ClassiGAN: Joint Image Reconstruction and Classification in Computational Microwave Imaging

International audienceComputational imaging (CI)-based systems have emerged as a viable alternative to address the challenges of high hardware complexity and slow data acquisition speed associated with conventional microwave imaging. However, CI-based systems are limited by a substantial computational burden during the scene reconstruction process. In particular, image reconstruction and target classification problems for CI systems are computationally complex tasks. To tackle this challenge, a generative deep learning model named ClassiGAN is proposed to jointly solve the image reconstruction and target classification tasks by only using the backscattered measured signals as input. In particular, an adaptive loss function is employed to effectively integrate the respective loss functions for the two tasks, thereby enhancing training efficiency. This adaptive loss function dynamically adjusts the weights of the losses associated with each task, facilitating a more effective integration of the differing loss functions. Notably, ClassiGAN significantly reduces the run time for image reconstruction tasks compared to conventional CI methods. Compared to other state-of-the-art methods, ClassiGAN not only achieves lower average normalized mean squared error (NMSE) and higher structural similarity (SSIM) but also provides a higher accuracy in recognizing imaging targets. Extensive experimental tests further validate ClassiGAN’s capability to simultaneously reconstruct and recognize the imaging target within practical settings. Hence, this shows that ClassiGAN can enhance the overall efficiency of CI-based systems at microwave frequencies by addressing challenges related to computational load during run time

Collision avoidance behaviours in chronic non-specific low back pain participants: A prospective cohort study

International audienceObjective: Chronic non-specific low back pain (cNSLBP) is a leading cause of disability, influenced by bio-psycho-social factors. However, its impact on everyday activities such as navigating streets and interacting with other pedestrians remains underexplored. This study aimed to assess the effect of cNSLBP on perceptual-motor processes in a pedestrian crossing task, focusing on 1) collision avoidance behaviours, 2) the walker's role in avoiding collisions, and 3) the influence of pain perception.Methods: Seventeen asymptomatic adults (AA, 11 females, 46.4 ± 12.8 years) and seventeen cNSLBP participants (10 females, 47.9 ± 12.7 years) performed a task involving crossing paths at a 90° angle with another walker. Participants interacted in three groups pairings: AA-AA, AA-cNSLBP, and cNSLBP-cNSLBP. Key metrics included crossing order inversion, collision risk threshold informing movement adaptation, crossing distance, and the walker's contribution (speed/orientation).Results and discussion: No significant differences were observed between groups for the collision risk threshold (≈0.93 m) or crossing distance (≈0.8 m). However, cNSLBP participants exhibited distinct avoidance strategies, especially in cNSLBP-cNSLBP interactions, which showed more frequent inversions. When crossing first, cNSLBP participants contributed less, whereas when crossing second, they contributed more, primarily by adjusting their speed. A significant negative correlation emerged between depression scores and the level of contribution when cNSLBP participants crossed second.Conclusion: These findings suggest that pain perception may influence collision avoidance behaviours. Further research, potentially incorporating virtual reality, is needed to control environmental factors and deepen our understanding of these interactions

Wearable multi-sensory haptic devices

International audienceHaptic devices enable communication via touch, augmenting visual and auditory displays or offering alternative channels of communication when vision and hearing are unavailable. Because there are numerous types of haptic stimuli that are perceivable by users – vibration, skin stretch, pressure, and temperature, among others – devices can be designed to communicate complex information through the delivery of multiple types of haptic stimuli simultaneously. These multi-sensory haptic devices are often designed to be wearable, and have been developed for use in a wide variety of applications including communication, entertainment, and rehabilitation. Multi-sensory haptic devices present unique challenges to designers, since human perceptual acuity can vary widely, both due to the location on the body where a wearable might be located, and because of normal heterogeneity in human perceptual performance, particularly when multiple cues are presented simultaneously. Additionally, packaging the mechanisms of haptic feedback actuation in a wearable form factor presents its own engineering challenges. By understanding the state of the art and specific obstacles present in the field – challenges of cue masking, device mounting, actuator capabilities, and more – we can guide haptic research to produce multi-sensory devices that enhance the human capacity for haptic interaction and information transmission

