Value of information in product recovery decisions: A Bayesian approach

There is a widespread recognition of the need for better information sharing and provision to improve the viability of end-of-life (EOL) product recovery operations. The emergence of automated data capture and sharing technologies such as RFID, sensors and networked databases has enhanced the ability to make product information; available to recoverers, which will help them make better decisions regarding the choice of recovery option for EOL products. However, these technologies come with a cost attached to it, and hence the question 'what is its value?' is critical. This paper presents a probabilistic approach to model product recovery decisions and extends the concept of Bayes' factor for quantifying the impact of product information on the effectiveness of these decisions. Further, we provide a quantitative examination of the factors that influence the value of product information, this value depends on three factors: (i) penalties for Type I and Type II errors of judgement regarding product quality; (ii) prevalent uncertainty regarding product quality and (iii) the strength of the information to support/contradict the belief. Furthermore, we show that information is not valuable under all circumstances and derive conditions for achieving a positive value of information. © 2010 Taylor & Francis.

Hybridisation platform demonstrating all optical wavelength conversion at 10 and 20Gbit/s

The development of a high performance hybrid integration platform is demonstrated using an all optical wavelength converter based on an integrated SOA MZI. The device structure, transfer functions, power penalties and regenerative properties are presented. © 2004 Optical Society of America.

Wavelength conversion based on an integrated semiconductor optical amplifier/DFB laser at 10 Gb/s with low input power

A study of the relative performance of an integrated semiconductor optical amplifier (SOA)/distributed feedback laser wavelength converter that can operate with negative penalties at 10 Gb/s rates is conducted. It is found that reduction of more than 25 times in required input powers are achieved when compared with laser or SOA converters.

Experimental demonstration of a record high 11.25Gb/s real-time optical OFDM transceiver supporting 25km SMF end-to-end transmission in simple IMDD systems.

The fastest ever 11.25Gb/s real-time FPGA-based optical orthogonal frequency division multiplexing (OOFDM) transceivers utilizing 64-QAM encoding/decoding and significantly improved variable power loading are experimentally demonstrated, for the first time, incorporating advanced functionalities of on-line performance monitoring, live system parameter optimization and channel estimation. Real-time end-to-end transmission of an 11.25Gb/s 64-QAM-encoded OOFDM signal with a high electrical spectral efficiency of 5.625bit/s/Hz over 25km of standard and MetroCor single-mode fibres is successfully achieved with respective power penalties of 0.3dB and -0.2dB at a BER of 1.0 x 10(-3) in a directly modulated DFB laser-based intensity modulation and direct detection system without in-line optical amplification and chromatic dispersion compensation. The impacts of variable power loading as well as electrical and optical components on the transmission performance of the demonstrated transceivers are experimentally explored in detail. In addition, numerical simulations also show that variable power loading is an extremely effective means of escalating system performance to its maximum potential.

Min-Max Moving Horizon Estimation for a Class of Hybrid Systems

In this paper, a strategy for min-max Moving Horizon Estimation (MHE) of a class of uncertain hybrid systems is proposed. The class of hybrid systems being considered are Piecewise Affine systems (PWA) with both continuous valued and logic components. Furthermore, we consider the case when there is a (possibly structured) norm bounded uncertainty in each subsystem. Sufficient conditions on the time horizon and the penalties on the state at the beginning of the estimation horizon to guarantee convergence of the MHE scheme will be provided. The MHE scheme will be implemented as a mixed integer semidefinite optimisation for which an efficient algorithm was recently introduced.

Convex approaches to model wavelet sparsity patterns

Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing of the simple Markovian dependency structure. This leads to reconstruction problems that are non-convex optimizations. Past work has dealt with this issue by resorting to greedy or suboptimal iterative reconstruction methods. In this paper, we propose new modeling approaches based on group-sparsity penalties that leads to convex optimizations that can be solved exactly and efficiently. We show that the methods we develop perform significantly better in de-convolution and compressed sensing applications, while being as computationally efficient as standard coefficient-wise approaches such as lasso. © 2011 IEEE.

