While much work has addressed the problem of maintaining materialized views, the important question of optimizing queries in the presence of materialized views has not been resolved. In this paper, we analyze the optimization question and provide a comprehensive and efficient solution. Our solution has the desirable property that it is a simple generalization of the traditional query optimization algorithm.

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The LDL system provides a declarative logic-based language and integrates relational database and logic programming technologies so as to support advanced data and knowledge-based applications. This paper contains a comprehensive overview of the system and contains a description of the LDL language and the compilation techniques employed to translate LDL queries into target queries on the stored data. The paper further contains a description of the architecture and runtime environment of the system and the optimization techniques employed in order to improve the performance and assure the safety of the compiled queries. The paper concludes with an account of the experience gained so far with the system, and discusses application areas where the LDL approach appears to be particularly effective.

We present a systematic approach to forward-motion-compensated predictive video coding. The first step is the definition of a flexible model that compactly represents motion fields. The inhomogeneity and spatial coherence properties of motion fields are captured using linear multiscale models. One possible design is based on linear finite elements and yields a multiscale extension of the triangle motion compensation (TMC) method. The second step is the choice of a computational technique that identifies the coefficients of the linear model. We study a modified optical flow technique and minimize a cost function closely related to Horn and Schunck's (1981) criterion. The cost function balances accuracy and complexity of the motion compensated predictor and is viewed as a measure of goodness of the motion field. It determines not only the coefficients of the model, but also the quantization method. We formulate the estimation and quantization problems jointly as a discrete optimization problem and solve it using a fast multiscale relaxation algorithm. A hierarchical extension of the algorithm allows proper handling of large displacements. Simulations on a variety of video sequences have produced improvements over TMC and over the half-pel-accuracy, full-search block matching algorithm, in excess of 0.5 dB in average. The results are visually superior as well. In particular, the reconstructed video is entirely free of blocking artifacts.