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Driving Behaviour Modelling Framework for Intelligent Powertrain Health Management
No full textYesImplementation of an intelligent powertrain health management relies on robust prognostics modelling. However, prognostics capability is often limited due to unknown future operating conditions, which varies with duty cycles and individual driver behaviours. On the other hand, the growing availability of data pertaining to vehicle usage allows advanced modelling of usage patterns and driver behavious, bringing optimisation opportunities for powertrain operation and health management. This paper introduces a methodology for driving behaviour modelling, underpinned by Machine Learning classification algorithms, generating model-based predictive insight for intelligent powertrain health management strategies. Specifically, the aim is to learn the patterns of driving behaviour and predict characteristics for the short-term future operating conditions as a basis for enhanced control strategies to optimise energy efficiency and system reliability. A case study of an automotive emissions aftertreatment system is used to comprehensively demonstrate the proposed framework. The case study illustrates the approach for integrating predictive insight from machine learning deployed on real world trip behaviour data, in conjunction with a reliability-based model of the operational behaviour of a particulate filter, to propose an intelligent active regeneration control strategy for improved efficiency and reliability performance. The effectiveness of the proposed strategy was demonstrated on an industry standard model-in-the-loop set up with a representative sample of real-world vehicle driving data.The authors acknowledge funding for the research presented in this article from Jaguar Land Rover under a research collaboration with the University of Bradford on “Intelligent Personalised Powertrain Healthcare”, and the Institute of Digital Engineering who have provided funding for proof of concept – the aiR-FORCE project
Aluminium surface impregnated with nano constituents for enhanced mechanical performance
Get PDFYesAluminium alloys are widely used structural materials in automotive, aerospace, and transportation, among several other notable industries. However, aluminium alloys' low hardness and poor tribological performance prevent potential use in applications requiring high contact pressures and wear resistance. This paper presents a novel two-step technique for enhancing the mechanical properties of the aluminium alloy by impregnating the surface with Ni-coating containing hard TiO2 nanoparticles using a high-intensity electric arc generated during tungsten inert gas welding. The results show that the process significantly changes the Microstructure and mechanical properties. The surface hardness increased from 0.48 GPa to 0.65 GPa with a corresponding change of Young's modulus from 15 GPa to 24 GPa of the treated surface
Team based learning and nurse education: a systematic review
Get PDFYesSummary of: Alberti S, Motta P, Ferri P, Bonetti L. The effectiveness of team-based learning in nursing education: A systematic review. Nurse Educ Today. 2021 Feb;97:104721. doi: 10.1016/j.nedt.2020.104721. Epub 2020 Dec 11
Tests of demountable reinforced concrete slabs
Get PDFYesThis paper presents an experimental investigation of demountable reinforced concrete slabs using dry connections between reinforced concrete slab elements. The test specimens comprised six full-scale reinforced concrete slabs; one control slab monolithically cast, while the other five slabs were produced with mid-span demountable dry connections. The slab elements were cast separately and assembled using top and bottom steel plates joined to each side of the slab element by high tensile steel bolts with or without a shear key and embedded steel block. Theoretical analysis of the behaviour of the demountable slabs tested in comparison with the control specimen was also conducted.
The test results showed that using a dry connection consisting of a shear key at the assembled section is the most effective technique in terms of moment resistance, deflection, and flexural stiffness. On the other hand, the dry connection with embedded steel blocks failed prematurely because of stress concentration at the block edges. The moment capacity and deflection predictions of demountable slabs have reasonably correlated with the experimental results but required additional calibrated data from experiments.This work was supported by an Institutional Links grant, ID 414633184, under the Newton-Kâtip Çelebi Fund partnership. The grant is funded by the UK Department for Business, Energy and Industrial Strategy and TÜBİTAK – Scientific and Technological Research Council of Turkey and delivered by the British Council. For further information, please visit www.newtonfund.ac.uk
Seismic response of prestressed precast reinforced concrete beam-column joints assembled by steel sleeves
Get PDFYesA novel prestressed precast reinforced concrete (RC) beam-column joint, composed of prestressed tendons, stiffened steel sleeves, and high-strength bolts, having improved self-centring ability and assembly efficiency is proposed in this paper. Four prestressed precast RC joints assembled by steel sleeves and one cast-in-place RC joint were tested under cyclic loading to investigate the seismic response of the proposed joint. The main parameters studied are the axial compression ratio of columns, stirrup ratio in the core area of the proposed joint and effective prestress of tendons. The energy dissipation capacity, bearing capacity, and self-centring ability of the prestressed precast RC beam-column joints assembled by steel sleeves are higher than those measured for the cast-in-place RC joint. For the prestressed precast RC joints assembled by steel sleeves, both yield and ultimate displacements increase with the increase of the axial compression ratio, stirrup ratio and effective prestress, but the ductility decreases with the increase of the axial compression ratio and effective prestress. The increasing of axial compression ratio can lead to an increase in the energy dissipation capacity, shear capacity and residual displacement. Finally, formulae to predict the shear capacity of prestressed precast RC joint assembled by steel sleeves are proposed, being in good agreement with the experimental results.The authors would like to thank the financial support provided by the Natural Science Foundation of Jiangsu Province, China (BK20201436), the Open Foundation of Jiangsu Province Engineering Research Center of Prefabricated Building and Intelligent Construction (2021), the Blue Project Youth Academic Leader of Colleges and Universities in Jiangsu Province (2020) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (KYCX21_3225)
Expressing Identity, Experiencing Belonging, and Everyday Life in Heavy Metal Music
Get PDFWhen heavy metal fans traverse through their everyday life, they are faced
with countless opportunities to engage in social interactions with others. Such
interactions question, establish, and strengthen fans’ heavy metal identities
whilst providing them with a sense of community and belonging through
engaging with others who also share a preference for heavy metal music. This
thesis is built on a qualitative research approach, complimented by an insider
and ethnographic orientation in order to explore identity expression, the feeling
of belonging and community, everyday life processes, and the role of heavy
metal music in the everyday life of heavy metal fans. Through social
interactions based on shared musical preference, heavy metal fans are able
to meaningfully engage with others through which communal affiliations are
strengthened and reinforced. Despite mainstream, and largely negative
attitudes towards heavy metal, the music provides a safety net for listeners
and is a driving force in their experience of the reciprocal relationship between
personal identity and group membership and community. Due to the deep
connection listeners have with heavy metal, the music becomes something
which fans are able to call theirs alone
What works where and how for uptake and impact of artificial intelligence in pathology: Review of theories for a realist evaluation
Get PDFYesThere is increasing interest in the use of artificial intelligence (AI) in pathology to increase accuracy and efficiency. To date, studies of clinicians' perceptions of AI have found only moderate acceptability, suggesting the need for further research regarding how to integrate it into clinical practice.
