Mitigation of welding distortion and residual stresses via cryogenic CO2 cooling - a numerical investigation

Fusion welding remains the most common and convenient fabrication method for large, thinplate welded structures. However, the resulting tendency to out-of-plane distortion exacts severe design and fabrication penalties in terms of poorer buckling performance, lack of fairness in external appearance, poor fit-up and frequent requirements for expensive rework. There are several ways to mitigate welding distortion and this study concentrates on the use of cryogenic CO2 cooling to reduce distortion. A feasible combination of welding process and cooling parameters, was investigated computationally and the resulting effects on final deformation were predicted. Three different computational strategies were developed and applied to butt-welding and fillet-welding processes, with and without the inclusion of cryogenic cooling. In the first method, a fully transient, uncoupled thermo-elastoplastic model was investigated. This method is comprehensive but not readily applicable to predict welding distortions in complex, industrial-scale, welded structures, due to the large computational requirement. More computationally efficient models are needed therefore and two further models of this type are suggested in this study. The results show good agreement between the different models, despite substantial differences in computational budget. In butt-welded plates, a significant decrease in out-of-plane distortion is obtained when cryogenic cooling is applied. In fillet-welded plates, cooling had much less effect on welding distortion. This was largely due to the size and configuration of the test case assemblies and the fact that the attached stiffener greatly increased the overall stiffness and resistance to contraction forces

Analysing the limitations of deep learning for developmental robotics

Deep learning is a powerful approach to machine learning however its inherent disadvantages leave much to be desired in the pursuit of the perfect learning machine. This paper outlines the multiple disadvantages of deep learning and offers a view into the implications to solving these problems and how this would affect the state of the art not only in developmental learning but also in real world applications

Complete Genome Sequence of Pelosinus fermentans JBW45, a Member of a Remarkably Competitive Group of Negativicutes in the Firmicutes Phylum.

The genome of Pelosinus fermentans JBW45, isolated from a chromium-contaminated site in Hanford, Washington, USA, has been completed with PacBio sequencing. Nine copies of the rRNA gene operon and multiple transposase genes with identical sequences resulted in breaks in the original draft genome and may suggest genomic instability of JBW45

Engaging the community in multidisciplinary TEL research: a case-study from networking in Europe

The STELLAR Network of Excellence was launched in February 2009 with the explicit intention of Sustaining Large Scale Multi-Disciplinary Research in Technology Enhanced Learning. So as to support this aim, the network has defined a number of different activity tracks, aimed at building capacity amongst senior-level researchers/decision makers, mid-level researchers and junior researchers/PhD students as well with a separate track dedicated to building community level capacity. In the abstract, the ‘community’ around any research study might usually be defined as the subject of the research. However, the focus of the community-capacity building activities of STELLAR, considers the role of the community as object of the research – a main consumer of the products of research, and having a stake in setting the research agenda itself. Thus, on the one hand, the STELLAR consortium needs to inform its actions and activities based on needs and wishes of stakeholders, while at the same time it intends to mobilise the same stakeholders, to forge common policy positions with respect to future development of TEL in Europe. This paper takes these activities as a case-study in structured social-network design, and considers the impact such activities may have on the field of technology enhanced learning in the coming years. The data is based on the first year of activities of the network, which are intended to last 40 months and are designed around the overlapping activities of connecting, orchestrating and contextualising stakeholders. The paper describes the elements of the stakeholder engagement plan as deployed by the STELLAR network in TELeurope, the activities conducted so far, and the plans for the future. It explains the consortium’s approach to stakeholder analysis, particularly the adaptation of existing methodologies, to produce a numerical ranking of stakeholders, by ‘alliance potential’. With regards to TELeurope, an emerging social platform being deployed by the STELLAR consortium so as to help this process of networking, it explains the current state of the affairs and plans for development of the platform, while referencing the work of Svensen & Laberge, and adapts the work of Bryson to contextualise these activities within a broader theoretical framework. Finally, the paper considers the quality monitoring elements and evaluation approach of the consortium, and makes recommendations as to how the networking strategy can be further energised, and as to how the process of evaluation can be improved. It concludes that the TELeurope strategy shows a high potential for stimulating engagement of stakeholders, subject to a number of caveats, which can be avoided through judicious policy choices within the next year

Relativistic quantum theories and neutrino oscillations

Neutrino oscillations are examined under the broad requirements of Poincar\'e-invariant scattering theory in an S-matrix formulation. This approach can be consistently applied to theories with either field or particle degrees of freedom. The goal of this paper is to use this general framework to identify all of the unique physical properties of this problem that lead to a simple oscillation formula. We discuss what is in principle observable, and how many factors that are important in principle end up being negligible in practice.Comment: 21 pages, no figure

Action recognition with unsynchronised multi-sensory data

Action recognition is a multi-faceted challenge that requires solving three principal challenges in its design: Synchronization, Segmentation and Uncertainty, all of which have specific implications to classification performance and possible solutions to mitigate these implications. We subsequently use observations carried out during the training of an action recognition system to generalize to the challenges encountered in the classification of any time-dependant signal

An integrated probabilistic framework for robot perception, learning and memory

Learning and perception from multiple sensory modalities are crucial processes for the development of intelligent systems capable of interacting with humans. We present an integrated probabilistic framework for perception, learning and memory in robotics. The core component of our framework is a computational Synthetic Autobiographical Memory model which uses Gaussian Processes as a foundation and mimics the functionalities of human memory. Our memory model, that operates via a principled Bayesian probabilistic framework, is capable of receiving and integrating data flows from multiple sensory modalities, which are combined to improve perception and understanding of the surrounding environment. To validate the model, we implemented our framework in the iCub humanoid robotic, which was able to learn and recognise human faces, arm movements and touch gestures through interaction with people. Results demonstrate the flexibility of our method to successfully integrate multiple sensory inputs, for accurate learning and recognition. Thus, our integrated probabilistic framework offers a promising core technology for robust intelligent systems, which are able to perceive, learn and interact with people and their environments

Memory and mental time travel in humans and social robots.

From neuroscience, brain imaging and the psychology of memory, we are beginning to assemble an integrated theory of the brain subsystems and pathways that allow the compression, storage and reconstruction of memories for past events and their use in contextualizing the present and reasoning about the future-mental time travel (MTT). Using computational models, embedded in humanoid robots, we are seeking to test the sufficiency of this theoretical account and to evaluate the usefulness of brain-inspired memory systems for social robots. In this contribution, we describe the use of machine learning techniques-Gaussian process latent variable models-to build a multimodal memory system for the iCub humanoid robot and summarize results of the deployment of this system for human-robot interaction. We also outline the further steps required to create a more complete robotic implementation of human-like autobiographical memory and MTT. We propose that generative memory models, such as those that form the core of our robot memory system, can provide a solution to the symbol grounding problem in embodied artificial intelligence. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.Funding. The preparation of this chapter was supported by funding from the EU Seventh Framework Programme as part of the projects Experimental Functional Android Assistant (EFAA, FP7-ICT-270490) and What You Say Is What You Did (WYSIWYD, FP7-ICT-612139) and by the EU H2020 Programme as part of the Human Brain Project (HBP-SGA1, 720270; HBP-SGA2, 785907). Acknowledgements. The authors are grateful to Paul Verschure, Peter Dominey, Giorgio Metta, Yiannis Demiris and the other members of the WYSIWYD and EFAA consortia; to members of the HBP EPISENSE group; and to our colleagues at the University of Sheffield who have helped us to develop memory systems for the iCub, particularly Luke Boorman, Harry Jackson and Matthew Evans. The Sheffield iCub was purchased with the support of the UK Engineering and Physical Sciences Research Council (EPSRC)

Can Gluons Trace Baryon Number?

QCD as a gauge non-Abelian theory imposes severe constraints on the structure of the baryon wave function. We point out that, contrary to a widely accepted belief, the traces of baryon number in a high-energy process can reside in a non-perturbative configuration of gluon fields, rather than in the valence quarks. We argue that this conjecture can be tested experimentally, since it can lead to substantial baryon asymmetry in the central rapidity region of ultra-relativistic nucleus-nucleus collisions.Comment: 12 pages, LaTeX, figures available upon reques