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Journal articleGonzalez-Toledo D, Cuevas-Rodriguez M, Vicente T, et al., 2024,
Spatial release from masking in the median plane with non-native speakers using individual and mannequin head related transfer functions
, JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, Vol: 155, Pages: 284-293, ISSN: 0001-4966 -
Journal articleMorrison L, 2024,
Timbre space: on the flat history of a multidimensional metaphor
, Music & Science, Vol: 7, ISSN: 2059-2043This article reflects on the “flat” history of timbre space, tracking its emergence as a technical inscription in psychoacoustic experiments and its rise to become a dominant conceptual metaphor in timbre studies. Drawing on Bruno Latour's notion of “immutable mobiles,” the author shows how the idea of a multidimensional timbre space has been propagated through the circulation of diagrams, which make perceptual data on listeners accessible to remote viewers. After surveying laboratory tools and techniques required for the production of these diagrams, the article considers how models of timbre space have been built into new technologies for music composition, performance, and listening, as well as into audio classification schemes and metadata formatting standards like MPEG-7. Mapping connections between psychoacoustic discourses and design practices, the article sheds light on the technoscientific origins of timbre space, examining its articulation to research labs at Bell, CCRMA, and IRCAM, and interrogating its role in determining what counts as sound knowledge.
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Journal articleZHOU J, Porat T, Van Zalk N, 2024,
Humans mindlessly treat AI virtual agents as social beings, but this tendency diminishes among the young: evidence from a Cyberball experiment
, Human Behavior and Emerging Technologies, Vol: 2024, ISSN: 2578-1863The "social being" perspective has largely influenced the design and research of AI virtual agents. Do humans really treat these agents as social beings? To test this, we conducted a 2 between (Cyberball condition: exclusion vs. fair play) ×2 within (co-player type: AGENT vs. HUMAN) online experiment employing the Cyberball paradigm; we investigated how participants (N = 244) responded when they observed an AI virtual agent being ostracised or treated fairly by another human in Cyberball, and we compared our results with those from human-human Cyberball research. We found that participants mindlessly responded to the ostracised agent as they would to other humans by applying the social norm of inclusion during the interaction. This finding suggests that individuals tend to mindlessly treat AI virtual agents as social beings, supporting the media equation theory; however, age (no other user characteristics) influenced this tendency, with younger participants less likely to mindlessly apply the inclusion norm. We also found that participants showed increased sympathy towards the ostracised agent, but they did not devalue the human player for their ostracising behaviour; this indicates that participants did not mindfully perceive AI virtual agents as comparable to humans. Furthermore, we uncovered two other exploratory findings: the association between frequency of agent usage and sympathy, and the carryover effect of positive usage experience. Our study advances the theoretical understanding of the human side of human-agent interaction. Practically, it provides implications for the design of AI virtual agents, including the consideration of social norms, caution in human-like design, and age-specific targeting.
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Journal articleCacciarelli D, Kulahci M, 2024,
Active learning for data streams: a survey
, Machine Learning, Vol: 113, Pages: 185-239, ISSN: 0885-6125<jats:title>Abstract</jats:title><jats:p>Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of minimizing the cost associated with collecting labeled observations has gained a lot of attention in recent years, particularly in real-world applications where data is only available in an unlabeled form. Annotating each observation can be time-consuming and costly, making it difficult to obtain large amounts of labeled data. To overcome this issue, many active learning strategies have been proposed in the last decades, aiming to select the most informative observations for labeling in order to improve the performance of machine learning models. These approaches can be broadly divided into two categories: static pool-based and stream-based active learning. Pool-based active learning involves selecting a subset of observations from a closed pool of unlabeled data, and it has been the focus of many surveys and literature reviews. However, the growing availability of data streams has led to an increase in the number of approaches that focus on online active learning, which involves continuously selecting and labeling observations as they arrive in a stream. This work aims to provide an overview of the most recently proposed approaches for selecting the most informative observations from data streams in real time. We review the various techniques that have been proposed and discuss their strengths and limitations, as well as the challenges and opportunities that exist in this area of research.</jats:p>
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Journal articlePatel AM, Baxter W, Porat T, 2024,
Towards guidelines for designing holistic integrated information visualisations [hi-viz] for time-critical contexts: a systematic review
, Journal of Medical Internet Research, Vol: 26, ISSN: 1438-8871Background:With the extensive volume of information from various and diverse data sources, it is essential to present information in a way that allows for quick understanding and interpretation. This is particularly crucial in health care, where timely insights into a patient’s condition can be lifesaving. Holistic visualizations that integrate multiple data variables into a single visual representation can enhance rapid situational awareness and support informed decision-making. However, despite the existence of numerous guidelines for different types of visualizations, this study reveals that there are currently no specific guidelines or principles for designing holistic integrated information visualizations that enable quick processing and comprehensive understanding of multidimensional data in time-critical contexts. Addressing this gap is essential for enhancing decision-making in time-critical scenarios across various domains, particularly in health care.Objective:This study aims to establish a theoretical foundation supporting the argument that holistic integrated visualizations are a distinct type of visualization for time-critical contexts and identify applicable design principles and guidelines that can be used to design for such cases.Methods:We systematically searched the literature for peer-reviewed research on visualization strategies, guidelines, and taxonomies. The literature selection followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search was conducted across 6 databases: ACM Digital Library, Google Scholar, IEEE Xplore, PubMed, Scopus, and Web of Science. The search was conducted up to August 2024 using the terms (“visualisations” OR “visualizations”) AND (“guidelines” OR “taxonomy” OR “taxonomies”), with studies restricted to the English language.Results:Of 936 papers, 46 (4.9%) were included in the final review. In total, 48%
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Conference paperBaker CE, Li R, Montemeglio A, et al., 2024,
Exploring smart device sensor potential to assess simulated vulnerable road user head injury risk
, International Research Council on the Biomechanics of Injury, Publisher: IRCOBI, Pages: 603-604, ISSN: 2235-3151 -
Journal articleFalconer T, Kazempour J, Pinson P, 2024,
Bayesian Regression Markets
, JOURNAL OF MACHINE LEARNING RESEARCH, Vol: 25, ISSN: 1532-4435 -
Journal articleHogg A, Jenkins M, Liu H, et al., 2024,
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection
, IEEE Transactions on Audio, Speech and Language Processing, Vol: 32, Pages: 2085-2099, ISSN: 1558-7916An individualised (HRTF) is very important for creating realistic (VR) and (AR) environments. However, acoustically measuring high-quality HRTFs requires expensive equipment and an acoustic lab setting. To overcome these limitations and to make this measurement more efficient HRTF upsampling has been exploited in the past where a high-resolution HRTF is created from a low-resolution one. This paper demonstrates how (GAN) can be applied to HRTF upsampling. We propose a novel approach that transforms the HRTF data for direct use with a convolutional (SRGAN). This new approach is benchmarked against three baselines: barycentric upsampling, (SH) upsampling and an HRTF selection approach. Experimental results show that the proposed method outperforms all three baselines in terms of (LSD) and localisation performance using perceptual models when the input HRTF is sparse (less than 20 measured positions).
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Journal articleHan J, Childs PRN, Luo J, 2024,
Applications of artificial intelligence and cognitive science in design
, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol: 38, ISSN: 0890-0604Artificial intelligence and cognitive science are two core research areas in design. Artificial intelligence shows the capability of analysing massive amounts of data which supports making predictions, uncovering patterns and generating insights in varying design activities, while cognitive science provides the advantage of revealing the inherent mental processes and mechanisms of humans in design. Both artificial intelligence and cognitive science in design research are focused on delivering more innovative and efficient design outcomes and processes. Therefore, this thematic collection on “Applications of Artificial Intelligence and Cognitive Science in Design” brings together state-of-the-art research in artificial intelligence and cognitive science to showcase the emerging trend of applying artificial intelligence techniques and neurophysiological and biometric measures in design research. Three promising future research directions: 1) human-in-the-loop AI for design, 2) multimodal measures for design, and 3) AI for design cognitive data analysis and interpretation, are suggested by analysing the research papers collected. A framework for integration of artificial intelligence and cognitive science in design, incorporating the three research directions, is proposed to inspire and guide design researchers in exploring human-centred design methods, strategies, solutions, tools and systems.
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Journal articleCook D, Peters D, Moradbakhti L, et al., 2024,
A text-based conversational agent for asthma support: mixed-methods feasibility study
, Digital Health, Vol: 10, ISSN: 2055-2076ObjectiveMillions of people in the UK have asthma, yet 70% do not access basic care, leading to the largest number of asthma-related deaths in Europe. Chatbots may extend the reach of asthma support and provide a bridge to traditional healthcare. This study evaluates ‘Brisa’, a chatbot designed to improve asthma patients’ self-assessment and self-management.MethodsWe recruited 150 adults with an asthma diagnosis to test our chatbot. Participants were recruited over three waves through social media and a research recruitment platform. Eligible participants had access to ‘Brisa’ via a WhatsApp or website version for 28 days and completed entry and exit questionnaires to evaluate user experience and asthma control. Weekly symptom tracking, user interaction metrics, satisfaction measures, and qualitative feedback were utilised to evaluate the chatbot's usability and potential effectiveness, focusing on changes in asthma control and self-reported behavioural improvements.Results74% of participants engaged with ‘Brisa’ at least once. High task completion rates were observed: asthma attack risk assessment (86%), voice recording submission (83%) and asthma control tracking (95.5%). Post use, an 8% improvement in asthma control was reported. User satisfaction surveys indicated positive feedback on helpfulness (80%), privacy (87%), trustworthiness (80%) and functionality (84%) but highlighted a need for improved conversational depth and personalisation.ConclusionsThe study indicates that chatbots are effective for asthma support, demonstrated by the high usage of features like risk assessment and control tracking, as well as a statistically significant improvement in asthma control. However, lower satisfaction in conversational flexibility highlights rising expectations for chatbot fluency, influenced by advanced models like ChatGPT. Future health-focused chatbots must balance conversational capability with accuracy and safety to main
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Journal articleLin Y, Alemu MY, Shi B, et al., 2024,
Influence of Soft Materials on Ultrasonic Waveguide Signal Quality for Wearable Human Motion Detection Across the Legs, Arms, and Face
, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol: 73, ISSN: 0018-9456 -
Book chapterDawber W, Foster L, Senior T, et al., 2024,
Design Development of a Repeatable Helmet Test System for Public Order Threat Recreations
, Lecture Notes in Mechanical Engineering, Publisher: Springer Nature Switzerland, Pages: 169-176, ISBN: 9783031580932 -
Journal articleSadan MK, Lian GJ, Smith RM, et al., 2023,
Co, Ni-free ultrathick free-standing dry electrodes for sustainable lithium-ion batteries
, ACS Applied Energy Materials, Vol: 6, Pages: 12166-12171, ISSN: 2574-0962The conventional method of manufacturing lithium-ion battery electrodes employs a complex slurry casting process with solvents that are not environmentally friendly and process parameters that are often difficult to control. This study explores a solvent-free dry electrode fabrication process of Co- and Ni-free LiMn2O4 (LMO) cathodes using a fibrillated polymer, polytetrafluoroethylene (PTFE). A thick, dry electrode (265–368 μm, 30–64 mg cm–2) of LMO cathode was prepared successfully for the first time. Altering the conductive additives in the LMO dry electrode revealed multiwalled carbon nanotubes (CNTs) as the best conducting agent for dry electrode formulation in terms of conductivity and rate performance. Additionally, an all-dry electrode full cell consisting of both a dry electrode cathode (LMO) and an anode (LTO) delivered a stable cycling performance with a capacity retention of 82.8% after 200 cycles, demonstrating the scope for all-dry electrode full cells for future applications.
