Higher Institute on Territorial Systems for Innovation
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Seeing is Believing: Assessing and Enhancing Android Privacy Indicators Through Eye-Tracking Analysis
No full textToday, mobile device privacy is more crucial than ever, pushing Android to introduce Privacy Indicators (PIs) to enhance transparency and protect users. These visual alert systems signal when sensitive resources, like the camera or microphone, are in use. The effectiveness of these visual elements is clearly linked to their ability to capture the users’ gaze. In this paper, we leverage eye-tracking technology to explore PIs’ ability to catch the users’ attention. In a controlled experiment with 29 participants, we uncovered significant gaps in PI effectiveness, particularly during high-engagement tasks, showing that changes in the PI implementation may affect its visibility, still highlighting the need for more attention-grabbing privacy notifications. Building on these findings, a second experiment with 14 participants assessed the Disk PI—the best performer from the initial study—across passive (video watching) and active (app usage) usage contexts. Even concerning these two factors, the results show the limits of the proposed solution, suggesting the need for careful analysis of the UI elements that are most effective in capturing the user’s gaze to create a better solution. Heatmap analysis revealed that users consistently focus on centrally located, dynamic elements and text while ignoring static and peripheral areas. Inspired by these insights, we developed a new Popup PI, strategically positioned at the top center of the screen with dynamic animations and textual information. This Popup PI significantly increased user attention and retention, proving to be a more effective solution for privacy notifications. Our research underscores the urgent need for intuitive and user-friendly privacy indicators in the Android ecosystem. The compelling evidence points to the Popup PI as a superior alternative, greatly enhancing user awareness and privacy protection. These findings are a pivotal step towards evolving privacy mechanisms, fostering a safer and more transparent digital environment for all users, and advancing the methodology of utilizing eye tracking in user experience research
The Impact of Transition and Turbulence Modeling on the SPLEEN High-Speed Low-Pressure Turbine Cascade
Get PDFIn high speed low pressure turbines (LPTs) for geared turbofan engine applications, transonic flow conditions combined with low Reynolds number operation depict a flow scenario where shock waves can interact with laminar or turbulent boundary layers, and the resulting flow topologies pose serious challenges for computational fluid dynamics (CFD) analyses. In this work, two different in house developed Reynolds Averaged Navier Stokes (RANS) solvers are applied to the study of a transonic low pressure turbine cascade over a range of Mach and Reynolds numbers, with a focus on the performance of transition and turbulent closures. The selected test case consists of the SPLEEN (Secondary and Leakage Flow Effects in High Speed Low Pressure Turbines) C1 cascade, a state of the art high speed low pressure turbine blade section that has been investigated in an extensive experimental campaign at the von Karman Institute, in the framework of the SPLEEN European Research Programme. The considered transition sensitive turbulence closures are representative of the most advanced techniques for RANS methods and range from correlation based intermittency transport approaches to phenomenological model based on the laminar kinetic energy (LKE) concept and the k v'2 w framework. It is shown how realistic transition modeling is crucial for predicting blade loading distributions and then addresses design challenges for transonic LPT bladings. A discussion concerning the reproduction of wake loss profiles demonstrates how classical linear eddy viscosity closures can be adequate in the case of attached flow even in transonic flow conditions but fall short in predicting the intense wake mixing brought about by the thick turbulent boundary layers that are formed past laminar separation bubbles
Effect of print orientation of 3D-printed aligner templates on the volumetric accuracy of transferred composite attachments: an in vitro study
No full textObjectives
This study aimed to evaluate the effect of print orientation on the dimensional accuracy of attachments in directly 3D-printed orthodontic aligners.
Materials and methods
For n = 10 patients, 34 single-tooth aligner segments were digitally designed (17 for tooth 1.1 and 17 for tooth 1.6) incorporating a planned 3 mm horizontal rectangular buccal attachment. These aligners were printed in TC-85 DAC resin (Graphy Inc, Seoul, Korea) at different inclinations (8 in anterotation and 8 in postrotation, at 10° intervals from the horizontal) and used as templates to transfer attachments onto corresponding 3D-printed dental models. This models with transferred attachments were scanned with a laboratory scanner and superimposed onto the attachment surface of the master digital file. Percentage volume deviations of the transferred versus planned attachment were quantified using Geomagic Control software (v.2020.1.1, ©2020 3D Systems, Inc., Rock Hill, SC) and analysed with an unpaired two-tailed t-test (P < 0.05).
