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1,444 results on '"Cappozzo, A"'

54. Three-Dimensional Reconstruction of the Human Skeleton in Motion

Author

Camomilla, Valentina, Cappozzo, Aurelio, Vannozzi, Giuseppe, Selbie, William Scott, Section editor, Müller, Bertram, Editor-in-Chief, Wolf, Sebastian I., Editor-in-Chief, Brüggemann, Gert-Peter, Section Editor, Deng, Zhigang, Section Editor, McIntosh, Andrew S., Section Editor, Miller, Freeman, Section Editor, and Selbie, W. Scott, Section Editor

Published
2018
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58. The Transmission of the Somniale Danielis, from Latin to Vernacular Italian (Laurenziano Martelli 12 and Riccardiano 859)

Author

Valerio Cappozzo

Subjects
French literature - Italian literature - Spanish literature - Portuguese literature, PQ1-3999
Abstract

The Somniale Danielis is a dream manual widely circulated in the Middle Ages and the Renaissance. It is structured through dream symbols and their concise explanation. Medieval manuscripts of the Somniale—from the ninth century to the end of the fifteenth century—generally bear the same dreams, but show changes in the structure of their entries. The coherence of its symbology throughout several centuries allows for a linguistic analysis across these dream manuals that situates them in specific cultural contexts. This article focuses on two manuscripts, each containing a Latin and an Italian version of the Somniale, and aims to show how the Italian versions develop, and vary from, the Latin texts, as the vernacular versions simplify the language of their source text in order to create shorter entries.

Published
2020
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60. SIAMOC position paper on gait analysis in clinical practice: General requirements, methods and appropriateness. Results of an Italian consensus conference

Author

Benedetti, Maria Grazia, Beghi, Ettore, De Tanti, Antonio, Cappozzo, Aurelio, Basaglia, Nino, Cutti, Andrea Giovanni, Cereatti, Andrea, Stagni, Rita, Verdini, Federica, Manca, Mario, Fantozzi, Silvia, Mazzà, Claudia, Camomilla, Valentina, Campanini, Isabella, Castagna, Anna, Cavazzuti, Lorenzo, Del Maestro, Martina, Croce, Ugo Della, Gasperi, Marco, Leo, Tommaso, Marchi, Pia, Petrarca, Maurizio, Piccinini, Luigi, Rabuffetti, Marco, Ravaschio, Andrea, Sawacha, Zimi, Spolaor, Fabiola, Tesio, Luigi, Vannozzi, Giuseppe, Visintin, Isabella, and Ferrarin, Maurizio

Published
2017
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68. Occurrence and anthropogenic-derived mortality of humpback whales (Megaptera novaeangliae) along the northern coast of Argentina, 2003–2021.

Author

Giardino, Gisela V., Gana, Joaquín C. M., De León, M. Carolina, Mandiola, M. Agustina, Dassis, Mariela, Denuncio, Pablo, Elissamburu, Andrea, Morón, Sergio, Rodríguez Heredia, Sergio, Alvarez, C. Karina, Loureiro, Juan P., Massola, Victoria, Valenzuela, Luciano O., Tamini, Leandro, Taraborelli, Paula, Saubidet, Alejandro, Faiella, Adrian, Cappozzo, H. Luis, Bastida, Ricardo O., and Rodríguez, Diego H.

Abstract

Sightings and strandings of humpback whales (Megaptera novaeangliae) along the coast of Buenos Aires Province in Argentina were once sporadic but have increased by up to 640% since 2018. Here, we assess the trends and seasonality of occurrence and anthropogenic-derived mortality in this population between 2003 and 2021. Most of the humpback whales found dead were young animals, and 27% of the stranded whales showed signs of anthropogenic interactions. The information collected from Buenos Aires Province over the past two decades clearly indicates that humpback whales are becoming more frequent and growing in numbers along the Argentinean coast. For their protection, governmental regulations need to be implemented as soon as possible. [ABSTRACT FROM AUTHOR]

Published
2024
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79. Outlier and Novelty Detection for Functional Data: a Semiparametric BayesianApproach

Author

Denti, F, Cappozzo, A, Greselin, F, Francesco Denti, Andrea Cappozzo, Francesca Greselin, Denti, F, Cappozzo, A, Greselin, F, Francesco Denti, Andrea Cappozzo, and Francesca Greselin

Abstract

A novelty detection model can be seen as a supervised classifier, trained on a fully- labeled training set, that allows for the presence of new classes in the test set not previously observed among the training units. When dealing with functional data, this requires learning the main patterns for the curves in the known classes, whilst being able to isolate signals that possess distinctive characteristics in the unlabeled set. In order to tackle this challenging problem, we propose a two-stage Bayesian semi-parametric novelty detector [2]. In the first stage, robust estimates are extracted from the training set via the Minimum Regularized Covariance Determinant (MRCD) estimator [1]. In the second stage, such information is employed to elicit informative priors within a Bayesian mixture of known groups plus a novelty term. To reflect the lack of knowledge on the latter component, we resort to a Dirichlet Process mixture model, thus overcoming the problematic a-priori specification of the expected number of novelties that may be present in the test set. The described methodology is applied to a spectroscopic dataset within a food authenticity study.

