3,671 research outputs found
Além da enxada, a utopia: a colonização italiana no oeste catarinense
No full textDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Filosofia e Ciências Humanas. Programa de Pós-Graduação em História.Através da teoria e metodologia da História Oral, busca perceber a experiência migratória dos italianos e seus descendentes que migraram da Região Colonial Italiana, no Rio Grande do Sul, para o Oeste de Santa Catarina, a partir das primeiras décadas do séc. XX. Apresenta vários aspectos do cotidiano dos migrantes na nova terra, como o trabalho, o lazer e a família. Analisa quais as representações do passado são transmitidas pelas pessoas que vivenciaram a referida experiência migratória
A imagem de Alessandro Baricco no Brasil
No full textDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Comunicação e Expressão, Programa de Pós-Graduação em Estudos da Tradução, Florianópolis, 2013.Com a intenção de delinear o modo pelo qual o escritor italiano Alessandro Baricco se inseriu no sistema literário brasileiro e os caminhos percorridos pelos seus livros traduzidos, esta dissertação dá voz às experiências tradutórias de seus tradutores. A inserção de Bariccono Brasil tem seu início em 1997, através de uma proposição da Profa. Dra. Roberta Barni à editora Iluminuras da tradução de Oceano Mare. A partir daí, outras sete obras foram publicadas no Brasil, sendo três delas traduzidas por Roberta Barni e as outras quatro por quatro tradutores diferentes. De um lado, considera-se o tradutor como figura principal namediação entre culturas, e, de outro, se analisa a realidade desta figuradentro do sistema literário, sua invisibilidade, seus limites e o exercíciode sua profissão. A pesquisa conta, ainda, com críticas e resenhas referentes ao autor italiano publicadas em jornais consagrados no Brasil, considerando estas como parte constituinte da imagem de Baricco refletida em território nacional. Abstract : Intending to delineate the way the Italian writer Alessandro Baricco has been inserted in the Brazilian literary system and the paths his translated books have followed, this thesis gives voice to the translating experiences of his translators. Baricco's insertion in Brazil began in 1997, through a personal project of Dr. Roberta Barni, with her translation of Oceano Mare. Since then, seven other of his works have been published in Brazil, three of which were translated by Roberta Barni and the other four by four different translators. On the one hand,the translator is considered as the main figure in mediation betweencultures and, on the other, this figure's reality is analyzed within theliterary system: its invisibility, its limits and its professional practice. Criticisms and reviews of this Italian author published in well established Brazilian newspapers are also considered, with the understanding that they are part of Baricco's image reflected here
“Famiglie in acqua”: un’esperienza “sportiva” orientata allo sviluppo globale di soggetti con disturbi dello spettro autistico.
No full textIl presente contributo descrive una ricerca empirica ispirata all’approccio etnometodologico, attraverso la quale si è indagato un progetto educativo rivolto a famiglie con bambini caratterizzati da disturbi dello spettro autistico. Sia l’indagine epistemica che il percorso didattico si sono focalizzati su particolari tipi d’azione: quelle spontanee, definite ludemi perché considerate alla stregua di segnali ludici. Questi ultimi risultano facilmente individuabili in quanto si tratta di espressioni liberamente emesse da parte della persona, dunque spiccano nei confronti dei movimenti non spontanei. Adottando la cornice teorica della Prasseologia motoria, i ludemi sono stati analizzati e classificati come elementi di un preciso codice prassemico, operazione risultata estremamente utile al fine di verificare con una certa precisione dimensioni quali: adeguatezza del contesto, andamento dello sviluppo sia dei singoli bambini che del gruppo, effetti dell’offerta formativa. I risultati mostrano infatti come il percorso appaia coerente con gli obiettivi attesi, confermando che gli stimoli forniti dal contesto appaiono in grado di favorire lo sviluppo comunicativo e delle autonomie dei partecipanti, evidenziando pure l'adeguatezza di alcuni aspetti didattici. In altre parole l’indagine non si è limitata a verificare l’utilità del percorso, ma ha anche cercato di mostrare le dimensioni e gli elementi processuali capaci di favorire il raggiungimento dei fini auspicati.This paper describes an empirical research inspired by an ethnomethodological approach, through which an educational project, designed for families with autism spectrum disorders children, was investigated. Both the epistemic work, and the didactic path, focus on a particular type of action: the spontaneous one, defined as “play signs” because it is considered as playful communication.
The latter is easily recognizable, because it is an expressions freely issued by a person, therefore stand out in contrast to a non-spontaneous action. By adopting the Motor Praxeology theoretical
framework, playful signs were analysed and classified as elements of a precise “praxeological code”. That operation seems extremely useful, in order to precisely evaluate some dimensions,
such as: type of action, particularly in relation to the context; development of both individual child and the group; educational offer’s impact. Evidences show that the project it appears consistent
with the expected goals, confirming that the stimuli provided by games played in a swimming pool context, are effective for the improvement of participants’ communication development and autonomy. In other words, the study did not limit itself to the project’s efficacy approval, but to show elements and methods able to achieve the expected aims
Dalle immagini allo spazio 3D: il ruolo dei punti chiave semantici per la percezione 3D
No full textUno degli obiettivi della Computer Vision è quello di comprendere la percezione 3D umana attraverso rappresentazioni 2D come immagini e video. Estrarre informazioni 3D robuste da quest’analisi è una sfida significativa. Questa tesi si concentra su rappresentazioni 3D basate su punti chiave, esplorando applicazioni in differenti scenari reali. Differentemente dai tradizionali descrittori puntuali come ORB o SIFT, i punti chiave semantici stabiliscono correlazioni tra specifici punti 3D appartenenti a oggetti rigidi o articolati. I recenti sviluppi in Deep Learning, in particolar modo nel rilevamento di punti chiave 2D, hanno aperto la strada per affrontare problemi complessi di visione 3D. Questa tesi dimostra l’applicazione di questi metodi nella guida autonoma e nella videosorveglianza, evidenziando la robustezza e la precisione nel ridurre il divario tra il piano immagine 2D e il mondo 3D.
Nel conteso automotive, la nostro indagine si concentra sui problemi di sintetizzazione di nuove viste e di ricostruzione 3D di veicoli in ambienti urbani. La rappresentazione 3D di un veicolo in una scena può essere utile per l’analisi del traffico e la prevenzione di incidenti. Perciò, progettiamo un metodo che sfrutta la localizzazione di punti chiave 2D in modo da aumentare le caratteristiche visuali per l’accurata classificazione di modelli 3D di veicoli. Assicurando una classificazione robusta, studiamo come migliorare la generazione di veicoli sintetici da punti di vista non visti attraverso un sistema di Deep Learning trainato su un insieme di immagini da singoli punti di vista. In aggiunta, per esplorare tecniche più sofisticate di ricostruzione 3D di oggetti da immagini, introduciamo un’architettura di Deep Learning capace di ricostruire oggetti di diverse categorie. Questo approccio è allenato su un insieme di immagini da singoli punti di vista e comporta la deformazione di rappresentazioni 3D esplicite.
La seconda area di ricerca si concentra sulla predizione di scheletri 3D di persone e robot osservati da una prospettiva esterna come le camere di videosorveglianza. I punti chiave in questo contesto sono integrati nella definizione di scheletro rappresentato come un grafo di punti semantici. Il focus iniziale è sul dominio robotico dove un sistema intelligente che predice scheletri 3D può essere cruciale per la sicurezza in ambienti collaborativi condivisi da persone e robot. Considerando le difficoltà nell’ottenere dataset reali in robotica, enfatizziamo il ruolo della simulazione. Il nostro approccio comporta la raccolta di un dataset sintetico e reale, affrontando il problema della stima della posa 3D attraverso una rappresentazione a due mappe di calore. Esploriamo il divario tra il dominio sintetico e reale utilizzando le mappe di profondità per aumentare l’accuratezza. Introducendo informazioni temporali, il nostro sistema sposa il nuovo paradigma di Pose Nowcasting, in cui predire le pose future rappresenta un problema ausiliario per raffinare la precisione della posa corrente. Passando allo scenario umano, proponiamo un sistema di raffinamento della posa basato sull’analisi di mappe di profondità. Contemporaneamente, la nostra indagine si estende all’interazione uomo-computer, in cui presentiamo un metodo non supervisionato per rilevare e classificare gesti delle mani dinamici usando dati di un sensore che traccia il movimento.
Questa tesi punta a dare un valido contributo all’intersezione tra la 3D Computer Vision e il Deep Learning in vari domini. Dopo uno sguardo sullo stato dell’arte esistente sui problemi di ricostruzione 3D e stima della posa 3D, presentiamo i nostri metodi con una spiegazione tecnica esaustiva supportata da indagini dettagliate dei risultati condotte su dataset ampiamente riconosciuti in letteratura.One of the goals of the Computer Vision community is to comprehend human 3D perception through 2D representations like images and videos. Extracting robust 3D insights from these analyses is a significant challenge. This dissertation focuses on the keypoint-based 3D representation, exploring applications in different real-world scenarios. Unlike traditional pointwise feature descriptors like ORB or SIFT, semantic keypoints establish correlations between specific 3D points belonging to a rigid or articulated object. Recent advances in Deep Learning, particularly in 2D keypoints detection, have paved the way for addressing complex 3D vision problem. This thesis demonstrates the application of these methods in autonomous driving and video surveillance, showcasing their robustness and precision in bridging the gap between 2D image planes and the 3D world.
