169,966 research outputs found
Città che si adattano? Adaptive cities?
No full textThe overall editorial project includes four books: Book 1 Adattabilità o incapacità adattiva di fronte al cambiamento / Adaptability or Adaptive Inability in the Face of Change (ed. by C. Cuneo), Book 2 Adattabilità in circostanze ordinarie Ordinary / Conditions Adaptability (ed. by C. Devoti and P. Bolca), Book 3 Processi urbani di adattamento e resilienza tra permanenza e precarietà / Urban Processes of Adaptation and Resilience Between Permanence and Precariousness (ed. by A. Longhi), Book 4 Strategie di adattamento e patrimonio critico / Adaptive Strategies and Critical Heritage (ed. by R. Tamborrino). The publication collects 509 chapters of 634 contributors from several universities and countries questioning the matter of urban adaptiveness and resilience, urban changes, traumatic events, disasters, and cultural heritage in face of extraordinary conditions. The papers followed the process of double peer review
Classification of hyperspectral images with copulas
No full textIn the last decade, supervised learning methods for the classification of remotely sensed images (RSI) have grown significantly, especially for hyper-spectral (HS) images. Recently, deep learning-based approaches have produced encouraging results for the land cover classification of HS images. In particular, the Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) have shown good performance. However, these methods suffer for the problem of the hyperparameter optimization or tuning that requires a high computational cost; moreover, they are sensitive to the number of observations in the learning phase. In this work we propose a novel supervised learning algorithm based on the use of copula functions for the classification of hyperspectral images called CopSCHI (Copula Supervised Classification of Hyperspectral Images). In particular, we start with a dimensionality reduction technique based on Singular Value Decomposition (SVD) in order to extract a small number of relevant features that best preserve the characteristics of the original image. Afterward, we learn the classifier through a dynamic choice of copulas that allows us to identify the distribution of the different classes within the dataset. The use of copulas proves to be a good choice due to their ability to recognize the probability distribution of classes and hence an accurate final classification with low computational cost can be conducted. The proposed approach was tested on two benchmark datasets widely used in literature. The experimental results confirm that CopSCHI outperforms the state-of-the-art methods considered in this paper as competitors
Prefazione
No full textI papers raccolti in questa opera esplorano una pluralità di argomenti che spaziano dalla pianificazione territoriale alla rigenerazione urbana, dalle strategie per la valorizzazione delle aree interne e dei centri storici allo sviluppo delle filiere olivicolo-olearie, senza trascurare l’importanza dell’approccio integrato della “One Health”
On the Classification of Hyperspectral Images with Different Copula Family
No full textIn the task of remote sensing, the Hyperspectral image (HSI) classification to analyze land cover is an established research topic. However, the nature of remote sensing data still poses several challenges including, the curse of dimensionality, the negligible number of samples during training or the presence of unbalanced data which makes learning difficult. Having a training set of pixels with the label of the assigned class, the operation that is performed in the classification of hyperspectral images is to assign a class label to each pixel in the test set based on the knowledge acquired with the training set. This paper discusses a new approach in the supervised classification of HS images considering the statistical tool of Copulas. Comparison with well-established techniques shows the good behaviour of this technique
Valorization of Olive By-Products: Innovative Strategies for Their Production, Treatment and Characterization
No full text: Presently, olive oil production signifies a valuable economic income for Mediterranean countries, where approximately 98% of the world's production is established [...]
