Fine-grained access control via policy-carrying data

W. W. Vasconcelos acknowledges the support of the Engineering and Physical Sciences Research Council (EPSRC, UK) within the research project “Scrutable Autonomous Systems” (SAsSY, http://www.scrutable-systems.org, Grant ref. EP/J012084/1). Also in: Journal ACM Transactions on Reconfigurable Technology and Systems (TRETS) - Special Section on FCCM 2016 and Regular Papers TRETS Homepage archive Volume 11 Issue 1, March 2018 Article No. 31 ACM New York, NY, USAPeer reviewedPostprin

Normative design using inductive learning

In this paper we propose a use-case-driven iterative design methodology for normative frameworks, also called virtual institutions, which are used to govern open systems. Our computational model represents the normative framework as a logic program under answer set semantics (ASP). By means of an inductive logic programming approach, implemented using ASP, it is possible to synthesise new rules and revise the existing ones. The learning mechanism is guided by the designer who describes the desired properties of the framework through use cases, comprising (i) event traces that capture possible scenarios, and (ii) a state that describes the desired outcome. The learning process then proposes additional rules, or changes to current rules, to satisfy the constraints expressed in the use cases. Thus, the contribution of this paper is a process for the elaboration and revision of a normative framework by means of a semi-automatic and iterative process driven from specifications of (un)desirable behaviour. The process integrates a novel and general methodology for theory revision based on ASP.Comment: Theory and Practice of Logic Programming, 27th Int'l. Conference on Logic Programming (ICLP'11) Special Issue, volume 11, issue 4-5, 201

Multi-sensor data fusion framework for CNC machining monitoring

Reliable machining monitoring systems are essential for lowering production time and manufacturing costs. Existing expensive monitoring systems focus on prevention/detection of tool malfunctions and provide information for process optimisation by force measurement. An alternative and cost-effective approach is monitoring acoustic emissions (AEs) from machining operations by acting as a robust proxy. The limitations of AEs include high sensitivity to sensor position and cutting parameters. In this paper, a novel multi-sensor data fusion framework is proposed to enable identification of the best sensor locations for monitoring cutting operations, identifying sensors that provide the best signal, and derivation of signals with an enhanced periodic component. Our experimental results reveal that by utilising the framework, and using only three sensors, signal interpretation improves substantially and the monitoring system reliability is enhanced for a wide range of machining parameters. The framework provides a route to overcoming the major limitations of AE based monitoring

Proceedings of the 4th European Workshop on Multi-Agent Systems (EUMAS 2006)

Proceedings of the 4th European Workshop on Multi-Agent Systems (EUMAS 2006) Lisbon, Portugal, 14-15 December 200

Mathematical Service Discovery: Architecture, Implementation and Performance

Service discovery and matchmaking in a distributed environment has been an active research issue since at least the mid 1990s Previous work on matchmaking has typically presented the problem and service descriptions as free or structured (marked-up) text, so that keyword searches, tree-matching or simple constraint solving are sufficient to identify matches. In this paper, we discuss the problem of matchmaking for mathematical services, where the semantics play a critical role in determining the applicability or otherwise of a service. A matchmaking architecture supporting the use of match plug-ins is first described, followed by the types of plug-ins that can be supported. The matched services are ranked based on the score obtained from each plug-in, with the user being able to decide which plug-in is most significant in the context of their particular application. We consider the effect of pre- and post-conditions of mathematical service descriptions on matching, and how and why to reduce queries into DNF and CNF before matching. Application examples demonstrate in detail how the matching process works for all four algorithms. Additionally, an evaluation of the ontological mode is provided, regarding performance of loading ontologies, query response time and the overall scalability is conducted. The performance results are used to demonstrate scalability issues in supporting ontology-based discovery within a Web Services environment