Improving analogues-based detection & attribution approaches for hurricanes

International audienceThis paper presents a proof of concept for a new analogue-based framework for the detection and attribution of hurricane-related hazards. This framework addresses two important limitations of existing analogue-based methodologies: the lack of observed similar events, and the unsuitability of the distance metrics for hurricanes. To do so, we use a track-based metric, and we make use of synthetic tracks catalogues. We show that our method allows for selecting a sufficient number of suitable analogues, and we apply it to nine hurricane cases. Our analysis does not reveal any robust changes in wind hazards, translation speed, seasonality, or frequency over recent decades, consistent with current literature. This framework provides a reliable alternative to traditional analogue-based methods in the case of hurricanes, complementing and potentially enhancing efforts in addressing extreme weather event attribution

A comparison of eight weakly dispersive Boussinesq-type models for non-breaking long-wave propagation in variable water depth

International audienceWeakly dispersive Boussinesq-type models are extensively used to model long-wave propagation in coastal areas and their interaction with coastal infrastructures. Many equations falling in this category have been formulated during the last decades, but few detailed comparisons between them can be found in the literature. In this work, we investigate theoretically and with computational experiments eight variants of the most popular models used by the coastal engineering community. Both weakly nonlinear and fully nonlinear models are considered, hoping to understand better when the additional complexity of the latter class of models is necessary or justified. We provide an overview and discuss the properties of these models, including the linear dispersion relation in uniform water depth, the second-order nonlinear coupling coefficient, the shoaling gradient, and the sensitivity to wave trough instabilities. The models are then numerically discretised using the same general strategy in a single numerical code, using fourth-order methods for time and space discretisation. Their capacity to simulate coastal wave propagation and their transformation when approaching the shore is assessed on three challenging one-dimensional benchmarks. It appears that fully nonlinear models are more consistent than their weakly nonlinear counterparts, which can occasionally perform better but show different behaviours depending on the case.</div

Found in Translation: semantic approaches for enhancing AI interpretability in face verification

The increasing complexity of machine learning models in computer vision, particularly in face verification, requires the development of explainable artificial intelligence (XAI) to enhance interpretability and transparency. This study extends previous work by integrating semantic concepts derived from human cognitive processes into XAI frameworks to bridge the comprehension gap between model outputs and human understanding. We propose a novel approach combining global and local explanations, using semantic features defined by user-selected facial landmarks to generate similarity maps and textual explanations via large language models (LLMs). The methodology was validated through quantitative experiments and user feedback, demonstrating improved interpretability. Results indicate that our semantic-based approach, particularly the most detailed set, offers a more nuanced understanding of model decisions than traditional methods. User studies highlight a preference for our semantic explanations over traditional pixelbased heatmaps, emphasizing the benefits of human-centric interpretability in AI. This work contributes to the ongoing efforts to create XAI frameworks that align AI models behaviour with human cognitive processes, fostering trust and acceptance in critical applications

Transport policy at an impasse: managing on-street delivery areas in Paris

International audienc

A note on the complexity of the picker routing problem in multi-block warehouses and related problems

International audienceThe Picker Routing Problem (PRP), which consists of finding a minimum-length tour between a set of storage locations in a warehouse, is one of the most important problems in the warehousing logistics literature. Despite its popularity, the tractability of the PRP in multi-block warehouses remains an open question. This technical note aims to fill this research gap by establishing that the problem is strongly NP-hard. As a corollary, the complexity status of other related problems is settled

Optimizing Resource Allocation and Scheduling towards FRMCS and GSM-R networks coexistence in Railway Systems

