Wireless ATM layouts for chain networks

In this paper we consider the problem of constructing ATM layouts for wireless networks in which mobile users can move along a chain of base stations. We first show that deciding the existence of a layout with maximum hop count h, load l and channel distance d is NP-complete for every fixed value of d greater or equal to 1. We then provide optimal layout constructions for the case d less than or equal to 2. Finally, optimal layout constructions are obtained also for any d within the class of the so-called canonic layouts, that so far have always been shown to be the optimal ones

Data augmentation using background replacement for automated sorting of littered waste

The introduction of sophisticated waste treatment plants is making the process of trash sorting and recycling more and more effective and eco-friendly. Studies on Automated Waste Sorting (AWS) are greatly contributing to making the whole recycling process more efficient. However, a relevant issue, which remains unsolved, is how to deal with the large amount of waste that is littered in the environment instead of being collected properly. In this paper, we introduce BackRep: a method for building waste recognizers that can be used for identifying and sorting littered waste directly where it is found. BackRep consists of a data-augmentation procedure, which expands existing datasets by cropping solid waste in images taken on a uniform (white) background and superimposing it on more realistic backgrounds. For our purpose, realistic backgrounds are those representing places where solid waste is usually littered. To experiment with our data-augmentation procedure, we produced a new dataset in realistic settings. We observed that waste recognizers trained on augmented data actually outperform those trained on existing datasets. Hence, our data-augmentation procedure seems a viable approach to support the development of waste recognizers for urban and wild environments

Influential users in Twitter: detection and evolution analysis

In this paper, we study how to detect the most influential users in the microblogging social network platform Twitter and their evolution over time. To this aim, we consider the Dynamic Retweet Graph (DRG) proposed in Amati et al. (2016) and partially analyzed in Amati et al. (IADIS Int J Comput Sci Inform Syst, 11(2) 2016), Amati et al. (2016). The model of the evolution of the Twitter social network is based here on the retweet relationship. In a DRGs, the last time a tweet has been retweeted we delete all the edges representing this tweet. In this way we model the decay of tweet life in the social platform. To detect the influential users, we consider the central nodes in the network with respect to the following centrality measures: degree, closeness, betweenness and PageRank-centrality. These measures have been widely studied in the static case and we analyze them on the sequence of DRG temporal graphs with special regard to the distribution of the 75% most central nodes. We derive the following results: (a) in all cases, applying the closeness measure results into many nodes with high centrality, so it is useless to detect influential users; (b) for all other measures, almost all nodes have null or very low centrality and (c) the number of vertices with significant centrality are often the same; (d) the above observations hold also for the cumulative retweet graph and, (e) central nodes in the sequence of DRG temporal graphs have high centrality in cumulative graph

Time-based Microblog Distillation

This paper presents a simple approach for identifying relevant and reliable news from the Twitter stream, as soon as they emerge. The approach is based on a near-real time systems for sentiment analysis on Twitter, implemented by Fondazione Ugo Bordoni, and properly modified in order to detect the most representative tweets in a specified time slot. This work represents a first step towards the implementation of a prototype supporting journalists in discovering and finding news on Twitter

Theoretical Computer Science in Italy: The Early Years

In this article, we provide an overview of the early developments of theoretical computer science research in Italy in the Sixties and early Seventies. In the same years, the community of researchers working in this domain were organizing to gain an identity among the more traditional disciplines and to obtain a recognition for the "new science" that was taking its first steps. This led in Italy to the creation of Group of Researchers in Theoretical Informatics, in parallel to the institution of European Association for Theoretical Computer Science at European level. In this article, we characterize the Italian contribution to theoretical computer science research in those early years by describing the landscape of activities developed in Italian Universities and research centers in the late sixties and early seventies, on the basis of a census run in 1971 by the newly born GRIT

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