Analysis of the introduction of a business process mapping system in Rosetti Marino spa

After a first theoric introduction about Business Process Re-engineering (BPR), are considered in particular the possible options found in literature regarding the following three macro-elements: the methodologies, the modelling notations and the tools employed for process mapping. The theoric section is the base for the analysis of the same elements into the specific case of Rosetti Marino S.p.A., an EPC contractor, operating in the Oil&Gas industry. Rosetti Marino implemented a tool developped internally in order to satisfy its needs in the most suitable way possible and buit a Map of all business processes,navigable on the Company Intranet. Moreover it adopted a methodology based upon participation, interfunctional communication and sharing. The GIGA introduction is analysed from a structural, human resources, political and symbolic point of view.

La dimensione frattale surface-based nelle neuroimmagini

La geometria frattale permette di definire un indice di complessitá strutturale di oggetti che presentano, fino a un certo livello d’ingrandimento, caratteristiche di auto-similaritá: il cervello umano ha un alto livello di complessitá, che cambia durante il corso della vita e con l’insorgenza di patologie. Tale complessitá puó essere descritta tramite la dimensione frattale (FD). L’obiettivo di questo elaborato ́e sviluppare un metodo di calcolo della FD surface-based, partendo dalla ricostruzione mediante mesh triangolari della superficie cerebrale. A questo scopo ́e stata implementata una procedura che utilizza gli strumenti di analisi di neuroimmagini, come FSL e FreeSurfer; l’algoritmo ́e stato validato su fantocci tridimensionali e testato su immagini di risonanza magnetica pesate in T1 del dataset International Consortium for Brain Mapping (ICBM), composto da 86 soggetti sani con etá compresa tra i 19 e gli 85 anni. Dalla ricerca condotta é emerso che il calcolo della FD surface-based restituisce valori accurati per i fantocci e permette di differenziare significativamnete gli uomini dalle donne. Concludendo, riteniamo che la FD surface-based si possa candidare come marcatore di complessitá strutturale nelle neuroimmagini, in modo complementare agli indici morfologici convenzionali.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Monitoring of macro- and microlitter in the Venice lagoon and coastal area

Marine litter and plastics are a significant and growing marine contaminant that has become a global problem. Macrolitter is subject to fragmentation and degradation due to physical, chemical and biological processes, leading to the formation of micro-litter, the so-called microplastics. The purpose of this research is to assess marine litter pollution by using remote sensing tools to identify areas of macrolitter accumulation and to evaluate the concentrations of microplastics in different environmental matrices: water, sediment and biota (i.e. mussels and fish) and to contribute to the European project MAELSTROM (Smart technology for MArinE Litter SusTainable RemOval and Management). The aim is to monitor the presence of macro- and microlitter at two sites of the Venice coastal area: an abandoned mussel farm at sea and a lagoon site near the artificial Island of Sacca Fisola; The results showed that both study areas are characterised by high amounts of marine litter, but the type of observed litter is different. In fact, in the mussel farm area, most of the litter is linked to aquaculture activities (ropes, nets, mooring blocks and floating buoys). In the Venice lagoon site, the litter comes more from urban activities and from the city of Venice (car tyres, crates, wrecks, etc.). Microplastics is present in both sites and in all the analysed matrices. Generally, higher microplastics concentrations were found at Sacca Fisola (i.e., in surface waters, mussels and fish). Moreover, some differences were also observed in shapes and colours comparing the two sites. At Sacca Fisola, white irregular fragments predominate in water samples, blue filaments in sediment and mussels, and transparent irregular fragments in fish. At the Mussel Farm, blue filaments predominate in water, sediment and mussels, while flat black fragments predominate in fish. These differences are related to the different types of macrolitter that characterised the two areas.