Archivio Istituzionale della Ricerca- Università del Salento
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Analyzing the Impact of Non-IID Data on IoT-Enabled Federated Learning for ECG Arrhythmia Detection
No full textThe integration of Federated Learning (FL) in the Internet of Medical Things (IoMT) represents a cutting-edge solution, enabling the training of Artificial Intelligence (AI) models directly on edge devices without the need to share sensitive patient information. This approach enhances privacy while preserving the quality and effectiveness of clinical analysis. However, in real-world scenarios, physical devices often generate data that is non-independent and non-identically distributed (Non-IID), creating significant challenges for the training process. This study proposes an experimental method to generate realistic data distributions from existing centralized datasets, capturing real-world heterogeneity in IoT-driven federated learning infrastructures. The proposed infrastructure utilizes advanced statistical techniques to transform IID datasets into Non-IID distributions. This transformation enables a systematic evaluation of the impact of Non-IID data on Federated Learning in ECG arrhythmia detection. Using the MIT-BIH Arrhythmia dataset, an accuracy drop of only 0.31% was observed in an extreme Non-IID scenario. However, significant execution time variability is observed, showing up to a 50% variation across clients, compared to medium Non-IID (15.5%) or IID (0.63%)conditions. This observation implies that Non-IID data leads to substantial disparities in computational workload across clients, which can slow down and destabilize the convergence process, as suggested by theoretical expectations
CULTURAL AND PERSONAL CONTEXTS IN THE DEVELOPMENT OF SELF-ESTEEM IN STUDENTS WITH NEURODEVELOPMENTAL DISORDERS: WHERE DOES THE DEFICIT END AND THE INFLUENCE OF THE CONTEXT BEGIN?
No full textPharmacological potential of endocannabinoid and endocannabinoid-like compounds in protecting intestinal structure and metabolism under high-fat conditions
No full textThe intestine plays a crucial role in nutrient absorption, digestion, and regulation of metabolic processes. Intestinal structure and functions are influenced by several factors, with dietary composition being one of the most significant. Diets rich in various types of fats, including saturated, monounsaturated, and polyunsaturated fats, have distinct effects on intestinal cell metabolism and overall intestinal health. High consumption of saturated fats, frequently found in animal products, has been associated with inflammation, altered gut microbiota composition, and impaired intestinal barrier function, with potential consequences such as metabolic disorders, obesity, and insulin resistance. In contrast, monounsaturated fats, found in foods such as olive oil and avocado, promote intestinal cell integrity, reducing inflammation and supporting a healthier microbiome. Polyunsaturated fatty acids, especially omega-3 fatty acids, have shown anti-inflammatory effects and may improve the function and adaptability of intestinal cells, promoting better nutrient absorption and immune regulation. Recent evidence suggests that endocannabinoids and endocannabinoid-like compounds, such as oleoylethanolamide have a protective effect on the function and structure of the intestine. These endocannabinoid pathways modulating compounds can act on receptors in the intestinal epithelium, improving the intestinal barrier and counteracting inflammation, facilitating a more favorable environment for intestinal health. Understanding how different fats influence intestinal metabolism and the protective role of endocannabinoids and endocannabinoid-like compounds is essential to developing dietary strategies to improve intestinal health and prevent diet-related diseases. This review explores the impact of high fats on intestinal metabolism and the main role of endocannabinoids and endocannabinoid-like compounds on these effects
Sustainable development, attractiveness, and competitive capacity of touristic local territorial systems (LTSs) in south Italy: a strategic positioning
Get PDFFilosofie dell'esperienza. Dal disincanto ideologico alla pedagogia incarnata
No full textUna nuova filosofia dell'esperienza emerge dall'incontro tra scienza, corporeità e libertà. Questo volume traccia un itinerario che, dalla riflessione degli Idéologues fino alla fenomenologia contemporanea, attraversa figure come Cabanis, Destutt deTracy e Merleau-Ponty, per restituire senso all'idea di un sapere incarnato e integrato. Attraverso una rigorosa esegesi teoretica e un'indagine storica ricca di riferimenti inediti, gli autori mostrano come la sensibilità e il corpo non siano semplici oggetti della conoscenza, ma i luoghi originari in cui essa si costituisce. L'esperienza educativa - intesa come formazione dell'umano nella sua s pienezza – si rivela così il campo privilegiato in cui filosofia, scienza e antropologia si intrecciano