Results
For tooth 1.1, the mean volumetric deviation of transferred attachments was significantly lower in postrotation orientations (88.87% ± 4.13) than in anterotation (69.01% ± 4.33), indicating that positioning the template with the vestibular surface facing the build platform improves accuracy (p < 0.0001). For tooth 1.6, no statistically significant difference was found (p = 0.0992; 78.16% ± 2.26 vs. 79.99% ± 1.87).
Conclusions
Composite attachments transferred with 3D-printed templates exhibited a volumetric alteration respect the master digital file and print orientation particularly affects anterior teeth’s attachments.
Clinical relevance
Aligners orientation during 3D-printing is crucial to ensure accurate attachments transfer, especially anterior regions
Biodiversity and Landscape: Towards an Alliance in Italian Spatial Planning
No full textProtecting biodiversity, as well as cultural and natural heritage, while enhancing the landscape, is a pressing priority in light of global environmental crises and land transformation. These challenges, driven by increased vulnerabilities and ecosystem fragmentation, require integrated solutions that connect conservation efforts with landscape policies. Therefore, a collaborative approach between spatial planning and conservation is crucial, especially when linking area-based values, such as Protected and Conserved Areas, with broader landscape strategies. In this perspective, spatial planning must evolve to prioritize the combined protection and enhancement of nature and culture, promoting sustainability and quality in transformative actions. Since 2003, nature conservation strategies have shifted to address broader landscape and territorial objectives. This evolution supports the active conservation of cultural heritage and identity, serving as a catalyst for economic development (as outlined in the European Landscape Convention).
This paper explores an integrated approach that combines knowledge frameworks and regulatory mechanisms to protect and enhance natural, cultural, and landscape heritage. It draws on planning experiences from sensitive contexts such as protected areas, rivers, and rural environments, contributing to the goals of the EU Biodiversity Strategy 2030 and the advancement of Green Infrastructure. Additionally, the paper examines the practical implementation of ecological connectivity at multiple scales
A novel approach using deep belief network patterns and attention binary decomposition for automated community emotion detection
Get PDFSound-based community emotion detection (SCED) estimates community emotion from environmental
sounds. It has value for public safety and human–computer interaction. Current SCED models have limited
adaptivity on complex audio and often need manual tuning.
Objective: We aim to design an accurate and efficient automated SCED model for large-scale data.
Methods: We propose a feature extraction framework that combines DBNPat feature generation with ATT-BP
attention-driven binary compression. The framework adapts to signal characteristics with low computational
cost. We also introduce a new dataset of 10,017 environmental sound clips (three seconds) with negative (n =
1,729), neutral (n = 6,154), and positive (n = 2,134) classes.
Results: The proposed SCED model achieves 87.28% accuracy on three-class SCED. It yields 81.30% UAR, 84.71%
precision, 82.97% F1, and 80.59% geometric mean on the imbalanced dataset. Conclusion: The model links
classical feature design and deep pattern generation in one adaptive pipeline. It offers a practical solution for
digital sound forensics and other ambient-audio systems that need fine emotion cues
Homogenization and 3D-2D dimension reduction of a functional on manifold valued Sobolev spaces
Get PDFWe study simultaneous homogenization and dimensional reduction of integral functionals for maps in manifold-valued Sobolev spaces. Due to the superlinear growth regime, we prove that the density of the Γ-limit is a tangential quasiconvex integrand represented by a cell formula
A performance-based incentive sharing mechanism for communities of residential end users leveraging an ontology-driven approach
Get PDFEnergy sharing, whether physical or virtual, is crucial for optimizing the use of locally generated renewable energy within communities of residential end users, including Renewable Energy Communities (RECs) and Collective Self-Consumption (CSC) groups. By sharing energy, participants can increase self-consumption of renewables while reducing reliance on the grid. To encourage participation, many frameworks provide economic incentives for shared energy, offering financial benefits to those who contribute to community energy goals. However, ensuring a fair allocation of both shared energy and its associated incentives remains a challenge. This study introduces a novel performance-based incentive-sharing mechanism that dynamically adjusts the allocation of economic benefits based on user ability to shift consumption in response to surplus availability. Different from traditional approaches, the mechanism integrates a dynamic baseline selection process with an ontology-driven metadata model, using SAREF and its domain-specific extensions to ensure interoperability and automation. This semantic framework enables scalable deployment across heterogeneous community configurations while reducing setup complexity. The process was tested over a seven-month period within a collective self-consumption group of 13 residential users who virtually share energy from a centralized PV system. Results show that users who adjusted their consumption to match surplus availability increased their daily incentives by up to 40% compared to a standard sharing mechanism, while those who performed below expectations experienced a corresponding decrease. These findings highlight the potential of structured data-driven approaches, supported by ontologies, to improve decision-making in community energy management
Migrazione e emergenza abitativa nel caso di Torino.
No full textAccording to the European Committee of Social Rights, the shortage of affordable housing in Europe—and in Italy in particular—constitutes a serious issue affecting an increasingly large share of the population. Barriers to access are even more pronounced for individuals with intersecting vulnerabilities, such as people with a migrant background. Although the right to housing for foreigners is guaranteed under Italian constitutional law as well as international and EU law, these groups experience greater difficulties, partly due to the lack of infrastructures that facilitate integration into housing pathways. One in two migrant households lives in overcrowded conditions (48.1percento, compared to 17.3percento among households composed solely of Italian nationals), highlighting the strong relationship between housing deprivation and migrant background (Istat 2022). Local territories often respond to this disparity with weak and insufficient emergency housing policies. This article proposes moving beyond such emergency driven approaches through an integrated analysis of the territorial housing access system, understood as a key indicator of integration trajectories. Launched in 2024, the Empower Housing study in the Turin metropolitan area assesses structural constraints and the socio economic variables that shape the transition from reception systems to autonomous housing pathways. Drawing on fieldwork, data collection and analysis, and structured dialogue with local stakeholders, the article examines innovative policies and practices for housing inclusion and outlines guidelines for co-design processes involving public authorities, the no profit sector, and private actors, while accounting for the specific needs of diverse migrant populations. Secondo il Comitato europeo per i diritti sociali, la carenza di alloggi a prezzi accessibili in Europa, e in Italia, è un problema grave che coinvolge una quota crescente della popolazione. Le barriere di accesso risultano ancora più marcate per soggetti con vulnerabilità intersezionali, come le persone con background migratorio. Pur essendo il diritto alla casa garantito dall’ordinamento italiano, internazionale e comunitario, tali gruppi sperimentano maggiori difficoltà anche per l’assenza di infrastrutture che facilitino l’integrazione abitativa. Una famiglia straniera su due vive in sovraffollamento (48,1percento, contro il 17,3percento delle famiglie italiane), evidenziando la forte relazione tra disagio abitativo e background migratorio (Istat 2022). A questa disparità i territori rispondono spesso con politiche emergenziali deboli e insufficienti. L’articolo propone di superare tali logiche attraverso un’analisi integrata del sistema territoriale di accesso all’alloggio, considerato indicatore cruciale dei percorsi di integrazione. Avviato nel 2024, lo studio Empower Housing, nel territorio torinese, valuta criticità strutturali e variabili socio economiche delle transizioni tra dispositivi di accoglienza e percorsi di autonomia. Basandosi su ricerca empirica e confronto con gli attori locali, l’articolo analizza politiche e pratiche di avanguardia per l’inclusione abitativa e propone linee guida per processi di coprogettazione tra pubblico, terzo settore e privato, tenendo conto delle specificità delle diverse popolazioni straniere
Biochar come Agente Multifunzionale per la Sicurezza Stradale Invernale: Analisi Termomeccanica e Benefici Ecosistemici Urbani
Get PDFL'impiego del biochar come alternativa o additivo ai metodi tradizionali di sbrinamento stradale (sale e sabbia) offre vantaggi significativi in termini di sicurezza e sostenibilità. Questo report analizza l'interazione fisica tra biochar e ghiaccio, evidenziando come la struttura porosa e la bassa albedo del materiale favoriscano l'ancoraggio meccanico (grip) e l'assorbimento radiativo. Attraverso test di frenata e analisi dell'usura degli pneumatici, viene dimostrata la superiorità del biochar nel ridurre le distanze di arresto e il deterioramento delle mescole gommose rispetto alla sabbia silicea. Lo studio esplora inoltre l'effetto "cappotto" del biochar sulla protezione termica del sottofondo stradale e delle radici degli alberi urbani, mitigando i danni da gelo e l'inquinamento da cloruri. Infine, un'analisi del ritorno economico (ROI) su un orizzonte decennale suggerisce che l'investimento nel biochar sia compensato dalla maggiore longevità delle infrastrutture e dai crediti di carbonio