio

Subjects
Business, Management and Accounting (miscellaneous), Management Science and Operations Research, Statistics, Probability and Uncertainty, Management Information Systems, Sustainable investment strategies, Multi-portfolio selection, ESG rating scores, Nash equilibrium problems, Bilevel optimization
Abstract

We rely on bilevel programming to model the problem of financial service providers that, in order to meet stakeholders’ demands and regulatory requirements, aim at incentivizing accounts’ holders to construct ESG-oriented portfolios so that the overall ESG impact of the firm is optimized, while the preferences of accounts’ owners are still satisfied. We analyze this complicated framework from a theoretical point of view and identify sufficient conditions that make it numerically tractable via a novel, specifically tailored algorithm, whose convergence properties are studied. Numerical testing on real-world data confirms the theoretical insights and shows that our model can be solved even when dealing with considerable problem sizes.

Published
2023

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