I will defend my HDR titled “Resource optimization and mobility management for wireless networks” on Thursday 16 December 2021 at 9:00 AM. For all those who want to attend, the presentation will be broadcast online at the following URL: https://bbb.univ-avignon.fr/b/had-gi3-dem
In the context of team Cornet’s seminars, Michael Poss (LIRMM) will present his research work on Optimization problems in graphs with location uncertainty on November 26, 2021, at 11:35 in the meeting room. Abstract: Many discrete optimization problems amount to select a feasible subgraph of least weight. We consider in this paper the context of spatial graphs where the positions of the vertices are uncertain and belong to known uncertainty sets. The objective is to minimize the sum of the distances in the chosen subgraph for the worst positions of the vertices in their uncertainty sets. We will present some of the results we obtained for these problems, including a numerical illustration on Steiner tree problems.
In the context of team Cornet’s seminars, Mathilde Vernet (LIA) will present her work on Connectivity in Dynamic Graphs on November 12, 2021, at 11:35 in the meeting room.
In the context of team Cornet’s seminars, Mathilde Vernet (LIA) will present her research work on October 22, 2021, at 11:35 in the meeting room.
I will defend my thesis titled ‘Multiplicity in the Partitioning of Signed Graphs’ on Tuesday, June 29th at 2 p.m. The presentation will be in French and will take place in a hybrid mode: at the Blaise Pascal amphitheater of the CERI and via video conference. The video link is: https://pod.univ-avignon.fr/live/these2/ You are all cordially invited. The jury will consist of: You are also invited to the thesis reception following the defense. Abstract: The partitioning of signed graphs is an important task from an application standpoint, as finding a balanced partition helps in understanding the system modeled by the signed graph. However, the standard approach in the literature aims to find a single partition, as if it adequately characterizes the system under study. Yet, multiple partitions may be needed to construct a fairer image of the studied system. Although this notion of multiplicity is crucial from the end-users’ perspective, it has been scarcely addressed in the literature. In this thesis, we aim to relax the assumption of a unique partition and search for multiple partitions, each within two distinct situations. The first situation concerns signed multiplex graphs. Such a graph consists of several separate graphs, referred to as layers, each Plus d'infos
I will defend my HDR entitled ‘Combining Heterogeneous Information: Contributions to the Extraction and Analysis of Feature-Rich Complex Networks’ on Wednesday, June 16, 2021, at 9 a.m. The presentation will be in English and will take place via video conference at the link https://pod.univ-avignon.fr/live/colloque/ You are all cordially invited to attend. Jury: Abstract: The concept of Complex Network is generally used in the literature to refer to a graph representing a real-world complex system. This confers such graphs so-called non-trivial topological properties that distinguish them from regular and random graphs. Among them, the most widely known are small-worldness and scale-freeness, whose study marked the beginning of a new research domain now called Network Science, and aiming at studying complex networks. It is a multidisciplinary field that relies largely on a number of pre-existing domains, in particular graph theory, quantitative sociology, computer science, operations research, statistical physics, and of course complex systems. Network Science is mainly a data science, as its starting point is the modeling of real-world systems. As such, its emergence is due not only to the convergence of interdisciplinary efforts, but also to the availability of the resources required to build and study large and/or numerous complex networks: Plus d'infos
Date: Tuesday 26 January 2021 at 9:00 AM. Title: Quality of Service and Privacy in Internet of Things Dedicated to Healthcare Jury: Abstract: The Internet of Things (IoT) based healthcare systems usually composed of medical and environmental sensors, remote servers, and the network. These systems focus on providing remote monitoring, disease diagnosis, and treatment progress observation. The healthcare systems in IoT domain helps in realizing long-term economical, ubiquitous, and patient centered care systems, that result in improving treatment and patient outcomes. This research contributes to the domain by proposing a Cloud-Fog based architecture that can embrace multiple healthcare scenarios, and able to adapt dynamically with the context and status of the patients. It allows the mobility and physical activity of the patients in the environment through deployment and implementation of an appropriate Received Signal Strength (RSS) based handoff mechanism. It also proposes a mobility-aware task scheduling and allocation approach in cloud-fog computing paradigm, called MobMBAR, with the objective of minimizing the total schedule time (makespan). MobMBAR performs dynamic balanced healthcare tasks distribution between the cloud and fog devices. It is a data locality based approach that depends on changing the location where the data is computed to where it actually resides. Plus d'infos
On January 22, 2021, Mayeul Matthias will defend his thesis entitled “Recommendation of Personalized Cultural Paths – An Interdisciplinary Study of Automated Visit Proposals.” This thesis is supervised by Juan-Manuel Torres and Didier Josselin, and co-supervised by Fen Zhou. The jury consists of: Abstract: This thesis focuses on recommending cultural visits through an interdisciplinary approach. These works combine techniques from Operations Research and natural language processing while drawing on concepts from audience sociology and geography. We propose new methods for evaluating cultural points of interest and automatically creating tourist routes that take into account the desires expressed by a visitor. These principles are applied on two different scales and contexts: museum visits and cultural paths within a city. In the first part, we concentrate on visits to art museums based on the preferences expressed by the visitor and the prestige of the artworks. This dual approach allows classifying the works both according to the cultural affinities of the visitor and their importance within the museum. The latter is calculated by applying automatic text summarization algorithms to the museum’s official descriptions of the works, providing a visit profile reflecting the discovery of a museum through its masterpieces. This profile can then Plus d'infos
This dataset consists of 3 TV series with manual annotations: All three files are in .json format and contain TV Series annotated data. Each TV Series is defined by its name, A TV Series contains seasons, defined by their ids. Every season is made of episodes, defined by their ids, titles, duration and fps. Each episode contains two basic kinds of data: scenes and speech segments. Scenes are defined by starting points and are made of shots (Seasons 1 only).A shot is defined by starting and ending positions, and recurring shot ids. The speech segments are defined by their starting and ending points; textual content (here encrypted for copyright reasons); speaker; possible interlocutors.
This dataset contains conversations between Wikipedia editors, which are annotated in terms of various types of abuse, at the level of messages. It aligns two existing corpora:
Laboratoire Informatique d'Avignon — Avignon Université