Fun2Mas: The Milan Robocup Team

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Machine learning-based dexterous control of hand prostheses

Upper-limb myoelectric prostheses are controlled by muscle activity information recorded on the skin surface using electromyography (EMG). Intuitive prosthetic control can be achieved by deploying statistical and machine learning (ML) tools to decipher the user’s movement intent from EMG signals. This thesis proposes various means of advancing the capabilities of non-invasive, ML-based control of myoelectric hand prostheses. Two main directions are explored, namely classification-based hand grip selection and proportional finger position control using regression methods. Several practical aspects are considered with the aim of maximising the clinical impact of the proposed methodologies, which are evaluated with offline analyses as well as real-time experiments involving both able-bodied and transradial amputee participants. It has been generally accepted that the EMG signal may not always be a reliable source of control information for prostheses, mainly due to its stochastic and non-stationary properties. One particular issue associated with the use of surface EMG signals for upper-extremity myoelectric control is the limb position effect, which is related to the lack of decoding generalisation under novel arm postures. To address this challenge, it is proposed to make concurrent use of EMG sensors and inertial measurement units (IMUs). It is demonstrated this can lead to a significant improvement in both classification accuracy (CA) and real-time prosthetic control performance. Additionally, the relationship between surface EMG and inertial measurements is investigated and it is found that these modalities are partially related due to reflecting different manifestations of the same underlying phenomenon, that is, the muscular activity. In the field of upper-limb myoelectric control, the linear discriminant analysis (LDA) classifier has arguably been the most popular choice for movement intent decoding. This is mainly attributable to its ease of implementation, low computational requirements, and acceptable decoding performance. Nevertheless, this particular method makes a strong fundamental assumption, that is, data observations from different classes share a common covariance structure. Although this assumption may often be violated in practice, it has been found that the performance of the method is comparable to that of more sophisticated algorithms. In this thesis, it is proposed to remove this assumption by making use of general class-conditional Gaussian models and appropriate regularisation to avoid overfitting issues. By performing an exhaustive analysis on benchmark datasets, it is demonstrated that the proposed approach based on regularised discriminant analysis (RDA) can offer an impressive increase in decoding accuracy. By combining the use of RDA classification with a novel confidence-based rejection policy that intends to minimise the rate of unintended hand motions, it is shown that it is feasible to attain robust myoelectric grip control of a prosthetic hand by making use of a single pair of surface EMG-IMU sensors. Most present-day commercial prosthetic hands offer the mechanical abilities to support individual digit control; however, classification-based methods can only produce pre-defined grip patterns, a feature which results in prosthesis under-actuation. Although classification-based grip control can provide a great advantage over conventional strategies, it is far from being intuitive and natural to the user. A potential way of approaching the level of dexterity enjoyed by the human hand is via continuous and individual control of multiple joints. To this end, an exhaustive analysis is performed on the feasibility of reconstructing multidimensional hand joint angles from surface EMG signals. A supervised method based on the eigenvalue formulation of multiple linear regression (MLR) is then proposed to simultaneously reduce the dimensionality of input and output variables and its performance is compared to that of typically used unsupervised methods, which may produce suboptimal results in this context. An experimental paradigm is finally designed to evaluate the efficacy of the proposed finger position control scheme during real-time prosthesis use. This thesis provides insight into the capacity of deploying a range of computational methods for non-invasive myoelectric control. It contributes towards developing intuitive interfaces for dexterous control of multi-articulated prosthetic hands by transradial amputees

Low Input Farming Systems: an Opportunity to Develop Sustainable Agriculture - Proceedings of the JRC Summer University - Ranco, 2-5 July 2007

