Type 1 diabetes is one of the major concerns in current medical studies, as the World Health Organisation plans to reduce mortality due to such disease by one third by 2030. Standard clinical practice involves self-ad...
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The implementation of robotics and human support technologies has opened up new possibilities for recovering the mobility impaired and increasing human productivity in the last few decades. Exoskeletons have been deve...
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Two of the most impressive features of biological neural networks are their high energy efficiency and their ability to continuously adapt to varying inputs. On the contrary, the amount of power required to train top-...
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This paper presents Fauno, the first and largest open-source Italian conversational Large Language Model (LLM). Our goal with Fauno is to democratize the study of LLMs in Italian, demonstrating that obtaining a fine-t...
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This paper proposes a deep-Q-network(DQN) controller for network selection and adaptive resource allocation in heterogeneous networks, developed on the ground of a Markov decision process(MDP) model of the problem. Ne...
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This paper proposes a deep-Q-network(DQN) controller for network selection and adaptive resource allocation in heterogeneous networks, developed on the ground of a Markov decision process(MDP) model of the problem. Network selection is an enabling technology for multi-connectivity, one of the core functionalities of 5G. For this reason, the present work considers a realistic network model that takes into account path-loss models and intra-RAT(radio access technology) interference. Numerical simulations validate the proposed approach and show the improvements achieved in terms of connection acceptance, resource allocation, and load *** particular, the DQN algorithm has been tested against classic reinforcement learning one and other baseline approaches.
This research focuses on a novel algorithm for Reinforcement Learning (RL) in Regular Decision Processes (RDPs), a model of non-Markovian decision processes where dynamics and rewards depend on regular properties of t...
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Digital image forensics currently mainly uses PRNU noise as a fingerprint to attribute an image to a particular camera. However PRNU is usually extracted manually using Maximum Likelihood estimation from multiple imag...
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This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR *** particular,the authors propose a new value iteration method to generate a sequence of monoton...
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This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR *** particular,the authors propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value *** method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration,and thus,the proposed approach is capable of achieving a better approximation for a given computation time compared with the existing *** numerical examples are presented in this paper to illustrate the effectiveness of the proposed method.
Human activities represent a major source of information for smart home automation. While performing their daily activities, humans trigger sensors producing measurements that flow into a sensor log. Vast majority of ...
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The aim of this work is to develop a robust control strategy able to drive the attitude of a spacecraft to a reference value,despite the presence of unknown but bounded uncertainties in the system parameters and exter...
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The aim of this work is to develop a robust control strategy able to drive the attitude of a spacecraft to a reference value,despite the presence of unknown but bounded uncertainties in the system parameters and external *** to the use of an extended observer design,the proposed control law is robust against all the uncertainties that affect the high-frequency gain matrix,which is shown to capture a broad spectrum of modelling issues,some of which are often neglected by traditional *** proposed controller then provides robustness against parametric uncertainties,as moment of inertia estimation,payload deformations,actuator faults and external disturbances,while maintaining its asymptotic properties.
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