Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Time reversal technique for health monitoring of metallic structure using Lamb waves

Time reversal active sensing using Lamb waves is investigated for health monitoring of a metallic structure. Experiments were conducted on an aluminum plate to study the time reversal behavior of A(0) and S-0 Lamb wave modes under narrow band and broad band pulse excitation. Damage in the form of a notch was introduced in the plate to study the changes in the characteristics of the time reversed Lamb wave modes experimentally. Time-frequency analysis of the time reversed signal was carried out to extract the damage information. A measure of damage based on wavelet transform was derived to quantify the hidden damage information in the time reversed signal. It has been shown that time reversal can be used to achieve temporal recompression of Lamb waves under broadband signal excitation. Further, the broad band excitation can also improve the resolution of the technique in detecting closely located defects. This is demonstrated by picking up the reflection of waves from the edge of the plate, from a defect close to the edge of the plate and from defects located near to each other. This study shows the effectiveness of Lamb wave time reversal for temporal recompression of dispersive Lamb waves for damage detection in health monitoring applications. (C) 2009 Elsevier B.V. All rights reserved.

A dynamic renormalization group study of active nematics

We carry out a systematic construction of the coarse-grained dynamical equation of motion for the orientational order parameter for a two-dimensional active nematic, that is a nonequilibrium steady state with uniaxial, apolar orientational order. Using the dynamical renormalization group, we show that the leading nonlinearities in this equation are marginally irrelevant. We discover a special limit of parameters in which the equation of motion for the angle field bears a close relation to the 2d stochastic Burgers equation. We find nevertheless that, unlike for the Burgers problem, the nonlinearity is marginally irrelevant even in this special limit, as a result of a hidden fluctuation-dissipation relation. 2d active nematics therefore have quasi-long-range order, just like their equilibrium counterparts.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

Starburst in the ultraluminous galaxy Arp 220: Constraints from observations of radio recombination lines and continuum

We present observations of radio recombination lines (RRL) from the starburst galaxy Arp 220 at 8.1 GHz (H92 alpha) and 1.4 GHz (H167 alpha and H165 alpha) and at 84 GHz (H42 alpha), 96 GHz (H40 alpha) and 207 GHz (H31 alpha) using the Very Large Array and the IRAM 30 m telescope, respectively. RRLs were detected at all the frequencies except 1.4 GHz, where a sensitive upper limit was obtained. We also present continuum flux measurements at these frequencies as well as at 327 MHz made with the VLA. The continuum spectrum, which has a spectral index alpha similar to -0.6 (S-nu proportional to nu(alpha)) between 5 and 10 GHz, shows a break near 1.5 GHz, a prominent turnover below 500 MHz, and a flatter spectral index above 50 GHz. We show that a model with three components of ionized gas with different densities and area covering factors can consistently explain both RRL and continuum data. The total mass of ionized gas in the three components is 3.2 x 10(7) M., requiring 3 x 10(5) O5 stars with a total Lyman continuum production rate N-Lyc similar to 1.3 x 10(55) photons s(-1). The ratio of the expected to observed Br alpha and Br gamma fluxes implies a dust extinction A(V) similar to 45 mag. The derived Lyman continuum photon production rate implies a continuous star formation rate (SFR) averaged over the lifetime of OB stars of similar to 240 M yr(-1). The Lyman continuum photon Production rate of similar to 3% associated with the high-density H II regions implies a similar SFR at recent epochs (t < 10(5) yr). An alternative model of high-density gas, which cannot be excluded on the basis of the available data, predicts 10 times higher SFR at recent epochs. If confirmed, this model implies that star formation in Arp 220 consists of multiple starbursts of very high SFR (few times 10(3) M. yr(-1)) and short duration (similar to 10(5) yr). The similarity of IR excess, L-IR/L-Ly alpha similar to 24, in Arp 220 to values observed in starburst galaxies shows that most of the high luminosity of Arp 220 is due to the ongoing starburst rather than to a hidden active galactic nucleus (AGN). A comparison of the IR excesses in Arp 220, the Galaxy, and M33 indicates that the starburst in Arp 220 has an initial mass function that is similar to that in normal galaxies and has a duration longer than 107 yr. If there was no infall of gas during this period, then the star formation efficiency (SFE) in Arp 220 is similar to 50%. The high SFR and SFE in Arp 220 is consistent with their known dependences on mass and density of gas in star-forming regions of normal galaxies.