The concept of sustainability applied to agriculture developed mainly as a result of growing awareness of negative impacts of intensive farming systems on the environment and the quality of life of rural and neighbouring communities. Intensive farming systems are based on genetically uniform crops and livestock breeds, vulnerable to pests and diseases. High yields are obtained through dependency on external inputs (especially fossil energy, fertilizers and pesticides) which can cause decreased air, water, soil and food quality. Intensification and specialisation also bring about landscape changes, resulting in its homogenisation and destruction of traditional landscape elements and, consequently, loss of habitats. Marginal areas, on the other hand, are threatened with cessation of agricultural practices and land abandonment. All these factors also lead, directly or indirectly, to the loss of biodiversity. Lewandowski et al. defined in 1999 sustainable agriculture as ¿the management and utilization of the agricultural ecosystem in a way that maintains its biological diversity, productivity, regeneration capacity, vitality, and ability to function, so that it can fulfill ¿ today and in the future ¿ significant ecological, economic and social functions at the local, national and global levels and does not harm other ecosystems¿. The search for sustainability of agriculture inevitably leads to the exploration of the potential of Low Input Farming Systems (LIFS) to achieve this goal. Within this context, the European Commission Joint Research Centre, Institute for Environment and Sustainability and SOLAGRO organized a Summer University ¿Low Input Farming Systems: an Opportunity to Develop Sustainable Agriculture¿ which took place on 2-5 July 2007 in Ranco (Italy). The programme of the Summer University has been drawn to reflect the diversity of Low Input Farming Systems in Europe and the complexity of factors currently impacting on European agriculture. This report contains the papers which were presented at the meeting as well as final conclusions, summarizing the main points of the discussions which suggested possible lines of future research and policy options which might support LIFS in EuropeJRC.H.5-Rural, water and ecosystem resource

Il design come bene culturale

Il design e, pi\uf9 in generale, le arti applicate e la cultura materiale \u2013 intesi come beni culturali \u2013 e il ruolo del progetto nella loro tutela, valorizzazione e fruizione, costituiscono il campo tematico di cui si occupa il numero 8 di MD Journal. La volont\ue0 di isolare l\u2019argomento all\u2019interno della pi\uf9 vasta riflessione sul design for cultural heritage nasce dal desiderio di mettere a fuoco alcune linee d\u2019indagine che, riconoscendo al design autonomia disciplinare e alle sue produzioni una adeguata collocazione nell\u2019ambito della cultura materiale, possano considerarli sia come oggetto privilegiato di studio, sia come un vasto giacimento culturale dotato di una specifica identit\ue0. All\u2019interno della duplice prospettiva di ricerca del design come bene culturale e del design per beni culturali (Irace, 2013), emerge come denominatore comune la relazione fra tali beni e i loro fruitori, ossia il tema della \u201cricezione culturale\u201d

Computational Architecture: development, design and optimization. Case study of a glass and steel roof for the Scuola Normale Superiore's courtyard in Pisa

This thesis is built around the conception, development and optimization of complex architecture, also known as free form. The project consists in a steel and glass roof over the inner courtyard of the Scuola Normale Superiore, with the aim to make the living space accessible at every moment of day life. The shape was conceived such that it would suit well the architecture of the Scuola Normale and the spirit it emobdies, with a special regard to energetics and fabrication, true weakness of architectures of this kind. The structure was modelled entirely on Grasshopper, a Rhino3D plug-in which allows to parametrically design objects. This programming environment allowed to interface add-ons, both proprietary and made on purpose by the author. With those tools, the author was able to develop algorithms for structural and geometric optimization. The former consisted in the process at the end of which the best structural performance is found, at constant weight: in the case studym genetic algorithms and iterative processes were used. Geometric optimization consisted in seeking the fabricability of the architecture, in the reduction of overall panel curvatures and eventually in the panelization of the surface. Finally, thanks to the code so created, it was possible to easily export all data and run required analysis exploiting the software more suited for each needing

Allegro non troppo

"A film that will let you see the music and listen to drawings; in a word, a film full of Fantasia!" Bruno Bozzetto's Allegro non Troppo tips its hand right away: it is an unabashed, yet full of admiration, retake on Walt Disney's 1940 "concert feature". The obvious nod to that model fuels many tongue-in-cheek jokes in the film; however, Allegro non Troppo soon departs from mere parody, and becomes a showcase for the multifaceted aesthetics of Italian animation in 1976, as well as a witty social satire and a powerful rethinking of the music-image relationship in cinema. Marco Bellano's open access book reconstructs the history of the production of Allegro non Troppo, on the basis of an original research developed with the contribution of Bozzetto himself; it also presents an audiovisual analysis of the work, as to reassess the international relevance of Bozzetto's achievements by giving insight into the director's creative process. The eBook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com