Stable feature selection based on instance learning,redundancy elimination and efficient subsets fusion

Neural Computing and Applications - Feature selection is frequently used as a preprocessing step to data mining and is attracting growing attention due to the increasing amounts of data emerging...     

Phase structure and mechanical properties of PP/EPR/CaCO3 nanocomposites: Effect of particle's size and treatment

Calcium carbonate (CaCO₃) reinforced polypropylene/ethylene propylene rubber (PP/EPR) copolymer composites for automotive use were developed by means of extrusion and injection molding process. Three kinds of CaCO₃ (stearic acid treated and untreated) nanoparticles and microparticles were used as fillers. The influence of stearic acid, particle size, and filler content on the state distribution and morphology were investigated by SEM and rheological measurements. Two different morphologies were observed: EPR and CaCO₃ dispersed in the PP matrix and a core shell structure, depending on the interactions between EPR and CaCO₃. Toughening mechanisms and mechanical properties of the different systems were investigated. Significant improvement in tensile modulus is observed in all composites, depending on filler content. Elongation and notched impact strength were drastically decreased, especially for composites with nano CaCO₃. Better impact properties were obtained with low content of treated particles, showing the importance of filler treatment. POLYM. ENG. SCI., 55:2859–2868, 2015. © 2015 Society of Plastics Engineers     

A multi-level conceptual data reduction approach based on the Lukasiewicz implication

Starting from fuzzy binary data represented as tables in the fuzzy relational database, in this paper, we use fuzzy formal concept analysis to reduce the tables size to only keep the minimal rows in each table, without losing knowledge (i.e., association rules extracted from reduced databases are identical at given precision level). More specifically, we develop a fuzzy extension of a previously proposed algorithm for crisp data reduction without loss of knowledge. The fuzzy Galois connection based on the Lukasiewicz implication is mainly used in the definition of the closure operator according to a precision level, which makes data reduction sensitive to the variation of this precision level.     

Consistency requirements in business process modeling: a thorough overview

Software and Systems Modeling - The field of business process modeling has been beset by inter-model consistency problems which are mainly due to the existence of multiple variants of the same...     

Delay-dependent Stabilization Conditions of Controlled Positive Continuous-time Systems

The stabilization problem for a class of linear continuous-time systems with time-varying non differentiable delay is solved while imposing positivity in closed-loop. In particular, the synthesis of state-feedback controllers is studied by giving sufficient conditions in terms of linear matrix inequalities(LMIs). The obtained results are then extended to systems with non positive delay matrix by applying a memory controller. The effectiveness of the proposed method is shown by using numerical examples.     

A recursive hierarchical parametric estimation algorithm for nonlinear systems described by Wiener‐Hammerstein models

In this paper, a recursive hierarchical parametric estimation (RHPE) algorithm is proposed for stochastic nonlinear systems which can be described by Wiener‐Hammerstein (W‐H) mathematical models. The formulation of parameters estimation problem is based on the prediction error approach and the gradient techniques. The convergence analysis of the developed RHPE algorithm is derived using stochastic gradient‐based theory. Wiener‐Hammerstein hydraulic process is treated to prove the efficiency of the proposed approach.