Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Temporally adaptive estimation of logistic classifiers on data streams

Modern technology has allowed real-time data collection in a variety of domains, ranging from environmental monitoring to healthcare. Consequently, there is a growing need for algorithms capable of performing inferential tasks in an online manner, continuously revising their estimates to reflect the current status of the underlying process. In particular, we are interested in constructing online and temporally adaptive classifiers capable of handling the possibly drifting decision boundaries arising in streaming environments. We first make a quadratic approximation to the log-likelihood that yields a recursive algorithm for fitting logistic regression online. We then suggest a novel way of equipping this framework with self-tuning forgetting factors. The resulting scheme is capable of tracking changes in the underlying probability distribution, adapting the decision boundary appropriately and hence maintaining high classification accuracy in dynamic or unstable environments. We demonstrate the scheme's effectiveness in both real and simulated streaming environments. © Springer-Verlag 2009.

A general design method for electric machines using magnetic circuit model considering the flux saturation problem

This paper proposes an analytical approach that is generalized for the design of various types of electric machines based on a physical magnetic circuit model. Conventional approaches have been used to predict the behavior of electric machines but have limitations in accurate flux saturation analysis and hence machine dimensioning at the initial design stage. In particular, magnetic saturation is generally ignored or compensated by correction factors in simplified models since it is difficult to determine the flux in each stator tooth for machines with any slot-pole combinations. In this paper, the flux produced by stator winding currents can be calculated accurately and rapidly for each stator tooth using the developed model, taking saturation into account. This aids machine dimensioning without the need for a computationally expensive finite element analysis (FEA). A 48-slot machine operated in induction and doubly-fed modes is used to demonstrate the proposed model. FEA is employed for verification.

Fracture and energy partitioning in uncooked and cooked noodles

Humans perform fascinating science experiments at home on a daily basis when they undertake the modification of natural and naturally-derived materials by a cooking process prior to consumption. The material properties of such foods are of interest to food scientists (texture is often fundamental to food acceptability), oral biologists (foods modulate feeding behavior), anthropologists (cooking is probably as old as the genus Homo and distinguishes us from all other creatures) and dentists (foods interact with tooth and tooth replacement materials). Materials scientists may be interested in the drastic changes in food properties observed over relatively short cooking times. In the current study, the mechanical properties of one of the most common (and oldest at 4,000+ years) foods on earth, the noodle, were examined as a function of cooking time. Two types of noodles were studied, each made from natural materials (wheat flour, salt, alkali and water) by kneading dough and passing them through a pasta-making machine. These were boiled for between 2-14 min and tested at regular intervals from raw to an overcooked state. Cyclic tensile tests at small strain levels were used to examine energy dissipation characteristics. Energy dissipation was >50% per cycle in uncooked noodles, but decreased by an order of magnitude with cooking. Fractional dissipation values remained approximately constant at cooking times greater than 7 min. Overall, a greater effect of cooking was on viscoplastic dissipation characteristics rather than on fracture resistance. The results of the current study plot the evolution of a viscoplastic mixture into an essentially elastic material in the space of 7 minutes and have broad implications for understanding what cooking does to food materials. In particular, they suggest that textural assessment by consumers of the optimally cooked state of food has a definite physical definition. © 2007 Materials Research Society.

High-order DES and zonal LES of a labyrinth seal

Hybrid numerical large eddy simulation (NLES) and detached eddy simulation (DES) methods are assessed on a labyrinth seal geometry. A high sixth order discretization scheme is used and is validated using a test case of a two dimensional vortex. The hybrid approach adopts a new blending function and along with DES is initially validated using a simple cavity flow. The NLES method is also validated outside of RANS zones. It is found that there is very little resolved turbulence in the cavity for the DES simulation. For the labyrinth seal calculations the DES approach is problematic giving virtually no resolved turbulence content. It is seen that over the tooth tips the extent of the LES region is small and is likely to be a strong contributor to excessive flow damping in these regions. On the other hand the zonal Hamilton-Jacobi approach did not suffer from this trait. In both cases the meshes used are considered to be hybrid RANS-LES adequate. Fortunately (or perhaps unfortunately) the DES profiles are in agreement with the time mean experimental measurements. It is concluded that for an inexperienced CFD practitioner this could have wider implications particularly if transient results such as unsteady loading are desired. Copyright © 2012 by the American Institute of Aeronautics and Astronautics, Inc.

Characteristics of the spectral dynamics of picosecond modulated AlGaAs/GaAs injection lasers

Breakdown of the optical spectrum of a train of picosecond pulses into components with a distance which exceeds kT (200 cm-1 at λ = 955 nm and T = 300 K) is discovered for the first time in an injection laser. The effect may be caused by combined interaction between photons and phonons, with collective excitations in the degraded electron-hole GaAs plasma, and with the stream of drifting carriers in the active medium of the laser.