Variety, flexibility, and use of abstract concepts. A multiple grounded perspective.

The nature of concepts is a matter of intense debate in cognitive sciences. While traditional views claim that conceptual knowledge is represented in a unitary symbolic system, recent Embodied and Grounded Cognition theories (EGC) submit the idea that conceptual system is couched in our body and influenced by the environment (Barsalou, 2008). One of the major challenges for EGC is constituted by abstract concepts (ACs), like fantasy. Recently, some EGC proposals addressed this criticism, arguing that the ACs comprise multifaced exemplars that rely on different grounding sources beyond sensorimotor one, including interoception, emotions, language, and sociality (Borghi et al., 2018). However, little is known about how ACs representation varies as a function of life experiences and their use in communication. The theoretical arguments and empirical studies comprised in this dissertation aim to provide evidence on multiple grounding of ACs taking into account their varieties and flexibility. Study I analyzed multiple ratings on a large sample of ACs and identified four distinct subclusters. Study II validated this classification with an interference paradigm involving motor/manual, interoceptive, and linguistic systems during a difficulty rating task. Results confirm that different grounding sources are activated depending on ACs kind. Study III-IV investigate the variability of institutional concepts, showing that the higher the law expertise level, the stronger the concrete/emotional determinants in their representation. Study V introduced a novel interactive task in which abstract and concrete sentences serve as cues to simulate conversation. Analysis of language production revealed that the uncertainty and interactive exchanges increase with abstractness, leading to generating more questions/requests for clarifications with abstract than concrete sentences. Overall, results confirm that ACs are multidimensional, heterogeneous, and flexible constructs and that social and linguistic interactions are crucial to shaping their meanings. Investigating ACs in real-time dialogues may be a promising direction for future research.

Rich media content adaptation in e-learning systems

The wide use of e-technologies represents a great opportunity for underserved segments of the population, especially with the aim of reintegrating excluded individuals back into society through education. This is particularly true for people with different types of disabilities who may have difficulties while attending traditional on-site learning programs that are typically based on printed learning resources. The creation and provision of accessible e-learning contents may therefore become a key factor in enabling people with different access needs to enjoy quality learning experiences and services. Another e-learning challenge is represented by m-learning (which stands for mobile learning), which is emerging as a consequence of mobile terminals diffusion and provides the opportunity to browse didactical materials everywhere, outside places that are traditionally devoted to education. Both such situations share the need to access materials in limited conditions and collide with the growing use of rich media in didactical contents, which are designed to be enjoyed without any restriction. Nowadays, Web-based teaching makes great use of multimedia technologies, ranging from Flash animations to prerecorded video-lectures. Rich media in e-learning can offer significant potential in enhancing the learning environment, through helping to increase access to education, enhance the learning experience and support multiple learning styles. Moreover, they can often be used to improve the structure of Web-based courses. These highly variegated and structured contents may significantly improve the quality and the effectiveness of educational activities for learners. For example, rich media contents allow us to describe complex concepts and process flows. Audio and video elements may be utilized to add a “human touch” to distance-learning courses. Finally, real lectures may be recorded and distributed to integrate or enrich on line materials. A confirmation of the advantages of these approaches can be seen in the exponential growth of video-lecture availability on the net, due to the ease of recording and delivering activities which take place in a traditional classroom. Furthermore, the wide use of assistive technologies for learners with disabilities injects new life into e-learning systems. E-learning allows distance and flexible educational activities, thus helping disabled learners to access resources which would otherwise present significant barriers for them. For instance, students with visual impairments have difficulties in reading traditional visual materials, deaf learners have trouble in following traditional (spoken) lectures, people with motion disabilities have problems in attending on-site programs. As already mentioned, the use of wireless technologies and pervasive computing may really enhance the educational learner experience by offering mobile e-learning services that can be accessed by handheld devices. This new paradigm of educational content distribution maximizes the benefits for learners since it enables users to overcome constraints imposed by the surrounding environment. While certainly helpful for users without disabilities, we believe that the use of newmobile technologies may also become a fundamental tool for impaired learners, since it frees them from sitting in front of a PC. In this way, educational activities can be enjoyed by all the users, without hindrance, thus increasing the social inclusion of non-typical learners. While the provision of fully accessible and portable video-lectures may be extremely useful for students, it is widely recognized that structuring and managing rich media contents for mobile learning services are complex and expensive tasks. Indeed, major difficulties originate from the basic need to provide a textual equivalent for each media resource composing a rich media Learning Object (LO). Moreover, tests need to be carried out to establish whether a given LO is fully accessible to all kinds of learners. Unfortunately, both these tasks are truly time-consuming processes, depending on the type of contents the teacher is writing and on the authoring tool he/she is using. Due to these difficulties, online LOs are often distributed as partially accessible or totally inaccessible content. Bearing this in mind, this thesis aims to discuss the key issues of a system we have developed to deliver accessible, customized or nomadic learning experiences to learners with different access needs and skills. To reduce the risk of excluding users with particular access capabilities, our system exploits Learning Objects (LOs) which are dynamically adapted and transcoded based on the specific needs of non-typical users and on the barriers that they can encounter in the environment. The basic idea is to dynamically adapt contents, by selecting them from a set of media resources packaged in SCORM-compliant LOs and stored in a self-adapting format. The system schedules and orchestrates a set of transcoding processes based on specific learner needs, so as to produce a customized LO that can be fully enjoyed by any (impaired or mobile) student.

