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  • Journal article
    Kharman AM, Ferraro P, Hamedmoghadam H, Shorten Ret al., 2025,

    Tree Proof-of-Position algorithms

    , IEEE Internet of Things Journal, Pages: 1-1, ISSN: 2327-4662

    A 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.
  • Conference paper
    Wang P, Zhang X, Zhou Z, Childs P, Lee K, Kleinsmann M, Wang SJet al., 2025,

    Typeface generation through style descriptions with generative models

    , 19th International Conference on Virtual-Reality Continuum and its Applications in Industry, Publisher: Association for Computing Machinery, Pages: 1-12

    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
  • 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
    Chappell D, Mulvey B, Perera S, Bello F, Kormushev P, Rojas Net al., 2025,

    Beyond humanoid prosthetic hands: modular terminal devices that improve user performance

    , IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 33, Pages: 466-475, ISSN: 1534-4320

    Despite 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.
  • Journal article
    Greif T, Barumerli R, Ignatiadis K, Tóth B, Baumgartner Ret al., 2025,

    The role of spatial perception in auditory looming bias: neurobehavioral evidence from impossible ears

    , Frontiers in Neuroscience, Vol: 19, ISSN: 1662-4548

    Introduction: Spatial hearing enables both voluntary localization of sound sources and automatic monitoring of the surroundings. The auditory looming bias (ALB), characterized by the prioritized processing of approaching (looming) sounds over receding ones, is thought to serve as an early hazard detection mechanism. The bias could theoretically reflect an adaptation to the low-level acoustic properties of approaching sounds, or alternatively necessitate the sound to be localizable in space. Methods: To investigate whether ALB reflects spatial perceptual decisions or mere acoustic changes, we simulated ears that disrupted spectrospatial associations on the perceptual level while maintaining the original spectrospatial entropy on the acoustic level. We then assessed sound localization, ALB and distance ratings. Results: Compared to native ears, these novel ears impaired sound localization in both the direction and ego-centric distance dimensions. ALB manifestation also differed significantly between native and novel ears, as evidenced by behavioral discrimination performance and early cortical activity (N1 latency). Notably, the N1 electroencephalographic response closely resembled distance ratings, suggesting a strong link between spatial perception and ALB-related neural processing. Integrating this neural marker into a hierarchical perceptual decision-making model improved explanatory power, underscoring its behavioral relevance. Discussion: These findings suggest a strong link between the localizability of sounds and their ability to elicit ALB.
  • Conference paper
    Hu X, Li J, Picinali L, Hogg AOTet al., 2025,

    A Machine Learning Approach for Denoising and Upsampling HRTFs

    , Pages: 201-205, ISSN: 2219-5491

    The demand for realistic virtual immersive audio continues to grow, with Head-Related Transfer Functions (HRTFs) playing a key role. HRTFs capture how sound reaches our ears, reflecting unique anatomical features and enhancing spatial perception. It has been shown that personalized HRTFs improve localization accuracy, but their measurement remains time-consuming and requires a noise-free environment. Although machine learning has been shown to reduce the required measurement points and, thus, the measurement time, a controlled environment is still necessary. This paper proposes a method to address this constraint by presenting a novel technique that can upsample sparse, noisy HRTF measurements. The proposed approach combines an HRTF Denoisy U-Net for denoising and an Autoencoding Generative Adversarial Network (AE-GAN) for upsampling from three measurement points. The proposed method achieves a log-spectral distortion (LSD) error of 5.41 dB and a cosine similarity loss of 0.0070, demonstrating the method’s effectiveness in HRTF upsampling.
  • Conference paper
    Wirler S, Meyer-Kahlen N, Pulkki V, 2025,

    Synthesizing a Virtual Height Channel from Planar Microphone Arrays

    , Pages: 96-100, ISSN: 2219-5491

    In spatial audio processing, the ability to capture sound scenes in three dimensions is important for applying algorithms such as beamforming and direction-of-arrival (DoA) estimation. Conventional microphone arrays require at least four microphones that are not on the same plane to achieve three-dimensional processing. This work presents a method for synthesizing a virtual height channel from planar microphone arrays that could, for example, be placed on a flat surface such as a table, enabling full 3D Ambisonic processing without requiring physically elevated microphones. The approach relies on transforming array signals into the spherical harmonics (SH) domain, where only the W, X, and Y components are available for a planar array. The missing Z-component is synthesized using spectral subtraction, assuming that sources only originate from the upper half-space. The basic method strictly requires time-frequency sparsity; here, we also present an improved version incorporating diffuseness estimation to enhance robustness in reverberant environments. Evaluation results demonstrate the effectiveness of the synthesized height channel for DoA estimation and beamforming in simulated conditions, achieving comparable performance to recordings with a true height channel. This technique enables practical implementations of 3D sound field analysis with simpler, more flexible microphone configurations.
  • Conference paper
    Meyer-Kahlen N, Deppisch T, 2025,

