Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

The role of technology at school: new perspectives on distance education and cyberbullying

The integration of digital technology in school is a complex phenomenon that affects both teaching and peer relationships. Accordingly, the main aim of this dissertation was to investigate the implementation of distance education among Italian teachers during the COVID-19 pandemic and analyze peer relationships concerning cyberbullying and bullying. While the theoretical section provided an overview of the phenomena, four empirical studies were presented. The first one tested a moderated moderation model among 178 secondary teachers on the interactions among perceived usefulness, perceived ease of use of technology and online teaching self-efficacy. Findings showed that each variable significantly predicted the intention to use technology. In addition, a moderation effect of online teaching self-efficacy on perceived usefulness was found. The second study analyzed the differences in factors promoting the integration of digital technology among 357 teachers of different levels and subjects and their positive and negative experiences with distance education. Results revealed several differences in the function of the grade and subjects taught. Moreover, four main themes emerged from the content analysis. The third study investigated the dyadic perception of bullying and cyberbullying among 50 students using the eye-tracker. Findings showed that, despite differences among different kinds of bullying and cyberbullying, the victim and bully were the most observed roles. Finally, the last study tested two multiple mediation models among 563 students on the association between bullying, cyberbullying, and well-being, considering three different variables related to the school context (peer network, teacher support and school connectedness). The results highlighted the importance of peer networks and school connectedness in mediating the association between victimization, cybervictimzation and well-being. Taken together, the findings provided a rich overview of digital technology integration in schools, highlighting positive and negative aspects and its implications for future research and school policies.

Innovation in aquaculture. Modeling the adoption and implementation processes of innovations in the Italian aquaculture sector

Since the turn of the century, fisheries have maintained a steady growth rate, while aquaculture has experienced a more rapid expansion. Aquaculture can offer EU consumers more diverse, healthy, and sustainable food options, some of which are more popular elsewhere. To develop the sector, the EU is investing heavily. The EU supports innovative projects that promote the sustainable development of seafood sectors and food security. Priority 3 promotes sector development through innovation dissemination. This doctoral dissertation examined innovation transfer in the Italian aquaculture sector, specifically the adoption of innovative tools, using a theoretical model to better understand the complexity of these processes. The work focused on innovation adoption, emphasising that it is the end of a well-defined process. The Awareness Knowledge Adoption Implementation Effectiveness (AKAIE) model was created to better analyse post-adoption phases and evaluate technology adoption implementation and impact. To identify AKAIE drivers and barriers, aquaculture actors were consulted. "Perceived complexity"—barriers to adoption that are strongly influenced by contextual factors—has been used to examine their perspectives (i.e. socio-economic, institutional, cultural ones). The new model will contextualise the sequence based on technologies, entrepreneur traits, corporate and institutional contexts, and complexity perception, the sequence's central node. Technology adoption can also be studied by examining complexity perceptions along the AKAIE sequence. This study proposes a new model to evaluate the diffusion of a given technology, offering the policy maker the possibility to be able to act promptly across the process. The development of responsible policies for evaluating the effectiveness of innovation is more necessary than ever, especially to orient strategies and interventions in the face of major scenarios of change.

Middleware principles and design for the integration of ubiquitos mobile services

Nowadays, in Ubiquitous computing scenarios users more and more require to exploit online contents and services by means of any device at hand, no matter their physical location, and by personalizing and tailoring content and service access to their own requirements. The coordinated provisioning of content tailored to user context and preferences, and the support for mobile multimodal and multichannel interactions are of paramount importance in providing users with a truly effective Ubiquitous support. However, so far the intrinsic heterogeneity and the lack of an integrated approach led to several either too vertical, or practically unusable proposals, thus resulting in poor and non-versatile support platforms for Ubiquitous computing. This work investigates and promotes design principles to help cope with these ever-changing and inherently dynamic scenarios. By following the outlined principles, we have designed and implemented a middleware support platform to support the provisioning of Ubiquitous mobile services and contents. To prove the viability of our approach, we have realized and stressed on top of our support platform a number of different, extremely complex and heterogeneous content and service provisioning scenarios. The encouraging results obtained are pushing our research work further, in order to provide a dynamic platform that is able to not only dynamically support novel Ubiquitous applicative scenarios by tailoring extremely diverse services and contents to heterogeneous user needs, but is also able to reconfigure and adapt itself in order to provide a truly optimized and tailored support for Ubiquitous service provisioning.

