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...     

Robust tools for prediction of variability and optimization in structural dynamics

The aims of this work were to quantify the effects of uncertainties of design parameters on the variability of linear and non-linear behaviour of mechanical structures that we wish to optimize, and to calculate optimal and robust solutions resulting from numerical simulations. We propose a method that takes into account the propagation of uncertainties in finite-element models in a multi-objective optimization procedure. This method is based on coupling the stochastic response surface method (SRSM) and the non-dominated sorting genetic algorithm (NSGA). SRSM is based on application of the stochastic finite-element method via the polynomial chaos expansion method or the modal perturbation method. This strategy avoids the use of Monte Carlo simulation, in which costs can become prohibitive in optimization problems, especially when the finite-element models are large and have a considerable number of design parameters. The robust design described here has been developed to obtain an optimum value that is insensitive to changes of design variables within a feasible range.     

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...     

Stereoscopic video watermarking: a comparative study

Despite the sound theoretical, methodological, and experimental background inherited from 2D video, the stereoscopic video watermarking imposed itself as an open research topic. Paving the way towards practical deployment of such copyright protection mechanisms, the present paper is structured as a comparative study on the main classes of 2D watermarking methods (spread spectrum, side information, hybrid) and on their related optimal stereoscopic insertion domains (view or disparity based). The performances are evaluated in terms of transparency, robustness, and computational cost. First, the watermarked content transparency is assessed by both subjective protocols (according to ITU-R BT 500-12 and BT 1438 recommendations) and objective quality measures (five metrics based on differences between pixels and on correlation). Secondly, the robustness is objectively expressed by means of the watermark detection bit error rate against several classes of attacks, such as linear and nonlinear filtering, compression, and geometric transformations. Thirdly, the computational cost is estimated for each processing step involved in the watermarking chain. All the quantitative results are obtained out of processing two corpora of stereoscopic visual content: (1) the 3DLive corpus, summing up about 2 h of 3D TV content captured by French professionals, and (2) the MPEG 3D video reference corpus, composed of 17 min provided by both academic communities and industrials. It was thus established that for a fixed size of the mark, a hybrid watermark insertion performed into a new disparity map representation is the only solution jointly featuring imperceptibility (according to the subjective tests), robustness against the three classes of attacks, and nonprohibitive computational cost.     

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.     

A fault tolerant tracking control for a quadrotor UAV subject to simultaneous actuator faults and exogenous disturbances

ABSTRACT

An observer-based robust adaptive Fault Tolerant Control approach is proposed in this paper to tackle the problem of trajectory tracking for a quadrotor unmanned aerial vehicle (UAV) suffering simultaneous actuator faults, exogenous disturbances and actuator saturation limits. An adaptive fuzzy state observer is proposed to estimate the immeasurable states by using fuzzy logic systems to approximate the unknown nonlinear functions of the uncertain system model. Based on the estimates of the fuzzy observer, an Integral Terminal Sliding Mode Controller that guarantees finite time convergence of the states to a small neighbourhood of zero, even under impaired conditions, is developed. Stability analysis was carried over using the Lyapunov method. The proposed approach was implemented to a quadrotor UAV and its performance was assessed under nominal conditions, and by subjecting the quadrotor to disturbances, simultaneously occurring actuator faults and input saturation limits. Excellent tracking performance and robustness even under worst-case scenarios are among the positive features of the proposed approach.