Chapter Nuove iconografie per la rappresentazione del patrimonio su Instagram

The 43rd UID conference, held in Genova, takes up the theme of ‘Dialogues’ as practice and debate on many fundamental topics in our social life, especially in these complex and not yet resolved times. The city of Genova offers the opportunity to ponder on the value of comparison and on the possibilities for the community, naturally focused on the aspects that concern us, as professors, researchers, disseminators of knowledge, or on all the possibile meanings of the discipline of representation and its dialogue with ‘others’, which we have broadly catalogued in three macro areas: History, Semiotics, Science / Technology. Therefore, “dialogue” as a profitable exchange based on a common language, without which it is impossible to comprehend and understand one another; and the graphic sign that connotes the conference is the precise transcription of this concept: the title ‘translated’ into signs, derived from the visual alphabet designed for the visual identity of the UID since 2017. There are many topics which refer to three macro sessions: - Witnessing (signs and history) - Communicating (signs and semiotics) - Experimenting (signs and sciences) Thanks to the different points of view, an exceptional resource of our disciplinary area, we want to try to outline the prevailing theoretical-operational synergies, the collaborative lines of an instrumental nature, the recent updates of the repertoires of images that attest and nourish the relations among representation, history, semiotics, sciences

Tools development to optimize the use of micro-drones for architectural cultural heritage survey

In view of the increasingly widespread use of inoffensive UAS for photogrammetric acquisitions in the architectural and infrastructural spheres, there is a need to be able to program flight missions suited to the operator’s needs. This contribution presents the results of two experiments conducted by the research group. The first proposed procedure, based on low-cost instrumentation and algorithms in a VPL environment, fills the gap of proprietary applications and allows the coding and customisation of flight missions for photogrammetry. Obtaining this information is not always easy; immovable or unforeseen obstacles lead to lengthy post-production of the photogrammetric cloud to remove them. The second procedure, by constructing an object segmentation framework, fills this gap by automatically processing photogrammetric images by recreating masks that remove unwanted objects from the dense cloud calculation. Despite some shortcomings, the results are promising and manage to make up for these shortcomings, at least in part

Proportions, Constraints and Semantics for a Parametric Model

An approach to digitally model the decorative elements window’s of architectural heritage—the College of Nobles, Turin—in HBIM, by applying De Luca’s method. The strategy is to transform them into mathematical ratios and parameters in order to create fexible and adaptable models that can generate variations

H-BIM for the Torino Esposizioni complex: A fusion of Parametric Digital Modeling and Image Archive, bridging past and present

The article delves into the results of the renovation of the Torino Esposizioni complex, a masterpiece by Pier Luigi Nervi and a pivotal part of Turin’s architectural legacy. This building has once again become a focal point in contemporary discussions, given its central role in the Technical Economic Feasibility Plan (PFTE) proposed by the Isolarchitetti studio in collaboration with Rafael Moneo, slated for completion in 2022. This team played a pivotal role in implementing and refining the BIM methodology within the professional realm, specifically for crafting the architectural model of such a distinguished property. The process of breaking down the building into standard H-BIM components began with a preliminary phase of study that leveraged an extensive iconographic collection. This assemblage of images underscores the intricacy of an architectural entity deeply rooted in our heritage and chronicles its myriad modifications and restorations over the years. This paints a vivid picture, drawing profound parallels between historical images and today’s digital renditions

A Heritage of images witnessing the passage of time. The renovation of the Torino Esposizioni complex

The essay describes the outcomes of the restoration of the Torino Esposizioni complex, an exemplary work of mid-century engineering by Pier Luigi Nervi. The complex is well known to the community for its various uses over the years and for the complete state of neglect it has been in since the post-Olympic period. In line with the call’s suggestions, the Padiglione 2 well manifests the passage of time through a collection of images, between history and memory. The important work of digitizing the artifact and especially the HBIM modeling of the pavilion can be told through images

From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs

Many real-world datasets have an underlying dynamic graph structure, where entities and their interactions evolve over time. Machine learning models should consider these dynamics in order to harness their full potential in downstream tasks. Previous approaches for graph representation learning have focused on either sampling k-hop neighborhoods, akin to breadth-first search, or random walks, akin to depth-first search. However, these methods are computationally expensive and unsuitable for real-time, low-latency inference on dynamic graphs. To overcome these limitations, we propose graph-sprints a general purpose feature extraction framework for continuous-time-dynamic-graphs (CTDGs) that has low latency and is competitive with state-of-the-art, higher latency models. To achieve this, a streaming, low latency approximation to the random-walk based features is proposed. In our framework, time-aware node embeddings summarizing multi-hop information are computed using only single-hop operations on the incoming edges. We evaluate our proposed approach on three open-source datasets and two in-house datasets, and compare with three state-of-the-art algorithms (TGN-attn, TGN-ID, Jodie). We demonstrate that our graph-sprints features, combined with a machine learning classifier, achieve competitive performance (outperforming all baselines for the node classification tasks in five datasets). Simultaneously, graph-sprints significantly reduce inference latencies, achieving close to an order of magnitude speed-up in our experimental setting.Comment: 9 pages, 5 figures, 7 table

Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs

Money laundering is a global problem that concerns legitimizing proceeds from serious felonies (1.7-4 trillion euros annually) such as drug dealing, human trafficking, or corruption. The anti-money laundering systems deployed by financial institutions typically comprise rules aligned with regulatory frameworks. Human investigators review the alerts and report suspicious cases. Such systems suffer from high false-positive rates, undermining their effectiveness and resulting in high operational costs. We propose a machine learning triage model, which complements the rule-based system and learns to predict the risk of an alert accurately. Our model uses both entity-centric engineered features and attributes characterizing inter-entity relations in the form of graph-based features. We leverage time windows to construct the dynamic graph, optimizing for time and space efficiency. We validate our model on a real-world banking dataset and show how the triage model can reduce the number of false positives by 80% while detecting over 90% of true positives. In this way, our model can significantly improve anti-money laundering operations.Comment: 8 pages, 5 figure

The Italian Earthquakes and Tsunami Monitoring and Surveillance Systems

The Osservatorio Nazionale Terremoti (ONT) is the Italian seismic operational centre for monitoring earthquake, it is part of Istituto Nazionale di Geofisica e Vulcanologia (INGV) the largest Italian research institution, with focus in Earth Sciences. INGV runs the Italian National Seismic Network (network code IV) and other networks at national scale for monitoring earthquakes and tsunami. INGV is a primary node of European Integrated Data Archive (EIDA) for archiving and distributing, continuous, quality checked seismic waveforms (strong motion and weak motion recordings). ONT designed the data acquisition system to accomplish, in near-real-time, automatic earthquake detection, hypocentre and magnitude determination and evaluation of moment tensors, shake maps and other products. Database archiving of all parametric results are closely linked to the existing procedures of the INGV seismic monitoring environment and surveillance procedures. ONT organize the Italian earthquake surveillance service and the tsunami alert service (INGV is Tsunami Service Provider of the ICG/NEAM for the entire Mediterranean basin). We provide information to the Dipartimento di Protezione Civile (DPC) and to several Mediterranean countries. Earthquakes information are revised routinely by the analysts of the Italian Seismic Bulletin. The results are published on the web and are available to the scientific community and the general public.PublishedMontreal1SR TERREMOTI - Sorveglianza Sismica e Allerta Tsunam

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)