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Journal articleBaker CE, Ghajari M, 2025,
How do demographic factors, non-standard and out-of-position seating affect vehicle occupant injury outcomes in road traffic collisions?
, Safety Science, Vol: 187, ISSN: 0925-7535Advancements in smart, adaptive vehicle safety features offer significant potential to improve occupant safety by detecting and responding to diverse seating positions in real-time. Yet, current safety designs and crash testing primarily focus on occupants of distinct demographics statically seated in standard positions, raising challenges of equity and real-world representability. We investigated the link between out-of-position (OOP) occupants and injury severity in British road traffic collisions, using the comprehensive Road Accident In-Depth Studies (RAIDS) dataset. We quantified injury risks for unbelted and OOP occupants by analysing factors such as seat belt use, seat back recline angle, dashboard proximity and head restraint height in 5,362 RAIDS occupants from over 2,200 collisions. Unbelted occupants had a 1.88 times higher risk of severe injuries (maximum abbreviated injury scale - (MAIS3+) compared to belted occupants. Male occupants had overall lower seat belt use than female occupants and tended to be younger. Reclined seating angles over 110° were associated with a 3.99 times higher risk. For male occupants, not wearing a seat belt was associated with higher seat back recline angle and younger age. Occupant height and sex were observed to have a nuanced interaction with far back/forward seating positions. This shows even end-range manufacturer-approved seating positions had increased injury risk, emphasising the importance of protecting diverse occupant postures and populations. Our work highlights the potential for advanced sensing technologies to mitigate seating position related injury risks and guide research, testing and innovation to ensure equitable protection for all occupants in future vehicle systems featuring increased automation.
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Journal articleGuo H, Xiao Y, Pinson P, et al., 2025,
A negotiation-based incentive mechanism for efficient Transmission Expansion Planning considering generation investment equilibrium in deregulated environment
, Applied Energy, Vol: 386, ISSN: 0306-2619The current Transmission Expansion Planning (TEP) incentive mechanisms are inadequate. They either fail to ensure revenue sufficiency or achieve socially optimal investment. The non-negligible coordination between TEP and Generation Expansion Planning (GEP) in the deregulated environment introduces more computational challenges to the TEP problem. This paper proposes a novel negotiation mechanism that enables Generation Companies (GenCos) and Load-Serving-Entities (LSEs) to negotiate TEP strategies with Transmission Companies (TransCo) directly. The negotiation process is modeled based on the Nash Bargaining theory. We explore the intertwined relationship between TEP and GEP through a bi-level, single-leader-multi-follower model. We transform the upper-level problem for better tractability and introduce a modified Proximal-Message-Passing (PMP) decentralized algorithm to achieve generation investment equilibrium at the lower level. We then utilize an iterative solving approach to coordinate the two levels. The feasibility and efficiency of this mechanism and methodologies are demonstrated using an IEEE 24-bus test system. The numerical results verify that our mechanism ensures revenue sufficiency and achieves socially optimal TEP strategies comparable to state-of-the-art mechanisms. Additionally, our mechanism maintains transmission network user privacy, aligns the benefits of TransCo with those of transmission network users, and ensures a fair allocation of TEP costs and risks. The proactive participation of market players enabled by the negotiation mechanism can promote the transformation towards new market systems by mitigating the stranded cost issue. Moreover, our decentralized algorithm effectively addresses the non-cooperative nature of GEP, and the computational efficiency analysis justifies the model's scalability and practicality.
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Journal articleIkeya K, Guerrero-Gonzalez FJ, Kiewiet L, et al., 2025,
Hybrid lunar ISRU plant: A comparative analysis with carbothermal reduction and water extraction
, Acta Astronautica, Vol: 230, Pages: 148-168, ISSN: 0094-5765To establish a self-sustained human presence in space and to explore deeper into the solar system, extensive research has been conducted on In-Situ Resource Utilization (ISRU) systems. Past studies have proposed and researched many technologies to produce oxygen from regolith, such as carbothermal reduction and water extraction from icy regolith, to utilize it for astronauts’ life support and as the propellant of space systems. However, determining the most promising technology remains challenging due to uncertainties in the lunar environment and processing methods. To better understand the lunar environment and ISRU operations, it is crucial to gather more information. Motivated by this need for information gathering, this paper proposes a new ISRU plant architecture integrating carbothermal reduction of dry regolith and water extraction from icy regolith. Two different hybrid plant architectures integrating both technologies (1) in parallel and (2) in series are examined. The former involves mining and processing in both a Permanently Shadowed Region (PSR) and a peak of eternal light in parallel, while the latter solely mines in a PSR. In this series hybrid architecture, the dry regolith tailings from water extraction are further processed by carbothermal reduction. This paper conducts a comparative analysis of the landed mass and required power of each plant architecture utilizing subsystem-level models. Furthermore, based on uncertain parameters such as resource content in regolith, the potential performance range of each plant was discovered through Monte Carlo simulations. The result indicates the benefit of the series hybrid architecture in terms of regolith excavation rate and power consumption, while its mass cost seems the highest among the studied architectures.
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Book chapterHazeri K, Childs P, 2025,
Extension of the Consensual Assessment Technique to Consumer Products: Case Studies
, Creations The Nature of Creative Products in the 21st Century, Editors: Cropley, Publisher: Palgrave MacMillan, Pages: 161-186, ISBN: 9783031824142This edited book explores creative products (i.e. Creations) as part of the seven C's of creativity framework.
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Journal articleZhang Z, Sun S, Moradbakhti L, et al., 2025,
Health Care Professionals' Engagement With Digital Mental Health Interventions in the United Kingdom and China: Mixed Methods Study on Engagement Factors and Design Implications.
, JMIR Ment Health, Vol: 12BACKGROUND: Mental health issues like occupational stress and burnout, compounded with the after-effects of COVID-19, have affected health care professionals (HCPs) around the world. Digital mental health interventions (DMHIs) can be accessible and effective in supporting well-being among HCPs. However, low engagement rates of DMHIs are frequently reported, limiting the potential effectiveness. More evidence is needed to reveal the factors that impact HCPs' decision to adopt and engage with DMHIs. OBJECTIVE: This study aims to explore HCPs' motivation to engage with DMHIs and identify key factors affecting their engagement. Amongst these, we include cultural factors impacting DMHI perception and engagement among HCPs. METHODS: We used a mixed method approach, with a cross-sectional survey (n=438) and semistructured interviews (n=25) with HCPs from the United Kingdom and China. Participants were recruited from one major public hospital in each country. RESULTS: Our results demonstrated a generally low engagement rate with DMHIs among HCPs from the 2 countries. Several key factors that affect DMHI engagement were identified, including belonging to underrepresented cultural and ethnic groups, limited mental health knowledge, low perceived need, lack of time, needs for relevance and personal-based support, and cultural elements like self-stigma. The results support recommendations for DMHIs for HCPs. CONCLUSIONS: Although DMHIs can be an ideal alternative mental health support for HCPs, engagement rates among HCPs in China and the United Kingdom are still low due to multiple factors and barriers. More research is needed to develop and evaluate tailored DMHIs with unique designs and content that HCPs can engage from various cultural backgrounds.
