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  • Journal article
    Wang Q, Dai H-N, Yang J, Guo C, Childs P, Kleinsmann M, Guo Y, Wang Pet al., 2025,

    Learning-based artificial intelligence artwork: methodology taxonomy and quality evaluation

    , ACM Computing Surveys, Vol: 57, ISSN: 0360-0300

    With the development of the theory and technology of computer science, machine or computer painting is increasingly being explored in the creation of art. Machine-made works are referred to as artificial intelligence (AI) artworks. Early methods of AI artwork generation have been classified as non-photorealistic rendering, and, latterly, neural style transfer methods have also been investigated. As technology advances, the variety of machine-generated artworks and the methods used to create them have proliferated. However, there is no unified and comprehensive system to classify and evaluate these works. To date, no work has generalized methods of creating AI artwork including learning-based methods for painting or drawing. Moreover, the taxonomy, evaluation, and development of AI artwork methods face many challenges. This article is motivated by these considerations. We first investigate current learning-based methods for making AI artworks and classify the methods according to art styles. Furthermore, we propose a consistent evaluation system for AI artworks and conduct a user study to evaluate the proposed system on different AI artworks. This evaluation system uses six criteria: beauty, color, texture, content detail, line, and style. The user study demonstrates that the six-dimensional evaluation index is effective for different types of AI artworks.
  • Journal article
    Meyer J, Prepeliţă S, Picinali L, 2025,

    On the accuracy of finite-difference time-domain simulations of head-related transfer functions as a function of model complexity

    , Applied Acoustics, Vol: 228, ISSN: 0003-682X

    Wave-based numerical tools such as finite-difference time-domain (FDTD) solvers are useful for modeling several acoustic properties and interactions. While these numerical tools are widely used in acoustics, there seems to be less attention to assessing the quality of the produced outputs. However, in order to ensure that the obtained results are reliable, the quantification of the errors present in the simulation results is an essential step. There exists a mathematical process known as solution verification which aims at assessing the accuracy of the computed solutions. A relevant application for the FDTD method is the simulation of head-related transfer functions (HRTFs), since these are relatively complex to acoustically measure on humans. This paper aims at applying the solution verification process on HRTF modeling using the FDTD method to evaluate the accuracy of the simulated HRTF magnitudes with increased human head/torso model complexity. The FDTD-simulated HRTFs are also compared with respect to the similarity/dissimilarity of their spectrum and with respect to the relevance of these spectral variations on sound source localization. The results show that asymptotically extrapolating the FDTD-simulated HRTFs from a series of simulations provides more accurate HRTF predictions when compared to using single FDTD simulations ran on sub-millimeter grids, regardless of the model complexity. Results also demonstrate that the accuracy of the FDTD-simulated HRTF predictions decreases with increased model complexity. The localization performance predictions showed that the largest localization errors were obtained with models with the lowest complexities. Significant differences in predicted sound source localization performance were found between FDTD-simulated results.
  • Journal article
    Rostami-Tabar B, Pinson P, Porter MD, 2025,

    Guest editorial: Forecasting for social good

    , International Journal of Forecasting, Vol: 41, Pages: 1-2, ISSN: 0169-2070
  • Journal article
    Jagtap SS, Childs PRN, Stettler MEJ, 2024,

    Conceptual design-optimisation of a subsonic hydrogen-powered long-range blended-wing-body aircraft

    , International Journal of Hydrogen Energy, Vol: 96, Pages: 639-651, ISSN: 0360-3199

    The adoption of liquid hydrogen (LH2) holds promise for decarbonising long-range aviation. LH2 aircraft could weigh less than Jet-A aircraft, thereby reducing the thrust requirement. However, the lower volumetric energy density of LH2 can adversely impact the aerodynamic performance and energy consumption of tube-wing aircraft. In a first, this work conducts an energy performance modelling of a futuristic (2030+) LH2 blended-wing-body (BWB) aircraft (301 passengers and 13,890 km) using conceptual aircraft design-optimisation approach employing weight-sizing methods, while considering the realistic gravimetric and volumetric energy density effects of LH2 on aircraft design, and the resulting reduction in aircraft thrust requirement. This study shows that at the design point the futuristic LH2 BWB aircraft reduces the specific energy consumption (SEC, MJ/tonne-km) by 51.7–53.5% and 7.3–10.8%, compared to (Jet-A) Boeing 777-200LR and Jet-A BWB, respectively. At the off-design points, this study shows that by increasing the load factor for a given range and/or increasing range for all load factor cases, the SEC (or energy efficiency) of this LH2 BWB concept improves. The results of this work will inform future studies on use-phase emissions and contrails modelling, LH2 aircraft operations for contrail reduction, estimation of operating costs, and lifecycle climate impacts.
  • Journal article
    Jagtap SS, Childs PRN, Stettler MEJ, 2024,

    Conceptual design-optimisation of a future hydrogen-powered ultrahigh bypass ratio geared turbofan engine

    , International Journal of Hydrogen Energy, Vol: 95, Pages: 317-328, ISSN: 0360-3199

    Liquid hydrogen (LH2) is a proposed option to decarbonise long-haul aviation. LH2 aircraft (combustion-based) is expected to be lighter than Jet-A aircraft which necessitates reduction in the engine thrust requirement. Thus, the thermodynamic and energy performance of a LH2 aircraft engine, and its design and optimisation, is of significance. In a first, a conceptual design and optimisation of a future LH2 powered ultra-high bypass-ratio geared turbofan engine is conducted for reduced aircraft thrust requirement, using GasTurb 13 software and implementing future materials and component efficiencies. The thrust specific energy consumption (TSEC) of the optimised LH2 engine is 6–8% lower than Jet-A. The TSEC of LH2 engine is lower than Jet-A due to hydrogen's higher gravimetric energy density during combustion, higher specific heat of combustion products, and reduced thrust requirement. It is observed that optimised LH2 engine has 11% smaller diameter, 5.5–7.5% shorter length, 6–14% lower turbine entry temperature and 7.4–17.6% lower weight, than a Jet-A engine. The results of this work will be useful to future studies on LH2 engine and aircraft design, and LH2 aircraft emissions and contrails modelling.
  • Journal article
    McPherson A, Morrison L, Davison M, Wanderley Met al., 2024,

    On Mapping as a Technoscientific Practice in Digital Musical Instruments

    , Journal of New Music Research, ISSN: 0929-8215
  • Journal article
    Kench S, Squires I, Dahari A, Brosa Planella F, Roberts SA, Cooper SJet al., 2024,

    Li-ion battery design through microstructural optimization using generative AI

    , Matter, Vol: 7, Pages: 4260-4269, ISSN: 2590-2393

    Lithium-ion batteries are used across various applications, necessitating tailored cell designs to enhance performance. Optimizing electrode manufacturing parameters is a key route to achieving this, as these parameters directly influence the microstructure and performance of the cells. However, linking process parameters to performance is complex, and experimental or modeling campaigns are often slow and expensive. This study introduces a fast computational optimization framework for electrode manufacturing parameters. A generative model, trained on a small dataset of microstructural images associated with different manufacturing parameters, efficiently generates representative microstructures for new parameters. This model is integrated into a Bayesian optimization loop that includes microstructure generation, characterization, and simulation, aiming to find optimal manufacturing parameters for a particular application. Significant improvement in the energy density of a 4680 cell is achieved through bespoke cell design, highlighting the importance of cell-scale normalization. The framework's modularity allows its application to various advanced materials manufacturing scenarios.
  • Journal article
    Baker CE, Yu X, Lovell B, Tan R, Patel S, Ghajari Met al., 2024,

    How well do popular bicycle helmets protect from different types of head injury?

    , Annals of Biomedical Engineering, Vol: 52, Pages: 3326-3364, ISSN: 0090-6964

    Bicycle helmets are designed to protect against skull fractures and associated focal brain injuries, driven by helmet standards. Another type of head injury seen in injured cyclists is diffuse brain injuries, but little is known about the protection provided by bicycle helmets against these injuries. Here, we examine the performance of modern bicycle helmets in preventing diffuse injuries and skull fractures under impact conditions that represent a range of real-world incidents. We also investigate the effects of helmet technology, price, and mass on protection against these pathologies. 30 most popular helmets among UK cyclists were purchased within 9.99-135.00 GBP price range. Helmets were tested under oblique impacts onto a 45° anvil at 6.5 m/s impact speed and four locations, front, rear, side, and front-side. A new headform, which better represents the average human head's mass, moments of inertia and coefficient of friction than any other available headforms, was used. We determined peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and BrIC. We also determined the risk of skull fractures based on PLA (linear risk), risk of diffuse brain injuries based on BrIC (rotational risk), and their mean (overall risk). Our results show large variation in head kinematics: PLA (80-213 g), PRV (8.5-29.9 rad/s), PRA (1.6-9.7 krad/s2), and BrIC (0.17-0.65). The overall risk varied considerably with a 2.25 ratio between the least and most protective helmet. This ratio was 1.76 for the linear and 4.21 for the rotational risk. Nine best performing helmets were equipped with the rotation management technology MIPS, but not all helmets equipped with MIPS were among the best performing helmets. Our comparison of three tested helmets which have MIPS and no-MIPS versions showed that MIPS reduced rotational kinematics, but not linear kinematics. We found no significant effect of helmet price on exposure-adjusted inju
  • Journal article
    Chen L, Zuo H, Cai Z, Yin Y, Zhang Y, Sun L, Childs PRN, Wang Bet al., 2024,

    Towards controllable generative design: a conceptual design generation approach leveraging the FBS ontology and Large Language Models

    , Journal of Mechanical Design, Vol: 146, ISSN: 1050-0472

    Recent research in the field of design engineering is primarily focusing on using AI technologies such as Large Language Models (LLMs) to assist early-stage design. The engineer or designer can use LLMs to explore, validate and compare thousands of generated conceptual stimuli and make final choices. This was seen as a significant stride in advancing the status of the generative approach in computer-aided design. However, it is often difficult to instruct LLMs to obtain novel conceptual solutions and requirement-compliant in real design tasks, due to the lack of transparency and insufficient controllability of LLMs. This study presents an approach to leverage LLMs to infer Function-Behavior-Structure (FBS) ontology for high-quality design concepts. Prompting design based on the FBS model decomposes the design task into three sub-tasks including functional, behavioral, and structural reasoning. In each sub-task, prompting templates and specification signifiers are specified to guide the LLMs to generate concepts. User can determine the selected concepts by judging and evaluating the generated function-structure pairs. A comparative experiment has been conducted to evaluate the concept generation approach. According to the concept evaluation results, our approach achieves the highest scores in concept evaluation, and the generated concepts are more novel, useful, functional, and low-cost compared to the baseline.
  • Journal article
    Baker CE, Martin P, Montemeglio A, Li R, Wilson M, Sharp DJ, Ghajari Met al., 2024,

    Inherent uncertainty in pedestrian collision reconstruction: How evidence variability affects head kinematics and injury prediction.

    , Accid Anal Prev, Vol: 208

    Reconstructing individual cases from real-world collision data is used as a tool to better understand injury biomechanics and determine injury thresholds. However, real-world data tends to have inherent uncertainty within parameters, such as ranges of impact speed, pre-impact pedestrian stance or pedestrian anthropometric characteristics. The implications of this input parameter uncertainty on the conclusions made from case reconstruction about injury biomechanics and risk is not well investigated, with a 'best-fit' approach more frequently adopted, leaving uncertainty unexplored. This study explores the implications of uncertain parameters in real-world data on the biomechanical kinematic metrics related to head injury risk in reconstructed real-world pedestrian-car collisions. We selected six pedestrian-car cases involving seven pedestrians from the highly detailed GB Road Accident In-Depth Studies (RAIDS) database. The collisions were reconstructed from the images, damage measurements and dynamics available in RAIDS. For each case, we varied input parameters within uncertain ranges and report the range of head kinematic metrics from each case. This includes variations of reconstructed collision scenarios that fits within the constraints of the available evidence. We used a combination of multibody and finite element modelling in Madymo to test whether the effect of input data uncertainty is the same on the initial head-vehicle and latter head-ground impact phase. Finally, we assessed whether the predicted range of head kinematics correctly predicted the injuries sustained by the pedestrian. Varying the inputs resulted in a range of output head kinematic parameters. Real-world evidence such as CCTV footage enabled predicted simulated values to be further constrained, by ruling out unrealistic scenarios which do not fit the available evidence. We found that input data uncertainty had different implications for the initial head-vehicle and latter head-ground impact
  • Journal article
    Kharman AM, Jursitzky C, Zhou Q, Ferraro P, Marecek J, Pinson P, Shorten Ret al., 2024,

    An adversarially robust data-market for spatial, crowd-sourced data

    , Distributed Ledger Technologies: Research and Practice

    <jats:p> We describe an architecture for a decentralised data market for applications in which agents are incentivised to collaborate to crowd-source their data. The architecture is designed to reward data that furthers the market's collective goal, and distributes reward fairly to all those that contribute with their data. We show that the architecture is resilient to <jats:italic>Sybil</jats:italic> , <jats:italic>wormhole</jats:italic> , and <jats:italic>data poisoning</jats:italic> attacks. In order to evaluate the resilience of the architecture, we characterise its breakdown points for various adversarial threat models in an automotive use case. </jats:p>
  • Journal article
    Weber ML, Jennings D, Fearn S, Cavallaro A, Prochazka M, Gutsche A, Heymann L, Guo J, Yasin L, Cooper SJ, Mayer J, Rheinheimer W, Dittmann R, Waser R, Guillon O, Lenser C, Skinner SJ, Aguadero A, Nemšák S, Gunkel Fet al., 2024,

    Thermal stability and coalescence dynamics of exsolved metal nanoparticles at charged perovskite surfaces