International audienceThe actual railway communication system used in Europe for high-speed trains (HST) is called the GSM-R system, which is a communication system based on 2G infrastructure. This system is meant to be replaced by a new system based on 5G NR infrastructure called the Future Railway Mobile Communication System (FRMCS) by 2030. For the next years, both systems will probably coexist in the same frequency band since the migration from GSM-R to FRMCS is planned to be done progressively until the GSM-R system is completely shut down, mainly due to safety and budget constraints. In this paper, we study the resource allocation for the FRMCS system sharing the same frequency band as the already deployed GSM-R system. We formulate the resource allocation problem as an integer linear problem (ILP), known to be NP-hard.To solve it in a reasonable time, we propose a scheduling algorithm, called Intelligent Traffic Scheduling Preemptor (ITSP), that allocates resources for the different FRMCS traffic types considered (critical traffic and performance traffic) in the same frequency band with the GSM-R system. Our algorithm is channel quality Indicator (CQI) aware and uses the preemption mechanism in 5G NR standards to optimize the resource allocation for the FRMCS system without impacting the actual GSM-R resource allocation in the context of the white space concept

Unconditionally stable time discretization of Lindblad master equations in infinite dimension using quantum channels

We examine the time discretization of Lindblad master equations in infinite-dimensional Hilbert spaces. Our study is motivated by the fact that, with unbounded Lindbladian, projecting the evolution onto a finite-dimensional subspace using a Galerkin approximation inherently introduces stiffness, leading to a Courant--Friedrichs--Lewy type condition for explicit integration schemes. We propose and establish the convergence of a family of explicit numerical schemes for time discretization adapted to infinite dimension. These schemes correspond to quantum channels and thus preserve the physical properties of quantum evolutions on the set of density operators: linearity, complete positivity and trace. Numerical experiments inspired by bosonic quantum codes illustrate the practical interest of this approach when approximating the solution of infinite dimensional problems by that of finite dimensional problems of increasing dimension

Log-normal Mutations and their Use in Detecting Surreptitious Fake Images

International audienceIn many cases, adversarial attacks against fake detectors employ algorithms specifically crafted for automatic image classifiers. These algorithms perform well, thanks to an excellent ad hoc distribution of initial attacks. However, these attacks are easily detected due to their specific initial distribution. Consequently, we explore alternative black-box attacks inspired by generic black-box optimization tools, particularly focusing on the log-normal algorithm that we successfully extend to attack fake detectors. Moreover, we demonstrate that this attack evades detection by neural networks trained to flag classical adversarial examples. Therefore, we train more general models capable of identifying a broader spectrum of attacks, including classical black-box attacks designed for images, black-box attacks driven by classical optimization, and no-box attacks. By integrating these attack detection capabilities with fake detectors, we develop more robust and effective fake detection systems

Daniel WALDENSTRÖM Richer and More Equal : A New History of Wealth in the West Cambridge, Polity, 2024, 256 pages (Note de lecture)

Note de lecture sur l'ouvrage de Daniel WALDENSTRÖM Richer and More Equal : A New History of Wealth in the West Cambridge, Polity, 2024, 256 page

Toward more robust net primary production projections in the North Atlantic Ocean

International audiencePhytoplankton plays a crucial role in both climate regulation and marine biodiversity, yet it faces escalating threats due to climate change. Understanding future changes in phytoplankton biomass and productivity under climate change requires the utilization of Earth system models capable of resolving marine biogeochemistry. These models often differ significantly from one another, and most studies typically use the average response across an ensemble of models as the most reliable projection. However, in the North Atlantic, this straightforward method falls short of providing robust projections of phytoplankton net primary production (NPP) over the 21st century. A new inter-comparison approach was therefore developed and applied to eight models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) exhibiting substantial divergence in their NPP projections in the North Atlantic. The basin was first divided into three bioregions tailored to the characteristics of each model using a novel method based on a clustering procedure. The mechanisms controlling NPP projections were then identified in each model and in each bioregion, revealing two mechanisms responsible for a large part of model divergence: diazotrophy in the subtropical region and the presence of an ammonium pool in the subpolar region. This allowed for an informed selection of models in each region based on the way they represent these two mechanisms, resulting in reduced projection uncertainty, enhanced total NPP decrease in the subtropical region, and a strengthened increase in small phytoplankton NPP in the subpolar North Atlantic. These model selections enhanced the decreases in carbon export and phytoplankton biomass but had no impact on zooplankton biomass. This innovative approach has strong synergies with other widely used inter-comparison techniques, such as emergent constraints, and their combination would provide valuable insights into the future trajectory of the Earth's climate syste