Entre le pape et le roi: la fiscalité des diocèses de l’Italie méridionale (XIIe-XVe siècle)
Get PDFLe but de cet article est de réfléchir sur l'économie et la fiscalité interne de l'Église de l'Italie du Sud, sur le rôle des pouvoirs publics laïcs dans son économie et sur l'importance de ses diocèses et monastères dans les finances de l'Église romaine. Dans le Mezzogiorno, l'Église tirait une grande partie de ses revenus de sa propriété immobilière, des sommes provenant de la liturgie commémorative et des taxes imposées sur les églises non diocésaines. Toutefois, la majeure partie des diocèses et nombreux monastères et églises locales dépendaient dans leur fonctionnement des ressources fournies par la cour royale en forme de "dîmes d'État", ou bien une partie des revenus fiscaux de la couronne. L'Église de l'Italie méridionale contribua relativement peu aux caisses de la Chambre Apostolique à travers les dîmes et subventions, mais fournissait aux papes des ressources importantes en forme de bénéfices, utilisées pour rémunérer les collaborateurs de la curie et depuis un certain moment aussi directement taxées
IoT-Driven Resilience Monitoring: Case Study of a Cyber-Physical System
No full textThis study focuses on Digital Twin-integrated smart energy systems, which serve as an example of Next-Generation Critical Infrastructures (CI). The resilience of these systems is influenced by a variety of internal features and external interactions, all of which are subject to change following cyber-physical disturbances. This necessitates real-time resilience monitoring for CI during crises; however, a significant gap remains in resilience monitoring. To address this gap, this study leverages the role of Internet of Things (IoT) in monitoring complex systems to enhance resilience through critical indicators relevant to cyber-physical safety and security. The study empirically implements Resilience-Key Performance Indicators (R-KPIs) from the domain, including Functionality Loss, Minimum Performance, and Recovery Time Duration. The main goal is to examine real-time IoT-based resilience monitoring in a real-life context. A cyber-physical system equipped with IoT-driven Digital Twins, data-driven microservices, and a False Data Injection Attack (FDIA) scenario is simulated to assess the real-time resilience of this smart system. The results demonstrate that real-time resilience monitoring provides actionable insights into resilience performance based on the selected R-KPIs. These findings contribute to a systematic and reusable model for enhancing the resilience of IoT-enabled CI, advancing efforts to ensure service continuity and secure essential services for society
L’Inattuale sulla storia come canone dello “storicismo” di Nietzsche
No full textL' "Inattuale" sulla storia, generalmente considerata il canone dello antistoricismo di Nietzsche, letta in senso storicistic
GenAI-aided Sustainable Digital Transformation: A Novel Framework and Early Results
No full textNowadays, rapid technological advancements play a central role in redefining the operational and strategic dynamics of businesses. Artificial Intelligence (AI), with particular emphasis on Generative AI, not only ensures greater efficiency in business processes but also holds the potential to completely revolutionize the way companies design, implement, and optimize their operations. These tools offer new opportunities to address one of the most pressing challenges of our time: the sustainability of processes.
This work proposes a framework structured into three blocks to assess the contribution of Generative AI to sustainable process optimization: (i) automatic process generation through Large Language Models (LLMs), (ii) automated conversion into BPMN models, and (iii) quantitative sustainability analysis.
Although the framework has been fully defined at a theoretical level, its implementation is still in progress. This work, in particular, focuses on the results achieved for the first block. Unlike traditional methods that require the involvement of domain experts, advanced Generative AI models are used to automate most (if not all) of the transformation. The study unfolds in two main phases: in the first phase, LLMs generate sustainable versions of processes from textual descriptions, following specific criteria such as carbon footprint reduction, material recycling, and energy efficiency. In the second phase, the results are evaluated using the G-Eval Framework, comparing model performances with expert-conducted analyses.
For the validation of the approach, an analysis was conducted on real processes taken from the Camunda repository. Each process was provided as input to different LLMs, accompanied by a carefully designed prompt specifying the sustainability criteria to be applied. The results proved to be very promising: the Claude 3.5 Haiku model achieved the highest performance (77%), while GPT-4 Turbo scored the lowest (66%)
