The period character’s meaning is highly ambiguous due to the frequency of abbreviations that require to be followed by a period. We have developed a hybrid method for period character disambiguation and the identification of abbreviations, combining rules that explore regularities in the right context of the period with lexicon-based, statistical methods which scrutinize the preceding token. T...

The classical DPO graph rewriting construction is re-expressed using the oppbration approach introduced originally for term graph rewriting. Using a skeleton category of graphs, a base of canonical graphs-in-context, with DPO rules as arrows, and with categories of redexes over each object in the base, yields a category of rewrites via the discrete Grothendieck construction. The various possibl...

The combination of rules and ontologies has a central role in the ongoing development of the Semantic Web. In previous work, autoepistemic logic (AEL) was advocated as a uniform host formalism to study different such combinations, enabling comparisons on a common basis. In this paper, we continue this line of research and investigate different embeddings of major proposals to combine rules and ...

—Amidst the conflicting experimental evidence of superiority of one over the other, we investigate the Sum and majority Vote combining rules in a two class case, under the assumption of experts being of equal strength and estimation errors conditionally independent and identically distributed. We show, analytically, that, for Gaussian estimation error distributions, Sum always outperforms Vote....

Sparse signal processing has been widely used in synthetic aperture radar imaging and feature enhancement of images the recent decade. regularization ℓ1 can reduce noise level suppress sidelobes. However, suppression sidelobes by sparse often pays price losing information weak targets. Therefore, method combining spatially variant apodization is proposed this paper, which noise, retain detail i...

In this paper, experiments on various classifiers and combining these classifiers are done, reported and analyzed. Combining the classifiers means having the single classifiers support each other in making a decision, instead of having only a single classifier’s decision as the final decision. The base experiment involves, both, applying different single classifiers on a dataset and applying th...

When more than a single classifier has been trained for the same recognition problem the question arises how this set of classifiers may be combined into a final decision rule. Several fixed combining rules are used that depend on the output values of the base classifiers only. They are almost always suboptimal. Usually, however, training sets are available. They may be used to calibrate the ba...

On the Semantic Web, there has been increasing demand for a ruleslike expressivity that goes beyond OWL-DL. Efforts of combining rules languages and description logics usually produce undecidable formalisms, unless constrained in a specific way. We look at one of the most expressive but decidable such formalisms proposed: DL-safe rules, and present a tableaux-based algorithm for query answering...