New phase unwrapping strategy for rapid and dense 3D data acquisition in structured light approach

Sinusoidal structured light projection (SSLP) technique, specifically-phase stepping method, is in widespread use to obtain accurate, dense 3-D data. But, if the object under investigation possesses surface discontinuities, phase unwrapping (an intermediate step in SSLP) stage mandatorily require several additional images, of the object with projected fringes (of different spatial frequencies), as input to generate a reliable 3D shape. On the other hand, Color-coded structured light projection (CSLP) technique is known to require a single image as in put, but generates sparse 3D data. Thus we propose the use of CSLP in conjunction with SSLP to obtain dense 3D data with minimum number of images as input. This approach is shown to be significantly faster and reliable than temporal phase unwrapping procedure that uses a complete exponential sequence. For example, if a measurement with the accuracy obtained by interrogating the object with 32 fringes in the projected pattern is carried out with both the methods, new strategy proposed requires only 5 frames as compared to 24 frames required by the later method.

Evolution of polyandry by reduction in progeny number variance in structured populations

When there is a variation in the quality of males in a population, multiple mating can lead to an increase in the genetic fitness of a female by reducing the variance of the progeny number. The extent of selective advantage obtainable by this process is investigated for a population subdivided into structured demes. It is seen that for a wide range of model parameters (deme size, distribution of male quality, local resource level), multiple mating leads to a considerable increase in the fitness. Frequency-dependent selection or a stable coexistence between polyandry and monandry can also result when the possible costs involved in multiple mating are taken into account.

Development of a structured program for conversion to prenex normal form

The method of structured programming or program development using a top-down, stepwise refinement technique provides a systematic approach for the development of programs of considerable complexity. The aim of this paper is to present the philosophy of structured programming through a case study of a nonnumeric programming task. The problem of converting a well-formed formula in first-order logic into prenex normal form is considered. The program has been coded in the programming language PASCAL and implemented on a DEC-10 system. The program has about 500 lines of code and comprises 11 procedures.

Dielectric relaxation in bismuth layer-structured BaBi4Ti4O15 ferroelectric ceramics

The dielectric properties of BaBi4Ti4O15 ceramics were investigated as a function of frequency (10(2)-10(6) Hz) at various temperatures (30 degrees C-470 degrees C), covering the phase transition temperature. Two different conduction mechanisms were obtained by fitting the complex impedance data to Cole-Cole equation. The grain and grain boundary resistivities were found to follow the Arrhenius law associated with activation energies: E-g similar to 1.12 eV below T-m and E-g similar to 0.70 eV above T-m for the grain conduction; and E-gb similar to 0.93 eV below T-m and E-gb similar to 0.71 eV above T-m for the grain boundary conduction. Relaxation times extracted using imaginary part of complex impedance Z `'(omega) and modulus M `'(omega) were also found to follow the Arrhenius law and showed an anomaly around the phase transition temperature. The frequency dependence of conductivity was interpreted in terms of the jump relaxation model and was fitted to the double power law. (C) 2010 Elsevier B. V. All rights reserved.

On the Existence of Hydromagnetic Interface Waves in a Structured Atmosphere

The conditions under which the hydromagnetic interface waves can exist at a magnetic interface is deduced. Using these conditions, it is shown that a slow interface wave with a phase velocity about 5Km/s and a fast interface wave with a phase velocity 6.5 to 8km/s at the photospheric level can exist.

Nano structured carbon nitrides prepared by chemical vapour deposition

Nanostructured carbon nitride films were prepared by pyrolysis assisted chemical vapour deposition(CVD). A two zone furnace with a temperature profile having a uniform temperature over a length of 20 cm length has been designed and developed. The precursor Azabenzimidazole was taken in a quartz tube and evaporated at 400 degrees C. The dense vapours enter the pyrolysis zone kept at a desired temperature and deposit on the quartz substrates. The FTIR spectrum of the prepared samples shows peaks at 1272 cm(-1) (C-N stretching) and 1600 cm(-1) (C=N) confirms the bonding of nitrogen with carbon. Raman D and G peaks, are observed at 1360 cm(-1) and 1576 cm(-1) respectively. XPS core level spectra of C 1s and N 1s show the formation of pi bonding between carbon and nitrogen atoms. The size of the nano crystals estimated from the SEM images and XRD is similar to 100 nm. In some regions of the sample a maximum of 57 atom % of nitrogen has been observed.

Synthesis of Nano Structured Carbon Nitride by Pyrolysis Assisted Chemical Vapour Deposition

Nanostructured carbon nitride films were prepared by pyrolysis assisted chemical vapour deposition. A two zone furnace with a uniform temperature over a length of 20 cm in both the zones was built. The precursor Azabenzimidazole (C6H5N3) taken in a quartz tube was evaporated at zone A and pyrolysed at zone B at a temperature of 800 degrees C. The FTIR spectrum of the prepared sample shows peaks at 1272 cm(-1) and 1591 cm(-1) corresponding to C-N stretching and C=N respectively, which confirms the bonding of nitrogen with carbon. Raman D and G peaks are observed at 1357 cm(-1) and 1560 cm(-1) respectively. X-ray photoelectron spectroscopy (XPS) shows the formation of pi bonding between carbon and nitrogen atoms. These observations along with XRD analysis show the formation of crystallites of alpha-C3N4 and beta-C3N4 in the background of graphitic C3N4. The size of the nanocrystals estimated from the SEM images is similar to 100 nm.