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Journal articlePan Y, Ruan H, Regmi YN, et al., 2023,
A Machine Learning Accelerated Hierarchical 3D+1D Model for Proton Exchange Membrane Fuel Cells
, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 1706-1706<jats:p> Physics-based continuum models for proton exchange membrane fuel cells (PEMFCs) are an essential tool for fuel cell design and management. To date, many continuum models, ranging from 1D to 3D, have been developed for PEMFCs. Although computationally efficient, 1D models do not account for heterogeneity in flow fields, which negatively impact their accuracy. In contrast, 2D and 3D models are usually more representative of actual operating conditions but computationally intensive due to the coupled partial differential equations and large number of mesh elements involved. To overcome these issues, a hierarchical approach that combines a 2D/3D description of flow fields, gas diffusion layers (GDLs) and a simplified microporous layer (MPL)/catalyst layer (CL)/membrane sub-model has been proposed in the literature. However, studies based on this method often use a simplified or 0D MPL/CL/membrane sub-model, whose results may deviate from a full 1D description due to the neglected nonlinearity, especially at higher loads.</jats:p> <jats:p>In this study, we present a computationally efficient 3D+1D hierarchical model for PEMFCs accelerated by machine learning. The 3D model, which captures the two-phase flow in the gas channels and GDLs, is coupled with a full 1D description of the MPLs, membrane, CLs, and CL agglomerates by exchanging boundary values and fluxes, as shown in the figure. To avoid the high computing cost increase associated with the full 1D description, we develop a physics-informed neural network to replace the 1D sub-model for coupling with the 3D model, while maintaining the full description of fuel cell internal states. Large synthetic datasets are generated using the 1D model for training the neural network, ensuring the accuracy of the model. The proposed 3D+1D model is validated against experimentally obtained polarization curves and high frequency resistances under different relative humidities. The proposed
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Journal articleGovey-Scotland J, Johnstone L, Myant C, et al., 2023,
Towards a skin-on-a-chip for screening the dermal absorption of cosmetics
, Lab on a Chip: miniaturisation for chemistry, physics, biology, materials science and bioengineering, Vol: 23, Pages: 5068-5080, ISSN: 1473-0189Over the past few decades, there have been increasing global efforts to limit or ban the use of animals for testing cosmetic products. This ambition has been at the heart of international endeavours to develop new in vitro and animal-free approaches for assessing the safety of cosmetics. While several of these new approach methodologies (NAMs) have been approved for assessing different toxicological endpoints in the UK and across the EU, there remains an absence of animal-free methods for screening for dermal absorption; a measure that assesses the degree to which chemical substances can become systemically available through contact with human skin. Here, we identify some of the major technical barriers that have impacted regulatory recognition of an in vitro skin model for this purpose and propose how these could be overcome on-chip using artificial cells engineered from the bottom-up. As part of our future perspective, we suggest how this could be realised using a digital biomanufacturing pipeline that connects the design, microfluidic generation and 3D printing of artificial cells into user-crafted synthetic tissues. We highlight milestone achievements towards this goal, identify future challenges, and suggest how the ability to engineer animal-free skin models could have significant long-term consequences for dermal absorption screening, as well as for other applications.
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Journal articleMorley JD, George C, Hadler K, et al., 2023,
Crystallography of active particles defining battery electrochemistry
, Advanced Energy Materials, ISSN: 1614-6832Crystallographic features of battery active particles impose an inherent limitation on their electrochemical figures of merit namely capacity, roundtrip efficiency, longevity, safety, and recyclability. Therefore, crystallographic properties of these particles are increasingly measured not only to clarify the principal pathways by which they store and release charge but to realize the full potential of batteries. Here, state-of-the-art advances in Li+, K+, and Na+ chemistries are reviewed to reiterate the links between crystallography variations and battery electrochemical trends. These manifest at different length scales and are accompanied by a multiplicity of processes such as doping, cation disorder, directional crystal growth and extra redox. In light of this, an emphasis is placed on the need for more accurate correlations between crystallographic structure and battery electrochemistry in order to harness crystallographic beneficiation into electrode material design and manufacture, translating into high-performance and safe energy storage solutions.
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Journal articleYasin L, Atkinson A, Cooper SJ, et al., 2023,
Identifiability of the mechanisms governing the reaction kinetics of MIEC electrodes in solid oxide cells
, Electrochimica Acta, Vol: 472, ISSN: 0013-4686The oxygen reduction reaction (ORR) is the main phenomenon occurring in mixed ionic and electronic conductors (MIECs) used as air electrodes in solid oxide cells. Their optimisation requires the identification of the ORR regime, which is typically performed via electrochemical impedance spectroscopy (EIS). In this study we present a physics-based model to simulate the impedance spectra of p-type oxygen-deficient perovskite MIEC materials. The EIS response of four extreme kinetic scenarios, characterised by the rate-determining step (electron-transfer or ion-transfer) and the high/low surface coverage of adsorbed oxygen, is mechanistically interpreted for both dense films and porous electrodes. A strategy for kinetic identification is proposed based on distinctive EIS fingerprints at different oxygen partial pressures (pO2) and cathodic bias. However, distinguishing the kinetic scenarios is not free from ambiguity even in dense films since some scenarios are discriminated only via a quantitative analysis, which may be susceptible to experimental errors in real measurements, and reverse behaviours appear when combining cathodic bias with pO2 variation. More difficulties arise in porous electrodes since bulk oxygen vacancy transport interacts with the ORR response. Application of the proposed strategy using literature data for some common MIEC materials shows the typical challenges of kinetic identification when relying solely on EIS.
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Journal articleBigestans D, Cardin M-A, Kazantzis N, 2023,
Economic performance evaluation of flexible centralised and decentralised blue hydrogen production systems design under uncertainty
, Applied Energy, Vol: 352, ISSN: 0306-2619Blue hydrogen is viewed as an important energy vector in a decarbonised global economy, but its large-scale and capital-intensive production displays economic performance vulnerabities in the face of increased market and regulatory uncertainty. This study analyses flexible (modular) blue hydrogen production plant designs and evaluates their effectiveness to enhance economic performance under uncertainty. The novelty of this work lies in the development of a comprehensive techno-economic evaluation framework that considers flexible centralised and decentralised blue hydrogen plant design alternatives in the presence of irreducible uncertainty, whilst explicitly considering the time value of money, economies of scale and learning effects. A case study of centralised and decentralised blue hydrogen production for the transport sector in the San Francisco area is developed to highlight the underlying value of flexibility. The proposed methodological framework considers various blue hydrogen plant designs (fixed, phased, and flexible) and compares them using relevant economic indicators (net present value (NPV), capex, value-at-risk/gain, etc.) through a detailed Monte Carlo simulation framework. Results indicate that flexible centralised hydrogen production yields greater economic value than alternative designs, despite the associated cost-premium of modularity. It is also shown that the value of flexibility increases under greater uncertainty, higher learning rates and weaker economies of scale. Moreover, sensitivity analysis reveals that flexible design remains the preferred investment option over a wide range of market and regulatory conditions except for high initial hydrogen demand. Finally, this study demonstrates that major regulatory and market uncertainties surrounding blue hydrogen production can be effectively managed through the application of flexible engineering system design that protects the investment from major downside risks whilst allowing access to
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Journal articleYi Y, Demirel P, 2023,
The impact of sustainability-oriented dynamic capabilities on firm growth: investigating the green supply chain management and green political capabilities
, Business Strategy and the Environment, Vol: 32, Pages: 5873-5888, ISSN: 0964-4733Building on the dynamic capabilities literature and natural-resource-based view, the paper examines whether firms can attain sales growth through a range of sustainability-oriented dynamic capabilities including (1) internal green supply chain management capabilities, (2) external green supply chain management capabilities and (3) green political capabilities. Based on a dataset of 277 public US firms between 2010 and 2020, a panel quantile model of firm growth showcases that while internal green supply chain capabilities and green political capabilities affect firms' growth performance positively, external green supply chain capabilities are associated with slower growth. Importantly, the results indicate that the positive growth effects of green political capabilities are short-lived, while those of internal green supply chain capabilities are long-lived. The study contributes to the sustainability-oriented dynamic capabilities literature by showing that different capabilities have different implications for firm growth depending on the firm's base performance and the time periods under consideration.
