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Finding meaningful paths in heterogeneous graphs with PathWays
International audienceGraphs, and notably RDF graphs, are a prominent way of sharing data. As data usage democratizes, users need help figuring out the useful content of a graph dataset. In particular, journalists with whom we collaborate are interested in identifying, in a graph, the connections between entities, e.g., people, organizations, emails, etc. We present a novel method for exploring data graphs through their data paths connecting Named Entities (NEs, in short); each data path leads to a tabular-looking set of results. NEs are extracted from the data through dedicated Information Extraction modules. Our method builds upon the pre-existing ConnectionLens platform and follow-up work in the Abstra project, which builds simple, visual ER-style summaries of semi-structured data. The contribution of the present work, and its novelty, is twofold. First, we propose a novel analysis of entity-to-entity paths contained in datasets of any nature, and propose a new method for ranking paths, leveraging a novel Information Extraction (IE) module we built on top of ChatGPT. Second, we present an efficient approach to enumerate and compute NE paths, based on an algorithm which automatically recommends sub-paths to materialize, and rewrites the path queries using these subpaths. Our experiments demonstrate the interest of NE paths and the efficiency of our method for computing and ranking them
A numerical study of vortex nucleation in 2D rotating Bose-Einstein condensates
International audienceThis article introduces a new numerical method for the minimization under constraints of a discrete energy modeling multicomponents rotating Bose-Einstein condensates in the regime of strong confinement and with rotation. Moreover, we consider both segregation and coexistence regimes between the components. The method includes a discretization of a continuous energy in space dimension 2 and a gradient algorithm with adaptive time step and projection for the minimization. It is well known that, depending on the regime, the minimizers may display different structures, sometimes with vorticity (from singly quantized vortices, to vortex sheets and giant holes). In order to study numerically the structures of the minimizers, we introduce in this paper a numerical algorithm for the computation of the indices of the vortices, as well as an algorithm for the computation of the indices of vortex sheets. Several computations are carried out, to illustrate the efficiency of the method, to cover different physical cases, to validate recent theoretical results as well as to support conjectures. Moreover, we compare this method with an alternative method from the literature
Self-Defense: Optimal QIF Solutions and Application to Website Fingerprinting
International audienceQuantitative Information Flow (QIF) provides a robust information-theoretical framework for designing secure systems with minimal information leakage. While previous research has addressed the design of such systems under hard constraints (e.g. application limitations) and soft constraints (e.g. utility), scenarios often arise where the core system's behavior is considered fixed. In such cases, the challenge is to design a new component for the existing system that minimizes leakage without altering the original system. In this work we address this problem by proposing optimal solutions for constructing a new row, in a known and unmodifiable information-theoretic channel, aiming at minimizing the leakage. We first model two types of adversaries: an exact-guessing adversary, aiming to guess the secret in one try, and a s-distinguishing one, which tries to distinguish the secret s from all the other secrets.Then, we discuss design strategies for both fixed and unknown priors by offering, for each adversary, an optimal solution under linear constraints, using Linear Programming.We apply our approach to the problem of website fingerprinting defense, considering a scenario where a site administrator can modify their own site but not others. We experimentally evaluate our proposed solutions against other natural approaches. First, we sample real-world news websites and then, for both adversaries, we demonstrate that the proposed solutions are effective in achieving the least leakage. Finally, we simulate an actual attack by training an ML classifier for the s-distinguishing adversary and show that our approach decreases the accuracy of the attacker
Variance estimation of modal parameters from the poly-reference least-squares complex frequency-domain algorithm
International audienceModal parameter estimation from input/output data is a fundamental task in engineering. The poly-reference least-squares complex frequency-domain (pLSCF) algorithm is a fast and robust method for this task, and is extensively used in research and industry. As with any method using noisy measurement data, the modal parameter estimates are afflicted with uncertainty. However, their uncertainty quantification has been incomplete, in particular for the case of real-valued polynomial coefficients in the modelling of the frequency response functions (FRFs) in the pLSCF algorithm, and no expressions have been available for the covariance of participation vectors and mode shapes that are subsequently estimated with the least-squares frequency domain (LSFD) approach. This paper closes these gaps. Uncertainty expressions for the modal parameters, including participation vectors and mode shapes, are derived and presented. It is shown how to estimate the covariance between different modal parameters, and a complete method is provided for modal parameter covariance estimation from pLSCF. The method is propagating the uncertainty of FRFs through the algorithm using first-order perturbation theory and the delta method. The method is validated via extensive Monte-Carlo simulations and the applicability is illustrated using a laboratory experiment.</div
Encoding TLA+ proof obligations safely for SMT
International audienceThe TLA + Proof System (TLAPS) allows users to verify proofs with the support of automated theorem provers, including SMT solvers. To increase trust in TLAPS, we revisited the encoding of TLA + for SMT, whose implementation had become too complex. Our approach is based on a first-order axiomatization with E-matching patterns. The new encoding is available with TLAPS and achieves performances similar to the previous version, despite its simpler design
Global Inequalities in the Production of Artificial Intelligence: A Four-Country Study on Data Work
