1,720,955 research outputs found
Enhanced models for privacy and utility in continuous-time diffusion networks
No full textControlling the propagation of information in social networks is a problem of growing importance. On one hand, users wish to freely communicate and interact with their peers. On the other hand, the information they spread can bring to harmful consequences if it falls in the wrong hands. There is therefore a trade-off between utility, i.e. reaching as many intended nodes as possible, and privacy, i.e. avoiding the unintended ones. The problem has attracted the interest of the research community: some models have already been proposed to study how information propagates and to devise policies satisfying the intended privacy and utility requirements. In this paper, we adapt the basic framework of Backes et al. to include more realistic features, that in practice influence the way in which information is passed around. More specifically, we consider: (a) the topic of the shared information, (b) the time spent by users to forward information among them and (c) the user social behaviour. For all features, we show a way to reduce our model to the basic one, thus allowing the methods provided in the original paper to cope with our enhanced scenarios. Furthermore, we propose an enhanced formulation of the utility/privacy policies, to maximize the expected number of reached users among the intended ones, while minimizing this number among the unintended ones, and we show how to adapt the basic techniques to these enhanced policies. We conclude by giving a new approach to the maximization/minimization problem by finding a trade-off between the risk and the gain function through biobjective optimization
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Effect of different conditions of dehydration on the volatile composition of Nebbiolo grapes (Vitis vinifera L.)
No full textIn the wine sector when we speak of post-harvest, we mean of dehydration or withering technologies used for making not only sweet wines.
This work is part of a research project aimed to optimize, in field and after harvest, the production of chemical compounds of oenological interest, that is polyphenols and volatile organic compounds.
Until some years ago, the dehydration of grapes has been seen as a process of concentration of simple sugars without any important regard for other quality characteristics, in particular aroma. But, the water loss is responsible for large and significant changes in the metabolism of fruits and vegetables (e.g. respiration and cell wall enzyme activity). For this reason, the technology or practice of dehydrating grapes can play an important role in modulating the production and release of secondary metabolites like free and bound volatile compounds in grape and wine (1, 2). The biosynthesis of aroma compounds is a very complex process that involves various metabolisms. The activation or inhibition of these metabolisms is strongly dependent on the grape maintenance procedure (temperature, relative humidity, dehydration rate, light) before and after harvest. Moreover, the drying process affects the physical state of the berry (shape, tissue texture) depending on ambient conditions and this could change the extractability of aroma compounds from the different portions of the berry during winemaking.
In this paper we present the results of an experimental study conducted using a dehydration tunnel for the dehydration of Nebbiolo grapes at different condition of temperature (10°C and 20°C; 60% relative humidity). Our attention was mainly focused on comparing the free volatiles present in skin and pulp of grapes dehydrated at 0%, 10% and 20% of weight loss
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
DOCTOR: A Simple Method for Detecting Misclassification Errors
No full textDeep neural networks (DNNs) have shown to perform very well on large scale object recognition problems and lead to widespread use for real-world applications, including situations where DNN are implemented as “black boxes”. A promising approach to secure their use is to accept decisions that are likely to be correct while discarding the others. In this work, we propose DOCTOR, a simple method that aims to identify whether the prediction of a DNN classifier should (or should not) be trusted so that, consequently, it would be possible to accept it or to reject it. Two scenarios are investigated: Totally Black Box (TBB) where only the soft-predictions are available and Partially Black Box (PBB) where gradient-propagation to perform input pre-processing is allowed. Empirically, we show that DOCTOR outperforms all state-of-the-art methods on various well-known images and sentiment analysis datasets. In particular, we observe a reduction of up to 4% of the false rejection rate (FRR) in the PBB scenario. DOCTOR can be applied to any pre-trained model, it does not require prior information about the underlying dataset and is as simple as the simplest available methods in the literature
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