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Journal articleSadek M, Calvo R, Mougenot C, 2023,
Co-designing conversational agents: a comprehensive review and recommendations for best practices
, Design Studies, Vol: 89, ISSN: 0142-694XThis paper presents a comprehensive review of fifty-two studies co-designing conversational agents (CAs). Its objectives are to synthesise prior CA co-design efforts and provide actionable recommendations for future endeavours in CA co-design. The review systematically evaluates studies' methodological and contextual aspects, revealing trends and limitations. These insights converge into practical recommendations for co-designing CAs, including (1) selecting the most suitable design technique aligned with desired CA outcomes, (2) advocating continuous stakeholder involvement throughout the design process, and (3) emphasising the elicitation and embodiment of stakeholder values to ensure CA designs align with their perspectives. This paper contributes to standardising and enhancing co-design practices, promising to improve the quality of outcomes in the case of CAs while benefiting stakeholders and users.
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Journal articleBonkile MP, Jiang Y, Kirkaldy N, et al., 2023,
Coupled electrochemical-thermal-mechanical stress modelling in composite silicon/graphite lithium-ion battery electrodes
, Journal of Energy Storage, Vol: 73, ISSN: 2352-152XSilicon is often added to graphite battery electrodes to enhance the electrode-specific capacity, but it undergoes significant volume changes during (de)lithiation, which results in mechanical stress, fracture, and performance degradation. To develop long-lasting and energy-dense batteries, it is critical to understand the non-linear stress behaviour in composite silicon-graphite electrodes. In this study, we developed a coupled electrochemical-thermal-mechanical model of a composite silicon/graphite electrode in PyBaMM (an open-source physics-based modelling platform). The model is experimentally validated against a commercially available LGM50T battery, and the effects of C-rates, depth-of-discharge (DoD), and temperature are investigated. The developed model can reproduce the voltage hysteresis from the silicon and provide insights into the stress response and crack growth/propagation in the two different phases. The stress in the silicon is relatively low at low DoD but rapidly increases at a DoD >~80%, whereas the stress in the graphite increases with decreasing temperature and DoD. At higher C-rates, peak stress in the graphite increases as expected, however, this decreases for silicon due to voltage cut-offs being hit earlier, leading to lower active material utilisation since silicon is mostly active at high DoD. Therefore, this work provides an improved understanding of stress evolution in composite silicon/graphite lithium-ion batteries.
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Journal articleMiguel Angel M, Pinson P, Kazempour J, 2023,
Online decision making for trading wind energy
, Computational Management Science, Vol: 20, Pages: 1-31, ISSN: 1619-697XWe propose and develop a new algorithm for trading wind energy in electricity markets, within an online learning and optimization framework. In particular, we combine a component-wise adaptive variant of the gradient descent algorithm with recent advances in the feature-driven newsvendor model. This results in an online offering approach capable of leveraging data-rich environments, while adapting to the nonstationary characteristics of energy generation and electricity markets, also with a minimal computational burden. The performance of our approach is analyzed based on several numerical experiments, showing both better adaptability to nonstationary uncertain parameters and significant economic gains.
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Journal articleGong Y, Li J, Yang K, et al., 2023,
Towards Practical Application of Li-S Battery with High Sulfur Loading and Lean Electrolyte: Will Carbon-Based Hosts Win This Race?