    Direct-to-Reverberant Energy Ratio Estimation and Extrapolation from Own Speech

    , Pages: 321-325, ISSN: 2219-5491

    Accurately characterizing a user’s acoustic environment is essential for creating virtual sound sources in augmented reality that blend seamlessly into the real environment. The acoustic parameters of an environment can be calculated from a room impulse response (RIR) and the authors recently presented a method to blindly estimate RIRs from speech signals captured with a head-worn microphone array. The approach uses either speech from a distant speaker or own speech from the person wearing the array on their head. While both variants provide reliable reverberation time estimates, direct-to-reverberant energy ratio (DRR) estimates from the user’s own speech deviate significantly from the expected DRR of a distant virtual source due to the higher direct sound level. This study investigates the feasibility of extrapolating DRR values from own speech to predict DRRs of distant sources. The approach relies on two acoustic assumptions: (i), the mouth-to-array transfer paths do not change significantly between users and, (ii), a homogeneous reverberant field. Our findings show that the assumptions hold above the Schröder frequency and in sufficiently reverberant conditions. Average DRR extrapolation errors are below 2 dB at mid frequencies when using mouth simulator measurements and around 3 dB with actual speech recordings.
  • Conference paper
    Shakib F, Scarciotti G, Astolfi A, 2025,

    Physics-based and data-driven modeling for linear systems using moment matching

    , Pages: 3207-3212

    First-principle models often fail to accurately capture system dynamics due to modeling simplifications and parameter uncertainties. This article introduces a data-driven technique for linear systems, enhancing baseline first-principle state-space models with black-box models obtained from experimental steady-state data. The proposed method parameterises models that achieve moment matching by integrating a known baseline model with a black-box component. Tools are provided to enforce a known interconnection structure or other physical knowledge. A mass-spring-damper system demonstrates the effectiveness of the technique.
  • Conference paper
    Ballaben R, Astolfi A, Braun P, Zaccarian Let al., 2025,

    Towards global stabilization of a hovercraft model using hybrid systems and discontinuous feedback laws

    , Pages: 6579-6584, ISSN: 0743-1546

    In this paper we propose discontinuous control laws to globally stabilize a target position for a hovercraft. Equations of motion of the hovercraft are derived through a kinematic model approximation of a dynamic model taken from the literature. Discontinuous feedback laws for the kinematic and the dynamic model are derived and analyzed using a hybrid systems formulation of the closed-loop dynamics. Numerical simulations confirm the theoretical results and validate the kinematic model as a accurate simplification of the dynamic model.
  • Conference paper
    Safarika E, Astolfi A, 2025,

    Sparse control of linear continuous-time systems: A geometric approach

    , Pages: 5074-5079, ISSN: 0743-1546

    This paper provides a solution to the sparse control problem for linear two-input systems. This is achieved by developing a canonical form for sparse control and exploiting the theory of switched systems to design a sparse feedback law achieving asymptotic stability of the zero equilibrium of the closed-loop system. The results are illustrated through a simple case study.
  • Conference paper
    Sassano M, Astolfi A, 2025,

    Quasi-linear partial differential equations for the optimal control of nonlinear systems over an infinite horizon

    , Pages: 936-941, ISSN: 0743-1546

    The infinite-horizon optimal control problem is studied in the linear setting with the objective of revisiting the role of the underlying Algebraic Riccati Equation. It is shown that this may be interpreted in terms of a triangularizing change of coordinates for the Hamiltonian dynamics associated to the optimal control problem. Such a perspective leads to a few implications, including the observation that duality between the Riccati equations arising in various contexts is simply related to a choice of coordinates for the Hamiltonian dynamics. Similar arguments are then extended to the nonlinear setting. It is shown that, by relying on such alternative view point, the computational complexity associated to the solution of nonlinear optimal control problems over an infinite horizon tantamounts to the solution of an Algebraic Riccati Equation, for the linearized problem, and a quasi-linear partial differential equation.
  • Conference paper
    Bhattacharjee D, Moreschini A, Astolfi A, 2025,

