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People-centric computing and communications in smart cities
No full textThe extremely pervasive nature of mobile technologies, together with the user\u27s need to continuously interact with her personal devices and to be always connected, strengthen the user-centric approach to design and develop new communication and computing solutions. Nowadays users not only represent the final utilizers of the technology, but they actively contribute to its evolution by assuming different roles: they act as humans, by sharing contents and experiences through social networks, and as virtual sensors, by moving freely in the environment with their sensing devices. Smart cities represent an important reference scenario for the active participation of users through mobile technologies. It involves multiple application domains and defines different levels of user engagement. Participatory sensing, opportunistic sensing, and mobile social networks (MSNs) currently represent some of the most promising people-centric paradigms. In addition, their integration can further improve the user involvement through new services and applications. In this article we present SmartCitizen app, an MSN application designed in the framework of a smart city project to stimulate the active participation of citizens in generating and sharing useful contents related to the quality of life in their city. The app has been developed on top of a context- and social-aware middleware platform (CAMEO) able to integrate the main features of people-centric computing paradigms, lightening the app developer\u27s effort. Existing middleware platforms generally focus on a single people-centric paradigm, exporting a limited set of features to mobile applications. CAMEO overcomes these limitations and, through Smart- Citizen, we highlight the advantages of implementing this type of mobile application in a smart city scenario. Experimental results shown in this article can also represent the technical guidelines for the development of heterogeneous people-centric mobile applications embracing different application domains
Appetitive Pavlovian-instrumental Transfer: a review
No full textReward-related cues are an important part of our daily life as they often influence and guide our actions. This paper reviews one of the experimental paradigms used to study the effects of cues, the Pavlovian to Instrumental Transfer paradigm. In this paradigm, cues associated with rewards through Pavlovian conditioning alter motivation and choice of instrumental actions. The first transfer experiments date back to the 1940s, but only in the last decade has it been fully recognised that there are two types of transfer, specific and general. This paper presents a systematic review of both the neural substrates and the behavioral factors affecting both types of transfer. It also examines the recent application of the paradigm to study the effect of cues on human participants, both in normal and pathological conditions, and the interactions of transfer with drugs of abuse. Finally, the paper analyses the theoretical aspects of transfer to build an overall picture of the phenomenon, from early theories to recent hierarchical accounts
Stress still affects articulatory planning in reading aloud: A Reply to White and Besner (2016)
No full textIn their comment White and Besner (2016) argue against our conclusion that stress assignment may affect polysyllable pseudoword reading and conclude that, currently, we do not know whether the effect of stress position is solid and reliable. White and Besner state that because the experiments reported in Sulpizio, Spinelli and Burani (2015) have methodological problems, our conclusion is grounded on weak evidence. In this reply we present further analyses of our data that overcome the methodological weakness highlighted by White and Besner. The results of these new analyses consistently mirror those reported by Sulpizio and colleagues (2015) and speak in favor of the view that, in reading Italian pseudowords aloud, stress assignment affects articulatory planning of the stimulus
Interplay of rhythmic and discrete manipulation movements during development: a policy-search reinforcement-learning robot model
No full textThe flexibility of human motor behavior strongly relies on rhythmic and discrete movements. Developmental psychology has shown how these movements closely interplay during development, but the dynamics of that are largely unknown and we currently lack computational models suitable to investigate such interaction. This work initially presents an analysis of the problem from a computational and empirical perspective and then proposes a novel computational model to start to investigate it. The model is based on a movement primitive capable of producing both rhythmic and end-point discrete movements, and on a policy search reinforcement learning algorithm capable of mimicking trial-and-error learning processes underlying development and efficient enough to work on real robots. The model is tested with hand manipulation tasks ("touching," "tapping," and "rotating" an object). The results show how the system progressively shapes the initial rhythmic exploration into refined rhythmic or discrete movements depending on the task demand. The tests on the real robot also show how the system exploits the specific hand-object physical properties, some possibly shared with developing infants, to find effective solutions to the tasks. The results show that the model represents a useful tool to investigate the interplay of rhythmic and discrete movements during development
Role of 18F-FDG-PET imaging in the diagnosis of autoimmune encephalitis
No full textEstablishing the clinical diagnosis of autoimmune encephalitis can be challenging as patients present with various unspecific symptoms.1 In a Position Paper1 in The Lancet Neurology, Francesc Graus and colleagues proposed an initial diagnostic work-up relying on conventional neurological evaluation and standard diagnostic tests such as MRI, CSF sampling, and EEG. This approach would enable clinicians to make a timely diagnosis of "possible autoimmune encephalitis", allowing initiation of immunotherapy. In a second step, the authors proposed comprehensive antibody testing to help to establish a diagnosis of "probable autoimmune encephalitis" or "defi nite autoimmune encephalitis", potentially enabling refinement of treatment.
