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Tuttoscuola n. 560: Piccoli cittadini digitali a scuola di coding
No full textL\u27articolo descrive la collaborazione tra la Ludoteca del Registro .it e il progetto Pisa CoderDojoL\u27articolo descrive la collaborazione tra la Ludoteca del Registro .it e il progetto Pisa CoderDoj
Assigning Hierarchy to Collaborative Mobile Charging in Sensor Networks
No full textWireless power transfer is used to fundamentally address energy management problems in Wireless Rechargeable Sensor Networks (WRSNs). In such networks, mobile entities traverse the network and wirelessly replenish the energy of sensor nodes. In recent research on collaborative mobile charging, the mobile entities are also allowed to charge each other. In this chapter, we enhance the collaborative feature by forming a hierarchical charging structure. We distinguish the Chargers in two groups, the hierarchically lower, called Mobile Chargers, that charge sensor nodes and the hierarchically higher, called Special Chargers, that charge Mobile Chargers. We define the Coordination Decision Problem and prove that it is NP-complete. Also, we propose a new protocol for 1-D networks which we compare with a state-of-the-art protocol. Motivated by the improvement in 1-D networks, we design four new collaborative charging protocols for 2-D networks to achieve efficient charging and improve important network properties. Our protocols are either centralized or distributed, and assume different levels of network knowledge. Extensive simulation findings demonstrate significant performance gains, with respect to non-collaborative state-of-the-art charging methods. In particular, our protocols improve several network properties and metrics, such as the network lifetime, routing robustness, coverage, and connectivity. A useful feature of our methods is that they can be suitably added on top of non-collaborative protocols to further enhance their performance
Towards an Automated Analysis of the Online Supply Chain of Novel Psychoactive Substances
No full textNovel Psychoactive Substances (NPSs), also known as legal highs or smart drugs, are legal alternatives to illegal drugs. Many drugs consumers are appealed by the opportunity of buying substances without any legal consequences. Online shops, virtual marketplaces and other trade channels thrive in this legal grey area. The health risks connected to this phenomenon are high: every year hundreds of people present symptoms deriving to the use or abuse of those unknown chemicals, and health professionals may struggle to provide the appropriate treatments. EU is taking some countermeasures, forbidding the sale of the NPS as soon as it is established their risk for the health, but natural or synthetic new substances are continuously discovered or manufactured, and it is difficult for legislators to keep up. To cope with the lack of regulation in this market sector, EU is funding the CASSANDRA project, to study and comprehend NPSs lifecycle and supply chain, through the automatic analysis of user generated content (forums and social media) and online markets. During the first year of activity, we combined data gathering, analysis, and visualization techniques to i) provide an insight over two large forums, Bluelight and Drugs-forum, that host discussions about drugs since more than a decade; ii) investigate how substances sold by online shops of the NPSs supply chain map inside the forums and iii) investigate how social networks like Facebook and Twitter are used to avertise and discuss drug consumption. In order to gather as much data as possible from forums, we developed an ad-hoc web scraper. The system keeps track of the forum hierarchy and structure, keeping all tags and other metadata associated to posts, threads and forums. All the content is anonymized and stored in a relational database with an associated text indicization. We got a snapshot of Drugs-forum and Bluelight, whose content spans respectively from 2003 and 1999 to today, with more than 1 million and more than 3 millions of posts, and about 200 thousands and 350 thousands of users respectively. A selected set of 10 online NPSs shops underwent a similar scraping and storage phase, while we crawled the social media pages connected to those shops through the provided APIs. We extracted a list of the advertised products in those shops and pages, finding more than 250. The forums have been the starting point and the core of the analyses so far. We developed some interfaces to investigate their structure, the number of posts per thread and the number of posts per user (which, as expected, follow a power low distribution). Moreover, we analysed the textual content of the posts, showing the number of occurrences of terms over time (Figure 1), in which sections a series of known NPSs are first mentioned, the terms co-occurring with other terms. In particular, this last analysis is leading to an automated system to show the most frequent symptoms mentioned together with the name of a substance. We also analyzed the hyperlinks appearing in the forums, and compared them with a comprehensive list of online NPSs shops and related social media accounts, finding that they don?t quite overlap, and which NPSs sold in those shops are mentioned in the forums, finding that almost every substance is mentioned. In the future we plan to extend the analysis to dark web marketplaces. Future work will also involve the development of an automatic system to detect the mention of unknown substances, in order to monitor the discussion about them from the start, to understand where substances are first mentioned and sold, and how the supply chain evolves
Online User Behavioural Modeling with Applications to Price Steering
No full textPrice steering is the practice of ?changing the order of search results to highlight specific products? and products prices. In this paper, we show an initial investigation to quantify the price steering level in search results shown to different kind of users on Google Shopping. We mimic the category of affluent users. Affluent users visit websites offering expensive services, search for luxury goods and always click on the most costly items results at Google Shopping. The goal is checking if users trained in specific ways get different search results, based on the price of the products in the results. Evaluation is based on well known metrics to measure page results differences and similarities. Experiments are automised, rendering large-scale investigations feasible. Results of our experiments, based on a preliminary experimental setting, show that users trained on some particular topics are not always influenced by previous search and click activities. However, different trained users actually achieve different search results, thus paving the way for further investigation
Privacy-aware Data Sharing in a Tree-based Categorical Clustering Algorithm
No full textDespite being one of the most common approaches in unsupervised data analysis, a very small literature exists in applying formal methods to addressdata mining problems. This paper applies an abstract representation of a hierarchical categorical clustering algorithm (CCTree) to solve the problem of privacy-aware data clustering in distributed agents. The proposed methodology is based on rewriting systems, and automatically generates a global structure of the clusters. We prove that the proposed approach improves the time complexity.Moreover a metric is provided to measure the privacy gain after revealing the CCTree result. Furthermore, we discuss under what condition the CCTree clustering in distributed framework produces the comparable result to the centralized one
Stereo Visualisation of Historical Aerial Photos - an Useful and Important Aerial Archeology Research Tool
No full textIn this article we present some case studies in which historical aerial photos are central elements in the research process and we demonstrate how the investigation benefits from a stereo visualisation of these images, resulting in a useful tool for Aerial Archaeology. These examples include photographs from both WWI and WWII as well as images from the post war era, showing a landscape that is now transformed or not even accessible due to human constructions. Stereo images are useful as they give a much better understanding of what is actually seen on the ground than single photos ever can, thanks to the depth cue that helps understanding the content and adds the ability to distinguish each element on the ground. Hence, stereo helps in estimating heights of single objects, just as well as the relative height of all objects on the ground that form a site. Nonetheless, it is also important to stress that stereo also helps in understanding the surrounding landscape. This paper will discuss the challenges that still have to be faced in order to create stereo images useful for archaeologists and will reflect on the many possibilities and advantages that stereo visualisation of aerial photos offer
Optimal Deployment of Stations for a Car Sharing System with Stochastic Demands: a Queueing Theoretical Perspective
No full textCar sharing holds a promise of reducing trafficcongestion and pollution in cities as well as of boosting the useof public transport when used as a last-mile solution in a multimodaltransportation scenario. Despite this huge potential,several problems related to the deployment and operations ofcar sharing systems have yet to be fully addressed. In thiswork, we focus on station-based car sharing and we define anoptimization problem for the deployment of its stations. Thegoal of this problem is to find the minimum cost deployment(in terms of number of stations and their capacity) that canguarantee a pre-defined level of service to the customers (interms of probability of finding an available car/parking space).This problem combines insights from queueing theory (usedto model the stochastic demand for cars/parking spaces at thestations) with a variant of the classical set covering problem.For its evaluation, we use a trace of more than 100,000 pickupand drop-off events at a free-floating car sharing service in TheNetherlands, which are used to model the input demand of thecar sharing system. Our results show that the proposed solutionis able to strike the right balance between cost minimisationand quality of service, outperforming three alternative schemesused as benchmarks
Modeling Privacy Aware Information Sharing Systems: A Formal and General Approach
No full textThis paper presents and model a novel general framework for privacy aware collaborative information sharing for data analysis. Collaborative information sharing systems can be cross-domain, involve different data providers which might also be competitors. For this reason, shared information may imply privacy concerns, which must be addressed, applying privacy preserving mechanisms on information before sharing them. However, since the application of these privacy preserving mechanisms may negatively affect the accuracy of data analysis, a trade-off must be considered, and the privacy preserving mechanism to be applied must be chosen correctly. The proposed framework is based on the separation between a first level which enforces information privacy as specified by data providers, and a second level which performs data analysis on the sanitized data. The proposed framework defines and models a workflow which applies to any privacy aware collaborative information sharing system, defines indexes to measure the compatibility between privacy requirements, and includes a novel method to compute the trade-off between privacy and accuracy. This work also proposes a methodology to choose, case-by-case, the privacy mechanism whic maximizes the trade-off between privacy and accuracy. An applicative example on a real dataset with more than 30k records is also presented