    Enforcing input-output behavior in data-driven moment matching

    , Pages: 5806-5811, ISSN: 0743-1546

    While approximating dynamical systems, one may be interested in preserving physical insights of specific states of the underlying system, which can be achieved by fixing the output map of the model to be estimated. In this paper we derive a class of reduced-order models that achieve moment matching while enforcing an output map chosen by the designer. We show that such models can be constructed even without the knowledge of the underlying system by using data generated from experiments. In doing so, we highlight how the proposed method can be utilized to enforce input-output behavior, such as passivity and/or negative imaginary behavior in the reduced-order model, thus providing provable guarantees on various user-specified requirements. We demonstrate this aspect through several examples.
  • Conference paper
    Grimaldi RA, Astolfi A, 2025,

    Further results on exact penalization for linear quadratic optimal control problems

    , Pages: 3754-3760, ISSN: 0743-1546

    A systematic procedure for solving general linear quadratic optimal control problems with linear equality constraints is presented. We exploit the theory of exact penalization, in the spirit of [1], to transform a general linear quadratic problem with a set of linear equality constraints on the state into an equivalent penalized unconstrained problem. Both the finite and the infinite horizon cases are discussed, and the results are given under minimal feasibility assumptions on the constrained problem, which are expressed in a coordinate free form. Two simple examples illustrate the theory.
  • Conference paper
    Dvorkin V, Fioretto F, Van Hentenryck P, Pinson P, Kazempour Jet al., 2025,

    Privacy-Preserving Convex Optimization: When Differential Privacy Meets Stochastic Programming

    , Pages: 8149-8156, ISSN: 0743-1546

    Convex optimization finds many applications where optimization results may expose private data (e.g., health records, commercial information). To guarantee privacy to optimization data owners, we develop a new privacy-preserving perturbation strategy for convex optimization programs by combining stochastic (chance-constrained) programming and differential privacy. Unlike standard noise-additive strategies, which perturb either optimization data or result, we formulate optimization variables as functions of a random perturbation using linear decision rules; we then optimize these rules to accommodate the perturbation within the feasible region using chance constraints. The perturbation becomes feasible and makes adjacent - in the sense of some distance function - optimization datasets statistically similar in randomized optimization results, thereby enabling privacy guarantees.
  • Journal article
    Bowes A, Jagannath S, Njoki M, Pemble C, Quirke M, Davison L, Dawson Aet al., 2025,

    Scaling home designs for healthy cognitive ageing: a realist evaluation perspective

    , Social Sciences and Humanities Open, Vol: 12

    We present an empirically grounded theory of change (ToC) to support delivery at scale of home design for healthy cognitive ageing. Using a realist evaluation lens, we analyse how contexts, mechanisms, and outcomes (CMO) identified in the ‘Designing homes for healthy cognitive ageing’ (DesHCA) research shape scalability. Design principles and features were co-produced with older adults and housing professionals through VR-supported workshops, and in parallel a modified e-Delphi that prioritised outcomes for people and providers. The e-Delphi converged on five cross-cutting outcomes – independence, physical activity, enjoyment, safety, and adaptability – and highlighted system enablers (legislation/regulation, industry and public awareness) and the centrality of ‘value for money’. Workshop CMOs indicated that small, low-cost changes (e.g. contrast, lighting, storage, switch/socket placement) are implementable within existing standards; that flexibility in layouts is critical for diverse and changing needs; and that meaningful engagement between providers and occupants improves adoption. We synthesise these insights into a ToC specifying activities (knowledge, products, procurement levers, curriculum/CPD, local standards), assumptions, and short- and medium-term outcomes that culminate in scaled delivery through both new-build and retrofit. We discuss strengths and limits of the approach and its transferability. The ToC is now guiding an implementation programme in Central Scotland, with early signals of feasibility through cross-sector partnerships and professional demand for practical guidance.
  • Journal article
    Shafique S, Zanchi S, Setti W, Gori M, Picinali Let al., 2025,

    Does spatialized audio enhance the creation of mental representations?