Visualization-Driven Illumination for Density Plots

International audienceWe present a novel visualization-driven illumination model for density plots, a new technique to enhance density plots by effectively revealing the detailed structures in high- and medium-density regions and outliers in low-density regions, while avoiding artifacts in the density field's colors.When visualizing large and dense discrete point samples, scatterplots and dot density maps often suffer from overplotting, and density plots are commonly employed to provide aggregated views while revealing underlying structures. Yet, in such density plots, existing illumination models may produce color distortion and hide details in low-density regions, making it challenging to look up density values, compare them, and find outliers.The key novelty in this work includes (i) a visualization-driven illumination model that inherently supports density-plot-specific analysis tasks and (ii) a new image composition technique to reduce the interference between the image shading and the color-encoded density values. To demonstrate the effectiveness of our technique, we conducted a quantitative study, an empirical evaluation of our technique in a controlled study, and two case studies, exploring twelve datasets with up to two million data point samples

Concevoir des Interactions au Stylet pour la Productivité et la Créativité

Designed with the mouse and keyboard in mind, productivity tools and creativity support tools are powerful on desktop computers, but their structure becomes an obstacle when brought to interactive surfaces supporting pen and touch input.Indeed, the opportunities provided by the pen for precision and expressivity have been demonstrated in the HCI literature, but productivity and creativity tools require a careful redesign leveraging these unique affordances to take benefit from the intuitiveness they offer while keeping the advantages of structure. This delicate articulation between pen and structure has been overlooked in the literature.My thesis work focuses on this articulation with two use cases to answer the broad research question: “How to design pen-based interactions for productivity and creativity on interactive surfaces?” I argue that productivity depends on efficiency while creativity depends on both efficiency and flexibility, and explore interactions that promote these two dimensions.My first project, TableInk, explores a set of pen-based interaction techniques designed for spreadsheet programs and contributes guidelines to promote efficiency on interactive surfaces. I first conduct an analysis of commercial spreadsheet programs and an elicitation study to understand what users can do and what they would like to do with spreadsheets on interactive surfaces. Informed by these, I design interaction techniques that leverage the opportunities of the pen to mitigate friction and enable more operations by direct manipulation on and through the grid. I prototype these interaction techniques and conduct a qualitative study with information workers who performed a variety of spreadsheet operations on their own data. The observations show that using the pen to bypass the structure is a promising mean to promote efficiency with a productivity tool.My second project, EuterPen, explores a set of pen-based interaction techniques designed for music notation programs and contributes guidelines to promote both efficiency and flexibility on interactive surfaces. I first conduct a series of nine interviews with professional composers in order to take a step back and understand both their thought process and their work process with their current desktop tools. Building on this dual analysis, I derive guidelines for the design of features which have the potential to promote both efficiency with frequent or complex operations and flexibility in regard to the exploration of ideas. Then, I act on these guidelines by engaging in an iterative design process for interaction techniques that leverage the opportunities of the pen: two prototyping phases, a participatory design workshop, and a final series of interviews with eight professional composers. The observations show that on top of using the pen to leverage the structure for efficiency, using its properties to temporarily break the structure is a promising mean to promote flexibility with a creativity support tool.I conclude this manuscript by discussing several ways to interact with structure, presenting a set of guidelines to support the design of pen-based interactions for productivity and creativity tools, and elaborating on the future applications this thesis opens.Conçus pour une utilisation avec la souris et le clavier, les outils aidant à la productivité et à la créativité sont puissants sur les ordinateurs de bureau, mais leur structure devient un obstacle lorsqu'ils sont transposés sur des surfaces interactives offrant une saisie tactile et au stylet.En effet, les opportunités offertes par le stylet en termes de précision et d'expressivité ont été démontrées dans la littérature sur en IHM. Cependant, les outils de productivité et de créativité nécessitent une refonte minutieuse exploitant ces propriétés uniques pour tirer parti de l'intuitivité qu'ils offrent, tout en conservant les avantages liés à la structure. Cette articulation délicate entre le stylet et la structure a été négligée dans la littérature.Mon travail de thèse se concentre sur cette articulation à travers deux cas d'utilisation afin de répondre à la question de recherche générale : « Comment concevoir des interactions basées sur le stylet pour la productivité et la créativité sur des surfaces interactives ? » Je considère que la productivité dépend de l'efficacité, tandis que la créativité repose à la fois sur l'efficacité et la flexibilité, et j'explore des interactions qui favorisent ces deux dimensions.Mon premier projet, TableInk, explore un ensemble de techniques d'interaction basées sur le stylet et conçues pour les logiciels de tableurs, et propose des lignes directrices pour promouvoir l'efficacité sur les surfaces interactives. Je commence par analyser les logiciels commerciaux et par mener une étude d'élicitation pour comprendre ce que les utilisateurs peuvent faire et ce qu'ils aimeraient faire avec les tableurs sur des surfaces interactives. Sur la base de ces analyses, je conçois des techniques d'interaction qui exploitent les opportunités offertes par le stylet pour réduire les frictions et permettre plus d'opérations par manipulation directe sur et à travers la grille. Je prototype ces techniques d'interaction et mène une étude qualitative auprès d'utilisateurs qui effectuent diverses opérations sur tableurs avec leurs propres données. Les observations montrent que l'utilisation du stylet pour contourner la structure constitue un moyen prometteur de favoriser l'efficacité dans un outil de productivité.Mon deuxième projet, EuterPen, explore un ensemble de techniques d'interaction basées sur le stylet, et conçues pour les logiciels de notation musicale, et propose des lignes directrices pour promouvoir à la fois l'efficacité et la flexibilité sur les surfaces interactives. Je commence par une série de neuf entretiens avec des compositeurs professionnels afin de prendre du recul et de comprendre à la fois leur processus de réflexion et leur processus de travail avec leurs outils actuels sur ordinateur de bureau. Sur la base de cette analyse double, j'élabore des lignes directrices pour la conception de fonctionnalités ayant le potentiel de promouvoir à la fois l'efficacité pour les opérations fréquentes ou complexes et la flexibilité dans l'exploration des idées. Ensuite, je mets en œuvre ces lignes directrices à travers un processus de conception itératif : deux phases de prototypage, un atelier de conception participative et une série finale d'entretiens avec huit compositeurs professionnels. Les observations montrent qu'en plus d'utiliser le stylet pour profiter de la structure afin de favoriser l'efficacité, tirer parti de ses propriétés pour briser temporairement la structure constitue un moyen prometteur de promouvoir la flexibilité dans un outil de soutien à la créativité.Je conclus ce manuscrit en discutant de différentes manières d'interagir avec la structure, en présentant un ensemble de recommandations pour soutenir la conception d'interactions basées sur le stylet pour les outils de productivité et de créativité, et en élaborant sur les applications futures que cette thèse ouvre

