In the current industrial landscape, digitization is essential for the survival and growth of companies of all sizes. The adoption of new technologies and organizational structures is critical as companies navigate complex digital transformations. While Maturity Models (MMs) offer significant...
01a Articolo in rivista
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Modern organizations necessitate continuous business processes improvement to maintain efficiency, adaptability, and competitiveness. In the last few years, the Internet of Things, via the deployment of sensors and actuators, has heavily been adopted in organizational and industrial settings to...
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Early detection of illnesses and pest infestations in fruit cultivation is critical for maintaining yield quality and plant health. Computer vision and robotics are increasingly employed for the automatic detection of such issues, particularly using data-driven solutions. However, the rarity of...
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In today's fast-paced digital landscape, the importance of human factors in cybersecurity has become increasingly evident yet is often overlooked. This research employs the Delphi method to achieve expert consensus on the managerial actions that enhance cybersecurity by leveraging human factors....
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Omnidirectional robots can be realized using Mecanum wheels or using a suitable arrangement of conventional steerable wheels. The latter group, known as omnidirectional steerable wheeled mobile robots (SWMRs), are known to have a lower cost with respect to the former, and to be more robust thanks...
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This paper introduces a computationally efficient robust Model Predictive Control (MPC) scheme for controlling nonlinear systems affected by parametric uncertainties in their models. The approach leverages the recent notion of closed-loop state sensitivity and the associated ellipsoidal tubes of...
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We present a Robust Intrinsically Stable Model Predictive Control (RIS-MPC) framework for humanoid gait generation, which realizes as closely as possible a predefined sequence of footsteps in the presence of both persistent and impulsive perturbations. The MPC-based controller has two modes of...
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In this paper, we study the embedded feature selection problem in linear Support Vector Machines (SVMs), in which a cardinality constraint is employed, leading to an interpretable classification model. The problem is NP-hard due to the presence of the cardinality constraint, even though the...
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In this work, we consider minimizing the average of a very large number of smooth and possibly non-convex functions, and we focus on two widely used minibatch frameworks to tackle this optimization problem: Incremental Gradient (IG) and Random Reshuffling (RR). We define ease-controlled...
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In this paper we consider the issue of computing negative curvature directions, for nonconvex functions, within Newton–Krylov methods for large scale unconstrained optimization. In the last decades this issue has been widely investigated in the literature, and different approaches have been...