Online Social Networks
No full textThis special issue of Computer Communications is devoted to Online Social Networks (OSN). OSN are one of the most disruptive communication platforms of the last 15 years. Nowadays, most people use OSN regularly, as a normal facet of their daily lives. Moreover, the widespread diffusion of mobile personal devices (smartphones and tablets) is boosting the use of OSN services in mobility. The statistics about these facts are just impressive. For example, as of now Facebook reached 1.49 billion monthly active users and 1.31 mobile monthly active users 1, while Twitter reached 316 million active users, with 80% of the users active on mobile devices2. Beyond accessing OSN services from mobile, the penetration of OSN use through personal mobile devices is having very significant impacts also on the type of OSN services and, more in general, on people?s behaviour, as we discuss in the following. In fact, OSN have been indicated as one of the hot topics for Computer Communication
Word knowledge and word usage: a foreword
No full textThis special issue, together with its companion issue to appear in Italian Journal of Linguistics, stems from the NetWordS Final Conference "Word knowledge and word usage: representations and processes in the mental lexicon". The conference, held on the 30th and 31st of March, and the 1st of April 2015 in Pisa, concluded the 4-year NetWordS project, the European Network of Word Structure funded by the European Science Foundation within the Research Networking Programme. In line with the highly multidisciplinary profile of NetWordS agenda, the conference offered a comprehensive and inclusive forum focussing on two main lines of lexical inquiry: (i) usage-based approaches to bootstrapping word form and structure (morpho-phonological and morpho-syntactic issues), including: acquisition of lexical categories, emergence of morphological structure, lexical memories, anticipatory prediction-based mechanisms of word recognition, word production, frequency-based models of lexical productivity, word encoding, models of lexical architecture, family-based effects in word processing, word reading and writing; (ii) usage-based approaches to word meanings (lexical semantics and pragmatics in morphologically simple and complex words), including: distributional semantics, compound interpretation, concept composition and coercion, conceptualization of perception and action, time and space in the lexicon, metonymy and metaphor, lexico-semantic relations, perceptual grounding and embodied cognition, context-based and encyclopedic knowledge, semantic association and categorization. The multidisciplinary focus on word knowledge and word usage promoted by the Conference led participants to openly discuss an impressive range of approaches and empirical data: priming and lexical decision in a number of contexts, distributional semantics and models of semantic composition, neural networks, machine learning and mathematical modelling of empirical evidence, as well as their neuro-biological and neuro-functional correlates. It is widely acknowledged that looking at the same problem from different angles has an additive effect on the impact of current language research. Certainly more can be achieved, however, if, rather than simply adding more perspectives on the same subject, with individual research efforts staying within the boundaries of single knowledge domains, scholars manage to integrate them into a boundary-shifting methodological perspective. When psycholinguistic evidence from humans is successfully replicated algorithmically through a computational model implementing a few well-understood principles of time-series processing, we are in a position to empirically assess what input conditions favour memorisation and acquisition of symbolic strings by the model, and test these algorithmic predictions back on human subjects, thus going full circle. This may have a multiplicative effect on current research, providing not only mathematical modelling of present behavioural evidence, but amounting to fully explanatory mechanisms. Our current understanding of WHERE and WHEN some cognitive processes are implemented in the brain will be complemented by knowledge of WHAT information they rely on and HOW they integrate it. Other compelling examples of the full potential of cross-disciplinary integration can be found in the present volume and in the twin issue of Italian Journal of Linguistics. As a general point, we contend that only by putting single-domain acquisitions into the wider context of human communication, and developing an interdisciplinary framework whereby each specialist will take advantage of insights from other disciplines, we can make substantial progress in our understanding of the lexical roots of human verbal communication in real contexts. The edited selection of papers presented here provides a representative sample of the range of approaches debated at the NetWordS Pisa Conference, by way of illustration of how aspects of knowledge integration and methodological innovation can be put at the service of a better understanding of broad lexical issues