16 resultados para Space and time

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Slot and van Emde Boas Invariance Thesis states that a time (respectively, space) cost model is reasonable for a computational model C if there are mutual simulations between Turing machines and C such that the overhead is polynomial in time (respectively, linear in space). The rationale is that under the Invariance Thesis, complexity classes such as LOGSPACE, P, PSPACE, become robust, i.e. machine independent. In this dissertation, we want to find out if it possible to define a reasonable space cost model for the lambda-calculus, the paradigmatic model for functional programming languages. We start by considering an unusual evaluation mechanism for the lambda-calculus, based on Girard's Geometry of Interaction, that was conjectured to be the key ingredient to obtain a space reasonable cost model. By a fine complexity analysis of this schema, based on new variants of non-idempotent intersection types, we disprove this conjecture. Then, we change the target of our analysis. We consider a variant over Krivine's abstract machine, a standard evaluation mechanism for the call-by-name lambda-calculus, optimized for space complexity, and implemented without any pointer. A fine analysis of the execution of (a refined version of) the encoding of Turing machines into the lambda-calculus allows us to conclude that the space consumed by this machine is indeed a reasonable space cost model. In particular, for the first time we are able to measure also sub-linear space complexities. Moreover, we transfer this result to the call-by-value case. Finally, we provide also an intersection type system that characterizes compositionally this new reasonable space measure. This is done through a minimal, yet non trivial, modification of the original de Carvalho type system.

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A full set of geochemical and Sr, Nd and Pb isotope data both on bulk-rock and mineral samples is provided for volcanic rocks representative of the whole stratigraphic succession of Lipari Island in the Aeolian archipelago. These data, together with petrographic observations and melt/fluid inclusion investigations from the literature, give outlines on the petrogenesis and evolution of magmas through the magmatic and eruptive history of Lipari. This is the result of nine successive Eruptive Epochs developing between 271 ka and historical times, as derived from recentmost volcanological and stratigraphic studies, combined with available radiometric ages and correlation of tephra layers and marine terrace deposits. These Eruptive Epochs are characterized by distinctive vents partly overlapping in space and time, mostly under control of the main regional tectonic trends (NNW-SSE, N-S and minor E-W). A large variety of lava flows, scoriaceous deposits, lava domes, coulees and pyroclastics are emplaced, ranging in composition through time from calcalkaline (CA) and high-K (HKCA) basaltic andesites to rhyolites. CA and HKCA basaltic andesitic to dacitic magmas were erupted between 271 and 81 ka (Eruptive Epochs 1-6) from volcanic edifices located along the western coast of the island (and subordinately the eastern Monterosa) and the M.Chirica and M.S.Angelo stratocones. These mafic to intermediate magmas mainly evolved through AFC and RAFC processes, involving fractionation of mafic phases, assimilation of wall rocks and mixing with newly injected mafic magmas. Following a 40 ka-long period of volcanic quiescence, the rhyolitic magmas were lately erupted from eruptive vents located in the southern and north-eastern sectors of Lipari between 40 ka and historical times (Eruptive Epochs 7-9). They are suggested to derive from the previous mafic to intermediate melts through AFC processes. During the early phases of rhyolitic magmatism (Eruptive Epochs 7-8), enclaves-rich rocks and banded pumices, ranging in composition from HKCA dacites to low-SiO2 rhyolites were erupted, representing the products of magma mixing between fresh mafic magmas and the fractionated rhyolitic melts. The interaction of mantle-derived magmas with the crust represents an essential process during the whole magmatic hystory of Lipari, and is responsible for the wide range of observed geochemical and isotopic variations. The crustal contribution was particularly important during the intermediate phases of activity of Lipari when the cordierite-bearing lavas were erupted from the M. S.Angelo volcano (Eruptive Epoch 5, 105 ka). These lavas are interpreted as the result of mixing and subsequent hybridization of mantle-derived magmas, akin to the ones characterizing the older phases of activity of Lipari (Eruptive Epochs 1-4), and crustal anatectic melts derived from dehydration-melting reactions of metapelites in the lower crust. A comparison between the adjacent islands of Lipari and Vulcano outlines that their mafic to intermediate magmas seem to be genetically connected and derive from a similar mantle source affected by different degrees of partial melting (and variable extent of crustal assimilation) producing either the CA magmas of Lipari (higher degrees) or the HKCA to SHO magmas of Vulcano (lower degrees). On a regional scale, the most primitive rocks (SiO2<56%, MgO>3.5%) of Lipari, Vulcano, Salina and Filicudi are suggested to derive from a similar MORB-like source, variably metasomatized by aqueous fluids coming from the slab and subordinately by the additions of sediments.

