Exploiting Low-dimensional Structures to Enhance DNN Based Acoustic Modeling in Speech Recognition

We propose to model the acoustic space of deep neural network (DNN) class-conditional posterior probabilities as a union of low-dimensional subspaces. To that end, the training posteriors are used for dictionary learning and sparse coding. Sparse representation of the test posteriors using this dictionary enables projection to the space of training data. Relying on the fact that the intrinsic dimensions of the posterior subspaces are indeed very small and the matrix of all posteriors belonging to a class has a very low rank, we demonstrate how low-dimensional structures enable further enhancement of the posteriors and rectify the spurious errors due to mismatch conditions. The enhanced acoustic modeling method leads to improvements in continuous speech recognition task using hybrid DNN-HMM (hidden Markov model) framework in both clean and noisy conditions, where upto 15.4% relative reduction in word error rate (WER) is achieved

Bubbles, clusters and denaturation in genomic DNA: modeling, parametrization, efficient computation

The paper uses mesoscopic, non-linear lattice dynamics based (Peyrard-Bishop-Dauxois, PBD) modeling to describe thermal properties of DNA below and near the denaturation temperature. Computationally efficient notation is introduced for the relevant statistical mechanics. Computed melting profiles of long and short heterogeneous sequences are presented, using a recently introduced reparametrization of the PBD model, and critically discussed. The statistics of extended open bubbles and bound clusters is formulated and results are presented for selected examples.Comment: to appear in a special issue of the Journal of Nonlinear Mathematical Physics (ed. G. Gaeta

Sequence Dependence of Transcription Factor-Mediated DNA Looping

DNA is subject to large deformations in a wide range of biological processes. Two key examples illustrate how such deformations influence the readout of the genetic information: the sequestering of eukaryotic genes by nucleosomes, and DNA looping in transcriptional regulation in both prokaryotes and eukaryotes. These kinds of regulatory problems are now becoming amenable to systematic quantitative dissection with a powerful dialogue between theory and experiment. Here we use a single-molecule experiment in conjunction with a statistical mechanical model to test quantitative predictions for the behavior of DNA looping at short length scales, and to determine how DNA sequence affects looping at these lengths. We calculate and measure how such looping depends upon four key biological parameters: the strength of the transcription factor binding sites, the concentration of the transcription factor, and the length and sequence of the DNA loop. Our studies lead to the surprising insight that sequences that are thought to be especially favorable for nucleosome formation because of high flexibility lead to no systematically detectable effect of sequence on looping, and begin to provide a picture of the distinctions between the short length scale mechanics of nucleosome formation and looping.Comment: Nucleic Acids Research (2012); Published version available at http://nar.oxfordjournals.org/cgi/content/abstract/gks473? ijkey=6m5pPVJgsmNmbof&keytype=re

The beta-delayed neutron emission in 78Ni region

A systematic study of the total $\beta$-decay half-lives and $\beta$-delayed neutron emission probabilities is performed. The $\beta$-strength function is treated within the self-consistent density-functional + continuum-QRPA framework including the Gamow-Teller and first-forbidden transitions. The experimental total $\beta$-decay half-lives for the Ni isotopes with $A\leq$76 are described satisfactorily. The half-lives predicted from $A$=70 up to $A$=86 reveal fairly regular $A$-behaviour which results from simultaneous account for the Gamow-Teller and first-forbidden transitions. For $Z\approx$ 28 nuclei, a suppression of the delayed neutron emission probability is found when the $N$=50 neutron closed shell is crossed. The effect originates from the high-energy first-forbidden transitions to the states outside the $Q_{\beta} - S_n$-window in the daughter nuclei. PACS numbers: 23.40.Bw,21.60.Jz,25.30.Pt,26.30.+kComment: LaTeX, 13 pages, 5 figure

Dwell time symmetry in random walks and molecular motors

The statistics of steps and dwell times in reversible molecular motors differ from those of cycle completion in enzyme kinetics. The reason is that a step is only one of several transitions in the mechanochemical cycle. As a result, theoretical results for cycle completion in enzyme kinetics do not apply to stepping data. To allow correct parameter estimation, and to guide data analysis and experiment design, a theoretical treatment is needed that takes this observation into account. In this paper, we model the distribution of dwell times and number of forward and backward steps using first passage processes, based on the assumption that forward and backward steps correspond to different directions of the same transition. We extend recent results for systems with a single cycle and consider the full dwell time distributions as well as models with multiple pathways, detectable substeps, and detachments. Our main results are a symmetry relation for the dwell time distributions in reversible motors, and a relation between certain relative step frequencies and the free energy per cycle. We demonstrate our results by analyzing recent stepping data for a bacterial flagellar motor, and discuss the implications for the efficiency and reversibility of the force-generating subunits. Key words: motor proteins; single molecule kinetics; enzyme kinetics; flagellar motor; Markov process; non-equilibrium fluctuations.Comment: revtex, 15 pages, 8 figures, 2 tables. v2: Minor revision, corrected typos, added references, and moved mathematical parts to new appendice

Two approaches for effective modelling of rain-rate time-series for radiocommunication system simulations

The paper presents a model which allows to synthetically generate rain rate time-series for a fixed location. Rain rate time-series are very much correlated with signal attenuation in Ka band and above and, thus, enable to realistically simulate propagation effects on Earth-satellite links. The model presented are based on Markov chains

Mathematical models of games of chance: Epistemological taxonomy and potential in problem-gambling research

Games of chance are developed in their physical consumer-ready form on the basis of mathematical models, which stand as the premises of their existence and represent their physical processes. There is a prevalence of statistical and probabilistic models in the interest of all parties involved in the study of gambling – researchers, game producers and operators, and players – while functional models are of interest more to math-inclined players than problem-gambling researchers. In this paper I present a structural analysis of the knowledge attached to mathematical models of games of chance and the act of modeling, arguing that such knowledge holds potential in the prevention and cognitive treatment of excessive gambling, and I propose further research in this direction