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Journal articleEspinoza F, Cook D, Da Re M, et al., 2025,
Designing AI-Powered Chatbots for Dementia Care in Peru: Stakeholder Engagement and Field Observations
, Interacting with Computers, ISSN: 0953-5438<jats:title>Abstract</jats:title> <jats:p>In Peru, dementia caregivers face burnout, depression, stress and financial strain. Addressing their needs involves tackling the intricacies of resourcing, caregiving and managing emotional burdens. Chatbots could serve as a viable support mechanism for these issues in regions with limited resources. We study the perceptions of dementia caregivers in Peru regarding a chatbot tailored to offer care navigation and emotional support. We divided the study into four phases: the initial stage encompassed engaging stakeholders to understand potential design challenges; the second stage focused on the design of ‘Ana’, a chatbot for dementia caregivers; the third stage assessed the chatbot through interviews and a caregiver satisfaction survey and the fourth stage gathered contextual insights through a field study for culturally-sensitive recommendations for ‘Ana’. The findings reveal that caregivers seek immediate access to information on handling behavioural symptoms and a platform for emotional release. Moreover, ‘Ana’ was tested in two configurations—one employed predefined conversation patterns, while the other harnessed generative AI for more dynamic responses. Participants preferred the generative AI alternative of ‘Ana’ as it was perceived to be more empathic and human-like. The participants valued the generative approach despite knowing the potential risk of receiving inaccurate information. Lastly, the field observations challenge the practicality of offering care navigation due to the lack of resources available in the health system and highlight that ‘Ana’ needs to be accessible for the varying educational and technological literacy levels present in Peru. However, we found that WhatsApp could be leveraged to overcome the accessibility challenges due to its pervasiveness in Peruvian society and that Community Health Workers c
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Journal articleCorbett F, Van Zalk N, 2025,
Speech perception and hearing outcomes following pediatric bilateral cochlear implants: A scoping review of developmental contextual influences
, Frontiers in Audiology and Otology -
Journal articleLazo-Porras M, Tateishi-Serruto FJ, Butler C, et al., 2025,
Assessment of Health System Readiness and Quality of Dementia Services in Peru: Protocol for a Qualitative Study With Stakeholder Interviews and Documentation Review.
, JMIR Res Protoc, Vol: 14BACKGROUND: Dementia is a global health priority with significant challenges due to its complex nature and increasing prevalence. Health systems worldwide struggle to address chronic conditions like dementia, often providing fragmented care. However, information about how health systems respond to the needs of people with dementia and their carers, and the quality of care provided, is scarce in low- and middle-income countries. OBJECTIVE: This study aims to assess the quality of the health system to provide diagnosis and care for people with dementia and their carers in Peru. In order to do this, the study will explore the response of the Peruvian health system to people with dementia and their carers, and explore the experiences of people with dementia of receiving their diagnosis, management, and quality of care for this condition. METHODS: This study is part of a research program called "IMPACT Salud: Innovations using Mhealth for people with dementia and Co-morbidities," aimed at strengthening health systems to provide care for people with dementia and their carers. The study has a descriptive, cross-sectional design that uses a qualitative methodology, including stakeholder interviews and documentation review, and consists of 2 substudies, a health system assessment (HSA) and an exploration of the patient journey. The first substudy uses an HSA methodology suitable for low- and middle-income countries, conducting 160 structured interviews with 12 different stakeholder types across 3 levels of the health system (micro, meso, and macro) in 4 Peruvian regions, each with distinct geographical and urbanization profiles. The second substudy uses a patient journey methodology, which involves conducting 40 in-depth interviews with people with dementia, carers, and health care workers from the same 4 regions. The insights into the people with dementia patient and caregiver experience within the health system from the interviews will be used to produce a patien
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Journal articleDemirel P, Kesidou E, Gamze Ozturk D, 2025,
IT-Enabled Organisational Transformation and Green Employment Growth in Microfirms
, Business Strategy and the Environment, ISSN: 0964-4733 -
Journal articleZou Y, Zhao C, Childs P, et al., 2025,
User experience design for online sports shoe retail platforms: An empirical analysis based on consumer needs
, Behavioral Sciences, ISSN: 2076-328X -
Journal articleWang Q, Dai H-N, Yang J, et al., 2025,
Learning-based artificial intelligence artwork: methodology taxonomy and quality evaluation
, ACM Computing Surveys, Vol: 57, ISSN: 0360-0300With 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.
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Journal articleFrost E, Malhotra P, Porat T, et al., 2025,
HEaring and LIstening eXperience (HELIX): Evaluation of a co-designed serious game for auditory-cognitive training.
, Q J Exp Psychol (Hove)In the dementia field, a number of applications are being developed aimed at boosting functional abilities. There is an interesting gap as to how utilising serious games can further the knowledge on the potential relationship between hearing and cognitive health in mid-life. The aim of this study was to evaluate the auditory-cognitive training application HELIX, against outcome measures for speech-in-noise, cognitive tasks, communication confidence, quality of life, and usability. A randomised-controlled trial was completed for 43 participants with subjective hearing loss and/or cognitive impairment, over a play period of 4 weeks and a follow-up period of another 4 weeks. Outcome measures included a new online implementation of the Digit-Triplet-Test, a battery of online cognitive tests, and quality of life questionnaires. Paired semi-structured interviews and usability measures were completed to assess HELIX's impact on quality of life and usability. An improvement in the performance of the Digit-Triplet-Test, measured 4 and 8 weeks after the baseline, was found within the training group; however, this improvement was not significant between the training and control groups. No significant improvements were found in any other outcome measures. Thematic analysis suggested HELIX prompted the realisation of difficulties and actions required, improved listening, and positive behaviour change. Employing a participatory design approach has ensured HELIX is relevant and useful for participants who may be at risk of developing age-related hearing loss and cognitive decline. Although an improvement in the Digit-Triplet-Test was seen, it is not possible to conclude whether this was as a result of playing HELIX.
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Journal articleTan P, Zhu X, Bi T, et al., 2025,
RunMe: An adaptive sound system for running meditation
, ACM Transactions on Computer-Human Interaction, ISSN: 1073-0516<jats:p>Running has emerged as an alternative to traditional meditation practices that involve sitting with closed eyes. The rhythmic nature of running establishes a connection between mind and body to promote mindfulness and improve the overall experience and benefits of running. The use of technology-supported meditation is gaining attention in the fields of mental and physical wellness. However, existing meditation technologies primarily focus on one-way stimuli for sitting or walking meditation, with little emphasis on adaptive design and development for running meditation. To address this issue, we present the design framework and system development of RunMe, an adaptive sound system specifically designed for running meditation. RunMe integrates stimulation and regulation mechanisms to enhance adaptive data interactions between the sounds and runners’ biodata. We compared the significance of the RunMe group with three other groups: use of non-adaptive sound, use of favorite music and use of no music/sound. The results show that the RunMe group outperforms the other groups in attention regulation, body awareness, exercise motivation, and mindfulness. Importantly, RunMe has the potential to allow users to engage in running meditation without specialized equipment, making it accessible for daily practice. We also discuss the design framework and practical distinctions of RunMe, as well as the design implications and future directions for advancing running meditation.</jats:p>
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Journal articlevan der Klink M, Demirel P, 2025,
Implementing reusable medical textiles in NHS operating theatres: barriers and enablers
, Journal of Cleaner Production, Vol: 491, ISSN: 0959-6526Replacing resource-intensive single-use medical equipment such as disposable medical textiles with reusable alternatives is of paramount importance for reducing the environmental impact of healthcare. This study investigates the systemwide barriers and enablers/drivers for implementing reusable medical textiles in the UK's National Health System (NHS) operating theatres (OT). Based on insights from 21 in-depth stakeholder interviews with OT staff, procurers, suppliers, laundering services, and field experts, the study showcases the growing desire of clinicians to shift to a reusable medical textiles system. Yet, financial pressures, lack of integration with the infection control function in hospitals, legacy of customs and practices, supply chain complexities, and a lack of in-house sterilisation and laundry capabilities currently stand as main barriers in the way of adopting reusable medical textiles. Systemwide interventions in education, policy and protocols, and supply chain structures are proposed as the three major avenues to drive the adoption of reusable medical textiles in OTs.
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Journal articleTan X, Ahmed-Kristensen S, Zhu Q, et al., 2025,
Identification of excessive contact pressures under hand orthosis based on finite element analysis.
