We provide a resolution-based proof procedure for modal and description logics that improves on previous proposals in a number of important ways. First, it avoids translations into large undecidable logics , and works directly on modal or description logic formulas instead. Second, by using labeled formulas it avoids the complexities of earlier propositional resolution-based methods for modal l...

A new high-resolution flux-based finite volume method for general advection equations in non-divergent form including a level set equation for moving interfaces is introduced. The method is applicable to the case of non-divergence free velocity and to general unstructured grids in higher dimensions. We show that the method is consistent and that the numerical solution fulfils discrete minimum/m...

In this paper, two significant weaknesses of locally linear embedding (LLE) applied to computer vision are addressed: ‘‘intrinsic dimension’’ and ‘‘eigenvector meanings’’. ‘‘Topological embedding’’ and ‘‘multi-resolution nonlinearity capture’’ are introduced based on mathematical analysis of topological manifolds and LLE. The manifold topological analysis (MTA) method is described and is based ...

Multi-frame image super-resolution (SR) aims to utilize information from a set of lowresolution (LR) images to compose a high-resolution (HR) one. As it is desirable or essential in many real applications, recent years have witnessed the growing interest in the problem of multi-frame SR reconstruction. This set of algorithms commonly utilizes a linear observation model to construct the relation...

This paper presents a novel two-stage load profile super-resolution (LPSR) framework, ProfileSR-GAN, to upsample the low-resolution profiles (LRLPs) high-resolution (HRLPs). The LPSR problem is formulated as Maximum-a-Posteriori problem. In first-stage, GAN-based model adopted restore high-frequency components from LRLPs. To reflect load-weather dependency, aside LRLPs, weather data added an in...