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Jin Li

  1. Dynamics of stochastic non-Newtonian fluids driven by fractional Brownian motion with Hurst parameter $H \in (1/4,1/2)$.

    Пт, 07/15/2011 - 15:01 — SomNambul
    Authors: Jin Li, Jianhua Huang
    Subjects: Dynamical Systems
    Abstract

    In this paper we consider the Stochastic isothermal, nonlinear,
    incompressible bipolar viscous fluids driven by a genuine cylindrical
    fractional Bronwnian motion with Hurst parameter $H \in (1/4,1/2)$ under
    Dirichlet boundary condition on 2D square domain. First we prove the existence
    and regularity of the stochastic convolution corresponding to the stochastic
    non-Newtonian fluids. Then we obtain the existence and uniqueness results for
    the stochastic non-Newtonian fluids. Under certain condition, the random
    dynamical system generated by non-Newtonian fluids has a random attractor.

  2. Dynamics of 2D Stochastic non-Newtonian fluids driven by fractional Brownian motion.

    Втр, 05/17/2011 - 15:01 — SomNambul
    Authors: Jin Li, Jianhua Huang
    Subjects: Mathematical Physics
    Abstract

    In this paper, we establish the existence of solution for some kind of 2D
    Stochastic isothermal, nonlinear, incompressible bipolar viscous fluids driven
    by fractional Bronwnian motion with Hurst parameter $H \in (1/2,1)$. Under
    certain condition, the generated random dynamical system has a random
    attractor.

  3. Inter-Operator Feedback in Data Stream Management Systems via Punctuation.

    Пнд, 09/14/2009 - 09:02 — SomNambul
    Authors: Rafael Fernández-Moctezuma, Kristin Tufte, Jin Li
    Subjects: Databases
    Abstract

    High-volume, high-speed data streams may overwhelm the capabilities of stream
    processing systems; techniques such as data prioritization, avoidance of
    unnecessary processing and on-demand result production may be necessary to
    reduce processing requirements. However, the dynamic nature of data streams, in
    terms of both rate and content, makes the application of such techniques
    challenging. Such techniques have been addressed in the context of static and
    centralized query optimization; however, they have not been fully addressed for
    data stream management systems.

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