Extracting generic bases of association rules seems to be a promising issue in order to present informative and compact user addedvalue knowledge. However, extracting generic bases requires partially ordering costly computed itemset closures. To avoid the nightmarish itemset closure computation cost, specially for sparse contexts, we introduce an algorithm, called Prince, allowing an astute ext...

We derive a Feynman-Kac formula for functionals of a stochastic hybrid system evolving according to a piecewise deterministic Markov process. We first derive a stochastic Liouville equation for the moment generator of the stochastic functional, given a particular realization of the underlying discrete Markov process; the latter generates transitions between different dynamical equations for the...

A model for piezoelectric vibration energy harvesting with a piezoelectric cantilever beam is presented. The model incorporates expressions for variable geometry, tip mass, and material constants, and allows the parameterized determination of the voltage and power produced over a purely resistive load. The model is of a lumped-element form, with the base excitation acceleration and voltage repr...

In this paper, we show how the OMG’s metamodelling approach to domain-specific language definition can be exploited to infer human-usable textual notations (concrete syntaxes) from the conceptualization provided by metamodels (abstract syntaxes). We give general rules to derive a context-free EBNF (Extended Backus-Naur Form) grammar from a MOF-compliant metamodel, and we show how to instruct a ...

The problem of Intelligent Machine Draft ing is presented, and a description of an existing implementation as part of a graphical generator function is given. The concept of Graphical Deep Knowledge is defined as a representational basis for Intelligent Machine Draft ing problems as wel l as for physical object displays. A (partial) task domain analysis for Graphical Deep Knowledge is presented...

One way of verifying a grammar is the detection of ambiguities. Ambiguities are not always unwanted, but they can only be controlled if their sources are known. Unfortunately, the ambiguity problem for context-free grammars is undecidable in the general case. Various ambiguity detection methods (ADMs) exist, but they can never be perfect. In this paper we explore three ADMs to test whether they...

The Gini index (GI), GI II, and III are proven to be effective sparsity measures in the fields of machine condition monitoring fault diagnosis, they can reformulated as ratio different quasi-arithmetic means (RQAM). Under this framework, generalized indices (GGIs) have been developed for sparse quantification by applying nonlinear weights GI, another form referred here power function-based I (P...

This a r t i c l e i n t r o d u c e s a b i d i r e c t i o n a l g r a m m a r genera t ion sys tem called fea ture s t ructure-directed generat ion, developed for a d ia logue t rans la t ion sys tem. The sys tem utilizes typed feature structures to control the top-down derivation in a declarative way. This generation system also uses disjunctive feature structures to reduce the number of co...

FINGER iS a Lisp-based system to derive formulas needed in finite element analysis, and to generate FORTRAN code from these formulas. The generated programs can be used with existing, FORTRAN-based finite element analysis packages. This approach aims to replace tedious hand computations that are time consuming and error prone. The design and implementation of FINGER are presented. Techniques fo...

This paper discusses recent developments for pattern recognition focusing on boosting approach in machine learning. The statistical properties such as Bayes risk consistency for several loss functions are discussed in a probabilistic framework. There are a number of loss functions proposed for different purposes and targets. A unified derivation is given by a generator function U which naturall...