Abstract
Aiming to improve sustainability and life quality, urban space research is prompting an intensive use of communication and information technologies. With it, researchers are also facing more challenges regarding research data management and therefore seeking clear guidelines and tools for proper data organization, sharing and reuse. In the context of a smart cities research project, UrbanSense, held in the city of Porto, we proposed a data management plan, to support researchers from the moment they start to collect data up to the point of data publication. We also developed an ontology for the description of smart cities data, validated by UrbanSense researchers. Descriptions based on this ontology were evaluated by external parties, after the data was published in an institutional data repository. © 2018 IEEE.

Abstract
In this paper we report on a number of speaker identification experiments that assume a phonetic-oriented segmentation scheme exists such as to motivate the extraction of psychoacoustically-motivated phase and pitch related features. MFCC features are also considered for benchmarking. An emphasis is given to an innovative shift-invariant phase-related feature that is closely linked to the glottal source. A very simple statistical modeling is proposed and adapted in order to highlight the relative discrimination capabilities of different feature types. Results are presented for individual features and a discussion is also developed regarding possibilities of fusing features at the speaker modeling stage, or fusing distances at the speaker identification stage. Copyright

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Despite the growing adoption and acceptance of gamification approaches among firms, the relationship between gamification and the early stage of innovation is confusing and deserves further attention in order to produce added-value exploratory knowledge. This paper puts forward the idea that gamification approaches can support the early stage of innovation by making a cross-comparison of published case studies of firms where gamification was used to address innovation challenges, e.g. use of gamification elements and tools that support the generation of ideas for developing new product concepts or entering new markets. In order to understand and clarify the relationship between gamification and the early stage of innovation, the paper proposes an analytical framework that provides a consistent and organized picture of the use of gamification approaches for innovation purposes. Research findings provide a conceptualization of gamification in the context of the early stage of innovation and demonstrate significant outcomes of these types of approaches with regard to the various forms of engagement, team spirit, consensus building, knowledge transfer, creative thinking and productivity.

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This paper puts forth new recovery guarantees for the source separation problem in the presence of side information, where one observes the linear superposition of two source signals plus two additional signals that are correlated with the mixed ones. By positing that the individual components of the mixed signals as well as the corresponding side information signals follow a joint Gaussian mixture model, we characterise necessary and sufficient conditions for reliable separation in the asymptotic regime of low-noise as a function of the geometry of the underlying signals and their interaction. In particular, we show that if the subspaces spanned by the innovation components of the source signals with respect to the side information signals have zero intersection, provided that we observe a certain number of measurements from the mixture, then we can reliably separate the sources, otherwise we cannot. We also provide a number of numerical results on synthetic data that validate our theoretical findings.