Calibration of the AquaCrop model for winter wheat using MODIS LAI images

In semi-arid environments vegetation density and distribution is of considerable importance for the hydrological water balance. A number of hydrological models exploit Leaf Area Index (LAI) maps retrievedby remote sensing as a measure of the vegetation cover, in order to enhance the evaluation of evapotran-spiration and interception losses. On the other hand, actual evapotranspiration and vegetation development can be derived through crop growth models, such as AquaCrop, developed by FAO (Food and Agricultural Organization), which allows the simulation of the canopy development of the main field crops. We used MODIS LAI images to calibrate AquaCrop according to the canopy cover development of winter wheat. With this aim we exploited an empirical relationship between LAI and canopy cover. In detail Aquacrop was calibrated with MODIS LAI maps collected between 2008 and 2011, and validated with reference to MODIS LAI maps of 2013-2014 in Rocchetta Sant'Antonio and Sant'Agata, two test sites in the Carapelle watershed, Southern Italy. Results, in terms of evaluation of canopy cover, provided improvements. For example, for Rocchetta Sant'Antonio, the statistical indexes vary from r = 0.40, ER = 0.22, RMSE = 17.28 and KGE = 0.31 (using the model without calibration), to r = 0.86, ER = 0.08, RMSE = 6.01 and KGE 0.85 (after calibration). © 2015 Elsevier B.V

Touch or Touchless? Evaluating Usability of Interactive Displays for Persons with Autistic Spectrum Disorders

Interactive public displays have been exploited and studied for engaging interaction in several previous studies. In this context, applications have been focused on supporting learning or entertainment activities, specifically designed for people with special needs. This includes, for example, those with Autism Spectrum Disorders (ASD). In this paper, we present a comparison study aimed at understanding the difference in terms of usability, effectiveness, and enjoyment perceived by users with ASD between two interaction modalities usually supported by interactive displays: touch-based and touchless gestural interaction. We present the outcomes of a within-subject setup involving 8 ASD users (age 18-25 y.o., IQ 40-60), based on the use of two similar user interfaces, differing only by the interaction modality. We show that touch interaction provides higher usability level and results in more effective actions, although touchless interaction is more effective in terms of enjoyment and engagemen

Palmprint principal lines extraction

The palmprint recognition has become a focus in biological recognition and image processing fields. In this process, the features extraction (with particular attention to palmprint principal line extraction) is especially important. Although a lot of work has been reported, the representation of palmprint is still an open issue. In this paper we propose a simple, efficient, and accurate palmprint principal lines extraction method. Our approach consists of six simple steps: normalization, median filtering, average filters along four prefixed directions, grayscale bottom-hat filtering, combination of bottom-hat filtering, binarization and post processing. The contribution of our work is a new method for palmprint principal lines detection and a new dataset of hand labeled principal lines images (that we use as ground truth in the experiments). Preliminary experimental results showed good performance in terms of accuracy with respect to three methods of the state of the art

Predicting mid-air gestural interaction with public displays based on audience behaviour

© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/.Knowledge about the expected interaction duration and expected distance from which users will interact with public displays can be useful in many ways. For example, knowing upfront that a certain setup will lead to shorter interactions can nudge space owners to alter the setup. If a system can predict that incoming users will interact at a long distance for a short amount of time, it can accordingly show shorter versions of content (e.g., videos/advertisements) and employ at-a-distance interaction modalities (e.g., mid-air gestures). In this work, we propose a method to build models for predicting users’ interaction duration and distance in public display environments, focusing on mid-air gestural interactive displays. First, we report our findings from a field study showing that multiple variables, such as audience size and behaviour, significantly influence interaction duration and distance. We then train predictor models using contextual data, based on the same variables. By applying our method to a mid-air gestural interactive public display deployment, we build a model that predicts interaction duration with an average error of about 8 s, and interaction distance with an average error of about 35 cm. We discuss how researchers and practitioners can use our work to build their own predictor models, and how they can use them to optimise their deployment.Peer reviewe

Supporting tourism with public interactive displays

Interactive displays are common in public and semi-public areas, such as museums, shopping malls, train stations, and even on streets. Especially with the emergence of new ways of interaction, interactive displays could be introduced to popular tourist attractions to support tourism. The aim of this tutorial is to prepare its participants for designing such interactive public displays. The tutorial will first introduce participants to state of the art in interactive public displays. This will be followed by a city tour where a number of local attractions are visited. Finally, the participants will brainstorm and create concepts for novel interactive public displays that aim to improve the experience of visiting tourist attractions

Child-display interaction: exploring avatar-based touchless gestural interfaces

During the last decade, touchless gestural interfaces have been widely studied as one of the most promising interaction paradigms in the context of pervasive displays. In particular, avatars and sil- houettes have been proved to be effective in communicating the touchless gestural interactivity supported by displays. In the paper, we take a child-display interaction perspective by exploring avatar- based touchless gestural interfaces. We believe that large displays offer an opportunity to stimulate child experience and engagement, for instance when learning about art, as well as bringing a number of challenges. The purpose of this study is twofold: 1) identifying the relevant aspects of children’s interactions with a large display based on a touchless avatar-based interface, and 2) understanding the impact on recalling the content that arises from the interaction. We engaged 107 children over a period of five days during a public event at the university premises. Collected data were analyzed, and the outcomes transformed into three lessons learnt for informing the future design

Regional differences in Italian students' performance: a simulation model

This work presents the first results of a research project seeking to build a simulation model able to reproduce the differences of Italian students' performance at regional level. A preliminary qualitative cause-and-effect model defines the main variable involved in the inter-generational skill formation processes, as well as their interplay with the job market context and the triggering of motivational forces for new skill acquisition. Such model was designed according to a system dynamics perspective, considered suitable for capturing the interrelatedness of key variables and for providing useful simulation tools to conduct and communicate future scenario analyses. Keywords: regional difference; educational achievement; system dynamics; PISA

Toxic metals in Loggerhead sea turtles (Caretta caretta) stranded freshly dead along Sicilian coasts

Abstract Background: The Loggerhead sea turtle (Caretta caretta) is a marine reptile belonging to a monophyletic group of chelonians. As these animals are long-lived, they have the ability to accumulate pollutants. Aim: To collect epidemiological data on toxic metals in marine Loggerhead sea turtles. Materials and Methods: Forty Loggerhead sea turtles comprising 25 males and 15 females stranded freshly dead between 2013 and 2018 along the coasts of Sicily, Southern Italy, were examined for arsenic, cadmium, and lead accumulation in muscle and adipose tissues by means of a validated ICP-MS method. A modified K index as a growth condition factor, namely Fulton's K index, was used. Samples were tested in duplicate. A Wilcoxon rank sum test was carried out to evaluate metal contents differences between muscle and adipose tissues and between genders. Results: The Fulton's K index suggested a good body condition of the C. caretta recovered with mean values of 5.34±3.40 (n=40; ±SD). Detectable concentrations of lead were found in 70% of the samples analysed with mean values of 0.65±1.67 mg/kg wet weight and 0.51±1.29 mg/kg wet weight in muscle and adipose tissues, respectively. No significant differences in arsenic, cadmium, and lead were detected between genders. In addition, no significant correlation was found between modified K index and concentrations of arsenic, cadmium, and lead. Clinical relevance: Findings on muscle and adipose tissues suggest chronic exposure of Caretta caretta to high concentrations of especially lead which might negatively affect health and welfare of these marine turtles although body condition was good