A class of self-stabilizing MCA learning algorithms

In this letter, we propose a class of self-stabilizing learning algorithms for minor component analysis (MCA), which includes a few well-known MCA learning algorithms. Self-stabilizing means that the sign of the weight vector length change is independent of the presented input vector. For these algorithms, rigorous global convergence proof is given and the convergence rate is also discussed. By combining the positive properties of these algorithms, a new learning algorithm is proposed which can improve the performance. Simulations are employed to confirm our theoretical results.

Test–retest repeatability of self-reported environmental exposures in Parkinson’s disease cases and healthy controls

There is substantial disagreement among published epidemiological studies regarding environmental risk factors for Parkinson’s disease (PD). Differences in the quality of measurement of environmental exposures may contribute to this variation. The current study examined the test–retest repeatability of self-report data on risk factors for PD obtained from a series of 32 PD cases recruited from neurology clinics and 29 healthy sex-, age-and residential suburb-matched controls. Exposure data were collected in face-to-face interviews using a structured questionnaire derived from previous epidemiological studies. High repeatability was demonstrated for ‘lifestyle’ exposures, such as smoking and coffee/tea consumption (kappas 0.70–1.00). Environmental exposures that involved some action by the person, such as pesticide application and use of solvents and metals, also showed high repeatability (kappas>0.78). Lower repeatability was seen for rural residency and bore water consumption (kappa 0.39–0.74). In general, we found that case and control participants provided similar rates of incongruent and missing responses for categorical and continuous occupational, domestic, lifestyle and medical exposures.

Atomic Latin squares of order eleven

A Latin square is pan-Hamiltonian if the permutation which defines row i relative to row j consists of a single cycle for every i j. A Latin square is atomic if all of its conjugates are pan-Hamiltonian. We give a complete enumeration of atomic squares for order 11, the smallest order for which there are examples distinct from the cyclic group. We find that there are seven main classes, including the three that were previously known. A perfect 1-factorization of a graph is a decomposition of that graph into matchings such that the union of any two matchings is a Hamiltonian cycle. Each pan-Hamiltonian Latin square of order n describes a perfect 1-factorization of Kn,n, and vice versa. Perfect 1-factorizations of Kn,n can be constructed from a perfect 1-factorization of Kn+1. Six of the seven main classes of atomic squares of order 11 can be obtained in this way. For each atomic square of order 11, we find the largest set of Mutually Orthogonal Latin Squares (MOLS) involving that square. We discuss algorithms for counting orthogonal mates, and discover the number of orthogonal mates possessed by the cyclic squares of orders up to 11 and by Parker's famous turn-square. We find that the number of atomic orthogonal mates possessed by a Latin square is not a main class invariant. We also define a new sort of Latin square, called a pairing square, which is mapped to its transpose by an involution acting on the symbols. We show that pairing squares are often orthogonal mates for symmetric Latin squares. Finally, we discover connections between our atomic squares and Franklin's diagonally cyclic self-orthogonal squares, and we correct a theorem of Longyear which uses tactical representations to identify self-orthogonal Latin squares in the same main class as a given Latin square.

Effect of multiple transverse modes in self-mixing sensors based on vertical-cavity surface-emitting lasers

We investigate the effect of coexisting transverse modes on the operation of self-mixing sensors based on vertical-cavity surface-emitting lasers (VCSELs). The effect of multiple transverse modes on the measurement of displacement and distance were examined by simulation and in laboratory experiment. The simulation model shows that the periodic change in the shape and magnitude of the self-mixing signal with modulation current can be properly explained by the different frequency-modulation coefficients of the respective transverse modes in VCSELs. The simulation results are in excellent agreement with measurements performed on single-mode and multimode VCSELs and on self-mixing sensors based on these VCSELs.

Algorithms for sequence analysis via mutagenesis

Despite many successes of conventional DNA sequencing methods, some DNAs remain difficult or impossible to sequence. Unsequenceable regions occur in the genomes of many biologically important organisms, including the human genome. Such regions range in length from tens to millions of bases, and may contain valuable information such as the sequences of important genes. The authors have recently developed a technique that renders a wide range of problematic DNAs amenable to sequencing. The technique is known as sequence analysis via mutagenesis (SAM). This paper presents a number of algorithms for analysing and interpreting data generated by this technique.

Emotional Intelligence, emotional Self-Awareness, and Team Effectiveness

An issue at the forefront of recent emotional intelligence debates revolves around whether emotional intelligence can be linked to work performance. Although many authors continue to develop new and improved measures of emotional intelligence (e.g. Mayer, Caruso, & Salovey, 2001) to give us a better understanding of emotional intelligence, the links to performance in work settings, especially in the context of group effectiveness, have received much less attention. In this chapter, we present the results of a study in which we examined the role of emotional self-awareness and emotional intelligence as a predictor of group effectiveness. The study also addresses the utility of self- and peer assessment in measureing emotional self-awareness and emotional intelligence.

Surface Waves and Roughness in Self-Aerated Supercritical Flow

In high-velocity open channel flows, free-surface aeration is commonly observed. The effects of surface waves on the air-water flow properties are tested herein. The study simulates the air-water flow past a fixed-location phase-detection probe by introducing random fluctuations of the flow depth. The present model yields results that are close to experimental observations in terms of void fraction, bubble count rate and bubble/droplet chord size distributions. The results show that the surface waves have relatively little impact on the void fraction profiles, but that the bubble count rate profiles and the distributions of bubble and chord sizes are affected by the presence of surface waves.

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Self-Similarity of Air-Water Flows in Skimming Flows on Stepped Spillways

Skimming flows on stepped spillways are characterised by a significant rate of turbulent dissipation on the chute. Herein an advanced signal processing of traditional conductivity probe signals is developed to provide further details on the turbulent time and length scales. The technique is applied to a 22° stepped chute operating with flow Reynolds numbers between 3.8 and 7.1 E+5. The new correlation analyses yielded a characterisation of large eddies advecting the bubbles. The turbulent length scales were related to the characteristic depth Y90. Some self-similar relationships were observed systematically at both macroscopic and microscopic levels. These included the distributions of void fraction, bubble count rate, interfacial velocity and turbulence level, and turbulence time and length scales. The self-similarity results were significant because they provided a picture general enough to be used to characterise the air-water flow field in prototype spillways.

Fast evolution strategies

Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, the primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations. A new mutation operator based on the Cauchy distribution is proposed in this paper. It is shown empirically that the new evolution strategy based on Cauchy mutation outperforms the classical evolution strategy on most of the 23 benchmark problems tested in this paper. The paper also shows empirically that changing the order of mutating the objective variables and mutating the strategy parameters does not alter the previous conclusion significantly, and that Cauchy mutations with different scaling parameters still outperform the Gaussian mutation with self-adaptation. However, the advantage of Cauchy mutations disappears when recombination is used in evolution strategies. It is argued that the search step size plays an important role in determining evolution strategies' performance. The large step size of recombination plays a similar role as Cauchy mutation.