Automatic three-dimensional features extraction: The case study of L'Aquila for collapse identification after April 06, 2009 earthquake

This paper illustrates an innovative methodology for post-earthquake collapsed building recognition, based on satellite-image classification methodologies and height variation information. Together, the techniques create a robust classification that seems to yield good results in this application field. In the first part of this study, two different feature extraction methodologies were compared, based respectively on pixel-based and object-oriented approaches. Then the classification results of the most accurate classification methodology, obtained on an eight band WorldView-2 monoscopic image, were completed with height variation information before and after the event. The height difference is calculated, comparing a photogrammetric DSM, obtained using a photogrammetric rigorous orbital model on some EROS-B 0.7 metre across-track stereopairs with a 'roof model' before the earthquake

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

Power Forecasting of a Photovoltaic Plant Located in ENEA Casaccia Research Center

This work proposes an Artificial Neural Network (ANN) able to provide an accurate forecasting of power produced by photovoltaic (PV) plants. The ANN is customized on the basis of the particular season of the year. An accurate analysis of input variables, i.e., solar irradiance, temperature and air humidity, carried out by means of Pearson Correlation, has allowed to select, day by day, the most suitable set of inputs and ANN architecture also to reduce the necessity of large computational resource. Thus, features are added to the ANN as needed, avoiding waste of computational resources. The method has been validated through data collected from a PV plant installed in ENEA (National agency for new technologies, energy and sustainable economic development) Research Center, located in Casaccia, Rome (Italy). The developed strategy is able to furnish accurate predictions even in the case of strong irregularities of solar irradiance, providing accurate results in rapidly changing scenarios

A real-time MCU-based wireless system for PV applications

This paper presents a Wi-Fi-based stand-alone system for online monitoring of the operating conditions of a photovoltaic (PV) plant. The setup is constituted by a microcontroller unit (MCU), a power meter to periodically sample the values of voltage and current, a temperature sensor, Li-Ion rechargeable batteries, a DC-DC converter able to supply the circuitry, a pc running MATLAB. The core of the presented system is the use of an analytical method to calculate solar irradiance that allows not to resort to solar sensors. The system is thought to be embedded on the back of each PV panel constituting the PV plant and to provide quick information on the operating point and, hence, also on the power production of the device. A MATLAB instrument control interface is used to collect data about the whole plant and to manage the acquisition. The PV panel is simulated through a TerraSAS PV simulator able to emulate the electrical behavior of any solar array

A real-time MCU-based wireless system for remote monitoring of PV devices

The aim of this paper is to propose a system for an online checking of the conditions in which a photovoltaic (PV) plant is functioning. Its structure consists of a central core, i.e. a microcontroller (MCU), and sensors, in particular a power meter for sensing current and voltage and a temperature one; a DC-DC converter and some rechargeable batteries complete the setup. The whole system has to be intended as a 'sensing box' to be applied to the back of any PV device whose characteristics we have to acquire. The whole system is managed through a strategy developed in MATLAB environment. In particular, a mathematical method has allowed not to include any irradiance sensor in the setup since it has made possible to analytically calculate (and not to sense) the quantity irradiance. Thanks to a PV simulator it has been possible to test the method on several simulated PV modules with different characteristics and to prove the effectiveness of the proposed strategy. Finally, a graphical interface has been included to facilitate the acquisition phase for the user

On circuital topologies and reconfiguration strategies for PV systems inpartial shading conditions: A review

Photovoltaic (PV) power generation is heavily influenced by mismatching conditions, mainly caused by partial or full shading of an array portion. Such a non-uniform irradiation can lead to severe reductions in the power produced; some techniques, such as array reconfiguration or microconverters and microinverters technology are aimed at retrieving this power together with the use of Maximum Power Point (MPP) tracker algorithms, while others tend to mitigate the effects that power losses have on the PV system, i.e. overheating and aging. Solutions based on the use of bypass diodes and their re-adapted forms belong to this latter case. The complexity of the problem has shown the need of analyzing the role played by each one of the mentioned aspects; the focus of this paper is to give the reader a detailed review of the main solutions to PV arrays shading present in literature

Preliminary findings on the association between attachment patterns and levels of growth hormone in a sample of children with non-organic failure to thrive

Introduction. Deficiency of growth hormone (GH) in absence of pituitary injuries is one of the causes of short stature and of the non organic failure to thrive (NOFTT) condition. Advances in developmental psychology have highlighted the role of emotions and caregiving behaviors in the organization of child's personality and psychobiology, with the mother-son attachment bond being considered a fundamental developmental experience. The objective of the present preliminary study was to assess whether there are significant correlations between attachment patterns and GH levels in a sample of subjects with NOFTT. Methods. Overall, 27 children (mean age 9.49 +/- 2.63 years) with NOFTT were enrolled. Perceived attachment security was assessed through the Security Scale (SS) and its subscales focused on maternal and paternal security. Pearson partial correlation was used to test associations between GH levels and SS measures adjusting for confounding factors (i.e. age, gender and body mass index). Results. Across all subjects, GH was significantly positively correlated with general security (r=0.425; p=0.038) and maternal security (r=0.451; p=0.027) and not significantly correlated with paternal security (r=0.237; p=0.264). Discussion. These findings preliminarily suggest that the association between GH levels and perceived attachment security may play a role in the pathophysiology of NOFTT and add to the accumulating evidence that attachment patterns may be related with specific psychoendocrine underpinnings

Equivalent Circuit Model for Cu(In,Ga)Se₂ Solar Cells Operating at Different Temperatures and Irradiance

The modeling of photovoltaic cells is an essential step in the analysis of the performances and characterization of PV systems. This paper proposes an experimental study of the dependence of the five parameters of the one-diode model on atmospheric conditions, i.e., irradiance and temperature in the case of thin-film solar cells. The extraction of the five parameters was performed starting from two sets of experimental data obtained from Cu(In,Ga)Se2 solar cells fabricated by the low-temperature pulsed electron deposition technique. A reduced form approach of the one-diode model has been adopted, leading to an accurate identification of the cell. It was possible to elaborate suitable relations describing the behavior of the parameters as functions of the environmental conditions. This allowed accurately predicting the trends of the parameters from a pair of curves, instead of a whole set of measurements. The developed model describing the dependence on irradiance and temperature was validated by means of a large set of experimental measurements on several Cu(In,Ga)Se2 (CIGS) devices built with the same technological process