CitInES Project – Tool for the Sustainable Energy Action Plan for cities

Sustainable Energy Action Plan (SEAP) is the key document in which outlines how it intends to reach its CO2 reduction target by 2020. It defines the activities and measures set up to achieve the targets, together with time frames and assigned responsibilities. However to orient cities toward a low carbon society, longer lasting investment decisions and organisational changes will be necessary. In this conttext, the overall objective of CitInES European project is to design and demonstrate a multi-scale multi-energy decision-making tool to optimise the energy efficiency of cities to support the cities for the developemnt and monitoring of their SEAP. To achieve this goal, innovative energy system modelling and optimization algorithms were designed to allow end-users to optimize and monitor their energy strategy through detailed simulations of local energy production, storage, transport, distribution and consumption, including demand side management and coordination functionalities enabled by smart grid technologies. This paper presents the study case of the municipality of Cesena. This municipality, as a partner of the project, has implemented its SEAP under the tool to assess the impact of the measures taken under several scenarios and monitor its activities to validate the developed software. The different measure adopted to reduce the CO2 emissions and energy consumption together with an increase of the energy efficiency and use of renewables are such as increase of the green areas, increase of the use of cogeneration, renovation of the building or the promotion the use of PV and thermal solar panels

A Tiny Convolutional Neural Network driven by System Identification for Vibration Anomaly Detection at the Extreme Edge

Vibration data analysis is the driving tool for the Structural Health Monitoring (SHM) of structures in the dynamic regime, i.e., structures showing important oscillatory behaviours, which largely dominate the transportation back-bone: from terrestrial/aerial vehicles (e.g., trains, aircraft, etc.) to the supporting infrastructures (e.g., bridges, viaducts, etc.). Outstanding opportunities have recently been disclosed in the field of Intelligent Transportation Systems (ITS) by the advent of sensor-near processing functionalities, eventually empowered by Artificial Intelligence (AI). The latter allow for the extraction of damage-sensitive features at the extreme edge, without the need of transmitting long time series over the monitoring network. In this work, we explore for the first time a novel anomaly detection workflow for on-sensor vibration diagnostics, which combines the unique advantages of embedded System Identification (eSysId) as a data compression strategy with the computational/energy advantages of Tiny Machine Learning (TinyML). Experimental results conducted on a representative SHM dataset demonstrate that the proposed pipeline can achieve high classification scores (above 90%) for the health assessment of the well-known Z24 bridge. In particular, the minimal inference time (less than 44 ms) and power consumption performed while running on three different general-purpose microprocessors make it a promising solution for the development of the next generation of SHM-oriented ITS

An Integrated Approach to Improve the Knowledge of Ostreid Herpesvirus Type 1 and the Comprehension of Mortality Events in the Pacific Oyster Crassostrea Gigas

In a period of expansion of oysters farming in Italy, the present work aimed to contribute to this challenge approaching several important aspects connected with oyster health management. Firstly, we evidenced the presence of natural populations of C. gigas along the Italian coasts and showed differences in the distribution and density population between Adriatic and Tyrrhenian Sea. The presence of OsHV-1 infecting these wild populations was detected in all the Adriatic beds, demonstrating high diversity of genotypes, and showing that these individuals may play a role as reservoir of infection in farmed stocks allocated in the same sites. No other potential reservoir hosts have been evidenced during the investigation conducted in other mollusc species. The obtainment of the complete sequence of OsHV-1 µVar genome represents a significant goal reached during the present work. In particular, this result will permit the exploration of virulence factor in future, a better use of transcriptomics, and the development of new specific diagnostic tools.The complete comprehension of the mechanisms at the origin of the mortality events, observed during the two-year survey, is arduous but the study allowed to observe and obtain highly useful information on oyster mortalities and associated pathogens, specifically in the Italian context. In particular, the impact of V. aestuarianus seems to be relevant in some areas.A potential new pathogen for adult oysters, a Tenacibaculum strain, has been decribed

ENSINO REMOTO DURANTE A PANDEMIA DA COVID-19 NA UNIVERSIDADE ESTADUAL DE LONDRINA

Este estudo apresenta reflexões acerca do ensino remoto que foi a maneira encontrada para a retomada das atividades letivas diante da pandemia da Covid-19. O objetivo é compreender o que sentem e sob quais condições os alunos e alunas do curso de Pedagogia da Universidade Estadual de Londrina retomaram os estudos neste cenário. Trata-se de uma pesquisa de caráter qualitativo e exploratório, com a aplicação de um questionário semiestruturado para a coleta das informações sobre como os alunos estão lidando com esta condição das aulas no espaço doméstico. Dos 121 respondentes 80% estão na faixa etária entre 18 e 28 anos, elas dividem a casa com duas ou mais pessoas e 40% delas trabalham. O sentimento em relação à formação acadêmica neste cenário de ensino remoto é de insegurança, ansiedade, frustração e exaustão. As dificuldades giram em torno de encontrar um espaço adequado para realizar os estudos, o acesso à internet e/ou ao computador, a sobrecarga de atividades relacionadas às diversas disciplinas e as questões de cunho psicológico, 52% delas relatam dificuldades com a concentração. Quando perguntadas da possibilidade de não retornar neste momento e nestas condições, cerca de 76,9% delas responderam não ou talvez, indicando uma insatisfação com o ensino remoto

Analisi di un setup di localizzazione di tag ibridi RFID-UWB

Questa tesi tratta l'identificazione e la localizzazione di tag ibridi RFID-UWB (Radio Frequency Identification - Ultra-Wide Band). Si compone di due attività principali, una riguardante l'elaborazione e l'analisi di dati provenienti da una campagna di misure e una relativa allo studio di un nuovo setup di misura tramite una periferica USRP, una Software Defined Radio (SDR). Inoltre, sono stati sviluppati nuovi codici contenenti algoritmi di tipo LS (Least Square) per la localizzazione di tag. La tesi è strutturata come segue: • Il Capitolo 1 motiva l'interesse nei confronti della tecnologia RFID e offre una panoramica sulle attività svolte; • Il Capitolo 2 descrive i sistemi RFID, concentrandosi sul principio operativo della tecnologia e sui componenti, in particolare le diverse tipologie di tag; • Il Capitolo 3 illustra il funzionamento del protocollo EPC Gen2-UHF, analizzando lo strato fisico e l'interfaccia logica; • Nel Capitolo 4 viene proposto un nuovo possibile setup di misura che implementa un reader RFID mediante una periferica USRP. Vengono ripercorsi i passaggi seguiti durante l'attività ed illustrate le problematiche riscontrate; • Il Capitolo 5 descrive il setup utilizzato durante una campagna di misure precedente. Particolare attenzione è posta sul processo di localizzazione dei tag mediante un algoritmo di intersezione di ellissi. Vengono mostrate graficamente le posizioni dei tag così stimate in due scenari, che differiscono per l'orientazione delle antenne rispetto ai tag. Viene inoltre mostrato il procedimento seguito per compensare l'errore sistematico delle misure; • Il Capitolo 6 descrive due algoritmi per la localizzazione di tag, un algoritmo di tipo TDOA (Time Difference Of Arrival) e uno di tipo TOA (Time Of Arrival), entrambi basati su un metodo Least Square; • Nel Capitolo 7 viene mostrato il PEB (Position Error Bound) dell'algoritmo TDOA e TOA precedentemente descritti, per diverse configurazioni dei ricevitori e del trasmettitore

Design, verification and implementation of a non-volatile memory BIST

The main topic of this Thesis is the implementation of a Memory Built-In Self Test (MBIST) which tests a nonvolatile OTP (One-Time Programmable) memory to prove its basic functionalities before burning it. This new IP is meant to be suitable for integration in all products which embed the type of memory targeted by the MBIST. The MBIST reduces the test time from 12 s to 13.443 ms for the largest memory, and from 2.5 s to 5.2 ms for the smallest one. Moreover, it is adaptable to any memory size and its timing constraints can be automatically adjusted to any clock frequency. As a use case, the MBIST has been developed targeting a specific project, a switch LED-matrix manager with constant current regulation and integrated buck-boost controller for automotive headlight applications