Multi-Pattern Viterbi Algorithm for joint decoding of multiple speech patterns

Joint decoding of multiple speech patterns so as to improve speech recognition performance is important, especially in the presence of noise. In this paper, we propose a Multi-Pattern Viterbi algorithm (MPVA) to jointly decode and recognize multiple speech patterns for automatic speech recognition (ASR). The MPVA is a generalization of the Viterbi Algorithm to jointly decode multiple patterns given a Hidden Markov Model (HMM). Unlike the previously proposed two stage Constrained Multi-Pattern Viterbi Algorithm (CMPVA),the MPVA is a single stage algorithm. MPVA has the advantage that it cart be extended to connected word recognition (CWR) and continuous speech recognition (CSR) problems. MPVA is shown to provide better speech recognition performance than the earlier techniques: using only two repetitions of noisy speech patterns (-5 dB SNR, 10% burst noise), the word error rate using MPVA decreased by 28.5%, when compared to using individual decoding. (C) 2010 Elsevier B.V. All rights reserved.

Impact of dust on solar photovoltaic (PV) performance: Research status, challenges and recommendations

The peaking of most oil reserves and impending climate change are critically driving the adoption of solar photovoltaic's (PV) as a sustainable renewable and eco-friendly alternative. Ongoing material research has yet to find a breakthrough in significantly raising the conversion efficiency of commercial PV modules. The installation of PV systems for optimum yield is primarily dictated by its geographic location (latitude and available solar insolation) and installation design (tilt, orientation and altitude) to maximize solar exposure. However, once these parameters have been addressed appropriately, there are other depending factors that arise in determining the system performance (efficiency and output). Dust is the lesser acknowledged factor that significantly influences the performance of the PV installations. This paper provides an appraisal on the current status of research in studying the impact of dust on PV system performance and identifies challenges to further pertinent research. A framework to understand the various factors that govern the settling/assimilation of dust and likely mitigation measures have been discussed in this paper. (C) 2010 Elsevier Ltd. All rights reserved.

A Strategy for Conserving the Biodiversity of the Uttara Kannada District in South India

Taking the various values ascribed to biodiversity as its point of departure rather many years ago, the present study aims at deriving a conservation strategy for Uttara Kannada. This hilly district, with the highest proportion of its area under forests in South India, is divided into five ecological zones: coastal, northern evergreen, southern evergreen, moist deciduous, and dry deciduous. The heavily-populated coastal zone includes mangrove forests and estuarine wetlands. The evergreen forests are particularly rich in the diversity of plant species which they support - including wild relatives of a number of cultivated plants. They also serve a vital function in watershed conservation. The moist deciduous forests are rich in bird species; both moist and dry deciduous forests include a number of freshwater ponds and lakes that support a high diversity of aquatic birds.Reviewing the overall distribution of biodiversity, we identify specific localities - including estuaries, evergreen forests, and moist deciduous forests - which should be set aside as Nature reserves. These larger reserves must be complemented by a network of traditionally-protected sacred groves and sacred trees that are distributed throughout the district and that protect today, for instance, the finest surviving stand of dipterocarp trees.We also spell out the necessary policy-changes in overall development strategy that should stem the ongoing decimation of biodiversity. These include (1) revitalizing community-based systems of sustainable management of village forests and protection of sacred groves and trees; (2) reorienting the usage-pattern of reserve forests from production of a limited variety of timber and softwood species for industrial consumers, to production of a larger diversity of non-wood forest produce of commercial value to support the rural economy; (3) utilizing marginal lands under private ownership for generating industrial wood supplies; and (4) provision of incentives for in situ maintenance of land-races of cultivated plants - especially evergreen, fruit-yielding trees - by the local people.It is proposed that this broad framework be now taken to the local communities, and that an action-plan be developed on the basis of inputs provided - and initiatives taken - by them.

Characterizing and recognizing weak visibility polygons

A polygon is said to be a weak visibility polygon if every point of the polygon is visible from some point of an internal segment. In this paper we derive properties of shortest paths in weak visibility polygons and present a characterization of weak visibility polygons in terms of shortest paths between vertices. These properties lead to the following efficient algorithms: (i) an O(E) time algorithm for determining whether a simple polygon P is a weak visibility polygon and for computing a visibility chord if it exist, where E is the size of the visibility graph of P and (ii) an O(n2) time algorithm for computing the maximum hidden vertex set in an n-sided polygon weakly visible from a convex edge.

Experimental Test of the Quantum No-Hiding Theorem

The no-hiding theorem says that if any physical process leads to bleaching of quantum information from the original system, then it must reside in the rest of the Universe with no information being hidden in the correlation between these two subsystems. Here, we report an experimental test of the no-hiding theorem with the technique of nuclear magnetic resonance. We use the quantum state randomization of a qubit as one example of the bleaching process and show that the missing information can be fully recovered up to local unitary transformations in the ancilla qubits.

Autoregressive spectral array for graphical display of EEG data

A graphical display of the frequency content of background,electroencephalogram (EEG) activity is obtained by calculating the spectral estimates using autocorrelation autoregressive method and the classical Fourier transform method, Display of spectral content of consecutive data segments is made using hidden-line suppression technique so as to get a spectral array, The autoregressive spectral array (ASA) is found to be sensitive to baseline drift, Following baseline correction the autoregressive technique is found to be superior to the Fourier method of compressed spectral array (CSA) in detecting the transitions in the frequencies of the signal. The smoothed ASA gives a better picture of transitions and changes in the background activity, The ASA can be made to adapt to specific changes of dominant frequencies while eliminating unnecessary peaks in the spectrum. The utility,of the ASA for background EEG analysis is discussed,

Performance of the generalized delta rule in structural damage detection

The paper examines the suitability of the generalized data rule in training artificial neural networks (ANN) for damage identification in structures. Several multilayer perceptron architectures are investigated for a typical bridge truss structure with simulated damage stares generated randomly. The training samples have been generated in terms of measurable structural parameters (displacements and strains) at suitable selected locations in the structure. Issues related to the performance of the network with reference to hidden layers and hidden. neurons are examined. Some heuristics are proposed for the design of neural networks for damage identification in structures. These are further supported by an investigation conducted on five other bridge truss configurations.

Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

Direct measurement of phase of foreward-scattered light using polarization heterodyne interferometer

We describe direct measurement of phase of ballistic photons transmitted through objects hidden in a turbid medium using a polarization interferometer employing a rotating analyzer. The unwrapped phase difference measurements from interferometry was possible for medium levels of turbidity and accurate phase measurement from the sinusoidal intensity was not detectable when l/l* is increased beyond 4.3. The measured phase on reconstruction using standard tomographic algorithms resulted in the recovery of the refractive index profile of the object hidden in the turbid medium.

Nature's Swiss Army Knives: Ovipositor Structure Mirrors Ecology in a Multitrophic Fig Wasp Community

Background: Resource partitioning is facilitated by adaptations along niche dimensions that range from morphology to behaviour. The exploitation of hidden resources may require specially adapted morphological or sensory tools for resource location and utilisation. Differences in tool diversity and complexity can determine not only how many species can utilize these hidden resources but also how they do so. Methodology and Principal Findings: The sclerotisation, gross morphology and ultrastructure of the ovipositors of a seven-member community of parasitic wasps comprising of gallers and parasitoids developing within the globular syconia (closed inflorescences) of Ficus racemosa (Moraceae) was investigated. These wasps also differ in their parasitism mode (external versus internal oviposition) and their timing of oviposition into the expanding syconium during its development. The number and diversity of sensilla, as well as ovipositor teeth, increased from internally ovipositing to externally ovipositing species and from gallers to parasitoids. The extent of sclerotisation of the ovipositor tip matched the force required to penetrate the syconium at the time of oviposition of each species. The internally ovipositing pollinator had only one type of sensillum and a single notch on the ovipositor tip. Externally ovipositing species had multiple sensilla types and teeth on their ovipositors. Chemosensilla were most concentrated at ovipositor tips while mechanoreceptors were more widely distributed, facilitating the precise location of hidden hosts in these wasps which lack larval host-seeking behaviour. Ovipositor traits of one parasitoid differed from those of its syntopic galler congeners and clustered with those of parasitoids within a different wasp subfamily. Thus ovipositor tools can show lability based on adaptive necessity, and are not constrained by phylogeny. Conclusions/Significance: Ovipositor structure mirrored the increasingly complex trophic ecology and requirements for host accessibility in this parasite community. Ovipositor structure could be a useful surrogate for predicting the biology of parasites in other communities.