Existing consensus control algorithms for networked discrete-time linear systems have slow convergence to consensus trajectories due to limitations on the magnitude of the consensus gain. In this work we propose and analyze a new predictor-based consensus control protocol that recovers the positive...
01a Articolo in rivista
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Advancing our understanding of complex diseases requires an interdisciplinary dialogue beyond artificial intelligence (AI). Fostering collaboration and training among genetics, molecular biology, computational biology, and clinical research represents an imperative need to address precision...
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The Byzantine tolerant reliable communication primitive is a fundamental building block in distributed systems that guarantees the authenticity, integrity, and delivery of information exchanged between processes. We study the implementability of such a primitive in a distributed system with a...
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This paper aims to shed light on the determinants of sustainable products' purchase intention, with a focus on sustainable beer. Specifically, three determinants related to the theory of planned behavior (i.e., perceived consumer effectiveness, social influence, and environmental concern) and two...
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Critical Raw Materials attract increasing attention due to their depleting reserves and low recyclability. Niobium, one of the most rare and vital elements, is primarily found in Brazil. This research explores the potential impact of Circular Economy (CE) strategies on mitigating niobium's...
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Recently, the new industrial paradigm of circular economy (CE) has acquired increasing attention. In a CE, the value of materials is preserved by keeping them for as long as possible in the economic system, overcoming the "traditional" linear model (take-waste-disposal). Despite its benefits in...
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A recent trend in binary code analysis promotes the use of neural solutions based on instruction embedding models. An instruction embedding model is a neural network that transforms assembly instructions into embedding vectors. If the embedding network is able to processes sequences of assembly...
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DNNs are widely used for complex tasks like image and signal processing, and they are in increasing demand for implementation on Internet of Things (IoT) devices. For these devices, optimizing DNN models is a necessary task. Generally, standard optimization approaches require specialists to...
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Introduction: The primary objective of this research is to examine acrophobia, a widely prevalent and highly severe phobia characterized by an overwhelming dread of heights, which has a substantial impact on a significant proportion of individuals worldwide. The objective of our study was to...
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Gastric cancer (GC) is a significant healthcare concern, and the identification of high-risk patients is crucial. Indeed, gastric precancerous conditions present significant diagnostic challenges, particularly early intestinal metaplasia (IM) detection. This study developed a deep learning system...