Publications

Discrete Morse functions and watersheds

By Gilles Bertrand, Nicolas Boutry, Laurent Najman

2023-08-10

In Journal of Mathematical Imaging and Vision

Abstract

Any watershed, when defined on a stack on a normal pseudomanifold of dimension $d$, is a pure $(d-1)$-subcomplex that satisfies a drop-of-water principle. In this paper, we introduce Morse stacks, a class of functions that are equivalent to discrete Morse functions. We show that the watershed of a Morse stack on a normal pseudomanifold is uniquely defined, and can be obtained with a linear-time algorithm relying on a sequence of collapses. Last, we prove that such a watershed is the cut of the unique minimum spanning forest, rooted in the minima of the Morse stack, of the facet graph of the pseudomanifold.

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Introducing PC $n$-manifolds and $P$-well-composedness in partially ordered sets

By Nicolas Boutry

2023-08-01

In Journal of Mathematical Imaging and Vision

Abstract

In discrete topology, discrete surfaces are well-known for their strong topological and regularity properties. Their definition is recursive, and checking if a poset is a discrete surface is tractable. Their applications are numerous: when domain unicoherence is ensured, they lead access to the tree of shapes, and then to filtering in the shape space (shapings); they also lead to Laplacian zero-crossing extraction, to brain tumor segmentation, and many other applications related to mathematical morphology. They have many advantages in digital geometry and digital topology since discrete surfaces do not have any pinches (and then the underlying polyhedron of their geometric realization can be parameterized). However, contrary to topological manifolds known in continuous topology, discrete surfaces do not have any boundary, which is not always realizable in practice (finite hyper-rectangles cannot be discrete surfaces due to their non-empty boundary). For this reason, we propose the three following contributions: (1) we introduce a new definition of boundary, called border, based on the definition of discrete surfaces, and which allows us to delimit any partially ordered set whenever it is not embedded in a greater ambient space, (2) we introduce $P$-well-composedness similar to well-composedness in the sense of Alexandrov but based on borders, (3) we propose new (possibly geometrical) structures called (smooth) $n$-PCM’s which represent almost the same regularity as discrete surfaces and that are tractable thanks to their recursive definition, and (4) we prove several fundamental theorems relative to PCM’s and their relations with discrete surfaces. We deeply believe that these new $n$-dimensional structures are promising for the discrete topology and digital geometry fields.

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TTProfiler: Types and terms profile building for online cultural heritage knowledge graphs

By Lamine Diop, Béatrice Markhoff, Arnaud Soulet

2023-07-15

In J. Comput. Cult. Herit.

Abstract

As more and more knowledge graphs (KG) are published on the Web, there is a need for tools that show their content. This implies showing the schema-level patterns instantiated in the graph, but also the terms used to qualify its entities. In this article, we present a new profiling tool that we call TTprofiler. It shows the predicates that relate types in the KG, and also the terms present in this KG, because of their paramount importance in most KGs, especially in the Cultural Heritage (CH) domain. We recall the role of terminologies and how they are implemented and used on the Web, we give the algorithm for building a TT profile from an online KG’s Endpoint, and we report on experiments performed over a set of Cultural Heritage Web KGs. A tool for visualizing TT profiles is also provided.

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The Mealy-machine reduction functions of Spot

Abstract

We present functions for reducing Mealy machines, initially detailed in our FORTE’22 article. These functions are now integrated into Spot 2.11.2, where they are used as part of the ltlsynt tool for reactive synthesis. Of course, since Spot is a library, these functions can also be used on their own, and we provide Python bindings for easy experiments. The reproducible capsule benchmarks these functions on Mealy machines from various sources, and compare them to the MeMin tool.

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Création d’un graphe de connaissances géohistorique à partir d’annuaires du commerce parisien du 19 ème siècle: Application aux métiers de la photographie

By Solenn Tual, Nathalie Abadie, Bertrand Duménieu, Joseph Chazalon, Edwin Carlinet

2023-07-01

In 34es journées francophones d’ingénierie des connaissances (IC 2023) @ plate-forme intelligence artificielle (PFIA 2023)

Abstract

Les annuaires professionnels anciens, édités à un rythme soutenu dans de nombreuses villes européennes tout au long des XIXe et XXe si‘ecles, forment un corpus de sources unique par son volume et la possibilité qu’ils donnent de suivre les transformations urbaines à travers le prisme des activités professionnelles des habitants, de l’échelle individuelle jusqu’à celle de la ville enti‘ere. L’analyse spatiotemporelle d’un type de commerces au travers des entrées d’annuaires demande cependant un travail considérable de recensement, de transcription et de recoupement manuels. Pour pallier cette difficulté, cet article propose une approche automatique pour construire et visualiser un graphe de connaissances géohistorique des commerces figurant dans des annuaires anciens. L’approche est testée sur des annuaires du commerce parisien du XIXe si‘ecle allant de 1799 à 1908, sur le cas des métiers de la photographie.