, NANO-MICRO LETTERS, Vol: 15, ISSN: 2311-6706 -
Journal articleHarkin R, Wu H, Nikam S, et al., 2023,
Reuse of grade 23 Ti6Al4V powder during the laser-based powder bed fusion process
, Metals, Vol: 10, ISSN: 2075-4701Titanium alloy powder used for laser-based powder bed fusion (L-PBF) process is costly. One of the solutions is the inclusion of a powder recycling strategy, allowing unused or exposed powder particles to be recuperated post manufacture, replenished and used for future builds. However, during a L-PBF process, powder particles are exposed to high levels of concentrated energy from the laser. Particularly those in close proximity to the melt pool, leading to the formation of spatter and agglomerated particles. These particles can settle onto the powder bed, which can then influence the particle size distribution and layer uniformity. This study analysed extra-low interstitial (ELI) Ti6Al4V (Grade 23) powder when subjected to nine recycle iterations, tracking powder property variation across the successive recycling stages. Characterisation included chemical composition focusing upon O, N, and H content, particle size distribution, morphology and tapped and bulk densities. On review of the compositional analysis, the oxygen content exceeded the 0.13% limit for the ELI grade after 8 recycles, resulting in the degradation from Grade 23 level.
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Conference paperWang B, Zuo H, Cai Z, et al., 2023,
A task-decomposed AI-aided approach for generative conceptual design
, ASME 2023 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE2023)Generative algorithm-based conceptual design has beeninnovatively applied as an emerging digital design paradigm forearly-stage design ideation. With powerful large languagemodels (LLMs), designers can enter an initial prompt as a designrequirement to generate using machine reasoning capabilitydescriptive natural language content. The machine-generatedoutput can be used as stimuli to inspire designers during designideation. However, the lack of transparency and insufficientcontrollability of LLMs can limit their effectiveness whenassisting humans on a generative conceptual design task. Thisgeneration process lacks theoretical guidance and acomprehensive understanding of design requirements, whichmay potentially lead to generated concepts that are mismatchedor lack creativity. Inspired by the Function-Behavior-Structure(FBS) model, this paper proposes a task-decomposed AI-aidedapproach for generative conceptual design. We decompose aconceptual design task into three sub-tasks including functionalreasoning, behavioral reasoning, and structural reasoning.Prompt templates and specification signifiers are specified fordifferent steps to guide the LLMs to generate reasonable results,controllably. The output of each step becomes the input of thenext, aiding in aggregating gains per step and embedding theselection preferences of human designers at each stage. Aconceptual design experiment is conducted, and the results showthat the conceptual design ideation with our method are morereasonable and creative in comparison to a baseline.
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Journal articleChappell D, Bello F, Kormushev P, et al., 2023,
The hydra hand: a mode-switching underactuated gripper with precision and power grasping modes
, IEEE Robotics and Automation Letters, Vol: 8, Pages: 7599-7606, ISSN: 2377-3766Human hands are able to grasp a wide range of object sizes, shapes, and weights, achieved via reshaping and altering their apparent grasping stiffness between compliant power and rigid precision. Achieving similar versatility in robotic hands remains a challenge, which has often been addressed by adding extra controllable degrees of freedom, tactile sensors, or specialised extra grasping hardware, at the cost of control complexity and robustness. We introduce a novel reconfigurable four-fingered two-actuator underactuated gripper—the Hydra Hand—that switches between compliant power and rigid precision grasps using a single motor, while generating grasps via a single hydraulic actuator—exhibiting adaptive grasping between finger pairs, enabling the power grasping of two objects simultaneously. The mode switching mechanism and the hand's kinematics are presented and analysed, and performance is tested on two grasping benchmarks: one focused on rigid objects, and the other on items of clothing. The Hydra Hand is shown to excel at grasping large and irregular objects, and small objects with its respective compliant power and rigid precision configurations. The hand's versatility is then showcased by executing the challenging manipulation task of safely grasping and placing a bunch of grapes, and then plucking a single grape from the bunch.
