Hidden Conditional Random Fields for Visual Speech Recognition

In this paper we present the application of Hidden Conditional Random Fields (HCRFs) to modelling speech for visual speech recognition. HCRFs may be easily adapted to model long range dependencies across an observation sequence. As a result visual word recognition performance can be improved as the model is able to take more of a contextual approach to generating state sequences. Results are presented from a speaker-dependent, isolated digit, visual speech recognition task using comparisons with a baseline HMM system. We firstly illustrate that word recognition rates on clean video using HCRFs can be improved by increasing the number of past and future observations being taken into account by each state. Secondly we compare model performances using various levels of video compression on the test set. As far as we are aware this is the first attempted use of HCRFs for visual speech recognition.

Structural change in multipartite entanglement sharing: A random matrix approach

We study the typical entanglement properties of a system comprising two independent qubit environments interacting via a shuttling ancilla. The initial preparation of the environments is modeled using random matrix techniques. The entanglement measure used in our study is then averaged over many histories of randomly prepared environmental states. Under a Heisenberg interaction model, the average entanglement between the ancilla and one of the environments remains constant, regardless of the preparation of the latter and the details of the interaction. We also show that, upon suitable kinematic and dynamical changes in the ancillaenvironment subsystems, the entanglement-sharing structure undergoes abrupt modifications associated with a change in the multipartite entanglement class of the overall system's state. These results are invariant with respect to the randomized initial state of the environments.

Random walk simulations of fossil proxy data

A wealth of palaeoecological studies (e.g. pollen, diatoms, chironomids and macrofossils from deposits such as lakes or bogs) have revealed major as well as more subtle ecosystem changes over decadal to multimillennial timescales. Such ecosystem changes are usually assumed to have been forced by specific environmental changes. Here, we test if the observed changes in palaeoecological records may be reproduced by random simulations, and we find that simple procedures generate abrupt events, long-term trends, quasi-cyclic behaviour, extinctions and immigrations. Our results highlight the importance of replicated and multiproxy data for reliable reconstructions of past climate and environmental changes.

Quantifying the influence of humic acid adsorption on colloidal microsphere deposition onto iron-oxide-coated sand.

This article describes an approach for quantifying microsphere deposition onto iron-oxide-coated sand under the influence of adsorbed Suwannee River Humic Acid (SRHA). The experimental technique involved a triple pulse injection of model latex microspheres (microspheres) in pulses of (1) microspheres, followed by (2) SRHA, and then (3) microspheres, into a column filled with iron-coated quartz sand as a water-saturated porous medium. A random sequential adsorption model (RSA) simulated the gradual rise in the first (microsphere) breakthrough curve (BTC). Using the same model calibration parameters a dramatic increase in concentration at the start of the second particle BTC, generated after SRHA injection, could be simulated by matching microsphere concentrations to extrapolated RSA output. RSA results and microsphere/SRHA recoveries showed that 1 mg of SRHA could block 5.90 plus or minus 0.14 x 10^9 microsphere deposition sites. This figure was consistent between experiments injecting different SRHA masses, despite contrasting microsphere deposition/release regimes generating the second microsphere BTC.

Ultra-lightweight true random number generators

A series of ultra-lightweight digital true random number generators (TRNGs) are presented. These TRNGs are based on the observation that, when a circuit switches from a metastable state to a bi-stable state, the resulting state may be random. Four such circuits with low hardware cost are presented: one uses an XOR gate; one uses a lookup table; one uses a multiplexer and an inverter; and one uses four transistors. The three TRNGs based on the first three circuits are implemented on a field programmable gate array and successfully pass the DIEHARD RNG tests and the National Institute of Standard and Technology (NIST) RNG tests. To the best of the authors' knowledge, the proposed TRNG designs are the most lightweight among existing TRNGs.