Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Unified Taxonomy for Reference Ontology of Shape Features in Product Model

This paper presents a unified taxonomy of shape features. Such taxonomy is required to construct ontologies to address heterogeneity in product/shape models. Literature provides separate classifications for volumetric, deformation and free-form surface features. The unified taxonomy proposed allows classification, representation and extraction of shape features in a product model. The novelty of the taxonomy is that the classification is based purely on shape entities and therefore it is possible to automatically extract the features from any shape model. This enables the use of this taxonomy to build reference ontology.

Shape-function-relationship (SFR) framework for semantic interoperability of product model

The problem of semantic interoperability arises while integrating applications in different task domains across the product life cycle. A new shape-function-relationship (SFR) framework is proposed as a taxonomy based on which an ontology is developed. Ontology based on the SFR framework, that captures explicit definition of terminology and knowledge relationships in terms of shape, function and relationship descriptors, offers an attractive approach for solving semantic interoperability issue. Since all instances of terms are based on single taxonomy with a formal classification, mapping of terms requires a simple check on the attributes used in the classification. As a preliminary study, the framework is used to develop ontology of terms used in the aero-engine domain and the ontology is used to resolve the semantic interoperability problem in the integration of design and maintenance. Since the framework allows a single term to have multiple classifications, handling context dependent usage of terms becomes possible. Automating the classification of terms and establishing the completeness of the classification scheme are being addressed presently.

Noncoherent Integration for Signal Detection: Analysis Under Model Uncertainties

The performance of postdetection integration (PDI) techniques for the detection of Global Navigation Satellite Systems (GNSS) signals in the presence of uncertainties in frequency offsets, noise variance, and unknown data-bits is studied. It is shown that the conventional PDI techniques are generally not robust to uncertainty in the data-bits and/or the noise variance. Two new modified PDI techniques are proposed, and they are shown to be robust to these uncertainties. The receiver operating characteristics (ROC) and sample complexity performance of the PDI techniques in the presence of model uncertainties are analytically derived. It is shown that the proposed methods significantly outperform existing methods, and hence they could become increasingly important as the GNSS receivers attempt to push the envelope on the minimum signal-to-noise ratio (SNR) for reliable detection.

An early in-situ stress signature of the AlN-Si pre-growth interface for successful integration of nitrides with (111) Si

The integration of Metal Organic Chemical Vapor Deposition (MOCVD) grown group III-A nitride device stacks on Si (111) substrates is critically dependent on the quality of the first AlN buffer layer grown. A Si surface that is both oxide-free and smooth is a primary requirement for nucleating such layers. A single parameter, the AlN layer growth stress, is shown to be an early (within 50 nm), clear (<0.5 GPa versus > 1GPa), and fail-safe indicator of the pre-growth surface, and the AlN quality required for successful epitaxy. Grain coalescence model for stress generation is used to correlate growth stress, the AlN-Si interface, and crystal quality. (C) 2013 AIP Publishing LLC.

AIM-Spice Integration of a Recursive Model for Threshold Voltage Shift in Thin Film Transistors

Non-crystalline semiconductor based thin film transistors are the building blocks of large area electronic systems. These devices experience a threshold voltage shift with time due to prolonged gate bias stress. In this paper we integrate a recursive model for threshold voltage shift with the open source BSIM4V4 model of AIM-Spice. This creates a tool for circuit simulation for TFTs. We demonstrate the integrity of the model using several test cases including display driver circuits.

Molecular Dissection of Mycobacterium tuberculosis Integration Host Factor Reveals Novel Insights into the Mode of DNA Binding and Nucleoid Compaction

Background: mIHF belongs to a subfamily of proteins, distinct from E. coli IHF. Results: Functionally important amino acids of mIHF and the mechanism(s) underlying DNA binding, DNA bending, and site-specific recombination are distinct from that of E. coli IHF. Conclusion: mIHF functions could contribute beyond nucleoid compaction. Significance: Because mIHF is essential for growth, the molecular mechanisms identified here can be exploited in drug screening efforts. The annotated whole-genome sequence of Mycobacterium tuberculosis revealed that Rv1388 (Mtihf) is likely to encode for a putative 20-kDa integration host factor (mIHF). However, very little is known about the functional properties of mIHF or the organization of the mycobacterial nucleoid. Molecular modeling of the mIHF three-dimensional structure, based on the cocrystal structure of Streptomyces coelicolor IHF duplex DNA, a bona fide relative of mIHF, revealed the presence of Arg-170, Arg-171, and Arg-173, which might be involved in DNA binding, and a conserved proline (Pro-150) in the tight turn. The phenotypic sensitivity of Escherichia coli ihfA and ihfB strains to UV and methyl methanesulfonate could be complemented with the wild-type Mtihf but not its alleles bearing mutations in the DNA-binding residues. Protein-DNA interaction assays revealed that wild-type mIHF, but not its DNA-binding variants, binds with high affinity to fragments containing attB and attP sites and curved DNA. Strikingly, the functionally important amino acid residues of mIHF and the mechanism(s) underlying its binding to DNA, DNA bending, and site-specific recombination are fundamentally different from that of E. coli IHF. Furthermore, we reveal novel insights into IHF-mediated DNA compaction depending on the placement of its preferred binding sites; mIHF promotes DNA compaction into nucleoid-like or higher order filamentous structures. We therefore propose that mIHF is a distinct member of a subfamily of proteins that serve as essential cofactors in site-specific recombination and nucleoid organization and that these findings represent a significant advance in our understanding of the role(s) of nucleoid-associated proteins.

