A new 6-component accelerometer force balance for short duration ground testing facilities

A new six-component accelerometer force balance is developed and used in the HST2 shock tunnel of Indian Institute of Science. Aerodynamic forces and moments for a hypersonic slender body measured using this balance system at a free stream Mach number of 5.75 and Reynolds number of 1.5 million and stagnation enthalpy of 1.5 and 2 MJ/kg are presented. These measured values compare well with the theoretical values estimated using modified Newtonian theory.

Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Statistical Methods for Accelerated Life Testing with Particular Reference to Resin Impregnated Paper Bushings

Electrical failure of insulation is known to be an extremal random process wherein nominally identical pro-rated specimens of equipment insulation, at constant stress fail at inordinately different times even under laboratory test conditions. In order to be able to estimate the life of power equipment, it is necessary to run long duration ageing experiments under accelerated stresses, to acquire and analyze insulation specific failure data. In the present work, Resin Impregnated Paper (RIP) a relatively new insulation system of choice used in transformer bushings, is taken as an example. The failure data has been processed using proven statistical methods, both graphical and analytical. The physical model governing insulation failure at constant accelerated stress has been assumed to be based on temperature dependent inverse power law model.

Active Sequential Hypothesis Testing with Application to a Visual Search Problem

We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

Novel algorithms for distributed sequential hypothesis testing

This paper considers sequential hypothesis testing in a decentralized framework. We start with two simple decentralized sequential hypothesis testing algorithms. One of which is later proved to be asymptotically Bayes optimal. We also consider composite versions of decentralized sequential hypothesis testing. A novel nonparametric version for decentralized sequential hypothesis testing using universal source coding theory is developed. Finally we design a simple decentralized multihypothesis sequential detection algorithm.

Proportional resonant controller based circulating power setup for thermal testing of multilevel inverter

A regenerative or circulating-power method is presented in this paper for heat run test on the legs of a three-level neutral point clamped (NPC) inverter. This test ensures that only losses are drawn from the dc supply, while rated power is circulated between the two legs, thus minimising wastage of energy. A proportional-resonant (PR) controller based current control scheme is proposed here for the circulating power test setup in NPC inverter. Simulation and experimental results are presented to validate the controller design at various operating conditions. Results of thermal test on the inverter legs are presented at two different operating conditions.

Safety Assessment of a Masonry Arch Bridge: Field Testing and Simulations

The safety of an in-service brick arch railway bridge is assessed through field testing and finite-element analysis. Different loading test train configurations have been used in the field testing. The response of the bridge in terms of displacements, strains, and accelerations is measured under the ambient and design train traffic loading conditions. Nonlinear fracture mechanics-based finite-element analyses are performed to assess the margin of safety. A parametric study is done to study the effects of tensile strength on the progress of cracking in the arch. Furthermore, a stability analysis to assess collapse of the arch caused by lateral movement at the springing of one of the abutments that is elastically supported is carried out. The margin of safety with respect to cracking and stability failure is computed. Conclusions are drawn with some remarks on the state of the bridge within the framework of the information available and inferred information. DOI: 10.1061/(ASCE)BE.1943-5592.0000338. (C) 2013 American Society of Civil Engineers.

Language models for online handwritten Tamil word recognition

N-gram language models and lexicon-based word-recognition are popular methods in the literature to improve recognition accuracies of online and offline handwritten data. However, there are very few works that deal with application of these techniques on online Tamil handwritten data. In this paper, we explore methods of developing symbol-level language models and a lexicon from a large Tamil text corpus and their application to improving symbol and word recognition accuracies. On a test database of around 2000 words, we find that bigram language models improve symbol (3%) and word recognition (8%) accuracies and while lexicon methods offer much greater improvements (30%) in terms of word recognition, there is a large dependency on choosing the right lexicon. For comparison to lexicon and language model based methods, we have also explored re-evaluation techniques which involve the use of expert classifiers to improve symbol and word recognition accuracies.

Deformation mechanisms during superplastic testing of Ti-6Al-4V-0.1B alloy

Superplastic tensile tests on warm rolled and optimally annealed boron modified alloy Ti-6Al-4V-0.1B at a temperature of 850 degrees C and initial strain rate of 3 x 10(-4) s(-1) results in a higher elongation (similar to 500%) compared to the base alloy Ti-6Al-4V (similar to 400%). The improvement in superplasticity has been attributed to enhanced contribution from interfacial boundary sliding to the overall deformation for the boron modified alloy. The boundary sliding was facilitated by the starting microstructure which predominantly contains small equiaxed primary a grains with narrow size distribution. Dynamic processes such as coarsening and globularization of primary a phase occur under the test condition but do not significantly contribute to the observed difference in superplasticity between the two alloys. In spite of cavitation takes place around the TiB particles during deformation, they do not cause macroscopic cracking and early fracture by virtue of the cavities being extremely localized. Localized cavitation is found to correlate with increased material transfer due to faster diffusion.

Group testing based spectrum hole search using a simple sub-nyquist sampling scheme

In this paper, we consider the problem of finding a spectrum hole of a specified bandwidth in a given wide band of interest. We propose a new, simple and easily implementable sub-Nyquist sampling scheme for signal acquisition and a spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy in the frequency domain by testing a group of adjacent subbands in a single test. The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent sub-bands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes. We extend this framework to a multi-stage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including non-contiguous spectrum hole search. Further, we provide the analytical means to optimize the hypothesis tests with respect to the detection thresholds, number of samples and group size to minimize the detection delay under a given error rate constraint. Depending on the sparsity and SNR, the proposed algorithms can lead to significantly lower detection delays compared to a conventional bin-by-bin energy detection scheme; the latter is in fact a special case of the group test when the group size is set to 1. We validate our analytical results via Monte Carlo simulations.

Small-scale mechanical testing of materials

Small-scale mechanical testing of materials has gained prominence in the last decade or so due to the continuous miniaturization of components and devices in everyday application. This review describes the various micro-fabrication processes associated with the preparation of miniaturized specimens, geometries of test specimens and the small scale testing techniques used to determine the mechanical behaviour of materials at the length scales of a few hundred micro-meters and below. This is followed by illustrative examples in a selected class of materials. The choice of the case studies is based on the relevance of the materials used in today's world: evaluation of mechanical properties of thermal barrier coatings (TBCs), applied for enhanced high temperature protection of advanced gas turbine engine components, is essential since its failure by fracture leads to the collapse of the engine system. Si-based substrates, though brittle, are indispensible for MEMS/NEMS applications. Biological specimens, whose response to mechanical loads is important to ascertain their role in diseases and to mimic their structure for attaining high fracture toughness and impact resistance. An insight into the mechanisms behind the observed size effects in metallic systems can be exploited to achieve excellent strength at the nano-scale. A future outlook of where all this is heading is also presented.

In situ approach for testing the enantiopurity of chiral amines and amino alcohols by H-1 NMR

An in situ approach involving a simple mix and shake method for testing the enantiopurity of primary, secondary and tertiary chiral amines and their derivatives, chiral amino alcohols, by H-1-NMR spectroscopy is developed. The protocol involves the in situ formation of chiral ammonium borate salt from a mixture of C-2 symmetric chiral BINOL, trialkoxyborane and chiral amines. The proposed concept was demonstrated convincingly on a large number of chiral and pro-chiral amines and amino alcohols, and also aids the precise measurement of enantiomeric excess. The protocol can be completed in a couple of minutes directly in the NMR sample tube, without the need for any physical separation.