    , Nature Communications, Vol: 15, ISSN: 2041-1723

    Exsolution reactions enable the synthesis of oxide-supported metal nanoparticles, which are desirable as catalysts in green energy conversion technologies. It is crucial to precisely tailor the nanoparticle characteristics to optimize the catalysts’ functionality, and to maintain the catalytic performance under operation conditions. We use chemical (co)-doping to modify the defect chemistry of exsolution-active perovskite oxides and examine its influence on the mass transfer kinetics of Ni dopants towards the oxide surface and on the subsequent coalescence behavior of the exsolved nanoparticles during a continuous thermal reduction treatment. Nanoparticles that exsolve at the surface of the acceptor-type fast-oxygen-ion-conductor SrTi0.95Ni0.05O3−δ (STNi) show a high surface mobility leading to a very low thermal stability compared to nanoparticles that exsolve at the surface of donor-type SrTi0.9Nb0.05Ni0.05O3−δ (STNNi). Our analysis indicates that the low thermal stability of exsolved nanoparticles at the acceptor-doped perovskite surface is linked to a high oxygen vacancy concentration at the nanoparticle-oxide interface. For catalysts that require fast oxygen exchange kinetics, exsolution synthesis routes in dry hydrogen conditions may hence lead to accelerated degradation, while humid reaction conditions may mitigate this failure mechanism.
  • Journal article
    Yin Y, Childs P, 2024,

    A study of cognitive factor sequences and relations to creativity quality levels

    , Humanities & Social Sciences Communications, Vol: 11, ISSN: 2662-9992

    Cognitive factors such as association, memory, and combination have been verified to be related to the creative design process. However, limited research has considered the effects of cognitive factors and their interaction on creative processes in practical creative design processes. This study aimed to detect the interactive effects of cognitive factors on creative processes in a practical creative design process. In particular, how the sequence of cognitive factors affects creativity quality levels of the creative solutions was investigated. Seventy-one participants were recruited to undertake a design task using the think-aloud method. The results of this study are as follows. (i) The sequences of cognitive factors can contribute to different creativity quality levels of solutions. The sequence of semantic memory, common association, remote association, episodic memory, remote combination, idea expression, and idea evaluation is more likely to lead to a higher creativity quality level of solutions. (ii) The repetition of the same cognitive factor in a creative design process, especially semantic memory, does not necessarily contribute to a high-creativity-quality-level solution. (iii) Creativity quality levels of solutions are related to how many cognitive factors categories are involved in the creative design process. The more cognitive factors included, the higher the creativity quality of the solutions will be.
  • Journal article
    Mulvey B, Nanayakkara T, 2024,

    HAVEN: haptic and visual environment navigation by a shape-changing mobile robot with multimodal perception

    , Scientific Reports, Vol: 14, ISSN: 2045-2322

    Many animals exhibit agile mobility in obstructed environments due to their ability to tune their bodies to negotiate andmanipulate obstacles and apertures. Most mobile robots are rigid structures and avoid obstacles where possible. In this work,we introduce a new framework named Haptic And Visual Environment Navigation (HAVEN) Architecture to combine vision andproprioception for a deformable mobile robot to be more agile in obstructed environments. The algorithms enable the robot to beautonomously a) predictive by analysing visual feedback from the environment and preparing its body accordingly, b) reactiveby responding to proprioceptive feedback, and c) active by manipulating obstacles and gap sizes using its deformable body.The robot was tested approaching differently sized apertures in obstructed environments ranging from greater than its shapeto smaller than its narrowest possible size. The experiments involved multiple obstacles with different physical properties.The results show higher navigation success rates and an average 32% navigation time reduction when the robot activelymanipulates obstacles using its shape-changing body.
  • Conference paper
    Fringi E, Alshubaily N, Picinali L, Brewster SA, Guha T, Vinciarelli Aet al., 2024,

    Is Distance a Modality? Multi-Label Learning for Speech-Based Joint Prediction of Attributed Traits and Perceived Distances in 3D Audio Immersive Environments

    , ICMI '24: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, Publisher: ACM, Pages: 321-330
  • Journal article
    Sadek M, Calvo R, Mougenot C, 2024,

    Designing value-sensitive AI: a critical review and recommendations for socio-technical design processes

    , AI and Ethics, Vol: 9, Pages: 949-967, ISSN: 2730-5961

    This paper presents a critical review of how different socio-technical design processes for AI-based systems, from scholarly works and industry, support the creation of value-sensitive AI (VSAI). The review contributes to the emerging field of human-centred AI, and the even more embryonic space of VSAI in four ways: (i) it introduces three criteria for the review of VSAI based on their contribution to design processes’ overall value-sensitivity, and as a response to criticisms that current interventions are lacking in these aspects: comprehensiveness, level of guidance offered, and methodological value-sensitivity, (ii) it provides a novel review of socio-technical design processes for AI-based systems, (iii) it assesses each process based on the mentioned criteria and synthesises the results into broader trends, and (iv) it offers a resulting set of recommendations for the design of VSAI. The objective of the paper is to help creators and followers of design processes—whether scholarly or industry-based—to understand the level of value-sensitivity offered by different socio-technical design processes and act accordingly based on their needs: to adopt or adapt existing processes or to create new ones.
  • Journal article
    Chen L, Zhang Y, Han J, Sun L, Childs P, Wang Bet al., 2024,

