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International Conference on Information Fusion

作者： Chenyi Lyu Xingchi Liu James Wright Jordi Barr Alasdair Hunter Lyudmila Mihaylova Department of Automatic Control & Systems Engineering University of Sheffield UK Scientific Computing Department Rutherford Appleton Laboratory Science and Technology Facilities Council UK Defence Science and Technology Laboratory UK

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper explores the application of centralised and distributed Gaussian process algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is on the innovative implementation of Gaussian process methods with learning hyperparameters and implementation with a factorised variance of the Gaussian kernel. The performance of the methods with different kernels was evaluated, not only with the Gaussian kernel. Extensive experiments with various kernel configurations demonstrate their importance in enhancing prediction accuracy and efficiency, especially in real-time tracking. The case studies with manoeuvring targets show significant advancements in tracking capabilities, particularly in wireless sensor networks, using optimised Gaussian process methods. This work advances Stone Soup’s capabilities and lays the groundwork for future investigations into adaptive Gaussian Process applications in tracking and sensor data analysis.

关键词： Wireless sensor networks Technological innovation Analytical models Target tracking Data analysis Gaussian processes Benchmark testing Real-time systems Data models Kernel

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Asymmetry of the Relative Entropy in the Regularization of Empirical Risk Minimization

arXiv

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arXiv 2024年

作者： Daunas, Francisco Esnaola, Iñaki Perlaza, Samir M. Vincent Poor, H. The Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom INRIA Centre Inria d'Université Côte d'Azur Sophia Antipolis06902 France The Department of Automatic Control and Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States The GAATI Mathematics Laboratory University of French Polynesia Fa'a'ā98702 French Polynesia

The effect of relative entropy asymmetry is analyzed in the context of empirical risk minimization (ERM) with relative entropy regularization (ERM-RER). Two regularizations are considered: (a) the relative entropy of the measure to be optimized with respect to a reference measure (Type-I ERM-RER);or (b) the relative entropy of the reference measure with respect to the measure to be optimized (Type-II ERM-RER). The main result is the characterization of the solution to the Type-II ERM-RER problem and its key properties. By comparing the well-understood Type-I ERM-RER with Type-II ERM-RER, the effects of entropy asymmetry are highlighted. The analysis shows that in both cases, regularization by relative entropy forces the solution's support to collapse into the support of the reference measure, introducing a strong inductive bias that can overshadow the evidence provided by the training data. Finally, it is shown that Type-II regularization is equivalent to Type-I regularization with an appropriate transformation of the empirical risk function. © 2024, CC BY.

关键词： Risk assessment

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Modelling of Insulation in Concentrated Stator Coils for Characterisation and Material Changes

Modelling of Insulation in Concentrated Stator Coils for Cha...

引用

International Conference on Electrical Machines, ICEM

作者： Edward J. W. Stone Panagiotis A. Panagiotou Johannes Mühlthaler Andrew R. Mills Alexis Lambourne Geraint W. Jewell Department of Electronic and Electrical Engineering The University of Sheffield Sheffield UK Rolls-Royce Electrical Rolls-Royce Deutschland Ltd & Co KG Munich Germany Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK Rolls-Royce Central Services Rolls-Royce Plc. UK Derby UK

ISBN: (数字)9798350370607

ISBN: (纸本)9798350370614

The highly demanding operation of electrical machines in aerospace can lead to the degradation of electrical insulation systems within the machine windings over time. This paper presents a novel method for high frequency modelling of a coil from the concentrated stator winding of an 2MW aerospace generator, for the purpose of characterising the insulation system by the amplitude and phase responses by the Bode plots in the same framework as electrical impedance spectroscopy. This new approach of high frequency model utilises a finite element model, deployed in tandem with an electrical equivalent circuit representation. Matlab is used to quantify the results taken from finite element modelling and implemented into LTSpice, so that the model considers mutual coupling of inductances and high-frequency effects, such as proximity and skin effects. This novel methodology allows extraction of the impedance profile with respect to the material changes within the simulated insulation system.

关键词： Coils Insulation Spectroscopy Stator windings Mathematical models Finite element analysis Impedance High frequency Integrated circuit modeling Skin effect

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Identification of Thermal Failure Profiles in Stator Winding Insulation by Impedance Spectroscopy

Identification of Thermal Failure Profiles in Stator Winding...

引用

International Conference on Electrical Machines, ICEM

ISBN: (数字)9798350370607

ISBN: (纸本)9798350370614

This paper presents a novel application of impedance spectroscopy as a means of inspection for stator winding insulation. It proposes, for the first time, a means for health monitoring and failure identification during thermal degradation effects in the insulation systems of stator coils from a concentrated stator winding. By periodical ex-situ inspection of these coils, the thermal ageing data of the insulation are profiled up to the point of failure. The study maps this evolution of thermal degradation patterns via novel interpretation of the impedance frequency responses, using well known techniques such as the Bode and Nyquist plots. This grants further insight into the characteristics shown in the ageing profiles over time and frequency. These new profiles enable the identification of critical points that can act as pre-emptive indicators of coil health and failure inception. This is a key finding as it renders the capability to provide an adequate lifing tool for electrical machine windings and coil assemblies within industrial settings. The insulation system examined in this study is taken from the coils of a concentrated stator winding in a 2MW permanent magnet generator used in an aerospace application.