Improved bounds for subband-adaptive iterative shrinkage/thresholding algorithms.

This paper presents new methods for computing the step sizes of the subband-adaptive iterative shrinkage-thresholding algorithms proposed by Bayram & Selesnick and Vonesch & Unser. The method yields tighter wavelet-domain bounds of the system matrix, thus leading to improved convergence speeds. It is directly applicable to non-redundant wavelet bases, and we also adapt it for cases of redundant frames. It turns out that the simplest and most intuitive setting for the step sizes that ignores subband aliasing is often satisfactory in practice. We show that our methods can be used to advantage with reweighted least squares penalty functions as well as L1 penalties. We emphasize that the algorithms presented here are suitable for performing inverse filtering on very large datasets, including 3D data, since inversions are applied only to diagonal matrices and fast transforms are used to achieve all matrix-vector products.

Exhaust gas ignition (EGI)-a new concept for rapid light-off of automotive exhaust catalyst

Increasing pressure on lowering vehicle exhaust emissions to meet stringent California and Federal 1993/1994 TLEV emission standards of 0.125 gpm NMOG, 3.4 gpm CO and 0.4 gpm NOx and future ULEV emission standards of 0.04 gpm NMOG, 1.7 gpm CO and 0.2 gpm NOx has focused specific attention on the cold start characteristics of the vehicle's emission system, especially the catalytic converter. From test data it is evident that the major portion of the total HC and CO emissions occur within the first two minutes of the driving cycle while the catalyst is heating up to operating temperature. The use of an electrically heated catalyst (EHC) has been proposed to alleviate this problem but the cost and weight penalties are high and the durability has yet to be fully demonstrated (1)*. This paper describes a method of reducing the light-off time of the catalytic converter to less than 20 seconds by means of an afterburner. The system uses exhaust gases from the engine calibrated to run rich and additional air injected into the exhaust gas stream to form a combustible mixture. The key feature concerns the method of making this combustible mixture ignitable within 2 seconds from starting the engine when the exhaust gases arriving at the afterburner are cold and essentially non-reacting. © Copyright 1992 Society of Automotive Engineers, Inc.

Monolithic MZI-SOA hybrid switch for low-power and low-penalty operation.

We report the first experimental demonstration of a monolithically integrated hybrid dilated 2×2 modular optical switch using Mach-Zehnder modulators as low-loss 1×2 switching elements and short semiconductor optical amplifiers to provide additional extinction and gain. An excellent 40 dB cross-talk/extinction ratio is recorded with data-modulated signal-to-noise ratios of up to 44 dB in a 0.1 nm bandwidth. A switching time of 3 ns is demonstrated. Bit error rate studies show extremely low subsystem penalties of less than 0.1 dB, and studies indicate that, by using this hybrid switch building block, an 8×8 port switch could be achieved with 14 dB input power dynamic range for subsystem penalties of less than 0.5 dB.

Control of normal shock wave / turbulent boundary-layer interaction using streamwise slots

The effect of streamwise slots on the interaction of a normal shock wave / turbulent boundary layer has been investigated experimentally at a Mach number of 1.3. The surface pressure distribution for the controlled interaction was found to be significantly smeared, featuring a distinct plateau. This was due to a change in shock structure from a typical unseparated normal shock wave boundary layer interaction to a large bifurcated Lambda type shock pattern. Boundary layer velocity measurements downstream of the slots revealed a strong spanwise variation of boundary layer properties whereas the modified shock structure was relatively twodimensional. Oil flow visualisation indicated that in the presence of slots the boundary layer surface flow was highly three dimensional and confirmed that the effect of slots was mainly due to suction and blowing similar to that for passive control with uniform surface ventilation. Three hole probe measurements confirmed that the boundary layer was three dimensional and that the slots introduced vortical motion into the flowfield. Results indicate that when applied to an aerofoil, the control device has the potential to reduce wave drag while incurring only small viscous penalties. The introduction of streamwise vorticity may also be beneficial to delay trailing edge separation and the device is thought to be capable of postponing buffet onset. © 2001 by A N Smith.