Libra: An Interaction Model for Data Visualization

Honorable Mention AwardInternational audienceWhile existing visualization libraries enable the reuse, extension, and combination of static visualizations, achieving the same for interactions remains nearly impossible. Therefore, we contribute an interaction model and its implementation to achieve this goal. Our model enables the creation of interactions that support direct manipulation, enforce software modularity by clearly separating visualizations from interactions, and ensure compatibility with existing visualization systems. Interaction management is achieved through an instrument that receives events from the view, dispatches these events to graphical layers containing objects, and then triggers actions. We present a JavaScript prototype implementation of our model called Libra.js, enabling the specification of interactions for visualizations created by different libraries. We demonstrate the effectiveness of Libra by describing and generating a wide range of existing interaction techniques. We evaluate Libra.js through diverse examples, a metric-based notation comparison, and a performance benchmark analysis

Metamodeling elastic wave propagation using a mixed factorized Fourier encoder–decoder for online laser-ultrasound testing in additive manufacturing

International audienceLaser-ultrasound (LU) testing has emerged as a promising technique for characterizing the polycrystalline microstructure of metal components produced by wire-laser additive manufacturing (WLAM), with potential for real-time online application. Numerical models simulating elastic waves propagation provide valuable insights into the relationship between microstructural properties and laser-induced displacements, but their computational cost renders them impractical for automated high-throughput characterization. To overcome this limitation, we build a metamodel that maps a wide variety of two-dimensional anisotropic polycrystalline microstructures — simplified but representative of features commonly observed in WLAM — to simulated surface displacements. Addressing this challenging high-dimensional regression problem, several neural network surrogates relying on a novel combination of layers are investigated. Their architectures include usual convolutional encoder–decoder elements and spectral layers inspired from the Fourier neural operator (FNO) framework. These layers are adapted and some variants are proposed to provide versatility in network design. All metamodels can run both a forward and backward pass at least 100 times faster than a single forward call of the original model. The best architecture implies a trade-off between computational cost and accuracy. Notably, the architecture involving the channel-wise factorized variant of the spectral layers, which is characterized by a relatively small number of parameters, achieved the lowest approximation error. The metamodel successfully captures the primary effects of anisotropy on wave propagation, even for low-anisotropy inputs not included in the training data. These findings represent a promising initial step towards addressing inversion problems and facilitating the development of online LU testing protocols in additive manufacturing