    , Frontiers in Neuroscience, Vol: 19, ISSN: 1662-4548

    Navigating unfamiliar environments without vision is a considerable challenge for blind individuals, as it requires constructing accurate cognitive maps. Binaural audio feedback, which delivers spatialized auditory cues, has been proposed as a means of enhancing spatial navigation by leveraging the auditory system's natural ability to localize sounds in three dimensions. This study investigated whether binaural audio feedback offers measurable advantages over non-spatialized feedback in supporting spatial perception and mental representation. Fourteen participants, seven blind individuals and seven blindfolded sighted individuals, explored controlled environments under both feedback conditions and reconstructed the layouts using LEGO models. Performance was evaluated through spatial correlation analysis and distance accuracy measures. Results revealed no significant differences between binaural and non-spatialized conditions for either group. These findings indicate that spatialization of descriptive audio alone may not be sufficient to enhance spatial representations, suggesting that factors such as prior training, task design, and integration with other sensory cues may be critical for unlocking the full potential of binaural audio in assistive navigation.
  • Conference paper
    Riesco IR, Lampret B, Myant C, Boyle Det al., 2025,

    5-axis Multi-material Desktop Additive Manufacturing of Conformal Antennas

    This paper describes the novel use of low-cost, 5-axis, multi-material additive manufacturing to fabricate functional, complex conformal antennas. Using a customised open source 5-axis desktop printer incorporating conductive filaments, conformal S-band patch and Ultra-Wide Band antennas were fabricated and compared against planar-printed counterparts and electromagnetic simulations. Results show the potential of the approach for superior impedance matching, reduced fabrication time, and cost savings; highlighting the applicability of multi-axis multi-material prototyping of antennas with complex geometries.
  • Conference paper
    Cui L, Yu H, Pinson P, Paccagnan Det al., 2025,

    Inverse Game Theory: An Incenter-Based Approach

    , Pages: 3805-3813, ISSN: 1045-0823

    Estimating player utilities from observed equilibria is crucial for many applications. Existing approaches to tackle this problem are either limited to specific games or do not scale well with the number of players. Our work addresses these issues by proposing a novel utility estimation method for general multi-player non-cooperative games. Our main idea consists in reformulating the inverse game problem as an inverse variational inequality problem and in selecting among all utility parameters consistent with the data, the so-called incenter. We show that the choice of the incenter can produce parameters that are most robust to the observed equilibrium behaviors. However, its computation is challenging, as the number of constraints in the corresponding optimization problem increases with the number of players and the behavior space size. To tackle this challenge, we propose a loss function-based algorithm, making our method scalable to games with many players or a continuous action space. Furthermore, we show that our method can be extended to incorporate prior knowledge of player utilities, and that it can handle inconsistent data, i.e., data where players do not play exact equilibria. Numerical experiments on three game applications demonstrate that our methods outperform the state of the art. The code, datasets, and supplementary material are available at https://github.com/cuilvye/Incenter-Project.
  • Conference paper
    De Neufville R, Cardin MA, 2025,

    Climate adaption pathways for sea-level rise: case studies from Boston and the Netherlands

    , Pages: 61-68

    Climate change rise is having unprecedented impacts on the performance of our infrastructure for protection against sea level rise. This paper reports on the special aspects of designing for the adaptation to this challenge. Two case studies stress an essential aspect of this problem: it is not meaningful to define a specific requirement, or mission, for the design of any sea wall. Should it serve for until 2040, or 2045, or 2050 say? And then be adapted to for some future? If this is so, how do we plan for the adaptation? The case studies highlight the need to define plausible phasing and sequences of growth pathways, the range of uncertain evolutions of sea level rise, and their impact on the consequent choices of what to do when. Back figuring from these solutions, it becomes clear that we can improve overall performance by focusing on intermediate designs that we can adapt easily. Further improvement is possible if we invest in creating adaptability into original design. This observation blurs the distinction between adaptation and flexibility. The overall take-away is that flexibility and adaptability can be viewed as complementary in system design and management.
  • Conference paper
    Soligo A, Ferraro P, Boyle D, 2025,

    Inducing, Detecting and Characterising Neural Modules: A Pipeline for Functional Interpretability in Reinforcement Learning