Crowdsourcing: It matters who the crowd are. The impacts of between group variations in recording land cover
No full textVolunteered geographical information (VGI) and citizen science have become important sources data for much scientific research. In the domain of land cover, crowdsourcing can provide a high temporal resolution data to support different analyses of landscape processes. However, the scientists may have little control over what gets recorded by the crowd, providing a potential source of error and uncertainty. This study compared analyses of crowdsourced land cover data that were contributed by different groups, based on nationality (labelled Gondor and Non-Gondor) and on domain experience (labelled Expert and Non-Expert). The analyses used a geographically weighted model to generate maps of land cover and compared the maps generated by the different groups. The results highlight the differences between the maps how specific land cover classes were under- and over-estimated. As crowdsourced data and citizen science are increasingly used to replace data collected under the designed experiment, this paper highlights the importance of considering between group variations and their impacts on the results of analyses. Critically, differences in the way that landscape features are conceptualised by different groups of contributors need to be considered when using crowdsourced data in formal scientific analyses. The discussion considers the potential for variation in crowdsourced data, the relativist nature of land cover and suggests a number of areas for future research. The key finding is that the veracity of citizen science data is not the critical issue per se. Rather, it is important to consider the impacts of differences in the semantics, affordances and functions associated with landscape features held by different groups of crowdsourced data contributors
KPIs 4 workplace learning
No full textEnterprises and Public Administrations alike need to ensure that newly hired employees are able to learn the ropes fast. Employers also need to support continuous workplace learning. Workplace learning should be strongly related to business goals and thus, learning goals should directly add to business goals. To measure achievement of both learning and business goals we propose augmented Key Performance Indicators (KPI). In our research we applied model driven engineering. Hence we developed a model for a Learning Scorecard comprising of business and learning goals and their KPIs represented in an ontology. KPI performance values and scores are calculated with formal rules based on the SPARQL Inferencing Notation. Results are presented in a dashboard on an individual level as well as on a team/group level. Requirements, goals and KPIs as well as performance measurement were defined in close cooperation with Marche Region, business partner in Learn PAd
Learning Path Specification forWorkplace Learning based on Business Process Management
No full textIn modern society, workers are continuously challenged to acquire new skills and competencies while at work. Novel approaches and tools to support effective and efficient workplace learning in collaborative and engaging ways are needed. On the other hand, Business Process Management (BPM) is more and more employed to support and manage the complex processes carried out within organizations. We propose to use BPM also to drive workplace learning, with the advantage of aligning real tasks to training tasks. We introduce a specification of learning path that maps BPM tasks and activities into sequences of learning tasks that can be customized to learners competence. The learning path specification can be used to both drive learning sessions, and to inform a monitor that can assess learner\u27s progress. We describe a platform that is under development, and provide a simple motivational example to illustrate the approach. The goal is to combine work and learning in natural and effective way
What are features? An ontology-based review of the literature
No full textFeature-based product modeling is the leading approach for the integrated representation of engineering product data. On the one side, this approach has stimulated the development of formal models and vocabularies, data standards and computational ontologies. On the other side, the current ways to model features are considered problematic since it lacks a principled and uniform methodology for feature representation. This paper reviews the state of art of feature-based modeling approaches by concentrating on how features are conceptualized. It points out the drawbacks of current approaches and proposes a high-level ontology-based perspective to harmonize the definition of feature
#selfie: mapping the phenomenon
No full textThe introduction of smartphones equipped with a front camera and constantly connected to social networks has encouraged the spread of usergenerated content of multimedia nature. This led to the emergence of new social phenomena that have a strong impact on society, like the selfie, a modern evolution of the selfportrait usually taken with a digital camera or a camera phone. In the last three years, especially on Instagram, the selfie trend got popularity. Defined in 2013 as "a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and shared via social media", by the Oxford Dictionary, which added selfie to its lexicon and then named it name of the year. This work analyzes the phenomenon inside Instagram, a mobile socialbased network created specifically for image sharing. Given the strong social implications, we tried to understand the origin of this practice, the psychological and sociological reasons that gave birth to the trend. Then, through the webbased platform ALOS (A Lot Of Selfies) we collected information from instagram, performed face recognition and calculated statistics about the trend. As a case study, over 2 million selfies shared on Instagram in January February 2015 were analyzed. This highlighted how the selfie phenomenon is perceived differently in various cultures and societies. In particular, the results show that factors such religion, sex, customs and geopolitical situations affect the spacetime distribution of selfies around the world