Predicting oil recovery efficiency of a deepwater reservoir is a challenging task. One approach to characterize a deepwater reservoir and to predict its producibility is by analyzing its depositional information. This research proposes a deposition-based stratigraphic interpretation framework for deepwater reservoir characterization. In this framework, one critical task is the identification an...

This paper presents an application of finite state transducers weighted with feature structure descriptions, following Amtrup (2003), to the morphology of the Semitic language Tigrinya. It is shown that feature-structure weights provide an efficient way of handling the templatic morphology that characterizes Semitic verb stems as well as the long-distance dependencies characterizing the complex...

We present a new algorithm deciding for strings t and w whether w is an approximate generator of t with Levenshtein distance at most k. The algorithm is based on finite state transducers.

The paper describes a rule-based approach for hypernym and hyponym extraction from Russian texts. For this task we employ finite state transducers (FSTs). We developed 6 finite state transducers that encode 6 lexicosyntactic patterns, which show a good precision on Russian DBpedia: 79.5% of the matched contexts are correct.

This paper introduces a two-way Urdu– Roman transliterator based solely on a nonprobabilistic finite state transducer that solves the encountered scriptural issues via a particular architectural design in combination with a set of restrictions. In order to deal with the enormous amount of overgenerations caused by inherent properties of the Urdu script, the transliterator depends on a set of ph...

We show that the information rate of the language accepted by a reversalbounded deterministic counter machine is computable. For the nondeterministic case, we provide computable upper bounds. For the class of languages accepted by multi-tape deterministic finite automata, the information rate is computable as well.

Finite State Machines (FSM) are a fundamental building block in computer architecture, and are used to control and optimize all types of prediction and speculation, now even in the embedded space. They are used for branch prediction, cache replacement policies, and confidence estimation and accuracy counters for a variety of optimizations. In this paper, we present a framework for automated des...

Slicing is a technique, traditionally applied to programs, for extracting the parts of a program that affect the values computed at a statement of interest. In recent years authors have begun to consider slicing at the model level. We present a detailed review of existing work on slicing at the level of finite state machine-based models. We focus on state based modelling notations because these...

Given the prominence of finite-state techniques in natural language processing, toolkits are required that can provide finite-state capability for applications in this domain. For example, work in the context of Multi-Agent Speech Recognition requires such finite-state capability. In particular, an interface is required both for processing finite-state representations and for automatically acqu...