Structured systems methodology for evaluation of random interruptions in continuous process type manufacturing systems

A structured systems methodology was developed to analyse the problems of production interruptions occurring at random intervals in continuous process type manufacturing systems. At a macro level the methodology focuses on identifying suitable investment policies to reduce interruptions of a total manufacturing system that is a combination of several process plants. An interruption-tree-based simulation model was developed for macroanalysis. At a micro level the methodology focuses on finding the effects of alternative configurations of individual process plants on the overall system performance. A Markov simulation model was developed for microlevel analysis. The methodology was tested with an industry-specific application.

Efficient statistical modeling for the compression of tree structured intermediate code

We propose a scheme for the compression of tree structured intermediate code consisting of a sequence of trees specified by a regular tree grammar. The scheme is based on arithmetic coding, and the model that works in conjunction with the coder is automatically generated from the syntactical specification of the tree language. Experiments on data sets consisting of intermediate code trees yield compression ratios ranging from 2.5 to 8, for file sizes ranging from 167 bytes to 1 megabyte.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Meso-Structured Silica-Nafion Hybrid Membranes for Direct Methanol Fuel Cells

A series of novel organic-inorganic hybrid membranes have been prepared employing Nafion and acid-functionalized meso-structured molecular sieves (MMS) with varying structures and surface area. Acid-functionalized silica nanopowder of surface area 60 m(2)/g, silica meso-structured cellular foam (MSU-F) of surface area 470 m(2)/g and silica meso-structured hexagonal frame network (MCM-41) of surface area 900 m(2)/g have been employed as potential filler materials to form hybrid membranes with Nafion framework. The structural behavior, water uptake, proton conductivity and methanol permeability of these hybrid membranes have been investigated. DMFCs employing Nafion-silica MSU-F and Nafion-silica MCM-41 hybrid membranes deliver peak-power densities of 127 mW/cm(2) and 100 mW/cm(2), respectively; while a peak-power density of only 48 mW/cm(2) is obtained with the DMFC employing pristine recast Nafion membrane under identical operating conditions. The aforesaid characteristics of the hybrid membranes could be exclusively attributed to the presence of pendant sulfonic acid groups in the filler, which provide fairly continuous proton-conducting pathways between filler and matrix in the hybrid membranes facilitating proton transport without any trade-off between its proton conductivity and methanol crossover. (C) 2012 The Electrochemical Society. DOI: 10.1149/2.036211jes] All rights reserved.

Scalable multi-dimensional user intent identification using tree structured distributions

The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.

Structured Dispersion Matrices From Division Algebra Codes for Space-Time Shift Keying

We propose a novel method of constructing Dispersion Matrices (DM) for Coherent Space-Time Shift Keying (CSTSK) relying on arbitrary PSK signal sets by exploiting codes from division algebras. We show that classic codes from Cyclic Division Algebras (CDA) may be interpreted as DMs conceived for PSK signal sets. Hence various benefits of CDA codes such as their ability to achieve full diversity are inherited by CSTSK. We demonstrate that the proposed CDA based DMs are capable of achieving a lower symbol error ratio than the existing DMs generated using the capacity as their optimization objective function for both perfect and imperfect channel estimation.

Mammalian neuronal sodium channel Blocker mu-conotoxin BuIIIB has a structured N-terminus that influences potency

Among the mu-conotoxins that block vertebrate voltage-gated sodium channels (VGSCs), some have been shown to be potent analgesics following systemic administration in mice. We have determined the solution structure of a new representative of this family, mu-BuIIIB, and established its disulfide connectivities by direct mass spectrometric collision induced dissociation fragmentation of the peptide with disulfides intact The major oxidative folding product adopts a 1-4/2-5/3-6 pattern with the following disulfide bridges: Cys5-Cys17, Cys6-Cys23, and Cys13-Cys24. The solution structure reveals that the unique N-terminal extension in mu-BuIIIB, which is also present in mu-BuIIIA and mu-BuIIIC but absent in other mu-conotoxins, forms part of a short a-helix encompassing Glu3 to Asn8. This helix is packed against the rest of the toxin and stabilized by the Cys5-Cys17 and Cys6-Cys23 disulfide bonds. As such, the side chain of Val1 is located close to the aromatic rings of Trp16 and His20, which are located on the canonical helix that displays several residues found to be essential for VGSC blockade in related mu-conotoxins. Mutations of residues 2 and 3 in the N-terminal extension enhanced the potency of mu-BuIIIB for Na(v)1.3. One analogue, D-Ala2]BuIIIB, showed a 40-fold increase, making it the most potent peptide blocker of this channel characterized to date and thus a useful new tool with which to characterize this channel. On the basis of previous results for related mu-conotoxins, the dramatic effects of mutations at the N-terminus were unanticipated and suggest that further gains in potency might be achieved by additional modifications of this region.

Maltose Binding Protein Is Partially Structured in Its Molten Globule State

Seven double cysteine mutants of maltose binding protein (MBP) were generated with one each in the active cleft at position 298 and the second cysteine distributed over both domains of the protein. These cysteines were spin labeled and distances between the labels in biradical pairs determined by pulsed double electron-electron resonance (DEER) measurements. The values were compared with theoretical predictions of distances between the labels in biradicals constructed by molecular modeling from the crystal structure of MBP without maltose and were found to be in excellent agreement. MBP is in a molten globule state at pH 3.3 and is known to still bind its substrate maltose. The nitroxide spin label was sufficiently stable under these conditions. In preliminary experiments, DEER measurements were carried out with one of the mutants yielding a broad distance distribution as was to be expected if there is no explicit tertiary structure and the individual helices pointing into all possible directions.