Expert systems applications that involve uncertain inference can be represented by a multidimensional contingency table. These tables offer a general approach to inferring with uncertain evidence, because they can embody any form of association between any number of pieces of evidence and conclusions. (Simpler models may be required, however, if the number of pieces of evidence bearing on a con...

Abstract Multiple imputation is a commonly used approach to deal with missing values. In this approach, an imputer repeatedly imputes the missing values by taking draws from the posterior predictive distribution for the missing values conditional on the observed values, and releases these completed data sets to analysts. With each completed data set the analyst performs the analysis of interest...

In this paper cascaded reduction and growing of result sets is introduced as a principle for combining the results of different object detectors. First, different candidate operating points are selected for each object detection algorithm. This procedure is based on the analysis of precision and recall of the individual methods. Selecting an appropriate operating point prior to fusion is import...

Domain-specific Internet of Things (IoT) applications are becoming more and more popular. They process data coming from sensor measurements. Adding semantic annotations to the sensory observations and measurements can allow to reason on data via logical rules. Stemming from Linked Open Data and Linked Open Vocabularies, we have designed sensor-based Linked Open Rules (S-LOR). S-LOR allows explo...

In this work we present a system for the automatic annotation of opinions in Spanish texts. We focus mainly in the definition of a TFS-style model for the predicates of opinion and their arguments, in the creation of a lexicon of opinion predicates and in two additional variants for identifying the source of opinions. The original system extracts opinions and all its elements (predicate, source...

Unlike fixed combining rules, the trainable combiner is applicable to ensembles of diverse base classifier architectures with incomparable outputs. The trainable combiner, however, requires the additional step of deriving a second-stage training dataset from the base classifier outputs. Although several strategies have been devised, it is thus far unclear which is superior for a given situation...

New combining rules are proposed for the well depth, E , and interaction distance, a, describing nonbonded interatomic forces for rare gas pair interactions. Concepts underlying current combining rules applied in simulations of macromolecular and polymer systems are shown to be incompatible with experimental data on the rare gases. The current combining rules are compared with the new results u...

In this paper, we present an investigation into the combination of rules for text categorization using Dempster’s rule of combination. We first propose a boosting-like technique for generating multiple sets of rules based on rough set theory, and then describe how to use Dempster’s rule of combination to combine the classification decisions produced by multiple sets of rules. We apply these met...

The main objective of this study was to examine the role of neural activity in the development of cell layers in the dorsal lateral geniculate nucleus (LGN). We studied this relationship in postnatal tree shrews either by completely blocking retinal ganglion cell activity with TTX or by selectively blocking activity to the developing ON-center LGN layers (1 and 2) with 2-amino-4-phosphonobutyri...

Two-way communication is a key feature in a smart grid. It is enabled by either powerline communication or wireless communication technologies. Utilizing both technologies can potentially enhance communication reliability, and many diversity combining schemes have been proposed. In this paper, we propose a flexible real-time testbed to evaluate diversity combining schemes over physical channels...