Risultato di valorizzazione applicativa: progettazione e realizzazione di un prototipo di sensore wireless per il monitoraggio di carichi elettrici in ambiente Smart Building

Oggetto del presente lavoro è stata la progettazione e realizzazione di un prototipo di sensore wireless a basso costo per il monitoraggio di carichi elettrici in ambiente Smart Building, capace di inviare dati ad un sistema remoto (ad esempio un EMS) mediante una comune connessione WiFi. L’attività si inquadra nell’ambito di una collaborazione scientifica tra l’Istituto di Studi sui Sistemi Intelligenti per l’Automazione (ISSIA) del Consiglio Nazionale delle Ricerche (CNR) e il Dipartimento di Matematica e Informatica (DMI) dell’Università degli Studi di Palermo (UNIPA). Il prototipo è stato realizzato interfacciando opportunamente alcuni dispositivi hardware commerciali, aggiungendo gli opportuni circuiti per il condizionamento dei segnali da acquisire e scrivendo il codice per l’implementazione del firmware del sensore wireless (per l’invio dei dati) e del client remoto (per la ricezione dei dati)

Summary of the performances of the superconducting electron cyclotron resonance ion source at 14 GHz

This article deals with the most recent performance of the superconducting electron cyclotron resonance ion source (SERSE) working at 14 GHz with high magnetic fields after the required conditioning and optimization of several operating parameters. SERSE has now achieved an outstanding level of performance in delivering highly charged ion beams in argon and oxygen gases: the results obtained while operating in a stainless steel chamber and with an aluminum liner are shown and discussed

Ground-Based Measurements of the 2014–2015 Holuhraun Volcanic Cloud (Iceland)

The 2014–2015 Bárðarbunga fissure eruption at Holuhraun in central Iceland was distinguished by the high emission of gases, in total 9.6 Mt SO2, with almost no tephra. This work collates all ground-based measurements of this extraordinary eruption cloud made under particularly challenging conditions: remote location, optically dense cloud with high SO2 column amounts, low UV intensity, frequent clouds and precipitation, an extensive and hot lava field, developing ramparts, and high-latitude winter conditions. Semi-continuous measurements of SO2 flux with three scanning DOAS instruments were augmented by car traverses along the ring-road and along the lava. The ratios of other gases/SO2 were measured by OP-FTIR, MultiGAS, and filter packs. Ratios SO2/HCl = 30–110 and SO2/HF = 30–130 show a halogen-poor eruption cloud. Scientists on-site reported extremely minor tephra production during the eruption. OPC and filter packs showed low particle concentrations similar to non-eruption cloud conditions. Three weather radars detected a droplet-rich eruption cloud. Top of eruption cloud heights of 0.3–5.5 km agl were measured with ground- and aircraft-based visual observations, web camera and NicAIR II infrared images, triangulation of scanning DOAS instruments, and the location of SO2 peaks measured by DOAS traverses. Cloud height and emission rate measurements were critical for initializing gas dispersal simulations for hazard forecasting

Ground-Based measurements of the 2014-2015 holuhraun volcanic cloud (Iceland)

The 2014-2015 Bárðarbunga fissure eruption at Holuhraun in central Iceland was distinguished by the high emission of gases, in total 9.6 Mt SO2, with almost no tephra. This work collates all ground-based measurements of this extraordinary eruption cloud made under particularly challenging conditions: remote location, optically dense cloud with high SO2 column amounts, low UV intensity, frequent clouds and precipitation, an extensive and hot lava field, developing ramparts, and high-latitude winter conditions. Semi-continuous measurements of SO2 flux with three scanning DOAS instruments were augmented by car traverses along the ring-road and along the lava. The ratios of other gases/SO2 were measured by OP-FTIR, MultiGAS, and filter packs. Ratios of SO2/HCl = 30-110 and SO2/HF = 30-130 show a halogen-poor eruption cloud. Scientists on-site reported extremely minor tephra production during the eruption. OPC and filter packs showed low particle concentrations similar to non-eruption cloud conditions. Three weather radars detected a droplet-rich eruption cloud. Top of eruption cloud heights of 0.3-5.5 km agl were measured with ground-and aircraft-based visual observations, web camera and NicAIR II infrared images, triangulation of scanning DOAS instruments, and the location of SO2 peaks measured by DOAS traverses. Cloud height and emission rate measurements were critical for initializing gas dispersal simulations for hazard forecasting

A Classification Methodology Based on Subspace Graphs Learning

In this paper, we propose a design methodology for one-class classifiers using an ensemble-of-classifiers approach. The objective is to select the best structures created during the training phase using an ensemble of spanning trees. It takes the best classifier, partitioning the area near a pattern into \u3b3\u3b3-2 sub-spaces and combining all possible spanning trees that can be created starting from \u3b3 nodes. The proposed method leverages on a supervised classification methodology and the concept of minimum distance. We evaluate our approach on well-known benchmark datasets and results obtained demonstrate that it achieves comparable and, in many cases, state-of-the-art results. Moreover, it obtains good performance even with unbalanced datasets

Picture What you Read

Visualization refers to our ability to create an image in our head based on the text we read or the words we hear. It is one of the many skills that makes reading comprehension possible. Convolutional Neural Networks (CNN) are an excellent tool for recognizing and classifying text documents. In addition, it can generate images conditioned on natural language. In this work, we utilize CNNs capabilities to generate realistic images representative of the text illustrating the semantic concept. We conducted various experiments to highlight the capacity of the proposed model to generate representative images of the text descriptions used as input to the proposed model.Comment: 7 pages, Dicta2019 conferenc