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On the historical evolution of the performance versus cost ratio of Raspberry Pi computers

By David Beserra, Nida Meddouri, Célia Restes, Anys Nait Zerrad, Basma Bouharicha, Aurore Duvernoy

2023-07-01

In Conférence francophone d’informatique en parallélisme, architecture et système (compas 2023)

Abstract

This article aims to analyze the historical evolution of the cost/performance ratio of the Raspberry Pi family of computers, given their representativeness in the field of single-board computers. While comparing the cost/performance ratio of different models of single-board computers is not a new idea, there are no studies focused on evaluating the performance evolution and associated costs of all generations of the Raspberry Pi B line. Our analysis considered all generations of Raspberry Pi B line available on the market until 2023, and we adjusted computer prices based on the 2012 dollar value, the year of the first Raspberry Pi’s launch. The results indicate a clear trend of increasing performance over time, accompanied by a tendency for the price paid for performance to decrease. This reduction becomes even more pronounced when considering the depreciation of the dollar compared to its value in 2012.

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Security threats, countermeasures, and challenges of digital supply chains

By Badis Hammi, Sherali Zeadally, Jamel Nebhen

2023-07-01

In ACM Computing Surveys

Abstract

The rapid growth of Information Communication Technologies (ICT) has impacted many fields. In this context, the supply chain has also quickly evolved toward the digital supply chain where digital and electronic technologies have been integrated into every aspect of its end-to-end process. This evolution provides numerous beneits such as proit maximization, loss reduction, and the optimization of supply chain lead times. However, the use of such technologies has also considerably opened up various security threats and risks which have widened the attack surface on the entire end-to-end supply chain. We present a holistic survey on supply chain security. We discuss the different security issues and attacks that target the diferent supply chain technologies. Then, we discuss various countermeasures and security solutions proposed by academic and industry researchers to mitigate the identiied threats. Finally, we provide some recommendations and best practices that can be adopted to achieve a secure supply chain.

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Structural and spectral analysis of dynamic graphs for attack detection

By Majed Jaber, Nicolas Boutry, Pierre Parrend

2023-07-01

In Rencontre des jeunes chercheurs en inteligence artificielle (RJCIA-2023)

Abstract

At this time, cyberattacks represent a constant threat. Many approaches exist for detecting suspicious behaviors, but very few of them seem to benefit from the huge potential of mathematical approaches like spectral graph analysis, known to be able to extract topological features of a graph using its Laplacian spectrum. For this reason, we consider our network as a dynamic graph composed of nodes (representing the devices) and of edges (representing the requests), and we compute its Laplacian spectrum across time. An important change of topology inducing an important change in the spectrum, this spectrum seems to be the key to detect threats. Dynamic spectrum-based metrics have been developed for this aim.

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Structural analysis of the additive noise impact on the $\alpha$-tree

By Baptiste Esteban, Guillaume Tochon, Edwin Carlinet, Didier Verna

2023-06-30

In Proceedings of the 20th international conference on computer analysis of images and patterns (CAIP)

Abstract

Hierarchical representations are very convenient tools when working with images. Among them, the $\alpha$-tree is the basis of several powerful hierarchies used for various applications such as image simplifi- cation, object detection, or segmentation. However, it has been demon- strated that these tasks are very sensitive to the noise corrupting the image. While the quality of some $\alpha$-tree applications has been studied, including some with noisy images, the noise impact on the whole struc- ture has been little investigated. Thus, in this paper, we examine the structure of $\alpha$-trees built on images corrupted by some noise with re- spect to the noise level. We compare its effects on constant and natural images, with different kinds of content, and we demonstrate the relation between the noise level and the distribution of every $\alpha$-tree node depth. Furthermore, we extend this study to the node persistence under a given energy criterion, and we propose a novel energy definition that allows assessing the robustness of a region to the noise.

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Adaptive test recommendation for mastery learning

By Nassim Bouarour, Idir Benouaret, Cédric D’Ham, Sihem Amer-Yahia

2023-06-12

In Proceedings of the 2nd international workshop on data systems education: Bridging education practice with education research

Abstract

We tackle the problem of recommending tests to learners to achieve upskilling. Our work is grounded in two learning theories: mastery learning, an instructional strategy that guides learners by providing them tests of increasing difficulty, reviewing their test results, and iterating until they reach a level of mastery; Flow Theory, which identifies different test zones, frustration, learnable, flow and boredom zones, to determine the best k tests to recommend to a learner. We formalize the AdUp Problem and develop a multi-objective optimization solution that adapts the difficulty of recommended tests to the learner’s predicted performance, aptitude, and skill gap. We leverage existing models to simulate learner behavior and run experiments to demonstrate that our formalization is best to attain skill mastery. We discuss open research directions including the applicability of reinforcement learning and the recommendation of peers in collaborative projects.

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