in this study, an optimization model is proposed to design a global supply chain (gsc) for a medical device manufacturer under disruption in the presence of pre-existing competitors and price inelasticity of demand. therefore, static competition between the distributors’ facilities to more efficiently gain a further share in market of economic cooperation organization trade agreement (ecota) is...

The local Whittle (or Gaussian semiparametric) estimator of long range dependence, proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of convergence and a finite sample bias that can be large. In this paper, we generalize the local Whittle estimator to circumvent these problems. Instead of approximating the short-run component of the spectrum, φ(λ), by a cons...

Abstract: The problem of estimating the centre of symmetry of an unknown periodic function observed in Gaussian white noise is considered. Using the penalized blockwise Stein method, a smoothing filter allowing to define the penalized profile likelihood is proposed. The estimator of the centre of symmetry is then the maximizer of this penalized profile likelihood. This estimator is shown to be ...

Based on the Minimum Variance Distortionless Response-Sample Matrix Inversion (MVDRSMI) method, we propose a novel Adaptive Covariance Estimator (MVDR-ACE) beamformer for adaptation to multiple interference environments. The MVDR-ACE beamformer iteratively determines a minimum number of data samples required while maintaining its average signal-to-interference-noise to be within 3 dB from the p...

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identificati...

Blind source separation (BSS) aims to recover a set of statistically independent source signals from a set of linear mixtures of the same sources. In the noiseless real-mixture two-source two-sensor scenario, once the observations are whitened (decorrelated and normalized), only a Givens rotation matrix remains to be identified in order to achieve the source separation. In this paper, an adapti...

This paper considers output estimator based fault detection problem for a class of nonlinear systems with unknown system parameters. Because observer design for such systems is extremely difficult if not impossible, output estimator design is used for the purpose of fault detection. In order to achieve output estimator design using adaptive approaches, a multi-input multi-output (MIMO) nonlinea...

Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented with a particular focus on its adaptive features. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic nonlinear macroscopic traffic flow modeling and extended Kalman filtering. One major innovative aspect...