Molecular Dissection of Mycobacterium tuberculosis Integration Host Factor Reveals Novel Insights into the Mode of DNA Binding and Nucleoid Compaction

The annotated whole-genome sequence of Mycobacterium tuberculosis indicated that Rv1388 (Mtihf) likely encodes a putative 20 kDa integration host factor (mIHF). However, very little is known about the functional properties of mIHF or organization of mycobacterial nucleoid. Molecular modeling of the mIHF three-dimensional structure, based on the cocrystal structure of Streptomyces coelicolor IHF-duplex DNA, a bona fide relative of mIHF, revealed the presence of Arg170, Arg171, and Arg173, which might be involved in DNA binding, and a conserved proline (P150) in the tight turn. The phenotypic sensitivity of Escherichia coli Delta ihfA and Delta ihfB strains to UV and methylmethanesulfonate could be complemented with the wild-type Mtihf, but not its alleles bearing mutations in the DNA-binding residues. Protein DNA interaction assays revealed that wild-type mIHF, but not its DNA-binding variants, bind with high affinity to fragments containing attB and attP sites and curved DNA. Strikingly, the functionally important amino acid residues of mIHF and the mechanism(s) underlying its binding to DNA, DNA bending, and site-specific recombination are fundamentally different from that of E. coli IHF alpha beta. Furthermore, we reveal novel insights into IHF-mediated DNA compaction depending on the placement of its preferred binding sites; mIHF promotes compaction of DNA into nucleoid-like or higher-order filamentous structures. We hence propose that mIHF is a distinct member of a subfamily of proteins that serve as essential cofactors in site-specific recombination and nucleoid organization and that these findings represent a significant advance in our understanding of the role(s) of nucleoid-associated proteins.

Active learning in keyword search-based data integration

The problem of scaling up data integration, such that new sources can be quickly utilized as they are discovered, remains elusive: Global schemas for integrated data are difficult to develop and expand, and schema and record matching techniques are limited by the fact that data and metadata are often under-specified and must be disambiguated by data experts. One promising approach is to avoid using a global schema, and instead to develop keyword search-based data integration-where the system lazily discovers associations enabling it to join together matches to keywords, and return ranked results. The user is expected to understand the data domain and provide feedback about answers' quality. The system generalizes such feedback to learn how to correctly integrate data. A major open challenge is that under this model, the user only sees and offers feedback on a few ``top-'' results: This result set must be carefully selected to include answers of high relevance and answers that are highly informative when feedback is given on them. Existing systems merely focus on predicting relevance, by composing the scores of various schema and record matching algorithms. In this paper, we show how to predict the uncertainty associated with a query result's score, as well as how informative feedback is on a given result. We build upon these foundations to develop an active learning approach to keyword search-based data integration, and we validate the effectiveness of our solution over real data from several very different domains.

Integrating AlGaN/GaN high electron mobility transistor with Si: A comparative study of integration schemes

AlGaN/GaN high electron mobility transistor stacks deposited on a single growth platform are used to compare the most common transition, AlN to GaN, schemes used for integrating GaN with Si. The efficiency of these transitions based on linearly graded, step graded, interlayer, and superlattice schemes on dislocation density reduction, stress management, surface roughness, and eventually mobility of the 2D-gas are evaluated. In a 500 nm GaN probe layer deposited, all of these transitions result in total transmission electron microscopy measured dislocations densities of 1 to 3 x 10(9)/cm(2) and <1 nm surface roughness. The 2-D electron gas channels formed at an AlGaN-1 nm AlN/GaN interface deposited on this GaN probe layer all have mobilities of 1600-1900 cm(2)/V s at a carrier concentration of 0.7-0.9 x 10(13)/cm(2). Compressive stress and changes in composition in GaN rich regions of the AlN-GaN transition are the most effective at reducing dislocation density. Amongst all the transitions studied the step graded transition is the one that helps to implement this feature of GaN integration in the simplest and most consistent manner. (C) 2015 AIP Publishing LLC.