, Prosthet Orthot Int, Vol: 49, Pages: 119-126BACKGROUND: Implicit magnitudes and distribution of excessive contact pressures under hand orthoses hinder clinicians from precisely adjusting them to relieve the pressures. To address this, contact pressure under a hand orthosis were analysed using finite element method. METHODS: This paper proposed a method to numerically predict the relatively high magnitudes and critical distribution of contact pressures under hand orthosis through finite element analysis, to identify excessive contact pressure locations. The finite element model was established consisting of the hand, orthosis and bones. The hand and bones were assumed to be homogeneous and elastic bodies, and the orthosis was considered as an isotropic and elastic shell. Two predictions were conducted by assigning either low (fat) or high (skin) material stiffness to the hand model to attain the range of pressure magnitudes. An experiment was conducted to measure contact pressures at the predicted pressure locations. RESULTS: Identical pressure distributions were obtained from both predictions with relatively high pressure values disseminated at 12 anatomical locations. The highest magnitude was found at the thumb metacarpophalangeal joint with the maximum pressure range from 13 to 78 KPa. The measured values were within the predicted range of pressure magnitudes. Moreover, 6 excessive contact pressure locations were identified. CONCLUSIONS: The proposed method was verified by the measurement results. It renders understanding of interface conditions underneath the orthosis to inform clinicians regarding orthosis design and adjustment. It could also guide the development of 3D printed or sensorised orthosis by indicating optimal locations for perforations or pressure sensors.
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Journal articleChappell D, Yang Z, Clark A, et al., 2025,
Examining the physical and psychological effects of combining multimodal feedback with continuous control in prosthetic hands
, Scientific Reports, ISSN: 2045-2322 -
Journal articleKharman AM, Ferraro P, Hamedmoghadam H, et al., 2025,
Tree Proof-of-Position algorithms
, IEEE Internet of Things Journal, Pages: 1-1, ISSN: 2327-4662A growing issue across multiple fields involves verifying that an individual or object is truly in the location it claims to be and, despite the significance of this problem, the scientific community has not extensively explored how to provide proof for such claims. Accordingly, this paper presents a novel class of proof-of-position algorithms: Tree-Proof-of-Position (T-PoP). These algorithms are decentralised, collaborative and can be computed in a privacy preserving manner, such that agents do not need to reveal their position publicly. We make no assumptions of honest behaviour in the system, and consider varying ways in which agents may misbehave. T-PoP is therefore resilient to adversarial scenarios, which makes it suitable for a wide class of applications, namely those where trust in a centralised infrastructure may not be assumed, or high security risk scenarios. Our algorithm has a worst case quadratic runtime, making it suitable for hardware constrained IoT applications. We also provide a mathematical model that summarises T-PoP’s performance for varying operating conditions. Using a large number of agent-based simulations, we verify the agreement between TPoP’s performance and our mathematical predictions. T-PoP can achieve high levels of reliability and security by tuning its operating conditions, both in high and low density environments. Finally, we also present a mathematical model to probabilistically detect platooning attacks.
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Conference paperWang P, Zhang X, Zhou Z, et al., 2025,
Typeface Generation through Style Descriptions With Generative Models
Typeface design plays a vital role in graphic and communication design. Different typefaces are suitable for different contexts and can convey different emotions and messages. Typeface design still relies on skilled designers to create unique styles for specific needs. Recently, generative adversarial networks (GANs) have been applied to typeface generation, but these methods face challenges due to the high annotation requirements of typeface generation datasets, which are difficult to obtain. Furthermore, machine-generated typefaces often fail to meet designers' specific requirements, as dataset annotations limit the diversity of the generated typefaces. In response to these limitations in current typeface generation models, we propose an alternative approach to the task. Instead of relying on dataset-provided annotations to define the typeface style vector, we introduce a transformer-based language model to learn the mapping between a typeface style description and the corresponding style vector. We evaluated the proposed model using both existing and newly created style descriptions. Results indicate that the model can generate high-quality, patent-free typefaces based on the input style descriptions provided by designers. The code is available at: https://github.com/tqxg2018/Description2Typeface.
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Journal articleMeyer 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: 0003-682XWave-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.
