Biologically Plausible Connectionist Prediction of Natural Language Thematic Relations

In Natural Language Processing (NLP) symbolic systems, several linguistic phenomena, for instance, the thematic role relationships between sentence constituents, such as AGENT, PATIENT, and LOCATION, can be accounted for by the employment of a rule-based grammar. Another approach to NLP concerns the use of the connectionist model, which has the benefits of learning, generalization and fault tolerance, among others. A third option merges the two previous approaches into a hybrid one: a symbolic thematic theory is used to supply the connectionist network with initial knowledge. Inspired on neuroscience, it is proposed a symbolic-connectionist hybrid system called BIO theta PRED (BIOlogically plausible thematic (theta) symbolic-connectionist PREDictor), designed to reveal the thematic grid assigned to a sentence. Its connectionist architecture comprises, as input, a featural representation of the words (based on the verb/noun WordNet classification and on the classical semantic microfeature representation), and, as output, the thematic grid assigned to the sentence. BIO theta PRED is designed to ""predict"" thematic (semantic) roles assigned to words in a sentence context, employing biologically inspired training algorithm and architecture, and adopting a psycholinguistic view of thematic theory.Fapesp - Fundacao de Amparo a Pesquisa do Estado de Sao Paulo, Brazil[2008/08245-4

Developing predictable and flexible distributed real-time systems

Predictability is considered the most distinguishing characteristic of real-time systems. Besides that, adaptability is also a very important attribute because RT systems are usually designed for long life cycles, during which they will have to cope with change. This paper presents the STER real-time software development environment, designed to support the production of predictable, and yet flexible, distributed real-time systems. Flexibility is one of the main concerns of STER's programming model, based on the construction of reusable software modules. Modules can be reused with different timing constraints without having to be recoded, since the specification of their timing constraints is decoupled from their implementation. Predictable temporal behavior is obtained by an integrated allocation and scheduling strategy that involves off-line and online schedulers. The off-line scheduler tries to satisfy timing, precedence and allocation constraints of periodic hard real-time tasks, and to give the necessary leeway for the dynamic scheduling of aperiodic tasks. The paper shows how distributed programs are translated to scheduling graphs, and gives the results of some experiments conducted to evaluate the performance of the off-line algorithm