Expertise and the perception of kinematic and situational probability information

Two experiments were conducted on the nature of expert perception in the sport of squash. In the first experiment, ten expert and fifteen novice players attempted to predict the direction and force of squash strokes from either a film display (occluded at variable time periods before and after the opposing player had struck the ball) or a matched point-light display (containing only the basic kinematic features of the opponent's movement pattern). Experts outperformed the novices under both display conditions, and the same basic time windows that characterised expert and novice pick-up of information in the film task also persisted in the point-light task. This suggests that the experts' perceptual advantage is directly related to their superior pick-up of essential kinematic information. In the second experiment, the vision of six expert and six less skilled players was occluded by remotely triggered liquid-crystal spectacles at quasi-random intervals during simulated match play. Players were required to complete their current stroke even when the display was occluded and their prediction performance was assessed with respect to whether they moved to the correct half of the court to match the direction and depth of the opponent's stroke. Consistent with experiment 1, experts were found to be superior in their advance pick-up of both directional and depth information when the display was occluded during the opponent's hitting action. However, experts also remained better than chance, and clearly superior to less skilled players, in their prediction performance under conditions where occlusion occurred before any significant pre-contact preparatory movement by the opposing player was visible. This additional source of expert superiority is attributable to their superior attunement to the information contained in the situational probabilities and sequential dependences within their opponent's pattern of play.

It's all very well, in theory: Theoretical perspectives and their applications in contemporary pedagogical research

Current debates about educational theory are concerned with the relationship between knowledge and power and thereby issues such as who possesses a truth and how have they arrived at it, what questions are important to ask, and how should they best be answered. As such, these debates revolve around questions of preferred, appropriate, and useful theoretical perspectives. This paper overviews the key theoretical perspectives that are currently used in physical education pedagogy research and considers how these inform the questions we ask and shapes the conduct of research. It also addresses what is contested with respect to these perspectives. The paper concludes with some cautions about allegiances to and use of theories in line with concerns for the applicability of educational research to pressing social issues.

A method to lower the detection limit for optical beat signals from a frequency-dithered stabilized laser

A narrow absorption feature in an atomic or molecular gas (such as iodine or methane) is used as the frequency reference in many stabilized lasers. As part of the stabilization scheme an optical frequency dither is applied to the laser. In optical heterodyne experiments, this dither is transferred to the RF beat signal, reducing the spectral power density and hence the signal to noise ratio over that in the absence of dither. We removed the dither by mixing the raw beat signal with a dithered local oscillator signal. When the dither waveform is matched to that of the reference laser the output signal from the mixer is rendered dither free. Application of this method to a Winters iodine-stabilized helium-neon laser reduced the bandwidth of the beat signal from 6 MHz to 390 kHz, thereby lowering the detection threshold from 5 pW of laser power to 3 pW. In addition, a simple signal detection model is developed which predicts similar threshold reductions.

Quantum noise in optical fibers. I. Stochastic equations

We analyze the quantum dynamics of radiation propagating in a single-mode optical fiber with dispersion, nonlinearity, and Raman coupling to thermal phonons. We start from a fundamental Hamiltonian that includes the principal known nonlinear effects and quantum-noise sources, including linear gain and loss. Both Markovian and frequency-dependent, non-Markovian reservoirs are treated. This treatment allows quantum Langevin equations, which have a classical form except for additional quantum-noise terms, to be calculated. In practical calculations, it is more useful to transform to Wigner or 1P quasi-probability operator representations. These transformations result in stochastic equations that can be analyzed by use of perturbation theory or exact numerical techniques. The results have applications to fiber-optics communications, networking, and sensor technology.

Half-Filled Layered Organic Superconductors and the Resonating-Valence-Bond Theory of the Hubbard-Heisenberg Model

We present a resonating-valence-bond theory of superconductivity for the Hubbard-Heisenberg model on an anisotropic triangular lattice. Our calculations are consistent with the observed phase diagram of the half-filled layered organic superconductors, such as the beta, beta('), kappa, and lambda phases of (BEDT-TTF)(2)X [bis(ethylenedithio)tetrathiafulvalene] and (BETS)(2)X [bis(ethylenedithio)tetraselenafulvalene]. We find a first order transition from a Mott insulator to a d(x)(2)-y(2) superconductor with a small superfluid stiffness and a pseudogap with d(x)(2)-y(2) symmetry.

The effects of Australian tall poppy attitudes on American value based leadership theory

A survey study of twenty-two Australian CEOs and their subordinates assessed relationships between Australian leader motives, Australian value based leader behaviour, subordinate tall poppy attitudes and subordinate commitment, effectiveness, motivation and satisfaction (CEMS). On the whole, the results showed general support for value based leadership processes. Subsequent regression analyses of the second main component of Value Based Leadership Theory, value based leader behaviour, revealed that the collectivistic, inspirational, integrity and visionary behaviour sub-scales of the construct were positively related with subordinate CEMS. Although the hypothesis that subordinate tall poppy attitudes would moderate value based leadership processes was not clearly supported, subsequent regression analyses found that subordinate tall poppy attitudes were negatively related with perceptions of value based leader behaviour and CEMS. These findings suggest complex relationships between the three constructs, and the proposed model for the Australian context is accordingly amended. Overall, the research supports the need to consider cultural-specific attitudes in management development.

Trace Semantics for the Owicki-Gries Theory Integrated with the Progress Logic from UNITY

The theory of Owicki and Gries has been used as a platform for safety-based verifcation and derivation of concurrent programs. It has also been integrated with the progress logic of UNITY which has allowed newer techniques of progress-based verifcation and derivation to be developed. However, a theoretical basis for the integrated theory has thus far been missing. In this paper, we provide a theoretical background for the logic of Owicki and Gries integrated with the logic of progress from UNITY. An operational semantics for the new framework is provided which is used to prove soundness of the progress logic.

What is the Problem of Ad Hoc Hypotheses?

The received view of an ad hoc hypothesis is that it accounts for only the observation(s) it was designed to account for, and so non-adhocness is generally held to be necessary or important for an introduced hypothesis or modification to a theory. Attempts by Popper and several others to convincingly explicate this view, however, prove to be unsuccessful or of doubtful value, and familiar and firmer criteria for evaluating the hypotheses or modified theories so classified are characteristically available. These points are obscured largely because the received view fails to adequately separate psychology from methodology or to recognise ambiguities in the use of 'ad hoc'.

Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Quasi-birth-and-death (QBD) processes with infinite “phase spaces” can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase” giving the state of the first queue and the “level” giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts’s R-matrix and show that the decay rate of the stationary distribution of the “level” process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.

On the construction of nearest neighbour balanced row-column designs

Nearest–neighbour balance is considered a desirable property for an experiment to possess in situations where experimental units are influenced by their neighbours. This paper introduces a measure of the degree of nearest–neighbour balance of a design. The measure is used in an algorithm which generates nearest–neighbour balanced designs and is readily modified to obtain designs with various types of nearest–neighbour balance. Nearest–neighbour balanced designs are produced for a wide class of parameter settings, and in particular for those settings for which such designs cannot be found by existing direct combinatorial methods. In addition, designs with unequal row and column sizes, and designs with border plots are constructed using the approach presented here.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).