In the automotive context, our investigation centers on the tasks of novel view synthesis and 3D reconstruction of vehicles within urban scenes. A 3D representation of a vehicle in a scene can be valuable for traffic analysis and accident prevention. To achieve this, we design a method leveraging a 2D keypoint localization network to augment visual features for accurate classification of 3D vehicle models. Ensuring a robust classification, we study how to improve the generation of synthetic vehicles from unseen novel views through a deep learning pipeline trained on a collection of single-view images. Additionally, to explore more sophisticated techniques for 3D object reconstruction from images, we introduce a deep learning architecture capable of reconstructing objects across multiple categories. This approach is trained on a dataset of single-view images and involves the deformation of explicit 3D representations.
The second research area is focused on predicting the 3D skeletons of both humans and robots, observed from an external perspective, such as a video surveillance camera. The keypoints in this context are integrated into the definition of a skeleton, depicted as a graph of semantic points. Our initial focus is on the robotics domain, where an intelligent system for predicting 3D skeletons can be crucial for safety in collaborative environments shared by humans and robots. Given the challenges of obtaining real datasets in robotics, we emphasize the role of simulation. Our approach involves collecting a synthetic and real dataset, addressing the 3D pose estimation task through a double heatmap-based representation. We explore the domain gap between the synthetic and real data, utilizing depth maps to enhance accuracy. Introducing temporal cues, our pipeline embraces the novel Pose Nowcasting paradigm, where predicting future poses serves as an auxiliary task to refine current pose precision. Shifting to the human scenario, we propose a pose refinement framework based on depth map analysis. Simultaneously, our investigation extends to Human-Computer Interaction, where we present an unsupervised method for detecting and classifying dynamic hand gestures using data from a motion tracking sensor.
This thesis seeks to make a valuable contribution to the intersection of 3D Computer Vision and Deep Learning across various domains. Following an overview of the existing state-of-the-art in 3D reconstruction and 3D pose estimation tasks, we present our proposed methods with a comprehensive technical explanation supported by a detailed experimental investigation conducted on benchmark datasets widely acknowledged in the literature
Groundwater and ground displacement monitoring in the source area of the Montecchi earthflow (Northern Apennines, Italy)
No full textThe importance of pore water pressure regime for landslide activity is generally accepted. In the case of earthflows, generalized failures (reactivations) are rare and sustained slow movements can proceed for decades. The relationship between precipitation, pore water pressure responses and movement is not straightforward. We document rainfall, pore pressure regime and displacements in the source area of an active earthflow. Pressure heads at shallow depth are clearly related to infiltration from the surface and can be satisfactorily reproduced by a diffusive model while the hypothesis of gravity-dominated flow can be rejected based on the short delay between rainfall and pressure response. Displacement rates are very small to zero during the summer and increase a couple of months later than the onset of the precipitation of the wet season. Only late in the wet season, velocities attain peak values (up to 4 mm/day) and show a remarkable correlation to rainfall episodes. Higher displacement rates correspond to unexceptional pressure head values, we therefore believe that alternative mechanisms of water pressure build-up may exist. Fractures likely act as a preferential flow system and influence both the hydrological responses to rainfall and the deformation behavior of the landslide
Lithologic and morphologic controls on debris flow dynamics in the Dolomites (Italian Alps, Italy)
No full textIn high-relief landscapes, debris flows represent the most efficient mean of erosion and sediment transport across
spatial scales ranging from hectares to tens of square kilometers.
In the Dolomite region of Italy, the landscape is dominated by steep massifs mainly made of limestone and
dolostone rocks. Abundant talus and fan deposits connect the bottom of the valleys to the rocky massifs. Thick
debris talus was deposited in post-glacial climatic conditions and is actively fed by steep dolomitic rock walls.