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Journal articleChappell D, Mulvey B, Perera S, et al., 2025,
Beyond Humanoid Prosthetic Hands: Modular Terminal Devices That Improve User Performance
, IEEE Transactions on Neural Systems and Rehabilitation Engineering, ISSN: 1534-4320Despite decades of research and development, myoelectric prosthetic hands lack functionality and are often rejected by users. This lack in functionality can be partially attributed to the widely accepted anthropomorphic design ideology in the field; attempting to replicate human hand form and function despite severe limitations in control and sensing technology. Instead, prosthetic hands can be tailored to perform specific tasks without increasing complexity by shedding the constraints of anthropomorphism. In this paper, we develop and evaluate four open-source modular non-humanoid devices to perform the motion required to replicate human flicking motion and to twist a screwdriver, and the functionality required to pick and place flat objects and to cut paper. Experimental results from these devices demonstrate that, versus a humanoid prosthesis, non-humanoid prosthesis design dramatically improves task performance, reduces user compensatory movement, and reduces task load. Case studies with two end users demonstrate the translational benefits of this research. We found that special attention should be paid to monitoring end-user task load to ensure positive rehabilitation outcomes.
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Journal articleWu H, Lu Z, Hill S, et al., 2025,
Microstructure Characterisation and Modelling of Pre-Forging Solution Treatment of 7075 Aluminium Alloy Using Novel Heating Methods
, Journal of Manufacturing and Materials Processing, Vol: 9This study evaluates the effectiveness of these conventional heating methods, commonly adopted in the industry with long durations (typically one hour), in comparison to newer, potentially more efficient approaches such as induction coil heating, infrared module heating, and infrared furnaces that can perform solution heat treatment in significantly shorter times (5 to 20 min). The properties of the edge and centre regions of the solution-treated billets, including the state of precipitates, grain structures, and Vickers hardness, are investigated and compared. Results have shown that the 7075 billets heated by conventional heating methods sufficiently dissolved the stable precipitates, achieving hardness ranging from 137 to 141 HV, in contrast to the benchmark unheated, as-received sample of approximately 70 HV. In the meantime, the induction coil and infrared furnace demonstrate notable effectiveness, achieving hardness between 126 and 135 HV. The average grain sizes in the centre and edge regions for all samples are measured as 3 and 8 µm, respectively. However, the impact of the grain size on the hardness is negligible compared to the impact of the precipitates. Finite element (FE) modelling comparing the slowest heating method—the electric furnace—and the fastest heating method—induction coil heating—reveals the latter could heat the billet up to 450 °C at a rate ten times faster than the electric furnace. This study highlights the potential of novel heating techniques in promoting the efficiency of heat treatment processes for 7075 aluminium alloys.
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Conference paperShilov I, Le Cadre H, Bušić A, et al., 2025,
Forecast Trading as a Means to Reach Social Optimum on a Peer-to-Peer Market
, Pages: 121-130, ISSN: 0302-9743This paper investigates the coupling between a peer-to-peer (P2P) electricity market and a forecast market to alleviate the uncertainty faced by prosumers regarding their renewable energy sources (RES) generation. The work generalizes the analysis from Gaussian-distributed RES production to arbitrary distributions. The P2P trading is modeled as a generalized Nash equilibrium problem, where prosumers trade energy in a decentralized manner. Each agent has the option to purchase a forecast on the forecast market before trading on the electricity market. We establish conditions on arbitrary probability density functions (pdfs) under which the prosumers have incentives to purchase forecasts on the forecast market. Connected with the previous results, this allows us to prove the economic efficiency of the P2P electricity market, i.e., that a social optimum can be reached among the prosumers.
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Journal articleRizvi D, Boyle D, 2025,
Multi-agent reinforcement learning with action masking for UAV-enabled mobile communications
, IEEE Transactions on Machine Learning in Communications and Networking, Vol: 3, Pages: 117-132, ISSN: 2831-316XUnmanned Aerial Vehicles (UAVs) are increasingly used as aerial base stations to provide ad hoc communications infrastructure. Building upon prior research efforts which consider either static nodes, 2D trajectories or single UAV systems, this paper focuses on the use of multiple UAVs for providing wireless communication to mobile users in the absence of terrestrial communications infrastructure. In particular, we jointly optimize UAV 3D trajectory and NOMA power allocation to maximize system throughput. Firstly, a weighted K-means-based clustering algorithm establishes UAV-user associations at regular intervals. Then the efficacy of training a novel Shared Deep Q-Network (SDQN) with action masking is explored. Unlike training each UAV separately using DQN, the SDQN reduces training time by using the experiences of multiple UAVs instead of a single agent. We also show that SDQN can be used to train a multi-agent system with differing action spaces. Simulation results confirm that: 1) training a shared DQN outperforms a conventional DQN in terms of maximum system throughput (+20%) and training time (-10%); 2) it can converge for agents with different action spaces, yielding a 9% increase in throughput compared to Mutual DQN algorithm; and 3) combining NOMA with an SDQN architecture enables the network to achieve a better sum rate compared with existing baseline schemes.