Chemical Production and Microelectronic Applications of Graphene and Nano-Graphene Derivatives

Graphene and graphenic derivatives have rapidly emerged as an extremely promising system for electronic, optical, thermal, and electromechanical applications. Several approaches have been developed to produce these materials (i.e. scotch tape, CVD, chemical and solvent exfoliation). In this work we report a chemical approach to produce graphene by reducing graphene oxide (GO) via thermal or electrical methods. A morphological and electrical characterization of these systems has been performed using different techniques such as SPM, SEM, TEM, Raman and XPS. Moreover, we studied the interaction between graphene derivates and organic molecules focusing on the following aspects: - improvement of optical contrast of graphene on different substrates for rapid monolayer identification1 - supramolecular interaction with organic molecules (i.e. thiophene, pyrene etc.)4 - covalent functionalization with optically active molecules2 - preparation and characterization of organic/graphene Field Effect Transistors3-5 Graphene chemistry can potentially allow seamless integration of graphene technology in organic electronics devices to improve device performance and develop new applications for graphene-based materials. [1] E. Treossi, M. Melucci, A. Liscio, M. Gazzano, P. Samorì, and V. Palermo, J. Am. Chem. Soc., 2009, 131, 15576. [2] M. Melucci, E. Treossi, L. Ortolani, G. Giambastiani, V. Morandi, P. Klar, C. Casiraghi, P. Samorì, and V. Palermo, J. Mater. Chem., 2010, 20, 9052. [3] J.M. Mativetsky, E. Treossi, E. Orgiu, M. Melucci, G.P. Veronese, P. Samorì, and V. Palermo, J. Am. Chem. Soc., 2010, 132, 14130. [4] A. Liscio, G.P. Veronese, E. Treossi, F. Suriano, F. Rossella, V. Bellani, R. Rizzoli, P. Samorì and V. Palermo, J. Mater. Chem., 2011, 21, 2924. [5] J.M. Mativetsky, A. Liscio, E. Treossi, E. Orgiu, A. Zanelli, P. Samorì , V. Palermo, J. Am. Chem. Soc., 2011, 133, 14320

Integration of cognitive and affective processes in perception and decision-making

The relationship between emotion and cognition is a topic that raises great interest in research. Recently, a view of these two processes as interactive and mutually influencing each other has become predominant. This dissertation investigates the reciprocal influences of emotion and cognition, both at behavioral and neural level, in two specific fields, such as attention and decision-making. Experimental evidence on how emotional responses may affect perceptual and attentional processes has been reported. In addition, the impact of three factors, such as personality traits, motivational needs and social context, in modulating the influence that emotion exerts on perception and attention has been investigated. Moreover, the influence of cognition on emotional responses in decision-making has been demonstrated. The current experimental evidence showed that cognitive brain regions such as the dorsolateral prefrontal cortex are causally implicated in regulation of emotional responses and that this has an effect at both pre and post decisional stages. There are two main conclusions of this dissertation: firstly, emotion exerts a strong influence on perceptual and attentional processes but, at the same time, this influence may also be modulated by other factors internal and external to the individuals. Secondly, cognitive processes may modulate emotional prepotent responses, by serving a regulative function critical to driving and shaping human behavior in line with current goals.

Integration of MFA and LCA methodologies: the anthropogenic aluminium cycle in Italy

MFA and LCA methodologies were applied to analyse the anthropogenic aluminium cycle in Italy with focus on historical evolution of stocks and flows of the metal, embodied GHG emissions, and potentials from recycling to provide key features to Italy for prioritizing industrial policy toward low-carbon technologies and materials. Historical trend series were collected from 1947 to 2009 and balanced with data from production, manufacturing and waste management of aluminium-containing products, using a ‘top-down’ approach to quantify the contemporary in-use stock of the metal, and helping to identify ‘applications where aluminium is not yet being recycled to its full potential and to identify present and future recycling flows’. The MFA results were used as a basis for the LCA aimed at evaluating the carbon footprint evolution, from primary and electrical energy, the smelting process and the transportation, embodied in the Italian aluminium. A discussion about how the main factors, according to the Kaya Identity equation, they did influence the Italian GHG emissions pattern over time, and which are the levers to mitigate it, it has been also reported. The contemporary anthropogenic reservoirs of aluminium was estimated at about 320 kg per capita, mainly embedded within the transportation and building and construction sectors. Cumulative in-use stock represents approximately 11 years of supply at current usage rates (about 20 Mt versus 1.7 Mt/year), and it would imply a potential of about 160 Mt of CO2eq emissions savings. A discussion of criticality related to aluminium waste recovery from the transportation and the containers and packaging sectors was also included in the study, providing an example for how MFA and LCA may support decision-making at sectorial or regional level. The research constitutes the first attempt of an integrated approach between MFA and LCA applied to the aluminium cycle in Italy.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.