An IoT-enabled Framework for Context-aware Role-based Access Control

We present a framework for enforcing the application of context-aware Role-based Access Control policies based on an Internet of Things eco-system inspired by the Google\u2019s Physical Web. In this setting we are interested in capturing three contextual dimensions, namely who-where-when, and using these information to restrict access to shared resources. Formally, the framework consists of features types, an automata-based model of time-sensitive roles, context-aware permission rules, and an IoT infrastructure based on Eddystone Beacons for validating a policy against the current state of users

Context Aware Source Selection for Linked Data

The traditional Web is evolving into the Web of Data, which gathers huge collections of structured data over distributed, heterogeneous data sources. Live queries are needed to get current information out of this global data space. In live query processing, source selection allows the identification of the sources that most likely contain relevant content. Due to the semantic heterogeneity of the Web of Data, however, it is not always easy to assess relevancy. Context information might help in interpreting the user\u2019s information needs. In this paper, we discuss how context information can be exploited to improve source selection

Recurring retrieval needs in diverse and dynamic dataspaces: Issues and reference framework

Processing information requests over heterogeneous data spaces is very challenging because aimed at guaranteeing user satisfaction with respect to conflicting requirements on result quality and response time. In [3], it has been argued that, in dynamic contexts pre-venting substantial user involvement in interpreting requests, information on similar requests recurring overtime can be exploited during query processing. In this paper, referring to a graph-based modeling of dataspaces and requests, we propose a preliminary approach in this direction centered on the enabling concept of Profiled Graph Query Pattern (PGQP) as an aggregation of information on past evaluations of a set of previously executed queries. The information maintained in PGQP is not query results, as in materialized queries, but can include different kinds of data and metadata

Lossy Compressor preserving variant calling through Extended BWT

A standard format used for storing the output of high-throughput sequencing experiments is the FASTQ format. It comprises three main components: (i) headers, (ii) bases (nucleotide sequences), and (iii) quality scores. FASTQ files are widely used for variant calling, where sequencing data are mapped into a reference genome to discover variants that may be used for further analysis. There are many specialized compressors that exploit redundancy in FASTQ data with the focus only on either the bases or the quality scores components. In this paper we consider the novel problem of lossy compressing, in a reference-free way, FASTQ data by modifying both components at the same time, while preserving the important information of the original FASTQ. We introduce a general strategy, based on the Extended Burrows-Wheeler Transform (EBWT) and positional clustering, and we present implementations in both internal memory and external memory. Experimental results show that the lossy compression performed by our tool is able to achieve good compression while preserving information relating to variant calling more than the competitors. Availability: the software is freely available at https://github.com/veronicaguerrini/BFQzip.Comment: Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologie

Water pollution in wastewater treatment plants: An efficiency analysis with undesirable output

The environmental efficiency of 96 Tuscan (Italian) wastewater treatment plants (WWTPs) is investigated taking into account the quality of the outgoing water in terms of pollutant. In this regard, the presence of the residual nitrogen in the outgoing treated water is considered as undesirable output. The efficiency analysis is performed by applying a novel integrated Analytic Hierarchy Process/Non-radial Directional Distance Function (AHP/NDDF) approach, combining the benefits of the two techniques. Similarly to the standard NDDF approach, the suggested model allows to include simultaneously inputs, desirable and undesirable outputs and not to overestimate the efficiency scores. At the same time, the AHP inclusion gives the possibility to directly take into account the decision maker preferences in the weighting system and to encompass some existing directional distance function models as special cases.The obtained results are then used to identify the efficiency explanatory variables: among them, the facilities' capacity, the percentage of wastewater discharged by the industrial and agricultural activities and the level of compliance with the pollutant concentration threshold set by the legislator have a significant impact on the WWTP performance. The integrated performance assessment allows the water authorities to combine the WWTP efficiency together with the environmental sustainability issue and it has the potential for further promising environmental inspections