    , Pages: 56122-56147

    Interpretability is crucial for ensuring RL systems align with human values. However, it remains challenging to achieve in complex decision making domains. Existing methods frequently attempt interpretability at the level of fundamental model units, such as neurons or decision nodes: an approach which scales poorly to large models. Here, we instead propose an approach to interpretability at the level of functional modularity. We show how encouraging sparsity and locality in network weights leads to the emergence of functional modules in RL policy networks. To detect these modules, we develop an extended Louvain algorithm which uses a novel ‘correlation alignment’ metric to overcome the limitations of standard network analysis techniques when applied to neural network architectures. Applying these methods to 2D and 3D MiniGrid environments reveals the consistent emergence of distinct navigational modules for different axes, and we further demonstrate how these functions can be validated through direct interventions on network weights prior to inference.
  • Journal article
    Corcuera-Marruffo A, Meyer-Kahlen N, Lokki T, 2025,

    Audibility of reduced spatial resolution in musical instrument directivity

    , Acta Acustica, Vol: 9

    The directivity of sound sources plays an important role in the generation of auralizations. Researchers have invested a considerable amount of time and effort in generating directivity databases of musical instruments with high levels of detail. However, it is still unclear how precisely these data should be captured and modeled with respect to perception. Therefore, investigating if simplified patterns with lower spatial resolutions are perceptibly different from higher-resolution patterns provides valuable insights into determining the spatial resolution required for perceptually significant measurement and modeling of directivity patterns. In this study, we present a listening test that investigates the spatial resolution of the magnitude of directivity patterns using different spherical harmonic orders of two musical instruments (a trumpet and a ute) in two listener positions and rooms. Apart from changing the resolution for the entire simulation, we also tested hybrid responses for one of the rooms, where the order was modified only for the direct sound or the early reections.
  • Conference paper
    Lluís F, Meyer-Kahlen N, 2025,

    Blind Spatial Impulse Response Generation from Separate Room- and Scene-Specific Information

    , ISSN: 1520-6149

    For audio in augmented reality (AR), knowledge of the users’ real acoustic environment is crucial for rendering virtual sounds that seamlessly blend into the environment. As acoustic measurements are usually not feasible in practical AR applications, information about the room needs to be inferred from available sound sources. Then, additional sound sources can be rendered with the same room acoustic qualities. Crucially, these are placed at different positions than the sources available for estimation. Here, we propose to use an encoder network trained using a contrastive loss that maps input sounds to a low-dimensional feature space representing only room-specific information. Then, a diffusion-based spatial room impulse response generator is trained to take the latent space and generate a new response, given a new source-receiver position. We show how both room- and position-specific parameters are considered in the final output.
  • Journal article
    Zou Y, Childs P, Li Y, Mi P, Teng F, Garvey B, Dieckmann E, Duan H, Zhao Cet al., 2025,

    Society Optioneering: designing societal alternatives through morphological analysis

    , Landscape Architecture Frontiers, Vol: 13, Pages: 128-141, ISSN: 2096-336X

    In urban planning, landscape and architecture design, designers and planners often confront intricate and multidimensional societal issues. To effectively address these challenges, this paper introduces a Morphological Analysis (MA) approach that systematically explores and aids generation of a variety of societal design solutions. MA involves constructing a matrix of subsystems and the corresponding options. It integrates both quantitative and qualitative factors and allows designers to explore concepts and to clarify the certainties or uncertainties of a problem at an early stage of the design process through arising evaluation. This paper further integrates MA with artificial intelligence generated content (AIGC) to rapidly generate and evaluate design proposals, thereby enhancing the innovation and practicality of the design process. The proposed Society Optioneering framework improves the scientific and adaptability of solutions and fosters interdisciplinary collaboration. This integration enables designers to explore problems from multiple perspectives, discover a broader array of solutions, and evaluate them effectively using systematic tools. Thus it can maintain flexibility and adaptability throughout the design process, continually optimizing and adjusting the design strategy. This study enriches design theory and provides practical tools and guidance for related fields.
  • Journal article
    Watanabe T, Li J, Nakagami G, Dai M, Miura Y, Torii M, Nanayakkara T, Hirai Set al., 2025,

    Special issue on nursing robotics (Part II)

    , Advanced Robotics, Vol: 39, ISSN: 0169-1864
  • Book chapter
    Astolfi A, Scarciotti G, 2025,