Collecting & Linking Creative Cultures of Women. Women Designers and Women Clients for another history
No full textWomen's traces in the architectural archives are as faint as they are scarce, and, with a few famous exceptions, women's contributions in the modern era appear too vague when we consider the radical changes in society and the roles played therein by women. While female protagonists were becoming more common in certain fields, the field of architecture seemingly had no equivalent to, say, Maria Skłodowska Curie. What we should rather say is that there is no evidence of an analogous female contribution to the history of architecture and design. Moreover, this presumed lack of input into the field of design might be misinterpreted as a failure to participate in building common ground. It might ultimately appear to be a failure - a culpability even - to conceive of a new modern environment for their own new life in a modern society. This nonsensical vision of a lack or, at best, of a discontinuous range of initiatives made by women within this framework highlights the importance of the role played by archives and source material in making history, and this necessitates some preliminary considerations. Were women really disinterested in shaping, in terms of design, a way of life tied up with their emancipation, or, rather, are sources providing evidence of their involvement really just not accessible? Some examples of overlooked female creativity may help to underline this lack of information and the consequent need to reformulate crucial links between sources and history in order to gain a new understanding of women's contributions.
It is our belief that there is a need to put female creative culture in the spotlight, and a digital approach offers a new perspective by making it possible to create a new kind of digital archive. In any event, what is certain is that a new critical approach to collecting sources and making history is overdue. Institutional records offices are essential for the collection and spreading of cultural heritage as well as for the fostering of research. Digital platforms can create links capable of shaping a new cultural context since they provide an overview of the broad networks operating in design processes. From the point of view of both tangible and intangible cultural heritage, as well as of the built environment, there exists no single author-demiurge but rather a collective of collaborative workers. In this perspective we aim to introduce a couple of case studies of women's creative work as demonstrations of possible new critical approaches to architectural and design culture and its history. The first focuses on the little known designers Margaret and Frances Macdonald and the entrepreneur Kate Cranston, the second on the almost unknown landscape designer Norah Geddes. In this context they aim to articulate some aspects of this cultural perspective. Case studies takes into account the period just preceding the Modern Movement as a turn of important changes. Lastly we discuss how it is possible to create a digital archive is which makes known the historical, creative culture of women as this comes to light
Empirical density estimation based on spline quasi-interpolation with applications to copulas clustering modeling
No full textDensity estimation is a fundamental technique employed in various fields to model and to understand the underlying distribution of data. The primary objective of density estimation is to estimate the probability density function of a random variable. This process is particularly valuable when dealing with univariate or multivariate data and is essential for tasks such as clustering, anomaly detection, and generative modeling. In this paper we propose the monovariate approximation of the density using spline quasi interpolation and we apply it in the context of clustering modeling. The used clustering technique is based on the construction of suitable multivariate distributions which rely on the estimation of the monovariate empirical densities (marginals). Such an approximation is achieved by using the proposed spline quasi-interpolation, while the joint distributions to model the sought clustering partition is constructed with the use of copulas functions. In particular, since copulas can capture the dependence between the features of the data independently from the marginal distributions, a finite mixture copula model is proposed. The presented algorithm is validated on artificial and real datasets
Sentinel-2 Satellite Image Time-Series Land Cover Classification with Bernstein Copula Approach
No full textA variety of remote sensing applications call for automatic optical classification of satellite images. Recently, satellite missions, such as Sentinel-2, allow us to capture images in real-time of the Earth’s scenario. The classification of this large amount of data requires increasingly precise and fast methods, which must take into account not only the spectral features dependence of each individual image but also that of the temporal ones. Copulas are an excellent statistical tool, able to model joint distributions between even random variables. In this paper, we propose a new approach for Satellite Image Time-Series (SITS) land cover classification, which combines the matrix factorization to reduce the dimensionality of the data and the use of copulas distribution to model the dependencies. We will show how the use of particular copulas can improve the accuracy of classification compared to the latest methodologies used for the classification task, such as those using Neural Networks. Experiments were conducted at a study site located on Reunion Island, using Sentinel-2 SITS data. Results are compared to those achieved by several approaches commonly used to address SITS-based land cover mapping and show that the use of copulas, in combination with the matrix factorization, achieved the highest classification yield compared to competing approaches
Le cose del passato e le trasformazioni della città contemporanea: sulla definizione del concetto di "patrimonio"
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