Published
2022

80. Monitoring Hyperparameter Choice for Robust Cluster Weighted Model

Author

Cappozzo, A, García-Escudero, L, Greselin, F, Mayo-Iscar, A, Andrea Cappozzo, Luis A. García-Escudero, Francesca Greselin, Agustín Mayo-Iscar, Cappozzo, A, García-Escudero, L, Greselin, F, Mayo-Iscar, A, Andrea Cappozzo, Luis A. García-Escudero, Francesca Greselin, and Agustín Mayo-Iscar

Abstract

The estimation of the ClusterWeighted Model is particularly attractive for providing explicit modeling of the explanatory variables, in a mixture of regression. The Robust version of the model requires the specification of a set of crucial parameters, like the proportion of trimmed units U, the thresholds to be adopted for the constrained estimation of group scatter and for regression errors, beyond the number of components of the Mixture. To assist the choice of such hyper-parameters, a monitoring methodology could be of great help. The purpose is to provide a set of graphical tools to guide the final user in making an informed judgment, considering a landscape of plausible choices. The final output offers a set of optimal solutions, featured by the interval of hyper-parameters values in which their optimality holds, their stability and validity. An assessment of the role and extent of the outlying observations has been provided, introducing three new silhouette plots. The purpose is to understand the possible effects of the contaminated observations, with respect to the clustering of the covariate -, and the local regression lines, following the nature of the Cluster Weighted model.

Published
2022

89. Local processes with global impact: unraveling the dynamics of gas evasion in a step-and-pool configuration

Author

Paolo Peruzzo, Matteo Cappozzo, Nicola Durighetto, and Gianluca Botter

Abstract

Headwater streams are important sources of greenhouse gases to the atmosphere. The magnitude of gas emissions originating from such streams, however, is modulated by the characteristic microtopography of the river bed, which might promote the spatial heterogeneity of turbulence and air entrainment. In particular, recent studies have revealed that step-and-pools, usually found in close sequences along mountain streams, are important hotspots of gas evasion. Yet, the mechanisms that drive gas transfer at the water-air interface in a step and pool configuration are not fully understood. Here, we numerically simulated the hydrodynamics of an artificial step-and-pool configuration to evaluate the contribution of turbulence and air entrainment to the total gas evasion induced by the falling jet. The simulation was validated using observed hydraulic features (stage, velocity) and was then utilized to determine the patterns of energy dissipation, turbulence-induced gas exchange, and bubble-mediated transport. The results show that gas evasion is led by bubble entrainment and is mostly concentrated in a small and irregular region of a few dm2 near the cascade, where the local gas transfer velocity, k, peaks at 500 md−1. The enhanced spatial heterogeneity of k in the pool does not allow one to define a priori the region of the domain where the outgassing takes place, and makes the value of the spatial mean of k inevitably scale-dependent. Accordingly, we propose that the average mass transfer velocity could not be a meaningful metric to describe the outgassing in spatially heterogeneous flow fields, such as encountered in step-and-pool rivers.

Published
2023
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96. How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy

Author

Ilaria Pasciuto, Gabriele Ligorio, Elena Bergamini, Giuseppe Vannozzi, Angelo Maria Sabatini, and Aurelio Cappozzo

Subjects
3D orientation, MEMS gyroscopes, noise sources, motion analysis, gait, biomechanics, human, numerical integration, inertial sensors, Chemical technology, TP1-1185
Abstract

In human movement analysis, 3D body segment orientation can be obtained through the numerical integration of gyroscope signals. These signals, however, are affected by errors that, for the case of micro-electro-mechanical systems, are mainly due to: constant bias, scale factor, white noise, and bias instability. The aim of this study is to assess how the orientation estimation accuracy is affected by each of these disturbances, and whether it is influenced by the angular velocity magnitude and 3D distribution across the gyroscope axes. Reference angular velocity signals, either constant or representative of human walking, were corrupted with each of the four noise types within a simulation framework. The magnitude of the angular velocity affected the error in the orientation estimation due to each noise type, except for the white noise. Additionally, the error caused by the constant bias was also influenced by the angular velocity 3D distribution. As the orientation error depends not only on the noise itself but also on the signal it is applied to, different sensor placements could enhance or mitigate the error due to each disturbance, and special attention must be paid in providing and interpreting measures of accuracy for orientation estimation algorithms.

Published
2015
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