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Can space and place foster child development, and in particular social competence and ecological literacy? If yes, how can space and place do that? This study shows that the answer to the first question is positive and then tries to explain the way space and place can make a difference. The thesis begins with the review of literature from different disciplines – child development and child psychology, education, environmental psychology, architecture and landscape architecture. Some bridges among such disciplines are created and in some cases the ideas from the different areas of research merge: thus, this is an interdisciplinary study. The interdisciplinary knowledge from these disciplines is translated into a range of design suggestions that can foster the development of social competence and ecological literacy. Using scientific knowledge from different disciplines is a way of introducing forms of evidence into the development of design criteria. However, the definition of design criteria also has to pass through the study of a series of school buildings and un-built projects: case studies can give a positive contribution to the criteria because examples and good practices can help “translating” the theoretical knowledge into design ideas and illustrations. To do that, the different case studies have to be assessed in relation to the various themes that emerged in the literature review. Finally, research by design can be used to help define the illustrated design criteria: based on all the background knowledge that has been built, the role of the architect is to provide a series of different design solutions that can give answers to the different “questions” emerged in the literature review.

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The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

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Plant communities on weathered rock and outcrops are characterized by high values in species richness (Dengler 2006) and often persist on small and fragmented surfaces. Yet very few studies have examined the relationships between heterogeneity and plant diversity at small scales, in particular in poor-nutrient and low productive environment (Shmida and Wilson 1985, Lundholm 2003). In order to assess these relationships both in space and time in relationship, two different approaches were employed in the present study, in two gypsum outcrops of Northern Apennine. Diachronic and synchronic samplings from April 2012 to March 2013 were performed. A 50x50 cm plot was used in both samplings such as the sampling unit base. The diachronic survey aims to investigate seasonal patterning of plant diversity by the use of images analysis techniques integrated with field data and considering also seasonal climatic trend, the substrate quality and its variation in time. The purpose of the further, synchronic sampling was to describe plant diversity pattern as a function of the environmental heterogeneity meaning in substrate typologies, soil depth and topographic features. Results showed that responses of diversity pattern depend both on the resources availability, environmental heterogeneity and the manner in which the different taxonomic group access to them during the year. Species richness and Shannon diversity were positively affected by increasing in substrate heterogeneity. Furthermore a good turnover in seasonal species occurrence was detected. This vegetation may be described by the coexistence of three groups of species which created a gradient from early colonization stages, characterized by greater slope and predominance of bare rock, gradually to situation of more developed soil.

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Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

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Marine healthy ecosystems support life on Earth and human well-being thanks to their biodiversity, which is proven to decline mainly due to anthropogenic stressors. Monitoring how marine biodiversity changes trough space and time is needed to properly define and enroll effective actions towards habitat conservation and preservation. This is particularly needed in those areas that are very rich in species compared to their low surface extension and are characterized by strong anthropic pressures, such as the Mediterranean Sea. Subtidal rocky benthic Mediterranean habitats have a complex structural architecture, hosting a panoply of tiny organisms (cryptofauna) that inhabit crevices and caves, but that are still unknown. Different artificial standardized sampling structures (SSS) and methods have been developed and employed to characterize the cryptofauna, allowing for data replicability and comparability across regions. Organisms growing on these artificial structures can be identified coupling morphological taxonomy and DNA barcoding and metabarcoding. The metabarcoding allows for the identification of organisms in a bulk sample without morphological analysis, and it is based on comparing the genetic similarities of the assessed organisms with barcoding sequences present in online barcoding repositories. Nevertheless, barcoded species nowadays represent only a small portion of known species, and barcoding reference databases are not always curated and updated on a regular basis. In this Thesis I used an integrative approach to characterize benthic marine biodiversity, specifically coupling morphological and molecular techniques with the employment of SSS. Moreover, I upgraded the actual status of COI (cytochrome c oxidase subunit I) barcoding of marine metazoans, and I built a customized COI barcoding reference database for metabarcoding studies on temperate biogenic reefs. This work implemented the knowledge about diversity of Mediterranean marine communities, laying the groundworks for monitoring marine and environmental changes that will occur in the next future as consequences of anthropic and climate threats.