Capteurs sans batterie ou le mythe de l’autonomie infinie: Comment la variabilité et le vieillissement des composants impacte l’exécution de programmes ?

International audienceLes capteurs sans batterie, alimentés en puisant l'énergie présente dans l'environnement, promettent un fonctionnement autonome sans intervention humaine pendant de longues périodes. Limiter les distances parcourues pour les opérations de maintenance est un moyen de limiter l'impact environnemental des réseaux de capteurs, particulièrement significatif lorsqu'ils sont déployés dans des environnements difficiles d'accès.Cette promesse d'autonomie accrue reste cependant à démontrer. L'une des questions ouverte est l'impact des variations des caractéristiques des composants du capteurs sur la qualité de service . Ces variations sont causées par les conditions opératoires (température, humidité) mais aussi par le vieillissement naturel des matériaux. Nous nous intéressons ici au cas des (super)condensateurs utilisés comme tampon d'énergie

Efficient interaction-based offline runtime verification of distributed systems with lifeline removal

International audienceRuntime Verification (RV) refers to a family of techniques in which system executions are observed and confronted to formal specifications, with the aim of identifying faults. In offline RV, observation and verification are done in two separate and successive steps. In this paper, we define an approach to offline RV of Distributed Systems (DS) against interactions. Interactions are formal models describing communications within a DS. A DS is composed of subsystems deployed on different machines and interacting via message passing to achieve common goals. Therefore, observing executions of a DS entails logging a collection of local execution traces, one for each subsystem, collected on its host machine. We call multi-trace such observational artifacts. A major challenge in analyzing multi-traces is that there are no practical means to synchronize the ends of observations of all the local traces. We address this via an operation called lifeline removal, which we apply on-the-fly to the specification during the verification of a multi-trace once a local trace has been entirely analyzed. This operation removes from the interaction the specification of actions occurring on the subsystem that is no longer observed. This may allow further execution of the specification by removing potential deadlock. We prove the correctness of the resulting RV algorithm and introduce two optimization techniques, which we also prove correct. We implement a Partial Order Reduction (POR) technique by selecting a one-unambiguous action (as a unique first step to a linearization) whose existence is determined via the lifeline removal operator. Additionally, Local Analyses (LOC), i.e., the verification of local traces, can be leveraged during the global multi-trace analysis to prove failure more quickly. Experiments illustrate the application of our RV approach and the benefits of our optimizations

Scalable Structural Similarity Analysis of JSON documents Using MapReduce

International audienceThe increasing prevalence of JSON documents as a standard format for data storage and exchange in diverse applications has led to the need for efficient methods to compare and analyze hierarchical data structures. Traditional comparison methods often struggle with scalability and fail to account for structural variations in complex data formats. These limitations become particularly problematic in applications such as duplicate detection, anomaly analysis, and data integration, where accurate and scalable comparison of large JSON datasets is essential.To address these challenges, this paper presents a scalable framework for comparing JSON documents using the Aho-Hopcroft-Ullman (AHU) algorithm and the MapReduce paradigm. By generating canonical labels for hierarchical structures, the AHU algorithm captures structural similarities between JSON trees. The framework employs structural similarity measures, such as Longest Common Substring (LCS) and Levenshtein Distance, to quantify resemblance. MapReduce enables efficient processing of large JSON datasets, with a mapping phase for parsing and labeling and a reducing phase for similarity computations. This approach offers a robust and scalable solution for hierarchical data comparison, facilitating critical applications in duplicate detection and anomaly analysis.Index terms JSON comparison, AHU algorithm, structural similarity, MapReduce, hierarchical data, Levenshtein distance, LCS.</div