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Stress in context: morpho-syntactic properties affect lexical stress assignment in reading aloud.
No full textRecent findings from English and Russian have shown that grammatical category plays a key role in stress assignment. In these languages, some grammatical categories have a typical stress pattern and this information is used by readers. However, whether readers are sensitive to smaller distributional differences and other morpho-syntactic properties (e.g., gender, number, person) remains unclear. We addressed this issue in word and nonword reading in Italian, a language in which: 1) nouns and verbs differ in the proportion of words with a dominant stress pattern; 2) information specified by words sharing morpho-syntactic properties may contrast with other sources of information, such as stress neighborhood. Both aspects were addressed in two experiments in which context words were used to induce the desired morpho-syntactic properties. Experiment 1 showed that the relatively different proportions of stress patterns between grammatical categories do not affect stress processing in word reading. In contrast, Experiment 2 showed that information specified by words sharing morpho-syntactic properties outweighs stress neighborhood in nonword reading. Thus, while general information specified by grammatical categories may not be used by Italian readers, stress neighbors with morpho-syntactic properties congruent with those of the target stimulus have a primary role in stress assignment. These results underscore the importance of expanding investigations of stress assignment beyond single words, as current models of single-word reading seem unable to account for our results
Speial Issue (1984) - LIDAR stratospheric aerosol measurements at IROE 1983-1984 measurements
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Wireless Power Transfer in Sensor Networks with Adaptive, Limited Knowledge Protocols
No full textIn this chapter, we investigate the problem of efficient wireless power transfer in Wireless Rechargeable Sensor Networks (WRSNs). In such networks a special mobile entity (called the Mobile Charger) traverses the network and wirelessly replenishes the energy of sensor nodes. In contrast to other approaches, we envision methods that are distributed, adaptive and use limited network information. We propose three new, alternative protocols for efficient charging, addressing key issues which we identify, most notably (i) to what extent each sensor should be charged (ii) what is the best split of the total energy between the charger and the sensors and (iii) what are good trajectories the Mobile Charger should follow. One of our protocols (LRP) performs some distributed, limited sampling of the network status, while another one (RTP) reactively adapts to energy shortage alerts judiciously spread in the network. We conduct detailed simulations in uniform and non-uniform network deployments, using three different underlying routing protocol families. In most cases, both our charging protocols significantly outperform known state of the art methods, while their performance gets quite close to the performance of the global knowledge method (GKP) we also provide
Distributed Coordination Protocols for Wireless Charging in Sensor Networks
No full textChargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state-of-the-art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method
Social fingerprinting - or the truth About you
No full textInspired by biological DNA, we model the behaviour of online users as ?Digital DNA? sequences, introducing a strikingly novel, simple, and effective approach to discriminate between genuine and spambot online accounts
A novel security information and event management system for enhancing cyber security in a hydroelectric dam.
No full textSecurity information and event management (SIEM) systems are increasingly used to cope with the security challenges involved in critical infrastructure protection. However, these systems have several limitations. This paper describes an enhanced security information and event management system that (i) resolves conflicts between security policies; (ii) discovers unauthorized network data paths and appropriately reconfigures network devices; and (iii) provides an intrusion- and fault-tolerant storage system that ensures the integrity and non-forgeability of stored events. The performance of the enhanced system is demonstrated using a case study involving a hydroelectric dam. The case study considers an attack model that affects portions of the information technology infrastructure of the hydroelectric dam and demonstrates that the security information and event management system is successfully able to detect and respond to attacks
Spotting the diffusion of New Psychoactive Substances over the Internet
No full textOnline availability and diffusion of New Psychoactive Substances (NPS) represent an emerging threat to healthcare systems. In this work, we analyse drugs forums, online shops, and Twitter. By mining the data from these sources, it is possible to understand the dynamics of drugs di usion and their endorsement, as well as timely detecting new substances. We propose a set of visual analytics tools to support analysts in tackling NPS spreading and provide a better insight about drugs market and analysis
Madam: Effective and efficient behavior-based android malware detection and prevention
No full textAndroid users are constantly threatened by an increasing number of malicious applications (apps), generically called malware. Malware constitutes a serious threat to user privacy, money, device and file integrity. In this paper we note that, by studying their actions, we can classify malware into a small number of behavioral classes, each of which performs a limited set of misbehaviors that characterize them. These misbehaviors can be defined by monitoring features belonging to different Android levels. In this paper we present MADAM, a novel host-based malware detection system for Android devices which simultaneously analyzes and correlates features at four levels: kernel, application, user and package, to detect and stop malicious behaviors. MADAM has been designed to take into account those behaviors characteristics of almost every real malware which can be found in the wild. MADAM detects and effectively blocks more than 96% of malicious apps, which come from three large datasets with about 2,800 apps, by exploiting the cooperation of two parallel classifiers and a behavioral signature-based detector. Extensive experiments, which also includes the analysis of a testbed of 9,804 genuine apps, have been conducted to show the low false alarm rate, the negligible performance overhead and limited battery consumptio
A geographic distribution data set of biodiversity in Italian freshwaters
No full textWe present a data set on the biodiversity of Italian freshwaters, including lakeshores and riverbanks of natural (N=379: springs, streams and lakes) and artificial (N=11: fountains) sites. The data set belongs partly to the Italian Long Term Ecological Research network (LTER-Italy) and partly to LifeWatch, the European e-Science infrastructure for biodiversity and ecosystem research. The data included cover a time period corresponding to the last fifty years (1962-2014). They span a large number of taxa from prokaryotes and unicellular eukaryotes to vertebrates and plants, including taxa linked to the aquatic habitat in at least part of their life cycles (like immature stages of insects, amphibians, birds and vascular plants). The data set consists of 6463 occurrence data and distribution records for 1738 species. The complete data set is available in csv file format via the LifeWatch Service Centre