Uncovering the patterns of human mobility, which characterize the trajectories humans follow during their daily activity, is not only a major intellectual challenge, but also of importance for urban planning, transportation engineering, public health, and economic forecasting. Recently, the availability of mobile-phone records, global-positioning-system data and other mobility-related big data capturing aspects of human mobility are providing a new powerful social microscope, and have given empirically driven momentum to the subject. Based on these data, a new multidisciplinary research area is emerging at the crossroads of mobility, data mining, statistical modeling, and privacy. The seminar assesses this research frontier by providing an account on the models of human mobility recently developed by network scientists and statistical physicists, as well as on the methods for mobility data mining, such as trajectory pattern mining and trajectory clustering, developed by data mining researchers. We illustrate the key results of a European-wide research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, which created an integrated platform for complex analysis of mobility data, and show its analytical power in unvealing the complexity of urban mobility in a large scale experiment, based on a massive real life GPS dataset, obtained from 17,000 vehicles with on-board GPS receivers, tracked during one week of ordinary mobile activity in the city of Milan, Italy. We argue how statistical modeling and computational sciences are converging towards a data science that, powered by the big data of ICT-mediated human activities, is aiming at a quantitative understanding of social phenomena. We conclude with an example of how the combined methods of data mining and network science can provide deeper insight into the interplay between human mobility and the social network, and how the movement behavior of people impacts the dynamics of social ties.
New technologies have increased the possibilities of communicative expression and expanded processes and procedures of accessing, organizing and communicating information. If in the past it was possible to manually structure and visualize data, nowadays computation methods are intrinsic to how we deal with very large data sets, whether in the design of exploratory analytical tools or for communication purposes. The term Big Data well expresses the state of the field and the challenges ahead of us. A central question is how to prepare not only future generations, but ourselves included, to deal with the data proliferation: from learning how to structure and analyze data to developing skills and methods for effectively visualizing information. It is critical to foster understanding of relationships between visual thinking, visual representation, and visual communication. How can we promote informed criteria to support the design process of data visualization?
About the Speaker
Isabel Meirelles is an Associate Professor of Art & Design and the Associate Dean of the College of Arts, Media & Design at Northeastern University in Boston, MA. Isabel recent interests are in data visualization and visual analytics, and she collaborates with the Center for Complex Network Research of Northeastern Univ. in Boston and with the Knowledge Discovery and Data Mining laboratory (KDD LAB) in Pisa. A recent example of this line of her work is the visualization of the Human Development Index for the United Nations: http://hdr.undp.org/en/humandev/lets-talk-hd/.
Neuroengineering is a novel discipline combining engineering including micro and nanotechnology, electrical and mechanical, and computer science with cellular, molecular, cognitive neuroscience with two main goals: (i) increase our basic knowledge of how the nervous system works; (ii) develop systems able to restore functions in people affected by different types of neural disability. In the past years, several breakthroughs have been reached by neuroengineers in particular on the development of neural prostheses able to restore sensorimotor functions in disabled people.
In this presentation, two main research activities on this topic will be presented. First, the recent results achieved after the implantation of thin-film intra-fascicular electrodes in the median and ulnar nerves of an amputee will be shown. The possibility of decoding motor commands suitable to control a dexterous hand prosthesis has been investigated during a 4 week trial. The results showed that the extraction of motor information (i.e., grip types) is possible with good performance and that the user was able to improve his ability to provide useful motor commands over time.
Secondly, the progress towards the development of a novel neural prosthesis to restore locomotion in spinal cord injured people will be presented. To achieve this ambitious goal, we capitalize on recent breakthroughs that demonstrate the impressive capacity of spinal cord stimulations to promote the recovery of full weight bearing walking in paralyzed SCI rats. The preliminary results of the characterization of the response after epidural stimulation and of the processing of cortical signals to control the stimulation will be presented.
Mirror neurons are a set of neurons that discharge both when the monkey executes a specific motor act and when it observes another individual doing a similar act. In the first part of my talk, I will review the basic functional properties of monkey frontal mirror neurons. I will describe first their motor properties showing that they code the goal of a motor act. I will review then their visual properties and present evidence that mirror neurons represent a mechanism that allows a direct understanding of what the agent is doing. Mirror mechanism also exists in humans. I will present the data proving it will show evidence that, although there are other mechanisms through which one can understand the behavior of others, the mirror mechanism is the only one that allows understanding others “from the inside” providing the observer with a “first-person” person grasp of others’ motor goals, intentions and emotions. I will conclude discussing the relationship between autism deficits and damage to the mirror mechanism. I will show that while children with autism understand the what of an observed motor act, they fail to recognize the why behind it. Because of these impairments, children with autism lack experiential understanding of others and rely on external factors in their behavior.
Selex Sistemi Integrati activities will be presented, in particular about radar products and related processing technologies. The European Project SMECY (Smart Multicore Embedde System) and the results of the collaboration on CeCoNo (Cell Computing Node) Project will be described. The CeCoNo activity consists in the parallel design and realization of some high-performance critical sections of the STAP environment for radar processing, applying the methodology of the High-Performance Lab of the Computer Science Department.
The design of artificial systems able to learn and adapt has been one of the main goals of Artificial Intelligence since its very beginning. To this end, statistical modelling has proven to be a tool of extraordinary effectiveness. In some cases, however, statistics is not the most adequate language for analyzing the interaction between a learning agent and an ever-changing environment. Indeed, a research thread, emerged in parallel with statistical learning, views this interaction as a repeated game between agent and environment. This different approach allows to analyze, in a rigorous framework, predictive models without any statistical assumptions. In this talk we will trace the roots of the game-theoretic approach in learning theory and describe some of the key results.
Nel seminario verrà presentato il progetto di ricerca FIRB "Piattaforma di servizi integrati per l'accesso semantico e plurilingue ai contenuti culturali italiani nel web", il cui obiettivo principale è l'elaborazione di strumenti di selezione e classificazione dei contenuti relativi ai domini della Linguistica, dell'Arte e della Letteratura.
Dopo una panoramica generale sul progetto di ricerca verranno presentate in dettaglio le fasi dell'estrazione terminologica automatica e della successiva validazione, operata dagli esperti di settore. Verrà mostrato il procedimento dell'estrazione terminologica a partire da corpora testuali di dominio e verrà illustrata una proposta di classificazione delle unità lessicali estratte, sulla base dei concetti di "termine", "quasi-termine" e "non termine".
Verranno infine illustrate le prospettive di ricerca, con particolare riferimento alla costruzione di una base di conoscenza per ciascun dominio a partire dalle liste di termini validati.
Pagina 4 di 6