Design and optimisation of a novel magnetic detection scheme for encoded magnetic information carriers.

Previous work in the field has outlined a method to create micron-sized, tuneable encoded magnetic information carriers that can be redeposited through a liquid suspension. This thesis aims to build on this work, further characterising the information carriers and presenting a possible novel detection technique. The magnetic information carriers in this work use synthetic antiferromagnetic (SAF) particles with perpendicular magnetic anisotropy (PMA), attenuating the coupling strength between the magnetic layers using a platinum interlayer. This provides a controllable magnetic parameter which is used as the basis for the magnetic encoding. These particles can be lifted off the substrate into a solution for redeposition onto a surface which provides a magnetic ‘tag’. The particles are presented and characterised, including statistical distributions of switching events to better understand their detectable properties. A novel detection scheme for these particles is then proposed using inductive sensing and a rotating permanent magnet as a drive field source. Device efficacy is evaluated using computational simulations, allowing for the optimisation of the parameter space before physical building. The efficacy of different input parameters is evaluated using a figure of merit – the number of possible channels the detector can measure. The simulations begin with an idealised model of the detector and particle set, with zero coercivity SAF particles and perfect alignment. The different methods that the detector can be used in are assessed, as well as exploring the possible input geometries. Real-world constraints are later built into the model including the switching distributions of particles and the effects of misalignment. From these, the build constraints and electronic requirements of the system can be characterised. The detector is finally presented virtually through computer-aided design, which would be used to create a prototype model of the device

Strategic Port Graph Rewriting: an Interactive Modelling Framework

International audienceWe present strategic port graph rewriting as a basis for the implementation of visual modelling tools. The goal is to facilitate the specification and programming tasks associated with the modelling of complex systems. A system is represented by an initial graph and a collection of graph rewrite rules, together with a user-defined strategy to control the application of rules. The traditional operators found in strategy languages for term rewriting have been adapted to deal with the more general setting of graph rewriting, and some new constructs have been included in the strategy language to deal with graph traversal and management of rewriting positions in the graph. We give a formal semantics for the language, and describe its implementation: the graph transformation and visualisation tool Porgy

Contributions to Statistical Model Checking

Statistical Model Checking (SMC) is a powerful and widely used approach that consists in estimating the probability for a system to satisfy a temporal property. This is done by monitoring a finite number of executions of the system, and then extrapolating the result by using statistics. The answer is correct up to some confidence that can be parameterized by the user. It is known that SMC mitigates the state-space explosion problem and allows us to handle requirements that cannot be expressed in classical temporal logics. The approach has been implemented in several toolsets, and successfully applied in a wide range of diverse areas such as systems biology, robotic, or automotive. Unfortunately, SMC is not a panacea and many important classes of systems and properties are still out of its scope. Moreover, In addition, SMC still indirectly suffers from an explosion linked to the number of simulations needed to converge when estimating small probabilities. Finally,the approach has not yet been lifted to a professional toolset directly usable by industry people.In this thesis we propose several contributions to increase the efficiency of SMC and to wider its applicability to a larger class of systems. We show how to extend the applicability of SMC to estimate the probability of rare-events. The probability of such events is so small that classical estimators such as Monte Carlo would almost always estimate it to be null. We then show how to apply SMC to those systems that combine both non-deterministic and stochastic aspects. Contrary to existing work, we do not use a learning-based approach for the non-deterministic aspects, butrather exploit a smart sampling strategy. We then show that SMC can be extended to a new class of problems. More precisely, we consider the problem of detecting probability changes at runtime. We solve this problem by exploiting an algorithm coming from the signal processing area. We also propose an extension of SMC to real-time stochastic system. We provide a stochastic semantic for such systems, and show how to exploit it in a simulation-based approach. Finally, we also consider an extension of the approach for Systems of Systems.Our results have been implemented in Plasma Lab, a powerful but flexible toolset. The thesis illustrates the efficiency of this tool on several case studies going from classical verification to more quixotic applications such as robotic

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency

Automated Deduction – CADE 28

This open access book constitutes the proceeding of the 28th International Conference on Automated Deduction, CADE 28, held virtually in July 2021. The 29 full papers and 7 system descriptions presented together with 2 invited papers were carefully reviewed and selected from 76 submissions. CADE is the major forum for the presentation of research in all aspects of automated deduction, including foundations, applications, implementations, and practical experience. The papers are organized in the following topics: Logical foundations; theory and principles; implementation and application; ATP and AI; and system descriptions

Knowledge of knots: shapes in action

Logic is to natural language what knot theory is to natural knots. Logic is concerned with some cognitive performances; in particular, some natural language inferences are captured by various types of calculi (propositional, predicate, modal, deontic, quantum, probabilistic, etc.), which in turn may generate inferences that are arguably beyond natural logic abilities, or non-well synchronized therewith (eg. ex falso quodlibet, material implication). Mathematical knot theory accounts for some abilities - such as recognizing sameness or differences of some knots, and in turn generates a formalism for distinctions that common sense is blind to. Logic has proven useful in linguistics and in accounting for some aspects of reasoning, but which knotting performaces are there, over and beyond some intuitive discriminating abilities, that may require extensions or restrictions of the normative calculus of knots? Are they amenable to mathematical treatment? And what role is played in the game by mental representations? I shall draw from a corpus of techniques and practices to show to what extent compositionality, lexical and normative elements are present in natural knots, with the prospect of formally exploring an area of human competence that interfaces thought, perception and action in a complex fabric

Assessing the suitability of ship design for human factors issues associated with evacuation and normal operations

Evaluating ship layout for human factors (HF) issues using simulation software such as maritimeEXODUS can be a long and complex process. The analysis requires the identification of relevant evaluation scenarios; encompassing evacuation and normal operations; the development of appropriate measures which can be used to gauge the performance of crew and vessel and finally; the interpretation of considerable simulation data. In this paper we present a systematic and transparent methodology for assessing the HF performance of ship design which is both discriminating and diagnostic. The methodology is demonstrated using two variants of a hypothetical naval ship

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency