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Event-based boundary control of a linear 2x2 hyperbolic system via backstepping approach
No full textInternational audienceIn this paper, we introduce an event-based boundary control for a 2 × 2 coupled linear hyperbolic system. We use a well established backstepping controller which stabilizes the system along with a dynamic triggering condition which determines when the controller must be updated. The main contributions rely on the definition of an event-based controller under which global exponential stability of the system is achieved and furthermore, the existence of a minimal dwell-time between two triggering times is guaranteed. The well-posedness of the system under the event-based controller is stated. A simulation example is presented to illustrate the results
A Unified Framework of Clustering Approach in Vehicular Ad Hoc Networks
No full textInternational audienceEffective clustering algorithms are indispensable in order to solve the scalability problem in vehicular ad hoc networks. Although current existing clustering algorithms showincreased cluster stability under some certain traffic scenarios, it is still hard to address which clustering metric performs the best. In this paper, we propose a unified framework of clusteringapproach (UFC), composed of three important parts: 1) neighbor sampling; 2) backoff-based cluster head selection; and 3) backup cluster head based cluster maintenance. Three mobility-based clustering metrics, including vehicle relative position, relative velocity, and link lifetime, are considered in our approach under different traffic scenarios. Furthermore, a detailed analysis ofUFC with parameters optimization is presented. Extensive comparison results among UFC, lowest-ID, and VMaSC algorithms demonstrate that our clustering approach performs high clusterstability, especially under high dynamic traffic scenarios
A multi-criteria repair/recovery framework for the tail assignment problem in airlines
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Reproducible Evaluation of System Efficiency with a Model of Architecture: From Theory to Practice
No full textInternational audienceCurrent trends in high performance and embedded computing include design of increasingly complex hardware architectures with high parallelism, heterogeneous processing elements and non-uniform communication resources. In order to take hardware and software design decisions, early evaluations of the system non-functional properties are needed. These evaluations of system efficiency require Electronic System-Level (ESL) information on both the algorithms and the architecture. Contrary to algorithm models for which a major body of work has been conducted on defining formal Models of Computation (MoCs), architecture models from the literature are mostly empirical models from which reproducible experimentation requires the accompanying software. In this paper, a precise definition of a Model of Architecture (MoA) is proposed that focuses on reproducibility and abstraction and removes the overlap previously existing between the notions of MoA and MoC. A first MoA, called the Linear System-Level Architecture Model (LSLA), is presented. To demonstrate the generic nature of the proposed new architecture modeling concepts, we show that the LSLA Model can be integrated flexibly with different MoCs. LSLA is then used to model the energy consumption of a State-of-the-Art Multiprocessor System-on-Chip (MPSoC) when running an application described using the Synchronous Dataflow (SDF) MoC. A method to automatically learn LSLA model parameters from platform measurements is introduced. Despite the high complexity of the underlying hardware and software, a simple LSLA model is demonstrated to estimate the energy consumption of the MPSoC with a fidelity of 86%
Single-channel audio source separation with NMF: divergences, constraints and algorithms
No full textInternational audienceSpectral decomposition by nonnegative matrix factorisation (NMF) has become state-of-the-art practice in many audio signal processing tasks, such as source separation, enhancement or transcription. This chapter reviews the fundamentals of NMF-based audio decomposition, in unsupervised and informed settings. We formulate NMF as an optimisation problem and discuss the choice of the measure of fit. We present the standard majorisation-minimisation strategy to address optimisation for NMF with common beta-divergence, a family of measures of fit that takes the quadratic cost, the generalised Kullback-Leibler divergence and the Itakura-Saito divergence as special cases. We discuss the reconstruction of time-domain components from the spectral factorisation and present common variants of NMF-based spectral decomposition: supervised and informed settings, regularised versions, temporal models
Graph-Based Slice-to-Volume Deformable Registration
No full textInternational audienceDeformable image registration is a fundamental problem in computer vision and medical image computing. In this paper we investigate the use of graphical models in the context of a particular type of image registration problem, known as slice-to-volume registration. We introduce a scal-able, modular and flexible formulation that can accommodate low-rank and high order terms, that simultaneously selects the plane and estimates the in-plane deformation through a single shot optimization approach. The proposed framework is instantiated into different variants seeking either a compromise between computational efficiency (soft plane selection constraints and approximate definition of the data similarity terms through pair-wise components) or exact definition of the data terms and the constraints on the plane selection. Simulated and real-data in the context of ultrasound and magnetic resonance registration (where both framework instantiations as well as different optimization strategies are considered) demonstrate the potentials of our method
Multi-stage vector-borne zoonoses models: A global analysis
No full textInternational audienceA class of models that describes the interactions between multiple host species and an arthropod vector is formulated and its dynamics investigated. A host-vector disease model where the host's infection is structured into n stages is formulated and a complete global dynamics analysis is provided. The basic reproduction number acts as a sharp threshold, that is, the disease-free equilibrium is globally asymptotically stable (GAS) whenever R_{0}≤ 1 and that a unique interior endemic equilibrium exists and is GAS if R_{0} > 1. We proceed to extend this model with m host species, capturing a class of zoonoses where the cross-species bridge is an arthropod vector. The basic reproduction number of the multi-host-vector, R_{0} (m), is derived and shown to be the sum of basic reproduction numbers of the model when each host is isolated with an arthropod vector. It is shown that the disease will persist in all hosts as long as it persists in one host. Moreover, the overall basic reproduction number increases with respect to the host and that bringing the basic reproduction number of each isolated host below unity in each host is not sufficient to eradicate the disease in all hosts. This is a type of " amplification effect, " that is, for the considered vector-borne zoonoses, the increase in host diversity increases the basic reproduction number and therefore the disease burden
The Estimation and Testing of the Cointegration Order Based on the Frequency Domain
No full textInternational audienceThis article proposes a method to estimate the degree of cointegration in bivariate series and suggests a test statistic for testing noncointegration based on the determinant of the spectral density matrix for the frequencies close to zero. In the study, series are assumed to be I(d), 0 < d ⩽ 1, with parameter d supposed to be known. In this context, the order of integration of the error series is I(d − b), b ∈ [0, d]. Besides, the determinant of the spectral density matrix for the dth difference series is a power function of b. The proposed estimator for b is obtained here performing a regression of logged determinant on a set of logged Fourier frequencies. Under the null hypothesis of noncointegration, the expressions for the bias and variance of the estimator were derived and its consistency property was also obtained. The asymptotic normality of the estimator, under Gaussian and non-Gaussian innovations, was also established. A Monte Carlo study was performed and showed that the suggested test possesses correct size and good power for moderate sample sizes, when compared with other proposals in the literature. An advantage of the method proposed here, over the standard methods, is that it allows to know the order of integration of the error series without estimating a regression equation. An application was conducted to exemplify the method in a real context