Exploring Quantum Speed-up Through Cluster-state Computers

The aim of this thesis is to investigate the nature of quantum computation and the question of the quantum speed-up over classical computation by comparing two different quantum computational frameworks, the traditional quantum circuit model and the cluster-state quantum computer. After an introductory survey of the theoretical and epistemological questions concerning quantum computation, the first part of this thesis provides a presentation of cluster-state computation suitable for a philosophical audience. In spite of the computational equivalence between the two frameworks, their differences can be considered as structural. Entanglement is shown to play a fundamental role in both quantum circuits and cluster-state computers; this supports, from a new perspective, the argument that entanglement can reasonably explain the quantum speed-up over classical computation. However, quantum circuits and cluster-state computers diverge with regard to one of the explanations of quantum computation that actually accords a central role to entanglement, i.e. the Everett interpretation. It is argued that, while cluster-state quantum computation does not show an Everettian failure in accounting for the computational processes, it threatens that interpretation of being not-explanatory. This analysis presented here should be integrated in a more general work in order to include also further frameworks of quantum computation, e.g. topological quantum computation. However, what is revealed by this work is that the speed-up question does not capture all that is at stake: both quantum circuits and cluster-state computers achieve the speed-up, but the challenges that they posit go besides that specific question. Then, the existence of alternative equivalent quantum computational models suggests that the ultimate question should be moved from the speed-up to a sort of “representation theorem” for quantum computation, to be meant as the general goal of identifying the physical features underlying these alternative frameworks that allow for labelling those frameworks as “quantum computation”.

mHealth-based Methods for Neuromotor Assessment and Rehabilitation

Recent years observed massive growth in wearable technology, everything can be smart: phones, watches, glasses, shirts, etc. These technologies are prevalent in various fields: from wellness/sports/fitness to the healthcare domain. The spread of this phenomenon led the World-Health-Organization to define the term 'mHealth' as "medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants, and other wireless devices". Furthermore, mHealth solutions are suitable to perform real-time wearable Biofeedback (BF) systems: sensors in the body area network connected to a processing unit (smartphone) and a feedback device (loudspeaker) to measure human functions and return them to the user as (bio)feedback signal. During the COVID-19 pandemic, this transformation of the healthcare system has been dramatically accelerated by new clinical demands, including the need to prevent hospital surges and to assure continuity of clinical care services, allowing pervasive healthcare. Never as of today, we can say that the integration of mHealth technologies will be the basis of this new era of clinical practice. In this scenario, this PhD thesis's primary goal is to investigate new and innovative mHealth solutions for the Assessment and Rehabilitation of different neuromotor functions and diseases. For the clinical assessment, there is the need to overcome the limitations of subjective clinical scales. Creating new pervasive and self-administrable mHealth solutions, this thesis investigates the possibility of employing innovative systems for objective clinical evaluation. For rehabilitation, we explored the clinical feasibility and effectiveness of mHealth systems. In particular, we developed innovative mHealth solutions with BF capability to allow tailored rehabilitation. The main goal that a mHealth-system should have is improving the person's quality of life, increasing or maintaining his autonomy and independence. To this end, inclusive design principles might be crucial, next to the technical and technological ones, to improve mHealth-systems usability.