    A foundation model enhanced approach for generative design in combinational creativity

    , Journal of Engineering Design, Vol: 35, Pages: 1394-1420, ISSN: 0954-4828

    In creativity theory, combining two unrelated concepts into a novel idea is a common means of enhancing creativity. Designers can integrate the Additive concept into the Base concept to inspire and facilitate creative tasks. However, conceiving high-quality combinational ideas poses a challenge that combinational creativity itself demands the consideration of conceptual reasoning and synthesis. We propose an AI foundation model enhanced approach for supporting combinational creativity. This approach derives combinational embodiments, and assists humans in verbalising and externalising combinational ideas. Our experimental study demonstrates that the generated combinational ideas by the approach obtained highest scores compared to those ideas generated without an AI foundation model or combinational strategy. We built a combinational creativity tool called CombinatorX based on this approach to generate ideas. In a study with the comparison of an existing combinational creativity tool and Internet search, we validated that our approach improves the effectiveness of combinational idea generation, enables a reduction in labour force, and facilitates the refinement of combinational ideation.
  • Journal article
    Almukhtar A, Batcup C, Bowman M, Winter Beatty J, Leff D, Demirel P, Judah G, Porat Tet al., 2024,

    Interventions to achieve environmentally sustainable operating theatres: an umbrella systematic review using the behaviour change wheel

    , International Journal of Surgery, Vol: 110, Pages: 7245-7267, ISSN: 1743-9159

    Introduction: The healthcare sector is a major contributor to the climate crisis, and operating theatres (OTs) are one of the highest sources of emissions. To inform emissions reduction, this study aimed to (i) compare the outcomes of interventions targeting sustainable behaviours in OTs using the Triple Bottom Line framework, (ii) categorise the intervention strategies using the 5Rs (reduce, recycle, reuse, refuse, and renew) of circular economy, and (iii) examine Intervention Functions (IFs) using the Behaviour Change Wheel (BCW).Methods: Medline, Embase, PsychInfo, Scopus, and Web of Science databases were searched until June 2023 using the concepts: sustainability and surgery. The review was conducted in line with the Cochrane and Joanna Briggs Institution’s recommendations and was registered on PROSPERO. The results were reported in line with PRISMA, Supplemental Digital Content 1, https://links.lww.com/JS9/D210 (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines.Results: Sixteen reviews encompassing 43 life-cycle analyses, 30 interventions, 5 IFs, and 9 BCW policy categories were included. 28/30 (93%) interventions successfully led to sustainability improvements; however, the environmental outcomes were not suitable for meaningful comparisons due to their using different metrics and dependence on local factors. The ‘reduce’ strategy was the most prolific and commonly achieved through ‘education’ and/or ‘environmental restructuring’. However, single-session educational interventions were ineffective. Improving recycling relied on ‘environmental restructuring’. More intensive strategies such as ‘reuse’ require multiple intervention functions to achieve, either through a sustainability committee or through an intervention package.Conclusion: Policymakers must examine interventions within the local context. Comparing the outcomes of different interventions is difficult an
  • Journal article
    Cutting J, Deterding S, 2024,

    The task-attention theory of game learning: a theory and research agenda

    , Human-Computer Interaction, Vol: 39, Pages: 257-287, ISSN: 0737-0024

    Why do learning games fail or succeed? Recent evidence suggests that attention forms an important moderator of learning from games. While existing media effects and learning theories acknowledge the role of attentional limits, they fail to account for the specific ways that games as interactive media steer attention. In response, we here develop the Task-Attention Theory of Game Learning. Drawing on current psychological and games research, task-attention theory argues that games as interactive media demand and structure the pursuit of tasks, which ties into distinct attentional mechanisms, namely learned attentional sets which focus attentional selection onto task-relevant features, as well as active sampling: users navigate and manipulate the game to elicit task-relevant information. This active sampling and selection precedes and moderates what information can be learned. We identify task-related game features (mechanics, goals, rewards and uncertainty) and demands (cognitive and perceptual load, pressure) that affect active sampling and attentional selection. We articulate implications and future work for game-based learning research and design, as well as wider media effects, learning, and HCI research.
  • Journal article
    Zhao Y, Li H, Zhou H, Attar HR, Pfaff T, Li Net al., 2024,

    A review of graph neural network applications in mechanics-related domains

    , Artificial Intelligence Review: an international survey and tutorial journal, Vol: 57, ISSN: 0269-2821

