A service-based testbed for Trust Negotiation

Trust Negotiation allows users to develop trust incrementally, by disclosing credentials step by step. This way, services and resources can be shared in an open environment, and access rights can be granted on the basis of peer-to-peer trust relationships. This article presents a service-based testbed for Trust Negotiation. At its core, it is created as a generic framework based on the WS-Trust standard. It integrates a modular trust engine and a rule engine, which is used as a policy checker. The system is mainly oriented at Web services composition and location-based social networking scenarios

Multilanguage Semantic Interoperability in Distributed Applications

JOSI is a software framework that tries to simplify the development of such kinds of applications both by providing the possibility of working on models for representing such semantic information and by offering some implementations of such models that can be easily used by software developers without any knowledge about semantic models and languages. This software library allows the representation of domain models through Java interfaces and annotations and then to use such a representation for automatically generating an implementation of domain models in different programming languages (currently Java and C++). Moreover, JOSI supports the interoperability with other applications both by automatically mapping the domain model representations into ontologies and by providing an automatic translation of each object obtained from the domain model representations in an OWL string representation

A unified framework for traditional and agent-based social network modeling

In the last sixty years of research, several models have been proposed to explain (i) the formation and (ii) the evolution of networks. However, because of the specialization required for the problems, most of the agent-based models are not general. On the other hand, many of the traditional network models focus on elementary interactions that are often part of several different processes. This phenomenon is especially evident in the field of models for social networks. Therefore, this chapter presents a unified conceptual framework to express both novel agent-based and traditional social network models. This conceptual framework is essentially a meta-model that acts as a template for other models. To support this meta-model, the chapter proposes a different kind of agent-based modeling tool that we specifically created for developing social network models. The tool the authors propose does not aim at being a general-purpose agent-based modeling tool, thus remaining a relatively simple software system, while it is extensible where it really matters. Eventually, the authors apply this toolkit to a novel problem coming from the domain of P2P social networking platforms

Multilanguage Semantic Interoperability in Distributed Applications

JOSI is a software framework that tries to simplify the development of such kinds of applications both by providing the possibility of working on models for representing such semantic information and by offering some implementations of such models that can be easily used by software developers without any knowledge about semantic models and languages. This software library allows the representation of domain models through Java interfaces and annotations and then to use such a representation for automatically generating an implementation of domain models in different programming languages (currently Java and C++). Moreover, JOSI supports the interoperability with other applications both by automatically mapping the domain model representations into ontologies and by providing an automatic translation of each object obtained from the domain model representations in an OWL string representation

A DHT-Based Multi-Agent System for Semantic Information Sharing. In

Abstract. This paper presents AOIS, a multi-agent system that supports the sharing of information among a dynamic community of users connected through the Internet thanks to the use of a well-known DHT-based peer-to-peer platform: BitTorrent. In respect to Web search engines, this system enhances the search through domain ontologies, avoids the burden of publishing the information on the Web and guaranties a controlled and dynamic access to the information. The use of agent technologies has made the realization of three of the main features of the system straightforward: i) filtering of information coming from different users, on the basis of the previous experience of the local user, ii) pushing of some new information that can be of interest for a user, and iii) delegation of access capabilities, on the basis of a reputation network, built by the agents of the system on the community of its users. The use of BitTorrent will allow us to offer the AOIS systems to the hundreds of millions of users that already share documents though the BitTorrent platform

Emotion-based analysis of programming languages on Stack Overflow

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Anomaly detection in laser-guided vehicles' batteries: a case study

Detecting anomalous data within time series is a very relevant task in pattern recognition and machine learning, with many possible applications that range from disease prevention in medicine, e.g., detecting early alterations of the health status before it can clearly be defined as "illness" up to monitoring industrial plants. Regarding this latter application, detecting anomalies in an industrial plant's status firstly prevents serious damages that would require a long interruption of the production process. Secondly, it permits optimal scheduling of maintenance interventions by limiting them to urgent situations. At the same time, they typically follow a fixed prudential schedule according to which components are substituted well before the end of their expected lifetime. This paper describes a case study regarding the monitoring of the status of Laser-guided Vehicles (LGVs) batteries, on which we worked as our contribution to project SUPER (Supercomputing Unified Platform, Emilia Romagna) aimed at establishing and demonstrating a regional High-Performance Computing platform that is going to represent the main Italian supercomputing environment for both computing power and data volume.Comment: This paper contains a report on the research work carried out as a collaboration between the Department of Engineering and Architecture of the University of Parma and Elettric80 spa within project SUPER (Supercomputing Unified Platform Emilia Romagna

Fine-Grained Agent-Based Modeling to Predict Covid-19 Spreading and Effect of Policies in Large-Scale Scenarios

Modeling and forecasting the spread of COVID-19 remains an open problem for several reasons. One of these concerns the difficulty to model a complex system at a high resolution (fine-grained) level at which the spread can be simulated by taking into account individual features such as the social structure, the effects of the governments’ policies, age sensitivity to Covid-19, maskwearing habits and geographical distribution of susceptible people. Agent-based modeling usually needs to find an optimal trade-off between the resolution of the simulation and the population size. Indeed, modeling single individuals usually leads to simulations of smaller populations or the use of meta-populations. In this article, we propose a solution to efficiently model the Covid-19 spread in Lombardy, the most populated Italian region with about ten million people. In particular, the model described in this paper is, to the best of our knowledge, the first attempt in literature to model a large population at the single-individual level. To achieve this goal, we propose a framework that implements: i. a scale-free model of the social contacts combining a sociability rate, demographic information, and geographical assumptions; ii. a multi-agent system relying on the actor model and the High-Performance Computing technology to efficiently implement ten million concurrent agents. We simulated the epidemic scenario from January to April 2020 and from August to December 2020, modeling the government’s lockdown policies and people’s maskwearing habits. The social modeling approach we propose could be rapidly adapted for modeling future epidemics at their early stage in scenarios where little prior knowledge is available

Epstein-barr virus induced cellular changes in nasal mucosa

A 21-year-old man presented with nasal obstruction of the right nasal fossa of 1 year duration. Nasal endoscopy revealed in the right inferior turbinate head a rounded neoplasm about 1 cm in diameter. Cytologic study of a nasal scraping specimen disclosed numerous clusters containing columnar cells with cytomegaly, prominent multinucleation, markedly sparse shortened cilia; the cytoplasm contained an acidophil area and a small round area that stained poorly; cells with a large intracytoplasmic vacuole that was acidophil and PAS+. Serology tests using the nested polymer chain reaction (PCR) technique on serum, nasal and pharyngeal smears revealed an Epstein-Barr virus (EBV) infection that was confirmed at electron microscopy. The clinical and cytological features resolved 19 months after the initial evaluation. CONCLUSION: The authors advise carrying out clinical (endoscopy, serology, etc.) evaluation of all endonasal neoplasms and to routinely perform cytological study on nasal scraping specimens. When samples test positive for EBV, nasal and nasopharyngeal endoscopy should be performed regularly to detect possible evidence for nasopharyngeal carcinoma (NPC)