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Journal articleChen X, Chen W, Lee D, et al., 2025,
A Backbone for Long-Horizon Robot Task Understanding
, IEEE Robotics and Automation Letters, Vol: 10, Pages: 2048-2055End-to-end robotlearning, particularly for long-horizon tasks, often results in unpredictable outcomes and poor generalization. To address these challenges, we propose a novel Therblig-Based Backbone Framework (TBBF) as a fundamental structure to enhance interpretability, data efficiency, and generalization in robotic systems. TBBF utilizes expert demonstrations to enable therblig-level task decomposition, facilitate efficient action-object mapping, and generate adaptive trajectories for new scenarios. The approach consists of two stages: offline training and online testing. During the offline training stage, we developed the Meta-RGate SynerFusion (MGSF) network for accurate therblig segmentation across various tasks. In the online testing stage, after a one-shot demonstration of a new task is collected, our MGSF network extracts high-level knowledge, which is then encoded into the image using Action Registration (ActionREG). Additionally, Large Language Model (LLM)-Alignment Policy for Visual Correction (LAP-VC) is employed to ensure precise action registration, facilitating trajectory transfer in novel robot scenarios. Experimental results validate these methods, achieving 94.37% recall in therblig segmentation and success rates of 94.4% and 80% in real-world online robot testing for simple and complex scenarios, respectively.
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Journal articleMeyer J, Picinali L, 2025,
On the generalization of accommodation to head-related transfer functions
, Journal of the Acoustical Society of America, Vol: 157, Pages: 420-432, ISSN: 0001-4966To date, there is strong evidence indicating that humans with normal hearing can adapt to non-individual head-related transfer functions (HRTFs). However, less attention has been given to studying the generalization of this adaptation to untrained conditions. This study investigated how adaptation to one set of HRTFs can generalize to another set of HRTFs. Participants were divided into two groups and trained to localize a speech stimulus reproduced binaurally using either individual or non-individual HRTFs. Training led to an improved localization performance with the trained HRTFs for both groups of participants. Results also showed that there was no difference in the localization performance improvement between the trained and untrained HRTFs for both groups, indicating a generalization of adaptation to HRTFs. The findings did not allow to precisely determine which type of learning (procedural or perceptual) primarily contributed to the generalization, thus highlighting the potential need to expose participants to longer training protocols.
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Journal articleQian Q, Wang Y, Boyle D, 2025,
Adaptive Probabilistic Planning for the Uncertain and Dynamic Orienteering Problem
, IEEE Internet of Things JournalThe Orienteering Problem (OP) is a well-studied routing problem that has been extended to incorporate uncertainties, reflecting stochastic or dynamic travel costs, prize-collection costs, and prizes. Existing approaches may, however, be inefficient in real-world applications due to insufficient modeling knowledge and initially unknowable parameters in online scenarios. Thus, we propose the Uncertain and Dynamic Orienteering Problem (UDOP), modeling travel costs as distributions with unknown and time-variant parameters. UDOP also associates uncertain travel costs with dynamic prizes and prize-collection costs for its objective and budget constraints. To address UDOP, we develop an ADaptive Approach for Probabilistic paThs, ADAPT, iteratively performing 'execution' and 'online planning' based on an initial 'offline' solution. The execution phase updates the system status and records online cost observations. The online planner employs a Bayesian approach to adaptively estimate power consumption and optimize path sequence based on safety beliefs. We evaluate ADAPT in a practical Unmanned Aerial Vehicle (UAV) charging scheduling problem for Wireless Rechargeable Sensor Networks. The UAV must optimize its path to recharge sensor nodes efficiently while managing its energy under uncertain conditions. ADAPT maintains comparable solution quality and computation time while offering superior robustness. Extensive simulations show that ADAPT achieves a 100% Mission Success Rate (MSR) across all tested scenarios, outperforming comparable heuristic-based and frequentist approaches that fail up to 70% (under challenging conditions) and averaging 67% MSR, respectively. This work advances the field of OP with uncertainties, offering a reliable and efficient approach for real-world applications in uncertain and dynamic environments.
