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The article shows the role occupied by the favela and its residents in political and social debate during the first half of the 20th Century. It highlights the production of knowledge generated by journalists, physicians...

The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more or less the different explanatory factors ...

In this article we will introduce certain considerations that must be taken into account while implementing the change operations of the belief change theory. The abstract models of bellief change make no considerations ...

The present article introduces a five-valued logic and a deductive system. Here, the logic presented is a relevant fragment of the @-logic, which is also a space-time logic. These five values correspond to the following ...

Materias / palabras clave: Computer science; Software portability; Implementation; Ontology; Programming language; Vocabulary; Reuse; Knowledge representation and reasoning; Natural language processing; Ontology language; Software engineering; Art...

Abstract In the early 1980s, a strategy for graphical representation of multivariate (multi‐species) abundance data was introduced into marine ecology by, among others, Field, et al. (1982). A decade on, it is instruct...

Materias / palabras clave: Hierarchy; Scaling; Eigenvalues and eigenvectors; Pairwise comparison; Consistency (knowledge bases); Matrix (chemical analysis); Mathematics; Scale (ratio); Multidimensional scaling; Measure (data warehouse); Representa...

Abstract ERA‐Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF). The ERA‐Interim project was conducted in part to prepare for a new atmosp...

In a multi-agent system, a group of individ- uals interact in a social context in order to boost their capabilities and enhance global per- formance. Each individual's action repertoire may be reduced, but it's social ca...

Implicitly exploitable parallelism for Logic Programming has received ample attention. Defeasible Argutmentation is specially apt for this optimizing technique. Defeasible Logic Programming (DLP), which is based on a def...

Software radios are emerging as platforms for multiband multimode personal communications systems. Radio etiquette is the set of RF bands, air interfaces, protocols, and spatial and temporal patterns that moderate the us...

With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding ...

When certain enterprise domain needs to make an unusual decision, it will probably require new kind of information. If the interaction model among domains cannot be defined because the decision scenarios are unpredictabl...

Part 1 The lexical database: nouns in WordNet, George A. Miller modifiers in WordNet, Katherine J. Miller a semantic network of English verbs, Christiane Fellbaum design and implementation of the WordNet lexical database...

We derive a new self-organizing learning algorithm that maximizes the information transferred in a network of nonlinear units. The algorithm does not assume any knowledge of the input distributions, and is defined here f...

Suppose x is an unknown vector in Ropf m (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform...

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the...

Molecular structure does not easily identify the intricate noncovalent interactions that govern many areas of biology and chemistry, including design of new materials and drugs. We develop an approach to detect noncovale...

Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist Temporal Classification make it possible to train RNNs for sequence labelling problems where th...