关键词： Coils Degradation Insulation Spectroscopy Time-frequency analysis Stator windings Inspection Aging Impedance Thermal degradation

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A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy

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Computers in Biology and Medicine 2024年 181卷 109052-109052页

作者： Mamalakis, Michail Macfarlane, Sarah C. Notley, Scott V. Gad, Annica K.B. Panoutsos, George School of Electrical and Electronic Engineering University of Sheffield Sheffield United Kingdom Insigneo Institute for in-silico Medicine University of Sheffield Sheffield United Kingdom Department of Infection Immunity and Cardiovascular Disease Department of Computer science Sheffield United Kingdom Department of Psychiatry Cambridge University Cambridge United Kingdom Department of Oncology and Metabolism The Medical School University of Sheffield Sheffield United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Madeira Chemistry Research Centre University of Madeira Funchal Portugal Department of Oncology-Pathology Karolinska Institutet Stockholm Sweden

Metastasis driven by cancer cell migration is the leading cause of cancer-related deaths. It involves significant changes in the organization of the cytoskeleton, which includes the actin microfilaments and the vimentin intermediate filaments. Understanding how these filament change cells from normal to invasive offers insights that can be used to improve cancer diagnosis and therapy. We have developed a computational, transparent, large-scale and imaging-based pipeline, that can distinguish between normal human cells and their isogenically matched, oncogenically transformed, invasive and metastasizing counterparts, based on the spatial organization of actin and vimentin filaments in the cell cytoplasm. Due to the intricacy of these subcellular structures, manual annotation is not trivial to automate. We used established deep learning methods and our new multi-attention channel architecture. To ensure a high level of interpretability of the network, which is crucial for the application area, we developed an interpretable global explainable approach correlating the weighted geometric mean of the total cell images and their local GradCam scores. The methods offer detailed, objective and measurable understanding of how different components of the cytoskeleton contribute to metastasis, insights that can be used for future development of novel diagnostic tools, such as a nanometer level, vimentin filament-based biomarker for digital pathology, and for new treatments that significantly can increase patient survival. © 2024

关键词： Fluorescence microscopy

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Towards a simulation-based understanding of smart remanufacturing operations: a comparative analysis

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Journal of Remanufacturing 2024年第1期14卷 45-68页

作者： Okorie, Okechukwu Charnley, Fiona Ehiagwina, Augustine Tiwari, Divya Salonitis, Konstantinos Exeter Centre for Circular Economy Exeter Business School Streatham Court University of Exeter Rennes Drive Exeter EX4 4PU United Kingdom Liverpool Logistics Offshore and Marine Institute Liverpool John Moores University Brownlow Hill Liverpool L3 5UG United Kingdom Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Sustainable Manufacturing Systems Centre School of Aerospace Transport and Manufacturing Cranfield University Bedford MK43 0AL United Kingdom

While the majority of literature on remanufacturing operations examines an end-of-life (EOL) strategy which is both manual and mechanised, authors generally agree that digitalisation of remanufacturing is expected to increase in the next decade. Subsequently, a new research area described as digitally-enabled remanufacturing, remanufacturing 4.0 or smart remanufacturing is emerging. This is an automated, data-driven system of remanufacturing by means of Industry 4.0 (I4.0) paradigms. Insights into smart remanufacturing can be provided through simulation modelling of the remanufacturing process. While the use of simulation modelling in order to predict responses and behaviour is prevalent in remanufacturing, the use of these tools in smart remanufacturing is still limited in literature. The goal of this research is to present, as a first of its kind, a comparative understanding of simulation modelling in remanufacturing in order to suggest the ideal modelling tool for smart remanufacturing. The proposed comparison includes system dynamics, discrete event simulation and agent based modelling techniques. We apply these modelling techniques on a smart remanufacturing space of a sensor-enabled product and use assumptions derived from industry experts. We then proceed to model the remanufacturing operation from sorting and inspection of cores to final inspection of the remanufactured product. Through our analysis of the assumptions utilised and simulation modelling results we conclude that, while individual modelling techniques present important strategic and operational insights, their individual use may not be sufficient to offer comprehensive knowledge to remanufacturers due to the challenge of data complexity that smart remanufacturing offers. © 2020, The Author(s).

关键词： Agent-based simulation Discrete event simulation Simulation modelling Smart remanufacturing System dynamics

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Solving optimal control problems with non-smooth solutions using an integrated residual method and flexible mesh

Solving optimal control problems with non-smooth solutions u...

引用

IEEE Conference on Decision and control

作者： Lucian Nita Eric C. Kerrigan Eduardo M. G. Vila Yuanbo Nie Department of Electrical & Electronic Engineering Imperial College London London UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

Solutions to optimal control problems can be discontinuous, even if all the functionals defining the problem are smooth. This can cause difficulties when numerically computing solutions to these problems. While conventional numerical methods assume state and input trajectories are continuous and differentiable or smooth, our method is able to capture discontinuities in the solution by introducing time-mesh nodes as decision variables. This allows one to obtain a higher accuracy solution for the same number of mesh nodes compared to a fixed time-mesh approach. Furthermore, we propose to first solve a sequence of suitably-defined least-squares problems to ensure that the error in the dynamic equation is below a given tolerance. The cost functional is then minimized subject to an inequality constraint on the dynamic equation residual. We demonstrate our implementation on an optimal control problem that has a chattering solution. Solving such a problem is difficult, since the solution involves infinitely many switches of decreasing duration. This simulation shows how the flexible mesh is able to capture discontinuities present in the solution and achieve superlinear convergence as the number of mesh intervals is increased.

关键词： Costs Optimal control Mathematical models Trajectory Convergence

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Out-of-distribution Object Detection through Bayesian Uncertainty Estimation

arXiv

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arXiv 2023年

作者： Zhang, Tianhao Wang, Shenglin Bouaynaya, Nidhal Calinescu, Radu Mihaylova, Lyudmila Automatic Control and Systems Engineering The University of Sheffield United Kingdom Department of Electrical and Computer Engineering Rowan University United States Department of Computer Science University of York United Kingdom

The superior performance of object detectors is often established under the condition that the test samples are in the same distribution as the training data. However, in many practical applications, out-of-distribution (OOD) instances are inevitable and usually lead to uncertainty in the results. In this paper, we propose a novel, intuitive, and scalable probabilistic object detection method for OOD detection. Unlike other uncertainty-modeling methods that either require huge computational costs to infer the weight distributions or rely on model training through synthetic outlier data, our method is able to distinguish between in-distribution (ID) data and OOD data via weight parameter sampling from proposed Gaussian distributions based on pre-trained networks. We demonstrate that our Bayesian object detector can achieve satisfactory OOD identification performance by reducing the FPR95 score by up to 8.19% and increasing the AUROC score by up to 13.94% when trained on BDD100k and VOC datasets as the ID datasets and evaluated on COCO2017 dataset as the OOD dataset. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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DAFNI: A computational platform to support infrastructure systems research

引用

Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction 2023年第3期176卷 108-116页

作者： Matthews, Brian Hall, Jim Batty, Michael Blainey, Simon Cassidy, Nigel Choudhary, Ruchi Coca, Daniel Hallett, Stephen Harou, Julien J James, Phil Lomax, Nik Oliver, Peter Sivakumar, Aruna Tryfonas, Theodoros Varga, Liz Scientific Computing Department Science and Technology Facilities Council Didcot United Kingdom School of Geography and the Environment University of Oxford Oxford United Kingdom Centre for Advanced Spatial Analysis University College London London United Kingdom Transportation Research Group Faculty of Engineering and Physical Sciences University of Southampton Southampton United Kingdom Department of Civil Engineering University of Birmingham Birmingham United Kingdom Department of Engineering University of Cambridge Cambridge United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Centre for Environmental and Agricultural Informatics Cranfield University Cranfield United Kingdom Department of Mechanical Aerospace and Civil Engineering University of Manchester Manchester United Kingdom School of Engineering Newcastle University Newcastle United Kingdom School of Geography University of Leeds Leeds United Kingdom Department of Civil and Environmental Engineering Imperial College London London United Kingdom Department of Civil Engineering University of Bristol Bristol United Kingdom Department of Civil Environmental and Geomatic Engineering University College London London United Kingdom

Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a 'multi-systems' approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users' models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project. © 2023 Emerald Publishing Limited: All rights reserved.

关键词： Urban growth

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On the existence and uniqueness of equilibria in meshed DC microgrids with CPLs

On the existence and uniqueness of equilibria in meshed DC m...

引用

Mediterranean Conference on control and Automation (MED)

作者： Andrei-Constantin Braitor George C. Konstantopoulos Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield U.K Department of Electrical and Computer Engineering University of Patras Rion Greece

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

In this paper, we analyse the existence and uniqueness of equilibria of constant power loads (CPLs) in meshed DC microgrid architectures. Given the CPLs’ nonlinear characteristic and negative impedance behaviour, they are commonly known to introduce a destabilising effect into the system, effect intuitively coined as negative impedance instability. In the present approach, we start by deriving the characteristic polynomial from the power balance equation aiming to observe the nature of the CPLs voltage solutions, and assess their feasibility. Then, the algebraic expression is transformed into a problem of existence and uniqueness of a fixed point, and further tested by means of contraction mapping theory. A sufficient condition for the sources’ voltage references is obtained to guarantee the existence and uniqueness of equilibria. This provides a useful guidance in selecting the voltage references in the control design process. A numerical investigation on a meshed DC microgrid is carried out to verify the acquired sufficient condition and its underlying developed theory.

关键词： Sufficient conditions control design systems operation Process control Microgrids High-voltage techniques Stability analysis

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