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Journal articleSadek M, Kallina E, Bohné T, et al., 2025,
Challenges of responsible AI in practice: scoping review and recommended actions
, AI and Society: the journal of human-centered systems and machine intelligence, Vol: 40, Pages: 199-215, ISSN: 0951-5666Responsible AI (RAI) guidelines aim to ensure that AI systems respect democratic values. While a step in the right direction, they currently fail to impact practice. Our work discusses reasons for this lack of impact and clusters them into five areas: (1) the abstract nature of RAI guidelines, (2) the problem of selecting and reconciling values, (3) the difficulty of operationalising RAI success metrics, (4) the fragmentation of the AI pipeline, and (5) the lack of internal advocacy and accountability. Afterwards, we introduce a number of approaches to RAI from a range of disciplines, exploring their potential as solutions to the identified challenges. We anchor these solutions in practice through concrete examples, bridging the gap between the theoretical considerations of RAI and on-the-ground processes that currently shape how AI systems are built. Our work considers the socio-technical nature of RAI limitations and the resulting necessity of producing socio-technical solutions.
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Journal articleGriggs WM, Ghosh R, Mareček J, et al., 2025,
Unique ergodicity in feedback interconnections of ensembles of agents
, International Journal of Control, ISSN: 0020-7179Recent results on the unique ergodicity of feedback systems, which strive to orchestrate the behaviour of a single ensemble of agents, demonstrate that, under straightforward conditions, convergence in distribution of the feedback loop to a unique invariant measure can be guaranteed. These results were motivated by sharing-economy applications, where one strives to provide guarantees on the allocation of constrained resources under a feedback signal. In this paper, we extend these existing results to the case of larger-scale interconnections containing two or more ensembles of agents. This direction may be construed as an analogue of the classical theory of interconnected dynamical systems under uncertainty of the systems' models. Our key finding is that traditional small-gain-like results do not apply. In the case of linear filters and controllers, interconnections of such ensembles of agents are uniquely ergodic if and only if the controllers and filters are stable.
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Journal articleRostami-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 articleAlbanese A, Wang Y, Brunelli D, et al., 2025,
Is That Rain? Understanding Effects on Visual Odometry Performance for Autonomous UAVs and Efficient DNN-based Rain Classification at the Edge
, IEEE Internet of Things JournalThe development of safe and reliable autonomous unmanned aerial vehicles relies on the ability of the system to recognise and adapt to changes in the local environment based on sensor inputs. State-of-the-art local tracking and trajectory planning are typically performed using camera sensor input to the flight control algorithm, but the extent to which environmental disturbances like rain affect the performance of these systems is largely unknown. In this paper, we first describe the development of an open dataset comprising 335k images to examine these effects for seven different classes of precipitation conditions and show that a worst-case average tracking error of 1.5 m is possible for a state-of-the-art visual odometry system (VINS-Fusion). We then use the dataset to train a set of deep neural network models suited to mobile and constrained deployment scenarios to determine the extent to which it may be possible to efficiently and accurately classify these 'rainy' conditions. The most lightweight of these models (MobileNetV3 small) can achieve an accuracy of 90% with a memory footprint of just 1.28 MB and a frame rate of 93 FPS, which is suitable for deployment in resource-constrained and latency-sensitive systems. We demonstrate a classification latency in the order of milliseconds using typical flight computer hardware. Accordingly, such a model can feed into the disturbance estimation component of an autonomous flight controller. In addition, data from unmanned aerial vehicles with the ability to accurately determine environmental conditions in real time may contribute to developing more granular timely localised weather forecasting.
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