A matrix-calculation-based algorithm for numerical change propagation analysis

Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.

An online expectation-maximisation algorithm for nonnegative matrix factorisation models

In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples. © 2012 IFAC.

Droplet Generator

A method and device for periodically perturbing the flow field within a microfluidic device to provide regular droplet formation at high speed.

Comparison of bleed and micro-vortex generator effects on supersonic boundary-layers

An experimental study of bleed and vortex generators in supersonic ow has been conducted. Methods were developed to analyze and directly compare the two systems' effects on turbulent boundary layers to better understand their potential to mitigate ow separation. LDA was used to measure two components of velocity in the boundary-layer for three cases|baseline, with bleed, or with a VG|at Mach numbers of 1.3, 1.5 and 1.8. The bleed system was comprised of a series of 2mm diameter normal holes operated at different suction rates, removing up to 10% of the incoming boundary layer. Three VG shapes were tested only at Mach 1.5 and 1.8. Measurements of the evolution of Hi and Cf downstream of each device indicate that Hi is not an appropriate parameter to gauge the effectiveness of vortex generators due to boundary layer wake distortion. The skin friction coeficient Cf may be a more appropriate measure. Similar increases in Cf were generated by VGs and bleed. The recovery to baseline conditions downstream of bleed was sensitive to Mach number, and more investigation of that effect will be required. Copyright © 2012 by University of Cambridge.

Influence of the matrix properties on the performances of Er-doped Si nanoclusters light emitting devices

We investigated the properties of light emitting devices whose active layer consists of Er-doped Si nanoclusters (nc) generated by thermal annealing of Er-doped SiOx layers prepared by magnetron cosputtering. Differently from a widely used technique such as plasma enhanced chemical vapor deposition, sputtering allows to synthesize Er-doped Si nc embedded in an almost stoichiometric oxide matrix, so as to deeply influence the electroluminescence properties of the devices. Relevant results include the need for an unexpected low Si excess for optimizing the device efficiency and, above all, the strong reduction of the influence of Auger de-excitation, which represents the main nonradiative path which limits the performances of such devices and their application in silicon nanophotonics. © 2010 American Institute of Physics.

Crowbarless fault ride-through of the brushless doubly fed induction generator in a wind turbine under symmetrical voltage dips

The brushless doubly fed induction generator (BDFIG) shows commercial promise for wind power generation due to its lower cost and higher reliability when compared with the conventional DFIG. In the most recent grid codes, wind generators are required to be able to ride through a low-voltage fault and meet the reactive current demand from the grid. A low-voltage ride-through (LVRT) capability is therefore important for wind generators which are integrated into the grid. In this paper, the authors propose a control strategy enabling the BDFIG to successfully ride through a symmetrical voltage dip. The control strategy has been implemented on a 250-kW BDFIG, and the experimental results indicate that the LVRT is possible without a crowbar. © 1982-2012 IEEE.

A Hierarchical Model for Ordinal Matrix Factorization

This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based on Gibbs sampling and one based on variational Bayes. Importantly, these algorithms may be implemented in the factorization of very large matrices with missing entries. The model is evaluated on a collaborative filtering task, where users have rated a collection of movies and the system is asked to predict their ratings for other movies. The Netflix data set is used for evaluation, which consists of around 100 million ratings. Using root mean-squared error (RMSE) as an evaluation metric, results show that the suggested model outperforms alternative factorization techniques. Results also show how Gibbs sampling outperforms variational Bayes on this task, despite the large number of ratings and model parameters. Matlab implementations of the proposed algorithms are available from cogsys.imm.dtu.dk/ordinalmatrixfactorization.

Low-rank optimization for distance matrix completion

This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. The resulting algorithms scale to high-dimensional problems and monotonically converge to a global solution of the problem. Finally, numerical experiments illustrate the good performance of the proposed algorithms on benchmarks. © 2011 IEEE.

Optimization Algorithms on Matrix Manifolds

This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms.