SEISMIC DAMAGE OF BELL TOWERS

some studies on towers after recent earthquake in Emilia Romagna (Italy

Volume-based Semantic Labeling with Signed Distance Functions

Research works on the two topics of Semantic Segmentation and SLAM (Simultaneous Localization and Mapping) have been following separate tracks. Here, we link them quite tightly by delineating a category label fusion technique that allows for embedding semantic information into the dense map created by a volume-based SLAM algorithm such as KinectFusion. Accordingly, our approach is the first to provide a semantically labeled dense reconstruction of the environment from a stream of RGB-D images. We validate our proposal using a publicly available semantically annotated RGB-D dataset and a) employing ground truth labels, b) corrupting such annotations with synthetic noise, c) deploying a state of the art semantic segmentation algorithm based on Convolutional Neural Networks.Comment: Submitted to PSIVT201

Close Approaches of Debris to LARES Satellite During Its First Four Years of Operation

Since its launch in February 2012, the LAser RElativity Satellite (LARES) of the Italian Space Agency experienced four close approaches with space debris. LARES orbits at an altitude of 1450 km, in a region where the density of space debris has a peak. However, the probability of an impact with a debris during the operational life of the satellite was reasonably low. The analysis of the close approaches identified three of the objects, that are from two peculiar population of objects. This paper discusses the problem of space debris in low orbit, the approaches occurred with LARES, and some possible scenarios related to space regulations and space law in case of an impact

A large multilingual and multi-domain dataset for recommender systems

This paper presents a multi-domain interests dataset to train and test Recommender Systems, and the methodology to create the dataset from Twitter messages in English and Italian. The English dataset includes an average of 90 preferences per user on music, books, movies, celebrities, sport, politics and much more, for about half million users. Preferences are either extracted from messages of users who use Spotify, Goodreads and other similar content sharing platforms, or induced from their ”topical” friends, i.e., followees representing an interest rather than a social relation between peers. In addition, preferred items are matched with Wikipedia articles describing them. This unique feature of our dataset provides a mean to derive a semantic categorization of the preferred items, exploiting available semantic resources linked to Wikipedia such as the Wikipedia Category Graph, DBpedia, BabelNet and others

Scenario-based forecast for the electricity demand in Qatar and the role of energy efficiency improvements

We model the electricity consumption in the market segment that compose the Qatari electricity market. We link electricity consumption to GDP growth and Population Growth. Building on the estimated model, we develop long-range forecasts of electricity consumption from 2017 to 2030 over different scenarios for the economic drivers. In addition, we proxy for electricity efficiency improvements by reducing the long-run elasticity of electricity consumption to GDP and Population. We show that electricity efficiency has a crucial role in controlling the future development of electricity consumption. Energy policies should consider this aspect and support both electricity efficiency improvement programs, as well as a price reform

"MADE IN ITALY" AND "MADE IN CHINA". EMPIRICAL ANALYSIS AND INDUSTRIAL POLICY IMPLICATIONS

quality, sectoral specialisation, international trade, price differentials

Children Capabilities and Family Characteristics in Italy

This paper explores the possibilities of using structural equation modelling to measure capabilities of Italian children. In particular the paper focuses on two capabilities: “Senses, Imagination and Thought” and “Leisure and Play Activities ”. The indicators used to measure the capability of ‘Senses, imagination and thought’ for 6-13 years old children are attitude towards education, attendance to arts classes and other type of extra curriculum classes like computing and languages. The variables used as indicators of the capability of “Leisure and play activities” include how often children play in playground, various types of games, attendance to sports classes. We use both descriptive statistics, an ordered probit model, and a structural equation model in order to investigate the relation among the above mentioned indicators, the latent construct for capabilities and a set of covariates. Moreover we use a new data set in order to include family income among the covariates. The data result from the matching (through a propensity score method) of two data sets: Bank of Italy Survey on Income and Wealth for year 2000 and Istat Families, social subjects and childhood condition for year 1998.Education, Capabilities, Child Well Being, Structural Equation Modelling

Growth Rates Preservation (GRP) temporal benchmarking: Drawbacks and alternative solutions

Benchmarking monthly or quarterly series to annual data is a common practice in many National Statistical Institutes. The benchmarking problem arises when time series data for the same target variable are measured at different frequencies and there is a need to remove discrepancies between the sums of the sub-annual values and their annual benchmarks. Several benchmarking methods are available in the literature. The Growth Rates Preservation (GRP) benchmarking procedure is often considered the best method. It is often claimed that this procedure is grounded on an ideal movement preservation principle. However, we show that there are important drawbacks to GRP, relevant for practical applications, that are unknown in the literature. Alternative benchmarking models will be considered that do not suffer from some of GRP\u2019s side effects