International audienceLabor plays a major, albeit largely unrecognized role in the development of artificial intelligence. Machine learning algorithms are predicated on data-intensive processes that rely on humans to execute repetitive and difficult-to-automate, but no less essential, tasks such as labeling images, sorting items in lists, recording voice samples, and transcribing audio files. Online platforms and networks of subcontractors recruit data workers to execute such tasks in the shadow of AI production, often in lower-income countries with long-standing traditions of informality and lessregulated labor markets. This study unveils the resulting complexities by comparing the working conditions and the profiles of data workers in Venezuela, Brazil, Madagascar, and as an example of a richer country, France. By leveraging original data collected over the years 2018-2023 via a mixed-method design, we highlight how the cross-country supply chains that link data workers to core AI production sites are reminiscent of colonial relationships, maintain historical economic dependencies, and generate inequalities that compound with those inherited from the past. The results also point to the importance of less-researched, non-English speaking countries to understand key features of the production of AI solutions at planetary scale.</div
Objective and subjective evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge
International audienceSupervised models for speech enhancement are trained using artificially generated mixtures of clean speech and noise signals. However, the synthetic training conditions may not accurately reflect real-world conditions encountered during testing. This discrepancy can result in poor performance when the test domain significantly differs from the synthetic training domain. To tackle this issue, the UDASE task of the 7th CHiME challenge aimed to leverage real-world noisy speech recordings from the test domain for unsupervised domain adaptation of speech enhancement models. Specifically, this test domain corresponds to the CHiME-5 dataset, characterized by real multi-speaker and conversational speech recordings made in noisy and reverberant domestic environments, for which ground-truth clean speech signals are not available. In this paper, we present the objective and subjective evaluations of the systems that were submitted to the CHiME-7 UDASE task, and we provide an analysis of the results. This analysis reveals a limited correlation between subjective ratings and several supervised nonintrusive performance metrics recently proposed for speech enhancement. Conversely, the results suggest that more traditional intrusive objective metrics can be used for in-domain performance evaluation using the reverberant LibriCHiME-5 dataset developed for the challenge. The subjective evaluation indicates that all systems successfully reduced the background noise, but always at the expense of increased distortion. Out of the four speech enhancement methods evaluated subjectively, only one demonstrated an improvement in overall quality compared to the unprocessed noisy speech, highlighting the difficulty of the task. The tools and audio material created for the CHiME-7 UDASE task are shared with the community
Secrecy by typing in the computational model
International audienceIn this paper, we propose a way to automate proofs of cryptographic protocols in the computational setting. We focus on non-deducibility -- a weak notion of secrecy -- and we aim to use type systems. Techniques based on typing were mainly used in symbolic models, and we show how they can be adapted to the \ccsa framework to obtain computational guarantees.We consider for now a fixed set of primitives, namely symmetric and asymmetric encryption, as well as pairing (\ie concatenation). Our approach has the usual benefit of type systems: it is modular, allows the security analysis for an unbounded number of sessions, and could be extended to other primitives (e.g. hashing) without excessive difficulties. We successfully applied our framework on several protocols from the literature and the ISO/IEC 11770 standard
A Three-Actuator Cable-Driven Parallel Robot With a Rectangular Workspace
International audienceIn the realm of cable-driven parallel robots (CDPRs), the conventional notion entails that each cable is directly actuated by a corresponding actuator, implying a direct relationship between the number of cables and actuators. However, this article introduces a paradigm shift by contending that the number of cables should be contingent upon the desired workspace, while the number of actuators should align with the robot’s degrees-of-freedom (DoF). This novel perspective leads to an unconventional design methodology for CDPRs. Instead of commencing with the number of actuators and cables in mind, we propose an approach that begins with defining the required workspace shape and determines the requisite number of cables. Subsequently, an actuation scheme is established where each actuator can drive multiple cables. This process entails the formulation of a transmission matrix that captures the interplay between actuators and cables, followed by the mechanical implementation of the corresponding cable-pulley routing. To illustrate this approach, we provide an example involving a 2-DoF CDPR aimed at covering a rectangular workspace. Notably, the resulting wrench-closure workspace (WCW) and wench-feasible workspace (WFW) of the proposed designs exhibit favorable comparisons to existing CDPRs with more actuators
Image-based simulation of mitral valve dynamic closure including anisotropy
International audienceSimulation of the dynamic behavior of mitral valve closure could improve clinical treatment by predicting surgical procedures outcome. We propose here a method to achieve this goal by using the immersed boundary method. In order to go toward patient-based simulation, we tailor our method to be adapted to a valve extracted from medical image data. It includes investigating segmentation process, smoothness of geometry, case setup and the shape of the left ventricle. We also study the influence of leaflet tissue anisotropy on the quality of the valve closure by comparing with an isotropic model. As part of the anisotropy analysis, we study the influence of the principal material direction by comparing methods to obtain them without dissection.Results show that our method can be scaled to various image-based data. We evaluate the mitral valve closure quality based on measuring bulging area, contact map, and flow rate. The results show also that the anisotropic material model more precisely represents the physiological characteristics of the valve tissue. Furthermore, results indicate that the orientation of the principal material direction plays a role in the effectiveness of the valve seal