1,417 research outputs found

    PFTijah: text search in an XML database system

    Get PDF
    This paper introduces the PFTijah system, a text search system that is integrated with an XML/XQuery database management system. We present examples of its use, we explain some of the system internals, and discuss plans for future work. PFTijah is part of the open source release of MonetDB/XQuery

    The uncertain representation ranking framework for concept-based video retrieval

    Get PDF
    Concept based video retrieval often relies on imperfect and uncertain concept detectors. We propose a general ranking framework to define effective and robust ranking functions, through explicitly addressing detector uncertainty. It can cope with multiple concept-based representations per video segment and it allows the re-use of effective text retrieval functions which are defined on similar representations. The final ranking status value is a weighted combination of two components: the expected score of the possible scores, which represents the risk-neutral choice, and the scores’ standard deviation, which represents the risk or opportunity that the score for the actual representation is higher. The framework consistently improves the search performance in the shot retrieval task and the segment retrieval task over several baselines in five TRECVid collections and two collections which use simulated detectors of varying performance

    Parsimonious language models for a terabyte of text

    Get PDF

    Towards higher-order accurate mass lumping in explicit isogeometric analysis for structural dynamics

    Full text link
    We present a mass lumping approach based on an isogeometric Petrov-Galerkin method that preserves higher-order spatial accuracy in explicit dynamics calculations irrespective of the polynomial degree of the spline approximation. To discretize the test function space, our method uses an approximate dual basis, whose functions are smooth, have local support and satisfy approximate bi-orthogonality with respect to a trial space of B-splines. The resulting mass matrix is ``close'' to the identity matrix. Specifically, a lumped version of this mass matrix preserves all relevant polynomials when utilized in a Galerkin projection. Consequently, the mass matrix can be lumped (via row-sum lumping) without compromising spatial accuracy in explicit dynamics calculations. We address the imposition of Dirichlet boundary conditions and the preservation of approximate bi-orthogonality under geometric mappings. In addition, we establish a link between the exact dual and approximate dual basis functions via an iterative algorithm that improves the approximate dual basis towards exact bi-orthogonality. We demonstrate the performance of our higher-order accurate mass lumping approach via convergence studies and spectral analyses of discretized beam, plate and shell models

    Motivation and Productivity of Employees in Higher Education during the First Lockdown

    Get PDF
    In a cross-sectional study among 623 employees of a higher education institution, we examined the relations between perceived competence, autonomy, relatedness, intrinsic motivation, and productivity during the first lockdown in the spring of 2020. The results indicate that, relative to the period before the lockdown, the employees experienced an increase in autonomy and competence, but a decrease in relatedness, intrinsic motivation, and productivity. Structural equation modelling revealed that the decrease in productivity can be explained by a decrease in intrinsic motivation, which in turn can be explained by changes in relatedness, autonomy, and perceived competence. Thus, during the lockdown, both positive and negative motivational consequences of teleworking were observed. However, the ultimate consequence for employees’ productivity was negative. An important difference between this study and previous studies on the topic of teleworking, is that the present examined the motivational process under extreme circumstances in which employees had to switch overnight form onsite to remote working

    A Tchebycheffian extension of multi-degree B-splines: Algorithmic computation and properties

    Full text link
    In this paper we present an efficient and robust approach to compute a normalized B-spline-like basis for spline spaces with pieces drawn from extended Tchebycheff spaces. The extended Tchebycheff spaces and their dimensions are allowed to change from interval to interval. The approach works by constructing a matrix that maps a generalized Bernstein-like basis to the B-spline-like basis of interest. The B-spline-like basis shares many characterizing properties with classical univariate B-splines and may easily be incorporated in existing spline codes. This may contribute to the full exploitation of Tchebycheffian splines in applications, freeing them from the restricted role of an elegant theoretical extension of polynomial splines. Numerical examples are provided that illustrate the procedure described
    corecore