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Conference paperBallou N, Deterding S, 2023,
‘I Just Wanted to Get it Over and Done With’: a grounded theory of psychological need frustration in video games
, CHI PLAY 2023, Publisher: Association for Computing Machinery (ACM), Pages: 217-236, ISSN: 2573-0142Psychological need frustration—experiences like failure, loneliness, or coercion—is emerging as a promising explanation for why people disengage with games and other entertainment media, and how media may induce dysregulated use and ill-being. However, existing research on game-related need frustration relies on general instruments with unclear content validity for games. We also do not know how need frustration arises in video games, nor how it leads to disengagement. We therefore conducted a semi-structured interview study with 12 video game players, following grounded theory methods to develop a model of need-frustrating play. We find that need frustration is a common and impactful experience in games, with distinct antecedents not fully captured in existing measures. Felt need frustration arises when observed need-frustrating events negatively violate expected need frustration or satisfaction; repeated violations update players’ expectations, which lead them to modulate or quit play to reduce expected frustration exposure.
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Journal articleArteaga JM, Sanchez J, Elsakloul F, et al., 2023,
High frequency inductive power transfer through soil for agricultural applications
, IEEE Transactions on Power Electronics, Vol: 38, Pages: 13415-13429, ISSN: 0885-8993This paper presents 13.56 MHz inductive powertransfer (IPT) through soil for sensors in agricultural ap-plications. Two IPT system designs and their prototypes are presented. The first was designed for gathering data and observing the relationship between the performance of the coil driving circuits in response to water content, salinity, organic matter and compaction of the soil. The second prototype was designed as an application demonstrator, featuring IPT to an in-house sensor node enclosure buried 200 mm under the surface of an agricultural field. The results highlight that from the parameters studied, the combination of high salinity and high water content significantly increases the losses of the IPT system.The experiments demonstrate an over 40% rise in the losses from dc source to dc load after a 16% increase in soil water content and high salinity. In the technology demonstrator we mounted an IPT transmitter on a drone to wirelessly power an in-house bank of supercapacitors in the buried sensor-node enclosure. A peak power transfer of 30 W received at over 40% efficiency was achieved from a 22 V power supply on the drone to the energy storage under the ground. The coil separation in these experiments was 250 mm of which 200 mm correspond to the layer of soil. The coupling factor in all the experiments was lower than 5%. This system was trialled in the field for forty days andwireless power was performed five times throughout.
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Journal articleWang K, Xin G, Xin S, et al., 2023,
A unified model with inertia shaping for highly dynamic jumps of legged robots
, MECHATRONICS, Vol: 95, ISSN: 0957-4158 -
Conference paperWhitby MA, Iacovides I, Deterding S, 2023,
“Conversations with pigeons”: capturing players’ lived experience of perspective challenging games
, CHI PLAY 2023, Publisher: Association for Computing Machinery (ACM), Pages: 833-855, ISSN: 2573-0142Video games are increasingly designed to provoke reflection and challenge players’ perspectives. Yet we know little about how such perspective-challenging experiences come about in gameplay. In response, we used systematic self-observation diaries and micro-phenomenological interviews to capture players’ (n=15) lived experience of perspective challenges in purposely sampled games including Hatoful Boyfriend, The Stanley Parable, or Papers, Please. We found a sequence of trigger, reflection, and transformation constituting perspective-challenging experiences, matching Mezirow’s model of transformative learning. Most of these were game-related or ‘endo-game’, suggesting that medium self-reflection could be an overlooked part of everyday game reflection and appreciation. Reflections were accompanied by a wide range of emotions, including frequent epistemic emotions, and emotions could change drastically even during short gameplay experiences. Actual perspective change or transformation was rare. We construct a model of granular types of triggers, reflections, and transformations that can aid reflective game design.
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