Perceiving the 3d world from single images

Depth represents a crucial piece of information in many practical applications, such as obstacle avoidance and environment mapping. This information can be provided either by active sensors, such as LiDARs, or by passive devices like cameras. A popular passive device is the binocular rig, which allows triangulating the depth of the scene through two synchronized and aligned cameras. However, many devices that are already available in several infrastructures are monocular passive sensors, such as most of the surveillance cameras. The intrinsic ambiguity of the problem makes monocular depth estimation a challenging task. Nevertheless, the recent progress of deep learning strategies is paving the way towards a new class of algorithms able to handle this complexity. This work addresses many relevant topics related to the monocular depth estimation problem. It presents networks capable of predicting accurate depth values even on embedded devices and without the need of expensive ground-truth labels at training time. Moreover, it introduces strategies to estimate the uncertainty of these models, and it shows that monocular networks can easily generate training labels for different tasks at scale. Finally, it evaluates off-the-shelf monocular depth predictors for the relevant use case of social distance monitoring, and shows how this technology allows to overcome already existing strategies limitations.

Interconnection systems for highly integrated computation devices

The sustained demand for faster,more powerful chips has beenmet by the availability of chip manufacturing processes allowing for the integration of increasing numbers of computation units onto a single die. The resulting outcome, especially in the embedded domain, has often been called SYSTEM-ON-CHIP (SOC) or MULTI-PROCESSOR SYSTEM-ON-CHIP (MPSOC). MPSoC design brings to the foreground a large number of challenges, one of the most prominent of which is the design of the chip interconnection. With a number of on-chip blocks presently ranging in the tens, and quickly approaching the hundreds, the novel issue of how to best provide on-chip communication resources is clearly felt. NETWORKS-ON-CHIPS (NOCS) are the most comprehensive and scalable answer to this design concern. By bringing large-scale networking concepts to the on-chip domain, they guarantee a structured answer to present and future communication requirements. The point-to-point connection and packet switching paradigms they involve are also of great help in minimizing wiring overhead and physical routing issues. However, as with any technology of recent inception, NoC design is still an evolving discipline. Several main areas of interest require deep investigation for NoCs to become viable solutions: • The design of the NoC architecture needs to strike the best tradeoff among performance, features and the tight area and power constraints of the on-chip domain. • Simulation and verification infrastructure must be put in place to explore, validate and optimize the NoC performance. • NoCs offer a huge design space, thanks to their extreme customizability in terms of topology and architectural parameters. Design tools are needed to prune this space and pick the best solutions. • Even more so given their global, distributed nature, it is essential to evaluate the physical implementation of NoCs to evaluate their suitability for next-generation designs and their area and power costs. This dissertation focuses on all of the above points, by describing a NoC architectural implementation called ×pipes; a NoC simulation environment within a cycle-accurate MPSoC emulator called MPARM; a NoC design flow consisting of a front-end tool for optimal NoC instantiation, called SunFloor, and a set of back-end facilities for the study of NoC physical implementations. This dissertation proves the viability of NoCs for current and upcoming designs, by outlining their advantages (alongwith a fewtradeoffs) and by providing a full NoC implementation framework. It also presents some examples of additional extensions of NoCs, allowing e.g. for increased fault tolerance, and outlines where NoCsmay find further application scenarios, such as in stacked chips.

Evaluation of energy level to be absorbed by tractor ROPS: Actual Tests, Simulation and Computation

A highly dangerous situations for tractor driver is the lateral rollover in operating conditions. Several accidents, involving tractor rollover, have indeed been encountered, requiring the design of a robust Roll-Over Protective Structure (ROPS). The aim of the thesis was to evaluate tractor behaviour in the rollover phase so as to calculate the energy absorbed by the ROPS to ensure driver safety. A Mathematical Model representing the behaviour of a generic tractor during a lateral rollover, with the possibility of modifying the geometry, the inertia of the tractor and the environmental boundary conditions, is proposed. The purpose is to define a method allowing the prediction of the elasto-plastic behaviour of the subsequent impacts occurring in the rollover phase. A tyre impact model capable of analysing the influence of the wheels on the energy to be absorbed by the ROPS has been also developed. Different tractor design parameters affecting the rollover behaviour, such as mass and dimensions, have been considered. This permitted the evaluation of their influence on the amount of energy to be absorbed by the ROPS. The mathematical model was designed and calibrated with respect to the results of actual lateral upset tests carried out on a narrow-track tractor. The dynamic behaviour of the tractor and the energy absorbed by the ROPS, obtained from the actual tests, showed to match the results of the model developed. The proposed approach represents a valuable tool in understanding the dynamics (kinetic energy) and kinematics (position, velocity, angular velocity, etc.) of the tractor in the phases of lateral rollover and the factors mainly affecting the event. The prediction of the amount of energy to be absorbed in some cases of accident is possible with good accuracy. It can then help in designing protective structures or active security devices.