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A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.

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La tesi si propone di tracciare un confronto tra due autori molto distanti tra loro sia nel tempo che nello spazio: Nikolaj Gogol’ e Dario Fo; in particolare si analizzano le commedie Il Revisore di Gogol’ (1836) e Morte accidentale di un anarchico di Fo (1970). Il nesso tra le due opere è stato individuato dalla critica italiana (Franco Quadri, Ferdinando Taviani, Paolo Puppa). Tuttavia gli spunti interpretativi e comparativi non sono mai stati sviluppati appieno della critica. Nonostante le grandi distanze temporali e spaziali, l’analisi si propone dunque di evidenziare i numerosi motivi di consonanza tra le due opere e i due autori, che peraltro testimoniano anche della grande fortuna arrisa all’estero all’autore ucraino, attraverso la mediazione del teatro russo-sovietico del XX secolo. L’approccio metodologico adottato si fonda sui testi dei formalisti russi, di Lotman, sulla Stilkritik di Aurbach, sugli studi di Frye sulla Bibbia intesa come “grande canone” della letteratura occidentale, e soprattutto sull’analisi della cultura carnevalesca e popolare condotta da Bachtin. Lo studio è indirizzato su alcuni elementi precisi: la trama, lo scambio della personalità, l’impostura, la paura e il riso. Per ciascun di questi elementi è stata svolta l’analisi comparativa delle due opere, situandole in un contesto letterario e culturale che va all’antichità e al Medio Evo, dal quale entrambi gli autori mutuano molte suggestioni.

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I temi della ricerca riguardano il rapporto fra avvento del web e la modificazione dei processi di formazione di identità personale e sociale, della percezione dello spazio e del tempo, del prosumerismo digitale e delle varie forme di partecipazione ed associazione. Centrale è stata l’analisi del rapporto fra il Web 2.0 e la trasformazione delle forme di comunicazione a vari livelli, sia personali che sociali. Partendo da una analisi dei contesti socio-economici globali che hanno trasformato la società moderna nella società informazionale, è stato impostato un percorso di ricerca che approfondisse gli attuali criteri di strutturazione della propria identità, alla luce dell’avvento dei social network e delle reti virtuali di comunicazione come strumento preferenziale di socializzazione. La realtà delle reti sociali è stata analizzata in un’ottica di aggregazione spontanea mirata tanto alla comunicazione quanto alla tutela dei consumatori, e le trasformazioni portate dal Web 2.0 sono state la chiave di lettura per ridefinire i parametri della partecipazione dal basso generata dalla rete. Per comprendere la portata di tali trasformazioni nel contesto italiano è stato impostato un paragone tra l’uso del web negli Stati Uniti e in Italia, avendo le recente campagne elettorali dimostrato l’importanza del web nella partecipazione politica bottom-up; il percorso di ricerca ha dunque affrontato una comparazione di due casi, quello italiano e quello statunitense, finalizzato a comprendere l’attuale ruolo dell’utente nelle dinamiche di comunicazione mediatica. Per focalizzare al meglio le trasformazioni sociali generate dalla partecipazione on line è stato infine analizzato il caso del citizen journalism, per misurare, attraverso la metodologia dell’etnografia digitale, l’entità delle trasformazioni in corso. Il portale di giornalismo partecipativo YouReporter è stato il contesto privilegiato dove poter verificare le ipotesi iniziali circa le dinamiche di partecipazione, e il supporto di programmi di elaborazione statistica netnografica ha permesso di destrutturare al meglio tali dinamiche.

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Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

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Il mio progetto di ricerca è nato da una riflessione concernente una domanda fondamentale che si pongono gli studiosi della comunicazione digitale: le attuali tecnologie mediali che hanno creato nuovi modelli comunicativi e inaugurato inedite modalità di interrelazione sociale conducono a un dualismo digitale o a una realtà aumentata? Si è cercato di dare una risposta a questo interrogativo attraverso un’indagine compiuta su un social network, Facebook, che è la piattaforma digitale più diffusa nel mondo. L’analisi su Facebook, è stata preceduta da una riflessione sui concetti dello spazio e del tempo elaborati dalla letteratura filosofica e sociologica. Tale riflessione è stata propedeutica all’analisi volta a cogliere l’impatto che hanno avuto sulla relazionalità intersoggettiva e sulle dinamiche di realizzazione del sé l’interazione semantica nello spazio delimitato della piazza tradizionale, la molteplicità e la potenza seduttiva delle offerte comunicative dei media elettronici nella estensione della piazza massmediale e soprattutto la nascita e l’affermazione del cyberspazio come luogo della comunicazione nella piazza digitale. Se la peculiarità della piazza tradizionale è nel farsi dei rapporti face to face e quella della piazza massmediale nella funzione rilevante della fonte rispetto al destinatario, la caratteristica della piazza digitale consiste nella creazione autonoma di un orizzonte inclusivo che comprende ogni soggetto che si collega con la rete il quale, all’interno del network, riveste il doppio ruolo di consumatore e di produttore di messaggi. Con l’avvento dell’online nella prassi della relazionalità sociale si producono e si attuano due piani di interazioni comunicative, uno relativo all’online e l’altro relativo all’offline. L’ipotesi di lavoro che è stata guida della mia ricerca è che la pervasività dell’online conduca all’integrazione dei due segmenti comunicativi: l’esperienza della comunicazione digitale si inserisce nella prassi sociale quotidiana arricchendo i rapporti semantici propri della relazione face to face e influenzandoli profondamente.

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La città medievale di Leopoli-Cencelle (fondata da Papa Leone IV nell‘854 d.C. non lontano da Civitavecchia) è stata oggetto di studio e di periodiche campagne di scavo a partire dal 1994. Le stratigrafie investigate con metodi tradizionali, hanno portato alla luce le numerose trasformazioni che la città ha subìto nel corso della sua esistenza in vita. Case, torri, botteghe e strati di vissuto, sono stati interpretati sin dall’inizio dello scavo basandosi sulla documentazione tradizionale e bi-dimensionale, legata al dato cartaceo e al disegno. Il presente lavoro intende re-interpretare i dati di scavo con l’ausilio delle tecnologie digitali. Per il progetto sono stati utilizzati un laser scanner, tecniche di Computer Vision e modellazione 3D. I tre metodi sono stati combinati in modo da poter visualizzare tridimensionalmente gli edifici abitativi scavati, con la possibilità di sovrapporre semplici modelli 3D che permettano di formulare ipotesi differenti sulla forma e sull’uso degli spazi. Modellare spazio e tempo offrendo varie possibilità di scelta, permette di combinare i dati reali tridimensionali, acquisiti con un laser scanner, con semplici modelli filologici in 3D e offre l’opportunità di valutare diverse possibili interpretazioni delle caratteristiche dell’edificio in base agli spazi, ai materiali, alle tecniche costruttive. Lo scopo del progetto è andare oltre la Realtà Virtuale, con la possibilità di analizzare i resti e di re-interpretare la funzione di un edificio, sia in fase di scavo che a scavo concluso. Dal punto di vista della ricerca, la possibilità di visualizzare le ipotesi sul campo favorisce una comprensione più profonda del contesto archeologico. Un secondo obiettivo è la comunicazione a un pubblico di “non-archeologi”. Si vuole offrire a normali visitatori la possibilità di comprendere e sperimentare il processo interpretativo, fornendo loro qualcosa in più rispetto a una sola ipotesi definitiva.

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Architettura e musica. Spazio e tempo. Suono. Esperienza. Queste le parole chiave da cui ha preso avvio la mia ricerca. Tutto è iniziato dall’intuizione dell’esistenza di un legame tra due discipline cui ho dedicato molto tempo e studio, completando due percorsi accademici paralleli, la Facoltà di architettura e il Conservatorio. Dopo un lavoro d’individuazione e analisi degli infiniti spunti di riflessione che il tema offriva, ho focalizzato l’attenzione su uno degli esempi più emblematici di collaborazione tra un architetto e un musicista realizzatasi nel Novecento: Prometeo, tragedia dell’ascolto (1984), composta da Luigi Nono con la collaborazione di Massimo Cacciari e Renzo Piano. Attraverso lo studio di Prometeo ho potuto affrontare la trattazione di molte delle possibili declinazioni del rapporto interdisciplinare tra musica e architettura. La ricerca si è svolta principalmente sullo studio dei materiali conservati presso l’Archivio Luigi Nono e l’archivio della Fondazione Renzo Piano. La tesi è organizzata in tre parti: una prima parte in cui si affronta il tema del ruolo dello spazio nelle opere di Nono precedenti a Prometeo, facendo emergere l’importanza dell’ambiente culturale e sonoro veneziano; una seconda parte in cui si approfondisce il processo compositivo che ha portato alle rappresentazioni di Prometeo a Venezia, Milano e a Parigi; una terza parte in cui si prende in considerazione quanto avvenuto dopo Prometeo e si riflette sui contributi che questa esperienza può portare alla progettazione di spazi per la musica, analizzando diversi allestimenti dell’opera senza arca e prendendo in considerazione i progetti dell’auditorium dell’International Art Village di Akiyoshidai e della sala della nuova Philharmonie di Parigi. Lo studio dell’esperienza di Prometeo ha lo scopo di stimolare la curiosità verso la ricerca e la sperimentazione di quegli infiniti possibili della composizione architettonica e musicale di cui parla Nono.

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The present Dissertation shows how recent statistical analysis tools and open datasets can be exploited to improve modelling accuracy in two distinct yet interconnected domains of flood hazard (FH) assessment. In the first Part, unsupervised artificial neural networks are employed as regional models for sub-daily rainfall extremes. The models aim to learn a robust relation to estimate locally the parameters of Gumbel distributions of extreme rainfall depths for any sub-daily duration (1-24h). The predictions depend on twenty morphoclimatic descriptors. A large study area in north-central Italy is adopted, where 2238 annual maximum series are available. Validation is performed over an independent set of 100 gauges. Our results show that multivariate ANNs may remarkably improve the estimation of percentiles relative to the benchmark approach from the literature, where Gumbel parameters depend on mean annual precipitation. Finally, we show that the very nature of the proposed ANN models makes them suitable for interpolating predicted sub-daily rainfall quantiles across space and time-aggregation intervals. In the second Part, decision trees are used to combine a selected blend of input geomorphic descriptors for predicting FH. Relative to existing DEM-based approaches, this method is innovative, as it relies on the combination of three characteristics: (1) simple multivariate models, (2) a set of exclusively DEM-based descriptors as input, and (3) an existing FH map as reference information. First, the methods are applied to northern Italy, represented with the MERIT DEM (∼90m resolution), and second, to the whole of Italy, represented with the EU-DEM (25m resolution). The results show that multivariate approaches may (a) significantly enhance flood-prone areas delineation relative to a selected univariate one, (b) provide accurate predictions of expected inundation depths, (c) produce encouraging results in extrapolation, (d) complete the information of imperfect reference maps, and (e) conveniently convert binary maps into continuous representation of FH.