The aim of the study was to determine contextual factors that may support or constrain the uptake of AI in pathology.
To go beyond a simple listing of barriers and facilitators, we drew on the approach of realist evaluation and undertook a review of the literature to elicit stakeholders' theories of how, for whom, and in what circumstances AI can provide benefit in pathology. Searches were designed by an information specialist and peer-reviewed by a second information specialist. Searches were run on the arXiv.org repository, MEDLINE, and the Health Management Information Consortium, with additional searches undertaken on a range of websites to identify gray literature. In line with a realist approach, we also made use of relevant theory. Included documents were indexed in NVivo 12, using codes to capture different contexts, mechanisms, and outcomes that could affect the introduction of AI in pathology. Coded data were used to produce narrative summaries of each of the identified contexts, mechanisms, and outcomes, which were then translated into theories in the form of context-mechanism-outcome configurations.
A total of 101 relevant documents were identified. Our analysis indicates that the benefits that can be achieved will vary according to the size and nature of the pathology department's workload and the extent to which pathologists work collaboratively; the major perceived benefit for specialist centers is in reducing workload. For uptake of AI, pathologists' trust is essential. Existing theories suggest that if pathologists are able to "make sense" of AI, engage in the adoption process, receive support in adapting their work processes, and can identify potential benefits to its introduction, it is more likely to be accepted.
For uptake of AI in pathology, for all but the most simple quantitative tasks, measures will be required that either increase confidence in the system or provide users with an understanding of the performance of the system. For specialist centers, efforts should focus on reducing workload rather than increasing accuracy. Designers also need to give careful thought to usability and how AI is integrated into pathologists' workflow
Meeting the challenges of chemical and biological weapons: strengthening the chemical and biological disarmament and non-proliferation regimes
Get PDFYesIn this report, we identify some of the key technical and political challenges currently
facing the broader Chemical and Biological Weapon (CBW) regime- with a particular
emphasis on major forthcoming diplomatic meetings. Most significantly the Ninth Review
Conference of the Biological and Toxins Weapons Convention (1972) (BTWC) which will
take place in 2022 and preparations for the Fifth Review Conference of the Chemical
Weapons Convention (1993) (CWC), expected in 2023. This report is an output of an
ongoing project, designed to stimulate thinking and discussion about these issues, within
relevant stakeholder communities. The report provides an introduction to this issue area
for the general reader before surveying key issues and developing a series of practical
policy suggestions for further consideration
A new perspective on the U.S. energy efficiency: The political context
Get PDFYesThis paper offers a new perspective on the energy efficiency literature by bringing evidence of political contextual factors as the predictors of energy efficiency. Specifically, we posit that the Democrat administration is more energy-efficient considering the reduction of environmental impact, in contrast, the Republican administration is more efficient considering only financial expenditures leading to the production of economic growth. In addition, we predict that political administration tenure is negatively correlated with green energy efficiency and that political distancing moderates the relationship between political party administration and energy efficiency. This study sheds light on these matters by performing an efficiency analysis of fifty North American states through a bootstrap DEA non-parametric model, followed by Tobit regressions to evaluate our hypotheses concerning the effect of the contextual factors on the calculated efficiency scores.This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
A multi-contextual lens on racism and discrimination in the multicultural marketplace
Get PDFYesThis article highlights the generative properties of context for consumer experiences of racism and discrimination. Drawing from conceptualizations of context in social anthropology and human geography, it develops a framework to systematically catalogue intersections of various micro- and macro-social contexts that configure within and across marketplace geographies and inform racism and discrimination. The framework is applied to an integrative review of studies on marketplace racism and discrimination. The review illuminates that: 1) application of intersectional perspectives varies significantly across cultural difference dimensions; 2) knowledge is clustered within specific micro-social context expressions of cultural difference dimensions; 3) studies intersecting micro- and macro-social expressions commonly reveal underexplored discrimination instances; and 4) knowledge on macro-social contextual forces significantly lacks non-western perspectives. Drawing on the review findings, a list of areas of advancement for future scholarship is presented, along with recommendations for marketing practitioners acting towards identifying, understanding, and counteracting racism and discrimination