LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees

Systems based on artificial intelligence and machine learning models should be transparent, in the sense of being capable of explaining their decisions to gain humans' approval and trust. While there are a number of explainability techniques that can be used to this end, many of them are only capable of outputting a single one-size-fits-all explanation that simply cannot address all of the explainees' diverse needs. In this work we introduce a model-agnostic and post-hoc local explainability technique for black-box predictions called LIMEtree, which employs surrogate multi-output regression trees. We validate our algorithm on a deep neural network trained for object detection in images and compare it against Local Interpretable Model-agnostic Explanations (LIME). Our method comes with local fidelity guarantees and can produce a range of diverse explanation types, including contrastive and counterfactual explanations praised in the literature. Some of these explanations can be interactively personalised to create bespoke, meaningful and actionable insights into the model's behaviour. While other methods may give an illusion of customisability by wrapping, otherwise static, explanations in an interactive interface, our explanations are truly interactive, in the sense of allowing the user to "interrogate" a black-box model. LIMEtree can therefore produce consistent explanations on which an interactive exploratory process can be built

GEANT4 : a simulation toolkit

Abstract Geant4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics. PACS: 07.05.Tp; 13; 2

The social sciences and the web : From ‘Lurking’ to interdisciplinary ‘Big Data’ research

Acknowledgements This research is supported by the award made by the RCUK Digital Economy theme to the dot.rural Digital Economy Hub (award reference: EP/G066051/1) and the UK Economic & Social Research Council (ESRC) (award reference: ES/M001628/1).Peer reviewedPublisher PD

The apparatus of digital archaeology

Digital Archaeology is predicated upon an ever-changing set of apparatuses – technological, methodological, software, hardware, material, immaterial – which in their own ways and to varying degrees shape the nature of Digital Archaeology. Our attention, however, is perhaps inevitably more closely focussed on research questions, choice of data, and the kinds of analyses and outputs. In the process we tend to overlook the effects the tools themselves have on the archaeology we do beyond the immediate consequences of the digital. This paper introduces cognitive artefacts as a means of addressing the apparatus more directly within the context of the developing archaeological digital ecosystem. It argues that a critical appreciation of our computational cognitive artefacts is key to understanding their effects on both our own cognition and on the creation of archaeological knowledge. In the process, it defines a form of cognitive digital archaeology in terms of four distinct methods for extracting cognition from the digital apparatus layer by layer

Renewing the Exploration Approach for Mid-Enthalpy Systems: Examples from Northern England and Scotland

After a promising start in the 1970s and 80s, the UK rather fell behind other countries in the search for viable mid-enthalpy geothermal resources. This situation began to turn around in 2004, when the first of three deep geothermal exploration boreholes were drilled in northern England. What distinguished these from earlier drilling in Cornwall was the deliberate search for naturallyhigh permeability associated with major faults, especially those that have undergone strike-slip reactivation during the Cenozoic. Boreholes at Eastgate in the North Pennines targeted buried radiothermal granite, whereas the 1,821m-deep Science Central Borehole in Newcastle upon Tyne targeted a postulated deep sedimentary aquifer (the Fell Sandstones), which were inferred to be connected laterally to the granitic heat source by a major fault (the reactivation of the Iapetus geo-suture). The drilling was in both cases rewarded with impressive heat flows, and in the case of Eastgate with what is believed to be the highest permeability yet found in a deep granite batholith anywhere in the world. In parallel with these developments, a re-assessment was made of the preexisting geothermal heat flow database for the UK, applying newly-standardised correction protocols for palaeoclimatic and topographic distortions, which were found to be particularly marked in Scotland (where only shallow boreholes had been used to establish geothermal gradients in the original 1980s analysis), Similar prospects in northern England (similar to that drilled at Science Central) are now the focus of commercial exploration efforts. Appraisal of fault dispositions relative to the present-day maximum compressive stress azimuth are being used to identify the most promising areas for intersecting fault-related permeability at depth. New geophysical tools – most notably atomic dielectric resonance scanning – are also being appraised for their ability to directly detect features (such as hot brines) which are indicative of localised convection in target fault zones and aquifers

Investigation on the aerodynamic performance of cycloidal rotors with active leading-edge morphing

A cycloidal rotor is a novel form of propulsion system which has a geometrical design differing completely from the conventional screw propeller. The blades of a cycloidal rotor rotate about the horizontal axis of rotation. A key advantage of this rotor system is the instantaneous control of the net thrust vector, meaning that the thrust can be adjusted to any desired direction, perpendicular to the rotor’s horizontal axis of rotation. Few investigations have been conducted to assess the negative impact dynamic stall has on the cycloidal rotor’s performance characteristics. Dynamic stall is a complex phenomenon associated with unsteady aerofoil pitching motion that generates large hysteresis effects on the blade’s aerodynamic characteristics during the pitch cycle. In this study, an investigation is conducted to assess the effect of active leading-edge morphing on alleviating the negative impact dynamic stall has on the aerofoil aerodynamic characteristics as well as the cycloidal rotor performance characteristics. Computational studies are performed for a large-scale cycloidal rotor and for a single pitch-oscillating symmetric aerofoil operating at a large Reynolds number, Re greater than 1,000,000. Dynamic stall wind tunnel testing of a single NACA0015 aerofoil with an active leading-edge flap is also conducted to validate the effects of leading-edge morphing from the single pitch-oscillating aerofoil’s CFD model. The main findings from this study showed that applying active leading-edge morphing resulted in significant improvements of both the single aerofoil’s aerodynamic characteristics and the cycloidal rotor’s performance characteristics. The results from the CFD for the single pitch-oscillating aerofoil showed that the negative effects of dynamic stall were alleviated when applying active leading-edge morphing. The results from the cycloidal rotor CFD simulations showed that the effects of dynamic stall were alleviated which led to a reduction in the level of blade-wake interference. This led to a significant improvement in the cycloidal rotor performance characteristics, such as a 4-blade cycloidal rotor with active leading-edge morphing applied producing less power dissipation in comparison to a rigid 2-blade cycloidal rotor. The main findings from the experimental analysis showed that active leading-edge morphing reduced negative effects of dynamic stall such as the level of aerodynamic hysteresis, as well as improving the aerodynamic efficiency

The use of knowledge management systems and Event-B modelling in a lean enterprise

This paper provides a case study describing an approach to improving the efficiency of an information system (IS) by supporting processes outside the IS, using the ontology-driven knowledge management systems (KMS) as a mini-application in the area of so-called lean enterprise. Lean enterprise is focused on creating a maximal value for final customers while eliminating all kinds of waste and unnecessary costs, which significantly helps to increase the level of its competitiveness. It is about managerial decision-making, which can be in some cases contradictory (solving a local problem can cause a problem in another place). In this paper, we describe the KMS ATOM, which supports the innovation process in a lean enterprise. We show how the risk of wrong decisions due to contradictory effects can be eliminated by implementing a safety-critical system into the traditional IS. Our model is supported by Event-B modelling, a refinement-based formal modelling method, which is successfully used in important areas such as infrastructure, medicine, nuclear engineering and transportation (fire alarm systems, robotic surgery machines, braking systems in transportation, etc.). Nowadays, Event-B modelling is starting to be used for various management decision-making activities, and it is becoming a powerful competitiveness tool. This paper introduces a simple example of how Event-B modelling and its proof obligations can help improve and automate the decision-making process by eliminating potential threats of inefficient decisions.RVO project "Modelling of effective production and administration processes parameters in industrial companies based on the concept Industry 4.0