Debris flows are widespread over the territory. They are commonly triggered by water discharge concentrated on
steep headwater catchments and delivered to talus slopes. Headwater catchments are typically very steep (45°-60°
on the average) and mostly consist of exposed bedrock with no vegetation and sparse to none soil cover. Debris
flow fans are relatively steep (10 to 30°)
Our study area extends over 250 km2 and includes about one-hundred debris flow catchments. We take advantage
of the remarkable morphological similarities of the catchments to characterize their lithology, morphometry and
investigate scale-relationships. We use LiDAR, field surveys and aerial photo interpretation to describe the
principal topographic conditions associated with debris-flow initiation, transportation, and deposition. Debris
flow-prone catchments associated to recent activity has been selected to investigate the role of geology and
morphology as influencing factor at basin scale. They display a decreasing specific sediment yield with increasing
size. Depending on the abundance of loose debris deposits, volumes of sediment delivered to the fan span about
one order of magnitude. Dependence of deposited sediment volumes on the basin scale is clear and translates into
an inverse proportionality when specific yield is considered
Deformation responses of slow moving landslides to seasonal rainfall in the Northern Apennines, measured by InSAR
No full textSlow moving landslides are widespread geomorphological features in the Northern Apennines of Italy where they represent one of the main landscape forming processes. The lithology of the Northern Apennines fold and thrust belt is characterized by alternations of sandstone, siltstone and clayshales, also known as flysch, and clay shales with a chaotic block in matrix fabric, which are often interpreted as tectonic or sedimentary mélanges. While flysch rocks with a high pelitic fraction host earthslides that occasionally evolve into flow like movements, earthflows are the dominant landslide type in chaotic clay shales. In the present work, we document the kinematic response to rainfall of landslides in these different lithologies using radar interferometry. The study area includes three river catchments in the Northern Apennines. Here, the Mediterranean climate is characterized by two wet seasons during autumn and spring respectively, separated by dry summers and winters with moderate precipitation. We use SAR imagery from the X-band satellite COSMO SkyMed and from the C-band satellite Sentinel 1 to retrieve spatial displacement measurements between 2009 and 2016 for 25 landslides in our area of interest. We also document detailed temporal and spatial deformation signals for eight representative landslides, although the InSAR derived deformation signal is only well constrained by our dataset during the years 2013 and 2015. In spring 2013, long enduring rainfalls struck the study area and numerous landslide reactivations were documented by the regional authorities. During 2013, we measured higher displacement rates on the landslides in pelitic flysch formations compared to the earthflows in the clay shales. Slower mean velocities were measured on most landslides during 2015. We analyse the temporal deformation signal of our eight representative landslides and compare the temporal response to precipitation. We show that earthslides in pelitic flysch formations accelerate faster than earthflows in chaotic clay shales and reach higher velocities, while the kinematic behaviour of the earthflows can be described as rather steady with only minor accelerations. Although we have no detailed pore pressure measurements for the period of interest, the observed behaviour can be explained in our view by the morphological and hydrological characteristics of the different landslide types. On the one hand landslide material and bedrock in the pelitic flysch rocks are more resistant, which is why slope angles are higher in this lithology. On the other hand, landslides in the pelitic flysch formations have often deeper slip surfaces and landslide material is more permeable. This is why long persistent rainfall is necessary to saturate the landslide material and induce pore pressures that are high enough to trigger displacement
Uncertainty of debris flow mobility relationships and its influence on the prediction of inundated areas
No full textEmpirical mobility relationships can be used for delineating debris flow inundated areas. A database of
documented events in alpine mountain catchments of northeastern Italy is used to test the model DFlowz
(Berti and Simoni, 2007). We back-analyzed 25 DF events, ranging in volume from 3000 to 350,000 m3, with
the support of high resolution topographic information derived from LiDAR. The analysis makes use of an
objective methodology for evaluating the accuracy of the predictions and involves the calibration of the model
based on factors describing the uncertainty associated with the empirical relationships.
Results indicate that the model is capable of reproducing the observed behavior with amaximum uncertainty
of a factor of 3. The most relevant source of error lies in the estimation of the deposited volumes which affects
the results of back-calculation and is mainly responsible also for the scatter associated with the empirical
mobility relationships. On the contrary, the influence of different flow properties on the depositional process
appears to play a minor role as the mutual relations between the three main scaling parameters (volume,
inundated area, and cross-sectional area) are respected in the vast majority of cases and calibrated mobility
coefficients show no significant relationship with the angle of reach of the deposit
Performance and reliability of empirical mobility relationships for the prediction of debris flow inundated areas.
No full textEmpirical mobility relationships can be used for preliminary DF Hazard assessment. An adaptation of the original relationships has been proposed for alpine debris flows (DFLOWZ model; Berti and Simoni, 2007). Once a reference debris flow volume is chosen, the code DFLOWZ allows to estimate the area potentially affected by the event based on the mutual relationships between channel cross-sectional area, planimetric area of the deposit and overall volume.
We back-analyzed 25 DF events occurred in the Bolzano province (Italy), ranging in volume from 3,000 to 300,000 m3 and evalutated the performance of the automated method through an objective reliability index. Our aim is:
- evaluate the effects of uncertainty associated with the empirical mobility relationships;
- assess other possible sources of error or violations of the assumptions that underlie the model.
Results indicate that a high-resolution DEM (≤ 2.5 m) is essential to get a reliable inundation prediction over a fan. The code itself performs well, in a wide range of situations, demonstrating the conceptual correctness of underlying assumptions. The most relevant source of error remains the uncertainty associated with the empirical mobility relationships, due mainly to errors in volume measurements of DF deposits. Their improvement can be achieved through the collection of high quality field data of DF events
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