1,482 research outputs found
Trees of Fusion Systems
We define a `tree of fusion systems' and give a sufficient condition for its
completion to be saturated. We apply this result to enlarge an arbitrary fusion
system by extending the automorphism groups of certain of its subgroups
LandLab Project and archaeology on-line. Web-based systems for the study of settlement patterns and excavation data in classical archaeology
The paper deals with the results of a research project, LandLab Project, finalized at the reconstruction of ancient landscapes. The use of Internet for presenting the results of the scientific research is discussed through the presentation of two web applications, which have been implemented by the Laboratory of Archaeological Computing of the Dept. of Cultural Heritage - University of Lecce, Italy: the WebGIS of the pre-Roman settlements of the Salento region and WODOS, the on-line version of the ODOS excavation data management system. The web-based applications are aimed at developing new approaches to the problem of data preservation and data dissemination. They use the methods and technologies available in the field of Information and Communication Technology for the transfer of data, information management systems and multimedia communication in the reconstruction of ancient landscapes and cultural systems. The project is unique in the geographical context in question here, in that it represents the first thematic laboratory for research into the ancient landscape completely based on Web Programming and Internet Technology
Gestione informatizzata dei dati archeologici e dei sistemi GIS. Applicazione al sito di Hierapolis di Frigia
The system used for organizing the data from the excavation at Hierapolis, a sample site for this research project, represents an example of the application of the methodology of GIS to a stratigraphically excavated site. The use of this methodology, based on the logical structuring of data in independent layers, makes it possible to reconstruct the micro-dynamics typical of a stratigraphic excavation. Once the archaeological layers are separated, divided and organized according to their geographic position, they are treated as a series of divisible and superimposable layers which can be used in order to create the floor plans of single monuments and, more in general, maps showing the different phases of the city. This type of data management makes it easier to understand the spatial organization and transformation of a city over time
Multi-temporal images and 3D dense models for archaeological site monitoring in Hierapolis of Phrygia (TK)
and range-based measurement systems have become increasingly interesting in excavation processes for monitoring purposes and large scale mapping, both from a terrestrial and aerial point of view. The paper will focus on the great challenge of monitoring sites over time, integrating and conforming multiple data coming from previous metric survey projects and image data collected in the past for different purposes. The test-site was the complex archaeological landscape of the ancient city of Hierapolis in Phrygia on which the MAIER – Italian Archaeological Mission of Hierapolis has operated since the 1960s and where the Politecnico di Torino conducted several survey campaigns. A set of multi-temporal datasets acquired in a series of campaigns in 1997, 2002, 2007, 2012, 2015 are presented, as well as their 3D multi-sensor models; the older dense models generated with archival images are intended to be compared and integrated with newer models generated by the LiDAR scans in 2012 and the UAV systems employed in the last mission in 2015. In particular, the case study was the massive complex of the ancient Bath-Church in the northern part of the city below the Northern Necropolis, and Building A of the Apollo Sanctuary, in the central Sacred Area near the Ancient Theatre. In these sites, many different sensors have been experimented with over the years and preliminary multi-temporal data integration has been tested in order to up-date and improve older archival records based on collected images and related to newer and updated documentation projects
PyPlutchik: Visualising and comparing emotion-annotated corpora
The increasing availability of textual corpora and data fetched from social networks is fuelling a huge production of works based on the model proposed by psychologist Robert Plutchik, often referred simply as the “Plutchik Wheel”. Related researches range from annotation tasks description to emotions detection tools. Visualisation of such emotions is traditionally carried out using the most popular layouts, as bar plots or tables, which are however sub-optimal. The classic representation of the Plutchik’s wheel follows the principles of proximity and opposition between pairs of emotions: spatial proximity in this model is also a semantic proximity, as adjacent emotions elicit a complex emotion (a primary dyad) when triggered together; spatial opposition is a semantic opposition as well, as positive emotions are opposite to negative emotions. The most common layouts fail to preserve both features, not to mention the need of visually allowing comparisons between different corpora in a blink of an eye, that is hard with basic design solutions. We introduce PyPlutchik the Pyplutchik package is available as a Github repository (http://github.com/alfonsosemeraro/pyplutchik) or through the installation commands pip or conda. For any enquiry about usage or installation feel free to contact the corresponding author, a Python module specifically designed for the visualisation of Plutchik’s emotions in texts or in corpora. PyPlutchik draws the Plutchik’s flower with each emotion petal sized after how much that emotion is detected or annotated in the corpus, also representing three degrees of intensity for each of them. Notably, PyPlutchik allows users to display also primary, secondary, tertiary and opposite dyads in a compact, intuitive way. We substantiate our claim that PyPlutchik outperforms other classic visualisations when displaying Plutchik emotions and we showcase a few examples that display our module’s most compelling features
Application of vegetation index time series to value fire effect on primary production in a Southern European rare wetland
Fire disturbance is an intrinsic component of the Mediterranean biome playing an important role in ecosystem dynamics and processes. However, frequent and severe anthropogenic wildfires can be detrimental to natural ecosystems, particularly in small natural protected areas, where they may hamper the flow of ecosystem services (ES). While post-fire dynamics of individual ES are heavily context-dependent, the primary productivity of the ecosystem can be regarded as a generic driver of several provisioning and regulating ES, as it represents the amount of energy available to plants for storage, growth, and reproduction, which drives future ecosystem structure and functions. The aim of this study was to evaluate the effect of anthropogenic wildfire on the primary productivity of a rare wetland ecosystem in the Natura 2000 site \u201cTorre Guaceto\u201d in Southern Europe. Productivity was estimated by calculating a 15-year time series of vegetation indices (EVI and NDWI)from remotely sensed MODIS imagery. Our results in terms of PP trends may be relevant to assess the change in ecosystems services provided by wetlands. Interactions between wildfire, ecosystem productivity and climate were then analyzed. During the selected period, climate did not play a significant effect on primary productivity, which was mainly driven by post-fire vegetation recovery. Findings of the present study demonstrate that the wildfire affecting the Natural Protected Area of Torre Guaceto in summer 2007 had a major effect on primary productivity, inducing the regeneration of Phragmites australis and the replacement of old individuals by structurally and functionally better ones
A general aspect-term-extraction model for multi-criteria recommendations
In recent years, increasingly large quantities of user reviews have been made available by several e-commerce platforms. This content is very useful for recommender systems (RSs), since it reflects the users' opinion of the items regarding several aspects. In fact, they are especially valuable for RSs that are able to exploit multi-faceted user ratings. However, extracting aspect-based ratings from unstructured text is not a trivial task. Deep Learning models for aspect extraction have proven to be effective, but they need to be trained on large quantities of domain-specific data, which are not always available. In this paper, we explore the possibility of transferring knowledge across domains for automatically extracting aspects from user reviews, and its implications in terms of recommendation accuracy. We performed different experiments with several Deep Learning-based Aspect Term Extraction (ATE) techniques and Multi-Criteria recommendation algorithms. Results show that our framework is able to improve recommendation accuracy compared to several baselines based on single-criteria recommendation, despite the fact that no labeled data in the target domain was used when training the ATE model
XAI.it 2020 - Preface to the first italian workshop on explainable artificial intelligence
Artificial Intelligence systems are increasingly playing an increasingly important role in our daily lives. As their importance in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as possible. It is not by chance that the recent General Data Protection Regulation (GDPR) emphasized the users’ right to explanation when people face artificial intelligence-based technologies. Unfortunately, the current research tends to go in the opposite direction, since most of the approaches try to maximize the effectiveness of the models (e.g., recommendation accuracy) at the expense of the explainability and the transparency. The main research questions which arise from this scenario is straightforward: how can we deal with such a dichotomy between the need for effective adaptive systems and the right to transparency and interpretability? Several research lines are triggered by this question: building transparent intelligent systems, analyzing the impact of opaque algorithms on final users, studying the role of explanation strategies, investigating how to provide users with more control in the behavior of intelligent systems. XAI.it, the first Italian workshop on Explainable AI, tries to address these research lines and aims to provide a forum for the Italian community to discuss problems, challenges and innovative approaches in the various sub-fields of XAI
Ocular Refraction at Birth and Its Development During the First Year of Life in a Large Cohort of Babies in a Single Center in Northern Italy
The purpose of this study was to investigate refraction at birth and during the first year of life in a large cohort of babies born in a single center in Northern Italy. We also aimed to analyze refractive errors in relation to the gestational age at birth. An observational ophthalmological assessment was performed within 24 h of birth on 12,427 newborns. Refraction was examined using streak retinoscopy after the administration of tropicamide (1%). Values in the range of between +0.50 ≤ D ≤ +4.00 were defined as physiological refraction at birth. Newborns with refraction values outside of the physiological range were followed up during the first year of life. Comparative analyses were conducted in a subgroup of babies with known gestational ages. The following distribution of refraction at birth was recorded: 88.03% of the babies had physiological refraction, 5.03% had moderate hyperopia, 2.14% had severe hyperopia, 3.4%, had emmetropia, 0.45%, had myopia, 0.94% had astigmatism, and 0.01% had anisometropia. By the end of the first year of life, we observed reductions in hyperopia and astigmatism, and stabilization of myopia. Preterm babies had a four-fold higher risk of congenital myopia and a three-fold higher risk of congenital emmetropia as compared to term babies. Refraction profiles obtained at birth changed during the first year of life, leading to a normalization of the refraction values. Gestational age at birth affected the incidence of refractive errors and amblyopia
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