529 research outputs found
Context-aware pervasive interfaces
No full textThe proliferation of pervasive services requires advanced methods to adapt the service provision to the user's context. The author presents a hybrid statistical and semantic framework for interface selection and adaptation. The approach is to find the best compromise between urgency and privacy requirements, avoiding interference with the user's activities
Environmental stress and flowering time: the photoperiodic connection
No full textPlants maximize their chances to survive adversities by reprogramming their development according to environmental conditions. Adaptive variations in the timing to flowering reflect the need for plants to set seeds under the most favorable conditions. A complex network of genetic pathways allows plants to detect and integrate external (e.g., photoperiod and temperature) and/or internal (e.g., age) information to initiate the floral transition. Furthermore different types of environmental stresses play an important role in the floral transition. The emerging picture is that stress conditions often affect flowering through modulation of the photoperiodic pathway. In this review we will discuss different modes of cross talk between stress signaling and photoperiodic flowering, highlighting the central role of the florigen genes in this process.Matteo Riboni, Alice Robustelli Test, Massimo Galbiati, Chiara Tonelli & Lucio
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Constructing the terrorist in the decisions of the supreme court of the United States and the European court of human rights
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Cor-split: Defending privacy in data re-publication from historical correlations and compromised tuples
No full textSeveral approaches have been proposed for privacy preserving data publication. In this paper we consider the important case in which a certain view over a dynamic dataset has to be released a number of times during its history. The insufficiency of techniques used for one-shot publication in the case of subsequent releases has been previously recognized, and some new approaches have been proposed. Our research shows that relevant privacy threats, not recognized by previous proposals, can occur in practice. In particular, we show the cascading effects that a single (or a few) compromised tuples can have in data re-publication when coupled with the ability of an adversary to recognize historical correlations among released tuples. A theoretical study of the threats leads us to a defense algorithm, implemented as a significant extension of the m-invariance technique. Extensive experiments using publicly available datasets show that the proposed technique preserves the utility of published data and effectively protects from the identified privacy threats. © 2009 Springer Berlin Heidelberg
Enhancing Citizen Engagement : Political Weblogs and Participatory Democracy
No full textThis chapter discusses the function of blogs as tools enhancing citizen participation in political communication. Adopting the perspective of corpus-assisted critical discourse analysis, a set of blogs from the US presidential election campaign are analysed in order to determine the frequency of reference to the candidates, the parties, as well as the bloggers themselves. The analysis of pronoun choice, verbs and modality indicate that blogs enhance participation rhetoric. The data further indicate that citizen bloggers attach more importance to individual political figures than party bloggers do. The tendency to refer to the candidates rather than to their political affiliation may be explained as evidence that people not belonging to parties interpret politics as a struggle between different politicians and not between different ideologies. Since the language representation of the political scene in citizens’ blogs shows distinct traces of the ongoing process of personalization of politics, the political blog can be considered as a “tool of citizen empowerment”
Microblogging as Professional Practice : The Use of Twitter by Academics
No full textThis study sets out to examine the language of microblogging interactions in the academic domain and specifically investigates the practice of conference live-tweeting. Live-tweeting, i.e posting a sequence of focused entries (“tweets” of 140 characters) on the microblogging platform. Scholars often adopt it to cover the conferences they attend, thus providing their audience with information as well as their personal observations. Live-tweets always include a hashtag (a keyword beginning with the # symbol) which performs the double function of detailing the content of the entry and of allowing users to retrieve all the tweets marked with the same hashtag (Serneels 2013). This means that people (notably academics) who cannot be physically present can have a real-time report -albeit mediated- of the conferences they are interested in by simply clicking on the hashtag link.
Building on previous studies on conference live-tweeting from a linguistic perspective, this paper intends to explore the textual and rhetorical features of Twitter messages posted by academics attending conferences. Twitter feeds are well-suited to automatic interrogation routines typical of corpus-based approaches (cf. among others, Sinclair 1991; Baker 2006): due to their interconnectedness and extensiveness, they are arguably better investigated as a whole rather than separately, as normally happens in other areas of discourse analysis (Myers 2015, p. 55). Consequently, an ad hoc corpus consisting of ca. 3,000 tweets was collected for the study and analyzed through the automatic interrogation routines typical of corpus linguistics; tweets were selected on the basis of hashtags in order to examine the microblogging coverage of three different sets of conference events with each set corresponding to a specific academic discipline (i.e. Linguistics, Medicine, and Web Development). The three subcorpora were investigated and compared both quantitatively and qualitatively in order to shed light onto the similarities as well as the peculiarities of conference live-tweeting practices of these three academic communities.
References
Baker, P. 2006. Using Corpora in Discourse Analysis. London: Continuum.
Myers, G. 2015. Social Media and Professional Practice in Medical Twitter. In Gotti, M., Maci S. and Sala M. (eds.), Insight into Medical Communication, Bern: Peter Lang, pp. 51- 69.
Serneels, A. 2013. How to Really Define A Live Tweet? Live Tweet App. Articles about Using Twitter for Your Events, Twitter Wall and Social News. 7th Feb 2013. . Accessed 16.04.2016.
Sinclair, J. M. 1991. Corpus, Concordance, Collocation. Oxford: Oxford University Press
Exploiting Feature Selection in Human Activity Recognition: Methodological Insights and Empirical Results Using Mobile Sensor Data
No full textHuman Activity Recognition (HAR) using mobile sensor data has gained increasing attention over the last few years, with a fast-growing number of reported applications. The central role of machine learning in this field has been discussed by a vast amount of research works, with several strategies proposed for processing raw data, extracting suitable features, and inducing predictive models capable of recognizing multiple types of daily activities. Since many HAR systems are implemented in resource-constrained mobile devices, the efficiency of the induced models is a crucial aspect to consider. This paper highlights the importance of exploiting dimensionality reduction techniques that can simplify the model and increase efficiency by identifying and retaining only the most informative and predictive features for activity recognition. More in detail, a large experimental study is presented that encompasses different feature selection algorithms as well as multiple HAR benchmarks containing mobile sensor data. Such a comparative evaluation relies on a methodological framework that is meant to assess not only the extent to which each selection method is effective in identifying the most predictive features but also the overall stability of the selection process, i.e., its robustness to changes in the input data. Although often neglected, in fact, the stability of the selected feature sets is important for a wider exploitability of the induced models. Our experimental results give an interesting insight into which selection algorithms may be most suited in the HAR domain, complementing and significantly extending the studies currently available in this field
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