Hierarchical Models for Relational Event Sequences

Interaction within small groups can often be represented as a sequence of events, where each event involves a sender and a recipient. Recent methods for modeling network data in continuous time model the rate at which individuals interact conditioned on the previous history of events as well as actor covariates. We present a hierarchical extension for modeling multiple such sequences, facilitating inferences about event-level dynamics and their variation across sequences. The hierarchical approach allows one to share information across sequences in a principled manner---we illustrate the efficacy of such sharing through a set of prediction experiments. After discussing methods for adequacy checking and model selection for this class of models, the method is illustrated with an analysis of high school classroom dynamics

Optimal low-dispersion low-dissipation LBM schemes for computational aeroacoustics

Lattice Boltmzmann Methods (LBM) have been proved to be very effective methods for computational aeroacoustics (CAA), which have been used to capture the dynamics of weak acoustic fluctuations. In this paper, we propose a strategy to reduce the dispersive and disspative errors of the two-dimensional (2D) multi-relaxation-time lattice Boltzmann method (MRT-LBM). By presenting an effective algorithm, we obtain a uniform form of the linearized Navier-Stokes equations corresponding to the MRT-LBM in wave-number space. Using the matrix perturbation theory and the equivalent modified equation approach for finite difference methods, we propose a class of minimization problems to optimize the free-parameters in the MRT-LBM. We obtain this way a dispersion-relation-preserving LBM (DRP-LBM) to circumvent the minimized dispersion error of the MRT-LBM. The dissipation relation precision is also improved.And the stability of the MRT-LBM with the small bulk viscosity is guaranteed. Von Neuman analysis of the linearized MRT-LBM is performed to validate the optimized dispersion/dissipation relations considering monochromatic wave solutions. Meanwhile, dispersion and dissipation errors of the optimized MRT-LBM are quantitatively compared with the original MRT-LBM . Finally, some numerical simulations are carried out to assess the new optimized MRT-LBM schemes.Comment: 33 page

Assessing the role of the universal addition of CT thorax to CT abdomen and pelvis in the COVID era. A retrospective multicentre cohort study

Peer reviewedPublisher PD

Online Allocation of Splitable Clients to Multiple Servers on Large Scale Heterogeneous Platforms

International audienceDans cet article, nous considérons l'allocation dynamique (online) d'un très grand nombre de tâches identiques et indépendantes sur une plate-forme maîtres-esclaves. Initialement, plusieurs nœuds maîtres possèdent ou génèrent les tâches qui sont ensuite transférées et traitées par des nœuds esclaves. L'objectif est de maximiser le débit (i.e., le nombre fractionnaire de tâches qui peut être traité en une unité de temps, en régime permanent, par la plate-forme). Nous considérons que les communications se déroulent suivant le modèle multi-port à degré borné, dans lequel plusieurs communications peuvent avoir lieu simultanément sous réserve qu'aucune bande passante ne soit dépassée et qu'aucun serveur n'ouvre simultanément un nombre de connections supérieur à son degré maximal. Sous ce modèle, la maximisation du débit correspond au problème Maximum-Througput- Bounded-Degree (MTBD) qui a été analysé dans~\cite{beaumont08}. Il a été montré que le problème est NP-Complet au sens fort mais qu'une augmentation de ressources minimale (de 1) sur le degré maximal des serveurs permet de le résoudre en temps polynomial. Dans cet article, nous considérons une extension de MTBD à la situation plus réaliste, dans le contexte des plates-formes de calcul à grande échelle, dans laquelle les nœuds esclaves rejoignent et quittent dynamiquement la plate-forme à des instants arbitraires (problème online MTBD). Nous montrons tout d'abord qu'aucun algorithme complètement à la volée (c.-à.-d. qui n'autorise pas les déconnections) ne peut conduire à un facteur d'approximation constant, quelle que soit l'augmentation de ressources utilisée. Ensuite, nous montrons qu'il est en fait possible de maintenir à tout instant la solution optimale (avec une augmentation de ressource additive de 1) en ne réalisant à chaque modification de la plate-forme qu'une déconnection et qu'une nouvelle connection par maître

Extended Version: Online Allocation of Splitable Clients to Multiple Servers on Large Scale Heterogeneous Platforms

In this paper, we consider the problem of the online allocation of a very large number of identical tasks on a master-slave platform. Initially, several masters hold or generate tasks that are transfered and processed by slave nodes. The goal is to maximize the overall throughput achieved using this platform, i.e., the (fractional) number of tasks that can be processed within one time unit. We model the communications using the so-called bounded degree multi-port model, in which several communications can be handled by a master node simultaneously, provided that bandwidths limitation are not exceeded and that a given server is not involved in more simultaneous communications than its maximal degree. Under this model, it has been proved that maximizing the throughput (MTBD problem) is NP-Complete in the strong sense but that a small additive resource augmentation (of 1) on the servers degrees is enough to find in polynomial time a solution that achieves at least the optimal throughput. In this paper, we consider the reasonable setting where the set of slave processors is not known in advance but rather join and leave the system at any time, i.e., the online version of MTBD. We prove that no fully online algorithm (where nodes cannot be disconnected even if they do not leave the system) can achieve a constant approximation ratio, whatever the resource augmentation on servers degrees. Then, we prove that it is possible to maintain the optimal solution at the cost of at most one change per server each time a new node joins and leave the system. At last, we propose several other greedy heuristics to solve the online problem and we compare the performance (in terms of throughput) and the cost (in terms of disconnexions and reconnections) of proposed algorithms through a set of extensive simulation results