Understanding person acquisition using an interactive activation and competition network

Face perception is one of the most developed visual skills that humans display, and recent work has attempted to examine the mechanisms involved in face perception through noting how neural networks achieve the same performance. The purpose of the present paper is to extend this approach to look not just at human face recognition, but also at human face acquisition. Experiment 1 presents empirical data to describe the acquisition over time of appropriate representations for newly encountered faces. These results are compared with those of Simulation 1, in which a modified IAC network capable of modelling the acquisition process is generated. Experiment 2 and Simulation 2 explore the mechanisms of learning further, and it is demonstrated that the acquisition of a set of associated new facts is easier than the acquisition of individual facts in isolation of one another. This is explained in terms of the advantage gained from additional inputs and mutual reinforcement of developing links within an interactive neural network system. <br/

Neural network trigger algorithms for heavy quark event selection in a fixed target high energy physics experiment

Abstract The study of particles containing heavy quarks is currently a major topic in high energy physics. In this paper, neural net trigger algorithms are developed to distinghish heavy quark (signal) events from light quark (background) events in a fixed target experiment. The event tracks which are parametrized by the impact parameter D and the angle Φ of the track with respect to the beam line, vary in number and in position in the Φ - D plane. An invariant second-order moment feature set and an invariant D -sequence representation are derived to characterize the signal and background event track patterns in the Φ - D plane. A three-layer perceptron is trained to classify events as signal/background via the moments and D -sequences. A nearest neighbor classifier is also developed to serve as a benchmark for comparing the performance of the neural net triggers. Results indicate that the selected moment feature set and the D -sequence representation contain essential signal/background discriminatory information. The results also show that the neural network trigger algorithms are superior to the nearest neighbor trigger algorithms. A very high discrimination against background events and a very high efficiency for selecting signal events is obtained with the D -sequence neural net trigger algorithm

Multiscale Discriminant Saliency for Visual Attention

The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio

Phase transitions in BaTiO3_3 from first principles

We develop a first-principles scheme to study ferroelectric phase transitions for perovskite compounds. We obtain an effective Hamiltonian which is fully specified by first-principles ultra-soft pseudopotential calculations. This approach is applied to BaTiO$_3$, and the resulting Hamiltonian is studied using Monte Carlo simulations. The calculated phase sequence, transition temperatures, latent heats, and spontaneous polarizations are all in good agreement with experiment. The order-disorder vs.\ displacive character of the transitions and the roles played by different interactions are discussed.Comment: 13 page

Accurate simulation estimates of phase behaviour in ternary mixtures with prescribed composition

This paper describes an isobaric semi-grand canonical ensemble Monte Carlo scheme for the accurate study of phase behaviour in ternary fluid mixtures under the experimentally relevant conditions of prescribed pressure, temperature and overall composition. It is shown how to tune the relative chemical potentials of the individual components to target some requisite overall composition and how, in regions of phase coexistence, to extract accurate estimates for the compositions and phase fractions of individual coexisting phases. The method is illustrated by tracking a path through the composition space of a model ternary Lennard-Jones mixture.Comment: 6 pages, 3 figure

Critical test of multi-{\it j} supersymmetries from magnetic moment measurements

Magnetic moment measurements in odd nuclei directly probe the distribution of fermion states and hence provide one of the most critical tests for multi-$j$ supersymmetries in collective nuclei. Due to complexity of calculations and lack of data, such tests have not been performed in the past. Using the Mathematica software, we derive analytic expressions for magnetic moments in the $SO^{(BF)}(6) \times SU^{(F)}(2)$ limit of the $U(6/12)$ supersymmetry and compare the results with recent measurements in $^{195}$Pt.Comment: 10 pages with 1 figur

Neutrino Clustering in the Galaxy with a Global Monopole

In spherically symmetric, static spacetime, we show that only j=1/2 fermions can satisfy both Einstein's field equation and Dirac's equation. It is also shown that neutrinos are able to have effective masses and cluster in the galactic halo when they are coupled to a global monopole situated at the galactic core. Astronomical implications of the results are discussed.Comment: 8 pages, Revtex

Why has research in face recognition progressed so slowly? The importance of variability

Despite many years of research, there has been surprisingly little progress in our understanding of how faces are identified. Here I argue that there are two contributory factors: (a) Our methods have obscured a critical aspect of the problem, within-person variability; and (b) research has tended to conflate familiar and unfamiliar face processing. Examples of procedures for studying variability are given, and a case is made for studying real faces, of the type people recognize every day. I argue that face recognition (specifically identification) may only be understood by adopting new techniques that acknowledge statistical patterns in the visual environment. As a consequence, some of our current methods will need to be abandoned

Asymmetric Fluid Criticality II: Finite-Size Scaling for Simulations

The vapor-liquid critical behavior of intrinsically asymmetric fluids is studied in finite systems of linear dimensions, $L$, focusing on periodic boundary conditions, as appropriate for simulations. The recently propounded ``complete'' thermodynamic $(L\to\infty)$ scaling theory incorporating pressure mixing in the scaling fields as well as corrections to scaling ${[arXiv:cond-mat/0212145]}$, is extended to finite $L$, initially in a grand canonical representation. The theory allows for a Yang-Yang anomaly in which, when $L\to\infty$, the second temperature derivative, $(d^{2}\mu_{\sigma}/dT^{2})$, of the chemical potential along the phase boundary, $\mu_{\sigma}(T)$, diverges when T\to\Tc -. The finite-size behavior of various special {\em critical loci} in the temperature-density or $(T,\rho)$ plane, in particular, the $k$-inflection susceptibility loci and the $Q$-maximal loci -- derived from $Q_{L}(T,_{L}) \equiv ^{2}_{L}/< m^{4}>_{L}$ where $m \equiv \rho - _{L}$ -- is carefully elucidated and shown to be of value in estimating \Tc and \rhoc. Concrete illustrations are presented for the hard-core square-well fluid and for the restricted primitive model electrolyte including an estimate of the correlation exponent $\nu$ that confirms Ising-type character. The treatment is extended to the canonical representation where further complications appear.Comment: 23 pages in the two-column format (including 13 figures) This is Part II of the previous paper [arXiv:cond-mat/0212145

Tetracritical behavior in strongly interacting theories

We suggest a tetracritical fixed point to naturally occur in strongly interacting theories. As a fundamental example we analyze the temperature--quark chemical potential phase diagram of QCD with fermions in the adjoint representation of the gauge group (i.e. adjoint QCD). Here we show that such a non trivial multicritical point exists and is due to the interplay between the spontaneous breaking of a global U(1) symmetry and the center group symmetry associated to confinement. Our results demonstrate that taking confinement into account is essential for understanding the critical behavior as well as the full structure of the phase diagram of adjoint QCD. This is in contrast to ordinary QCD where the center group symmetry associated to confinement is explicitly broken when the quarks are part of the theory.Comment: RevTex, 5 figures. Final version to appear in PR