    Mechanics-related tasks often present unique challenges in achieving accurate geometric and physical representations, particularly for non-uniform structures. Graph neural networks (GNNs) have emerged as a promising tool to tackle these challenges by adeptly learning from graph data with irregular underlying structures. Consequently, recent years have witnessed a surge in complex mechanics-related applications inspired by the advancements of GNNs. Despite this process, there is a notable absence of a systematic review addressing the recent advancement of GNNs in solving mechanics-related tasks. To bridge this gap, this review article aims to provide an in-depth overview of the GNN applications in mechanics-related domains while identifying key challenges and outlining potential future research directions. In this review article, we begin by introducing the fundamental algorithms of GNNs that are widely employed in mechanics-related applications. We provide a concise explanation of their underlying principles to establish a solid understanding that will serve as a basis for exploring the applications of GNNs in mechanics-related domains. The scope of this paper is intended to cover the categorisation of literature into solid mechanics, fluid mechanics, and interdisciplinary mechanics-related domains, providing a comprehensive summary of graph representation methodologies, GNN architectures, and further discussions in their respective subdomains. Additionally, open data and source codes relevant to these applications are summarised for the convenience of future researchers. This article promotes an interdisciplinary integration of GNNs and mechanics and provides a guide for researchers interested in applying GNNs to solve complex mechanics-related tasks.
  • Journal article
    Ge Y, Zong R, Chen X, Nanayakkara Tet al., 2024,

    An origami-inspired endoscopic capsule with tactile perception for early tissue anomaly detection

    , IEEE Robotics and Automation Letters, Vol: 9, Pages: 10018-10025, ISSN: 2377-3766

    Video Capsule Endoscopy (VCE) is currently one of the most effective methods for detecting intestinal diseases. However, it is challenging to detect early-stage small nodules with this method because they lack obvious color or shape features. In this letter, we present a new origami capsule endoscope to detect early small intestinal nodules using tactile sensing. Four soft tactile sensors made out of piezoresistive material feed four channels of phase-shifted data that are processed using a particle filter. The particle filter uses an importance assignment template designed using experimental data from six known sizes of nodules. Moreover, the proposed capsule can use shape changes to move forward or backward under peristalsis passively. In the experiment, it was able to return to a specific area for repeated detection in a straight, two-dimensional intestinal model. Experimental results show that the proposed capsule can detect nodules of more than 3 mm diameter with 100% accuracy.
  • Journal article
    Carman F, Ewen J, Bresme F, Wu B, Dini Det al., 2024,

    Molecular simulations of thermal transport across iron oxide-hydrocarbon interfaces

    , ACS Applied Materials and Interfaces, Vol: 16, Pages: 59452-59467, ISSN: 1944-8244

    The rational design of dielectric fluids for immersion cooling of batteries requires a molecular-level understanding of the heat flow across the battery casing/dielectric fluid interface. Here, we use nonequilibrium molecular dynamics (NEMD) simulations to quantify the interfacial thermal resistance (ITR) between hematite and poly-α-olefin (PAO), which are representative of the outer surface of the steel battery casing and a synthetic hydrocarbon dielectric fluid, respectively. After identifying the most suitable force fields to model the thermal properties of the individual components, we then compared different solid–liquid interaction potentials for the calculation of the ITR. These potentials resulted in a wide range of ITR values (4–21 K m2 GW–1), with stronger solid–liquid interactions leading to lower ITR. The increase in ITR is correlated with an increase in density of the fluid layer closest to the surface. Since the ITR has not been experimentally measured for the hematite/PAO interface, we validate the solid–liquid interaction potential using the work of adhesion calculated using the dry-surface method. The work of adhesion calculations from the simulations were compared to those derived from experimental contact angle measurements for PAO on steel. We find that all of the solid–liquid potentials overestimate the experimental work of adhesion. The experiments and simulations can only be reconciled by further reducing the strength of the interfacial interactions. This suggests some screening of the solid–liquid interactions, which may be due to the presence of an interfacial water layer between PAO and steel in the contact angle experiments. Using the solid–liquid interaction potential that reproduces the experimental work of adhesion, we obtain a higher ITR (33 K m2 GW–1), suggesting inefficient thermal transport. The results of this study demonstrate the potential for NEMD simulations to improve
  • Journal article
    Qian Q, Wang Y, Boyle D, 2024,

    On solving close enough orienteering problems with overlapped neighborhoods

    , European Journal of Operational Research, Vol: 318, Pages: 369-387, ISSN: 0377-2217

    The Close Enough Traveling Salesman Problem (CETSP) is a well-known variant of the classic TravelingSalesman Problem whereby the agent may complete its mission at any point within a target neighborhood.Heuristics based on overlapped neighborhoods, known as Steiner Zones (SZ), have gained attention inaddressing CETSPs. While SZs offer effective approximations to the original graph, their inherent overlapimposes constraints on the search space, potentially conflicting with global optimization objectives. Here weshow how such limitations can be converted into advantages in the Close Enough Orienteering Problem (CEOP)by aggregating prizes across overlapped neighborhoods. We further extend the classic CEOP with Non-uniformNeighborhoods (CEOP-) by introducing non-uniform cost considerations for prize collection. To tackle CEOP(and CEOP-), we develop a new approach featuring a Randomized Steiner Zone Discretization (RSZD)scheme coupled with a hybrid algorithm based on Particle Swarm Optimization (PSO) and Ant Colony System(ACS) — CRaSZe-AntS. The RSZD scheme identifies sub-regions for PSO exploration, and ACS determinesthe discrete visiting sequence. We evaluate the RSZD’s discretization performance on CEOP instances derivedfrom established CETSP instances and compare CRaSZe-AntS against the most relevant state-of-the-art heuristicfocused on single-neighborhood optimization for CEOP instances. We also compare the performance of theinterior search within SZs and the boundary search on individual neighborhoods in the context of CEOP-. Ourexperimental results show that CRaSZe-AntS can yield comparable solution quality with significantly reducedcomputation time compared to the single neighborhood strategy, where we observe an averaged 140.44%increase in prize collection and 55.18% reduction of algorithm execution time. CRaSZe-AntS is thus highlyeffective in solving emerging CEOP-, examples of which include truck-and-drone delivery scenarios.
  • Conference paper
    Davison M, Webb CJ, Ducceschi M, McPherson APet al., 2024,

    A self-sensing haptic actuator for tactile interaction with physical modelling synthesis

    , The International Conference on New Interfaces for Musical Expression (NIME 2024), Publisher: NIME Community, Pages: 574-581, ISSN: 2220-4806

    The use of transducers to excite physical modelling synthesisers with real-world audio signals is a well established practice within the digital musical instrument design community, yet it is normally presented as a unidirectional process – energy is transferred into the system from human to instrument. In this paper, a novel approach to tactile interaction with physical modelling synthesis is presented, through the use of a self-sensing vibrotactile transducer. This enables simultaneous collocated sensing and haptic actuation with a single moving coil transducer. A current drive amplifier is used for haptic actuation, using signals derived from the physical modelling synthesiser. The varying impedance of the transducer (due to changes in the mechanical damping) enables the sensing of force applied upon the device whilst also acting as a pickup to excite the physical model, all with simultaneous haptic actuation. A digital filter equivalent of the transducer’s impedance is used to prevent feedback in the system, allowing simultaneous excitation and haptic actuation without self-oscillation
  • Journal article
    Zhou Y, Sun Y, Li Y, Shen C, Lou Z, Min X, Stewart Ret al., 2024,

    A highly durable and UV‐resistant graphene‐based knitted textile sensing sleeve for human joint angle monitoring and gesture differentiation

    , Advanced Intelligent Systems, Vol: 6, ISSN: 2640-4567

    Flexible strain sensors based on textiles have attracted extensive attention owing to their light weight, flexibility, and comfort when wearing. However, challenges in integrating textile strain sensors into wearable sensing devices include the need for outstanding sensing performance, long-term monitoring stability, and fast, convenient integration processes to achieve comprehensive monitoring. The scalable fabrication technique presented here addresses these challenges by incorporating customizable graphene-based sensing networks into knitted structures, thus creating sensing sleeves for precise motion detection and differentiation. The performance and real-world application potential of the sensing sleeve are evaluated by its precision in angle estimation and complex joint motion recognition during intra- and intersubject studies. For intra-subject analysis, the sensing sleeve only exhibits a 2.34° angle error in five different knee activities among 20 participants, and the sensing sleeves show up to 94.1% and 96.1% accuracy in the gesture classification of knee and elbow, respectively. For inter-subject analysis, the sensing sleeve demonstrates a 4.21° angle error, and it shows up to 79.9% and 85.5% accuracy in the gesture classification of knee and elbow, respectively. An activity-guided user interface compatible with the sensing sleeves for human motion monitoring in home healthcare applications is presented to illustrate the potential applications.
  • Journal article
    Peters D, Sadek M, Ahmadpour N, 2024,

    Collaborative workshops at scale: a method for non-facilitated virtual collaborative design workshops

    , International Journal of Human-Computer Interaction, Vol: 40, Pages: 5997-6014, ISSN: 1044-7318

    This article introduces a method for conducting a fully online collaborative design workshop requiring no facilitation which we refer to as a Self-guided Collaborative Online Workshop (SCOW). The article provides three main contributions. Firstly, we present a process for the conversion of a face-to-face facilitated design workshop into a SCOW using a method we call the “playboard” which draws on concepts from CSCL literature. Secondly, we evaluate the efficacy of SCOWs using an iterative evaluation with 75 participants, including measures for participant satisfaction, subjective and objective learning outcomes, quality of the online and self-guided experience, and comparison with face-to-face workshops. Results across all measures indicate that the self-guided workshop was as successful as the in-person facilitated original. Moreover, participants reported advantages of the more scalable format including improved access to those with non-visible disabilities and in the Global South. Finally, based on our findings, we present a set of recommendations for others interested in using SCOWs as an inclusive and scalable way to support collaborative experiences.
  • Journal article
    Yu X, Baker CE, Ghajari M, 2024,

    Head impact location, speed and angle from falls and trips in the workplace

    , Annals of Biomedical Engineering, Vol: 52, Pages: 2687-2702, ISSN: 0090-6964

    Traumatic brain injury (TBI) is a common injury in the workplace. Trips and falls are the leading causes of TBI in the workplace. However, industrial safety helmets are not designed for protecting the head under these impact conditions. Instead, they are designed to pass the regulatory standards which test head protection against falling heavy and sharp objects. This is likely to be due to the limited understanding of head impact conditions from trips and falls in workplace. In this study, we used validated human multi-body models to predict the head impact location, speed and angle (measured from the ground) during trips, forward falls and backward falls. We studied the effects of worker size, initial posture, walking speed, width and height of the tripping barrier, bracing and falling height on the head impact conditions. Overall, we performed 1692 simulations. The head impact speed was over two folds larger in falls than trips, with backward falls producing highest impact speeds. However, the trips produced impacts with smaller impact angles to the ground. Increasing the walking speed increased the head impact speed but bracing reduced it. We found that 41% of backward falls and 19% of trips/forward falls produced head impacts located outside the region of helmet coverage. Next, we grouped all the data into three sub-groups based on the head impact angle: [0°, 30°], (30°, 60°] and (60°, 90°] and excluded groups with small number of cases. We found that most trips and forward falls lead to impact angles within the (30°, 60°] and (60°, 90°] groups while all backward falls produced impact angles within (60°, 90°] group. We therefore determined five representative head impact conditions from these groups by selecting the 75th percentile speed, mean value of angle intervals and median impact location (determined by elevation and azimuth angles) of each group. This led to two representative head impact conditions for trip
  • Journal article
    van der Meer D, Pinson P, Camal S, Kariniotakis Get al., 2024,

    CRPS-based online learning for nonlinear probabilistic forecast combination

    , International Journal of Forecasting, Vol: 40, Pages: 1449-1466, ISSN: 0169-2070

    Forecast combination improves upon the component forecasts. Most often, combination approaches are restricted to the linear setting only. However, theory shows that if the component forecasts are neutrally dispersed—a requirement for probabilistic calibration—linear forecast combination will only increase dispersion and thus lead to miscalibration. Furthermore, the accuracy of the component forecasts may vary over time and the combination weights should vary accordingly, necessitating updates as time progresses. In this paper, we develop an online version of the beta-transformed linear pool, which theoretically can transform the probabilistic forecasts such that they are neutrally dispersed. We show that, in the case of stationary synthetic time series, the performance of the developed method converges to that of the optimal combination in hindsight. Moreover, in the case of nonstationary real-world time series from a wind farm in mid-west France, the developed model outperforms the optimal combination in hindsight.
  • Book
    Childs P, Masen M, 2024,

    Mechanical Design Engineering Handbook

    , Publisher: Elsevier, ISBN: 9780443220777

    The aim of this handbook is to present an overview of the design process and to introduce the technology and selection of specific machine elements that are fundamental to a wide range of mechanical engineering design applications.
  • Journal article
    Lou Z, Min X, Li G, Avery J, Stewart Ret al., 2024,

    Advancing sensing resolution of impedance hand gesture recognition devices

    , IEEE Journal of Biomedical and Health Informatics, Vol: 28, Pages: 5855-5864, ISSN: 2168-2194

    Gestures are composed of motion information (e.g. movements of fingers) and force information (e.g. the force exerted on fingers when interacting with other objects). Current hand gesture recognition solutions such as cameras and strain sensors primarily focus on correlating hand gestures with motion information and force information is seldom addressed. Here we propose a bio-impedance wearable that can recognize hand gestures utilizing both motion information and force information. Compared with previous impedance-based gesture recognition devices that can only recognize a few multi-degrees-of-freedom gestures, the proposed device can recognize 6 single-degree-of-freedom gestures and 20 multiple-degrees-of-freedom gestures, including 8 gestures in 2 force levels. The device uses textile electrodes, is benchmarked over a selected frequency spectrum, and uses a new drive pattern. Experimental results show that 179 kHz achieves the highest signal-to-noise ratio (SNR) and reveals the most distinct features. By analyzing the 49,920 samples from 6 participants, the device is demonstrated to have an average recognition accuracy of 98.96%. As a comparison, the medical electrodes achieved an accuracy of 98.05%.

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