Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

A Computational Approach for Simulating P-type Silicon Piezoresistor Using Four Point Bending Setup

The piezoresistance effect is defined as change in resistance due to applied stress. Silicon has a relatively large piezoresistance effect which has been known since 1954. A four point bending setup is proposed and designed to analyze the piezoresistance effect in p-type silicon. This setup is used to apply uniform and uniaxial stress along the <110> crystal direction. The main aim of this work is to investigate the piezoresistive characteristic of p-type resistors as a function of doping concentrations using COMSOL Multiphysics. Simulation results are compared with experimental data.

Cataract surgical outcomes, visual function and quality of life in four rural districts in Vietnam.

BACKGROUND: To evaluate cataract surgical outcomes in four rural districts of Ha Tinh Province, Vietnam. DESIGN: Cross-sectional study. PARTICIPANTS: Post-cataract surgery patients sampled randomly from facilities in four rural districts of Ha Tinh Province >3 months after surgery. MAIN OUTCOME MEASURES: Postoperative visual acuity (VA), visual function and quality of life. RESULTS: Among 412 patients, the mean age was 74.5 ± 9.4 years, 67% (276) were female, and 377 (91.5%) received intraocular lenses (IOL). Nearly two-thirds of patients had no postoperative visits after discharge. Postoperatively, more than 40% of eyes had presenting VA <6/18, while 20% remained <6/60. The mean self-reported visual function and quality of life for all patients were 68.7 ± 23.8 and 73.8 ± 21.6, respectively. Most patients (89.5%) were satisfied with surgery and the majority (94.4%) would recommend surgery to others. One-third of patients paid ≥$US50 for surgery. In multiple regression modelling, older age (P < 0.01), intraoperative complications (P < 0.01) and failure to receive an IOL (P < 0.01) were associated with postoperative VA <6/60. CONCLUSION: Satisfaction with surgery was high, and many patients were willing to pay for their operations. Poor visual outcomes were common; however, and better surgical training is needed to reduce complications and their impact on visual outcomes. More intensive postoperative follow-up may also be beneficial. © 2011 The Authors. Clinical and Experimental Ophthalmology © 2011 Royal Australian and New Zealand College of Ophthalmologists.

Time-resolved four-wave-mixing spectroscopy for inner-valence transitions

Noncollinear four-wave-mixing (FWM) techniques at near-infrared (NIR), visible, and ultraviolet frequencies have been widely used to map vibrational and electronic couplings, typically in complex molecules. However, correlations between spatially localized inner-valence transitions among different sites of a molecule in the extreme ultraviolet (XUV) spectral range have not been observed yet. As an experimental step toward this goal, we perform time-resolved FWM spectroscopy with femtosecond NIR and attosecond XUV pulses. The first two pulses (XUV-NIR) coincide in time and act as coherent excitation fields, while the third pulse (NIR) acts as a probe. As a first application, we show how coupling dynamics between odd- and even-parity, inner-valence excited states of neon can be revealed using a two-dimensional spectral representation. Experimentally obtained results are found to be in good agreement with ab initio time-dependent R-matrix calculations providing the full description of multielectron interactions, as well as few-level model simulations. Future applications of this method also include site-specific probing of electronic processes in molecules.