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In this paper we study the liveness of several MUTEX solutions by representing them as processes in PAFAS s, a CCS-like process algebra with a specific operator for modelling non-blocking reading behaviours. Verification is carried out using the tool FASE, exploiting a correspondence between violations of the liveness property and a special kind of cycles (called catastrophic cycles) in some transition system. We also compare our approach with others in the literature. The aim of this paper is twofold: on the one hand, we want to demonstrate the applicability of FASE to some concrete, meaningful examples; on the other hand, we want to study the impact of introducing non-blocking behaviours in modelling concurrent systems

In the last few decades, we have witnessed an increasing focus on safety in the workplace. ICT has always played a leading role in this context. One ICT sector that is increasingly important in ensuring safety at work is the Internet of Things and, in particular, the new architectures referring to it, such as SIoT, MIoT and Sentient Multimedia Systems. All these architectures handle huge amounts of data to extract predictive and prescriptive information. For this purpose, they often make use of Machine Learning. In this paper, we propose a framework that uses both Sentient Multimedia Systems and Machine Learning to support safety in the workplace. After the general presentation of the framework, we describe its specialization to a particular case, i.e., fall detection. As for this application scenario, we describe a Machine Learning based wearable device for fall detection that we designed, built and tested. Moreover, we illustrate a safety coordination platform for monitoring the work environment, activating alarms in case of falls, and sending appropriate advices to help workers involved in falls.

A Private Assisted House aims to define a novel care model focusing on the changing needs of people to promote active life expectancy. This raises the need of personalization in the design and development of Smart Home, so starting from users requirements we stress the need of integration suitable to support such changing requirements. In this paper we discuss Private Assisted House integration platform focusing on its conceptual model and reference architecture. The platform is defined around a set of smart objects managed by a home gateway that communicate with a Cloud Center. This organization provide two kinds of processing: (i) local to the house, and (ii) remote. The local processing involves events, triggers, commands and automations managed directly for the gateway. The remote processing implies communication from the house to the Cloud Center that can provide intelligence to the house using high-level applications that use data correlation to perform specific tasks

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In this paper, we present FASE (Faster Asynchronous Systems Evaluation), a tool for evaluating the worst-case efficiency of asynchronous systems. The tool is based on some well-established results in the setting of a timed process algebra (PAFAS: a Process Algebra for Faster Asynchronous Systems). To show the applicability of FASE to concrete meaningful examples, we consider three implementations of a bounded buffer and use FASE to automatically evaluate their worst-case efficiency. We finally contrast our results with previous ones where the efficiency of the same implementations has already been considered.

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