Politecnio die Bari - Catalogo di prodotti della Ricerca
Not a member yet
36616 research outputs found
Sort by
Machine learning approach and physiological parameters evaluation: a case study on data acquired by Cinematic Virtual Reality scenarios
No full textIn response to the global concern over road traffic accidents, particularly among young drivers, there is increasing interest in innovative educational interventions to promote safer driving behaviors. Traditional media campaigns often fail to engage audiences meaningfully. This study, part of a broader research initiative, investigates the effects of Cinematic Virtual Reality (CVR) on participants' physiological responses, specifically focusing on heart rate variability, to assess the effectiveness of fear-based and positive reinforcement scenarios influencing road safety behaviors. A custom-developed CVR application delivered immersive 360° driving scenarios, one based on fear and the other on positive reinforcement, via a Meta Quest 2 headset. A total of 95 participants, aged 18 to 24 and all holding valid driver's licenses, were randomly assigned to one of the two experimental conditions. The study assessed the impact of these approaches on participants' physiological responses by recording electrocardiogram (ECG) data using the BioSignalPlux system. HRV parameters, indicators of stress and arousal, were analyzed to distinguish the physiological effects of the two scenarios. Time-domain, frequency-domain, and nonlinear HRV features were extracted and used for classification. Machine learning algorithms were employed to evaluate the system's performance in differentiating between the two experimental groups. The classification accuracy, sensitivity, and specificity were assessed using 10-fold cross-validation. Results showed that Linear Discriminant Analysis (LDA) achieved the highest classification accuracy
Primary Distribution Network Re-Energization Through Multiple Black Start Units
No full textThe increasing integration of distributed generation into distribution networks poses challenges to grid security and reliability, primarily due to the inherent intermittency and non-dispatchability of renewable energy sources (RES). Energy storage systems can mitigate these issues by enhancing RES controllability, thereby transforming them from a source of uncertainty into a flexible asset that contributes to system reliability. This study proposes a re-energization algorithm designed to exploit the microgrids (MGs) capabilities in ensuring energy supply during extreme events (e.g., blackouts). Specifically, the algorithm enables secure partitioning into network islands ensuring power balance
Commute Mode Choice Behavior of Academic Populations: A Comparative Study of Five Italian Universities
No full textA preliminary investigation on task-feature combinations for assigning maintenance tasks in Industry 5.0
Get PDFThe transition from Industry 4.0 (I4.0) to Industry 5.0 (I5.0) emphasises the need for human-centric industrial systems. In this context, maintenance operations represent a critical domain since they are inherently complex and directly related to the performance of production systems. According to the I5.0 perspective, a maintenance task allocation system should therefore be designed to optimise operator-task matches, minimising cognitive overloads and ensuring the operator's well-being. However, current literature lacks a standardised framework for identifying which operator's features significantly impact the proper accomplishment of maintenance tasks. This research therefore aims to understand the operator's features that most influence the proper accomplishment of maintenance tasks within the I4.0 context. To achieve the objective of the present work, a two-phase methodology was employed: firstly, two Systematic Literature Reviews allowed for identifying a sample of maintenance tasks and operator's features, and then a targeted survey was administered to professionals from companies with expertise in maintenance and I4.0 to understand which of the identified features are most relevant for the correct accomplishment of the analysed tasks. Although the study identified differences regarding the so-called cognitive and hybrid tasks, it generally demonstrated the importance of professional over individual features for the proper accomplishment of the identified maintenance tasks
Brackish water vs. brine outfall: impact of desalination plant discharge in vulnerable coastal sites
Get PDFThe potential of coastal springs has recently been explored as an alternative water source for desalination plants. Unlike conventional seawater-fed facilities, this approach produces a brackish effluent. Our study aims to investigate the environmental implications of the discharge of such brackish water from a planned desalination facility in a vulnerable coastal area of Southern Italy. We employ numerical modeling of hydrodynamics and plume dispersion to compare two scenarios: (1) discharge of hyposaline brackish water, as envisaged by the proposed approach; and (2) discharge of hypersaline brine, as in traditional plants. Year-long simulations reveal key differences between the two scenarios. We introduce and discuss two relevant metrics for assessing plume impacts: the eddy diffusivity, which quantifies mixing efficiency, and the characteristic time scale, which links plume length scale to ambient current speed. Our main findings highlight (i) how differences in plume density alter local hydrodynamics; (ii) the extent to which plume spreading time and length scales differ, with consequent variation in potential ecosystem impacts. Results suggest that brackish effluent management could represent a more sustainable alternative for coastal desalination, minimizing environmental risks. In contrast, hypersaline plumes may require offshore release to reduce ecological impact. Although this study is region-specific, the proposed framework is applicable to other coastal areas facing similar desalination challenges
Designing a New Collaborative Educational Platform on Glass Design and Engineering: A Case Study
No full textLong-Term Thermal Stability of Aerogel and Basalt Fiber Pipeline Insulation Under Simulated Atmospheric Aging
No full textThermal insulation materials used in power and industrial systems must maintain high performance under extreme environmental conditions. Among such materials, aerogel and basalt fiber are widely applied due to their low thermal conductivity and ease of installation. However, over time, these materials are susceptible to degradation, which can significantly impair their insulating efficiency and increase energy losses. Despite their importance, the long-term behavior of these materials under realistic climatic stressors has not been analyzed enough. This study investigates the degradation of thermal insulation performance in aerogel and basalt fiber materials subjected to complex atmospheric stressors, simulating long-term outdoor exposure. Aerogel and basalt fiber mats were tested under accelerated aging conditions using an artificial weather chamber equipped with xenon lamps to replicate full-spectrum solar radiation, high humidity, and elevated temperatures. The results show that the thermal conductivity of aerogel remained stable, indicating excellent durability under environmental stress. In contrast, basalt fiber insulation exhibited a deterioration in thermal performance, with a 9–11% increase in thermal conductivity, corresponding to reduced thermal resistance. Computational modeling using COMSOL Multiphysics confirmed that aerogel insulation outperforms basalt fiber, especially at temperatures exceeding 200 °C, offering better heat retention with thinner layers. These findings suggest aerogel-based materials are more suitable for long-term thermal insulation of high-temperature pipelines and industrial equipment
Measurement of the Drell–Yan forward-backward asymmetry and of the effective leptonic weak mixing angle in proton-proton collisions at s=13TeV
No full textThe forward-backward asymmetry in Drell–Yan production and the effective leptonic electroweak mixing angle are measured in proton-proton collisions at s=13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138fb−1. The measurement uses both dimuon and dielectron events, and is performed as a function of the dilepton mass and rapidity. The unfolded angular coefficient A4 is also extracted, as a function of the dilepton mass and rapidity. Using the CT18Z set of parton distribution functions, we obtain sin2θeffl=0.23152±0.00031, where the uncertainty includes the experimental and theoretical contributions. The measured value agrees with the standard model fit result to global experimental data. This is the most precise sin2θeffl measurement at a hadron collider, with a precision comparable to the results obtained at LEP and SLD