    System Structure, Controllability and Observability

    , Encyclopedia of Systems and Control Engineering, Pages: V1-34

    The study of linear control systems in the state-space approach relies on the characterization of the input-to-state and state-to-output interactions. These are described via the so-called structural properties, which allow describing to what extent the internal state of the system can be manipulated by the selection of the input signal, and to what extent the internal state of the system can be learned from measurements of the output signal.
  • Book chapter
    Scarciotti G, Astolfi A, 2025,

    Model Reduction For Nonlinear Systems

    , Encyclopedia of Systems and Control Engineering, Pages: V1-647

    This article addresses the problem of model order reduction for nonlinear systems. Among the many possible approaches that can be described, we select nonlinear moment matching and nonlinear balancing because of their close relation with control theoretic concepts. We first reinterpret linear methods from a nonlinear perspective, then show how nonlinear methods naturally evolve as extensions of the linear results.
  • Conference paper
    Fagerström J, Meyer-Kahlen N, Schlecht SJ, Välimäki Vet al., 2025,

    PERCEPTUAL DECORRELATOR BASED ON RESONATORS

    , Pages: 214-221, ISSN: 2413-6700

    Decorrelation filters transform mono audio into multiple decorrelated copies. This paper introduces a novel decorrelation filter design based on a resonator bank, which produces a sum of over a thousand exponentially decaying sinusoids. A headphone listening test was used to identify the minimum inter-channel time delays that perceptually match ERB-filtered coherent noise to corresponding incoherent noise. The decay rate of each resonator is set based on a group delay profile determined by the listening test results at its corresponding frequency. Furthermore, the delays from the test are used to refine frequency-dependent windowing in coherence estimation, which we argue represents the perceptually most accurate way of assessing interaural coherence. This coherence measure then guides an optimization process that adjusts the initial phases of the sinusoids to minimize the coherence between two instances of the resonator-based decorrelator. The delay results establish the necessary group delay per ERB for effective decorrelation, revealing higher-than-expected values, particularly at higher frequencies. For comparison, the optimization is also performed using two previously proposed group-delay profiles: one based on the period of the ERB band center frequency and another based on the maximum group-delay limit before introducing smearing. The results indicate that the perceptually informed profile achieves equal decorrelation to the latter profile while smearing less at high frequencies. Overall, optimizing the phase response of the proposed decorrelator yields significantly lower coherence compared to using a random phase.
  • Journal article
    Chen L, Song Y, Guo J, Sun L, Childs P, Yin Yet al., 2025,

    How generative AI supports human in conceptual design

    , Design Science, Vol: 11, ISSN: 2053-4701

    Generative Artificial Intelligence (Generative AI) is a collection of AI technologies that can generate new information such as texts and images. With its strong capabilities, Generative AI has been actively studied in creative design processes. However, limited studies have explored the roles of humans and Generative AI in conceptual design processes, which leaves a gap for human–AI collaboration investigation. To address this gap, this study attempts to uncover the contributions of different Generative AI technologies in assisting humans in the conceptual design process. Novice designers were recruited to complete two design tasks in the condition of with or without the assistance of Generative AI. The results revealed that Generative AI primarily assists humans in the problem definition and idea generation stages, while the idea selection and evaluation stage remains predominantly human-led. Additionally, with the assistance of Generative AI, the idea selection and evaluation stages were further enhanced. Based on the findings, we discussed the role of Generative AI in human–AI collaboration and the implications for enhancing future conceptual design support with Generative AI’s assistance.
  • Book chapter
    Buchanan J, Allais S, Anderson M, Calvo RA, Peter S, Pietsch Tet al., 2025,

    The futures of work: what education can and can't do

    , Handbook on Education and the Labour Market, Pages: 141-164

    It is commonly asserted that education is crucial for meeting the challenges concerning the futures of work. But education cannot overcome deficient economic policies causing declining job quality, mass unemployment and rising under-employment. Instead of pre-occupation with so-called 21st-century skills and micro-credentials, greater recognition needs to be given to what education does best. That is, helping people master bodies of conceptual knowledge as well as relationships between bodies of knowledge, nurturing learning dispositions and equipping people with skills and capacities that support disciplined creativity and adaptive capacity. These qualities enable people to handle the challenges of climate change, changing life courses, artificial intelligence and data-ification. Education can also support new configurations of expertise made possible by new technologies. While education cannot solve most problems concerning the futures of work, there can be no solution to these problems without quality, enduring institutions supporting education and occupational coherence in the labour market.

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