Abstract

n this paper, we demonstrate a computer vision applica-tion on mobile phones. One can take a picture at a her-itage site/monument and obtain associated annotations on a mid-end mobile phone instantly. This does not require any communication of images or features with a remote server,and all the necessary computations take place on the phone itself. We demonstrate the app on two Indian heritage sites:Golkonda Fort and Hampi Temples. Underlying our appli-cation, we have a Bag of visual Words (BoW) image retrieval system, and an annotated database of images.In the process of developing this mobile app, we extend the performance, scope and applicability of computer vision techniques: (i) we do a BoW-based image retrieval on mo-bile phones from a database of 10K images within 50 MB of storage and 10 MB of RAM. (ii) we introduce a vocabulary pruning method for reducing the vocabulary size. (iii) wede sign a simple method of database pruning, that helps in reducing the size of the inverted index by removing seman-tically similar images. In (ii) and (iii), we demonstrate how memory(RAM) and computational speed can be optimized without any loss in performance.

Abstract

In one aspect, the invention relates to methods for enhancing a Raman signal comprising the steps of providing a sample comprising a metal surface, an analyte adhered to the surface, and a metallic nanoparticle coupled to the surface, wherein the nanoparticle has a plasmon resonance band; exposing the sample to incident energy of an excitation wavelength; and detecting the Raman signal of the analyte. In a further aspect, the invention relates to a compositiion comprising a metal surface, a functionalized self-assembled monolayer adhered to the surface, wherin the self-assembled monolayer comprises an analyte, and a cetyltrimethylammonium halide-capped metallic nanoparticle coupled to the surface. In a further aspect, the invention relates to a cetyltrimethylammonium bromide-capped gold nanoparticle and a method for preparing same. This abstract is intended as a scanning tool for purposes of …

Abstract

Gold nanostars, possessing multiple sharp spikes, have emerged as promising plasmonic particles in the field of ultrasensitive sensing. We have developed a water-based method for high-yield synthesis of size-tunable anisotropic gold nanoparticles with a varying number of spiky surface protrusions, and performed systematic experimental and theoretical analyses of the optical properties of the single gold nanostars by characterizing them simultaneously with scanning electron microscopy and dark-field scattering spectroscopy. The morphologies and corresponding scattering spectra of the individual gold nanostars have been compared with electromagnetic simulations of the plasmonic resonances utilizing the finite-difference time-domain (FDTD) method. The study provides a correlation between the experimental and calculated scattering spectra and charge distributions of the different plasmon modes in the …

Abstract

The invention provides a method for manufacturing supported noble metal based alloy catalysts with a high degree of alloying and a small crystallite size. The method involves using polyol solvents as reaction medium and comprises a two-step reduction process in the presence of a support material. In the first step, the first metal (transition metal; eg Co, Cr, Ru) is activated by increasing the reaction temperature to 80 to 160 C. In the second step, the second metal (noble metal; eg Pt, Pd, Au) is added and the slurry is heated to the boiling point of the polyol solvent in a range of 160 to 300 C. The catalysts manufactured according to the method are used as electrocatalysts for polymer electrolyte membrane fuel cells (PEMFC), direct-methanol fuel cells (DMFC) or as gas phase catalysts for CO oxidation or exhaust gas purification.

Abstract

The combination of molecular dynamics simulation and neutron scattering techniques has emerged as a highly synergistic approach to elucidate the atomistic details of the structure, dynamics, and functions of biological systems. Simulation models can be tested by calculating neutron scattering structure factors and comparing the results directly with experiments. If the scattering profiles agree, the simulations can be used to provide a detailed decomposition and interpretation of the experiments, and if not, the models can be rationally adjusted. Comparison with neutron experiment can be made at the level of the scattering functions or, less directly, of structural and dynamical quantities derived from them. Here, we examine the combination of simulation and experiment in the interpretation of SANS and inelastic scattering experiments on the structure and dynamics of proteins and other biopolymers.

Abstract

An analytical approach is developed for reconstructing site-specific methyl-bearing protein side-chain conformational energy surfaces from NMR methyl axis order parameters (Oaxis2). Application of an enhanced sampling algorithm (adaptive biasing force) to molecular dynamics simulation of a protein, calcium-bound calmodulin, reveals a nonlinear correlation between Oaxis2 and the populations of rotamer states of protein side-chains, permitting the rotamer populations to be extracted directly from Oaxis2. The analytical approach yields side-chain conformational distributions that are in excellent agreement with those obtained from the enhanced-sampling MD results.

Abstract

With the recent emergence of cloud computing based services on the Internet, MapReduce and distributed file systems like HDFS have emerged as the paradigm of choice for developing large scale data intensive applications. Given the scale at which these applications are deployed, minimizing power consumption of these clusters can significantly cut down operational costs and reduce their carbon footprint—thereby increasing the utility from a provider’s point of view. This paper addresses energy conservation for clusters of nodes that run MapReduce jobs. The algorithm dynamically reconfigures the cluster based on the current workload and turns cluster nodes on or off when the average cluster utilization rises above or falls below administrator specified thresholds, respectively. We evaluate our algorithm using the GridSim toolkit and our results show that the proposed algorithm achieves an energy reduction of 33% under average workloads and up to 54% under low workloads.

Abstract

With the induction of UTF-8 unicode standards, web content in Hindi language is increasing at a rapid pace. There is a great opportunity to mine the content and get insight of sentiments and opinions expressed by people and various communities. In this paper, we present a graph based method to build a subjective lexicon for Hindi language, using WordNet as a resource. Our method takes a pre-annotated seed list and expands this list into a full lexicon using synonym and antonym relations. We show two different evaluation strategies to validate the Hindi Lexicon built. Main contribution of our work 1) Developing a Subjective lexicon of adjectives using Hindi WordNet. 2) Developing an annotated corpora of Hindi reviews.

Abstract

In this paper, we report our participation in Knowledge Base Population at TAC 2012. We adopted an Information Retrieval based approach for the Entity Linking and Slot Filling tasks. In Entity Linking we identify potential nodes from the Knowledge Base and then identify the mapping node using tf-idf similarity. We achieved very good performance in the Entity Linking task. For Slot Filling task we identify documents from the document collection that might contain attribute information. We extract the attribute information using a rule based approach. Our rule based approach hasnt performed up to the mark.

Abstract

The number of images on the World Wide Web has been increasing tremendously. Providing search services for images on the web has been an active research area. Web images are often surrounded by different associated texts like ALT text, surrounding text, image filename, html page title etc. Many popular internet search engines make use of these associated texts while indexing images and give higher importance to the terms present in ALT text. But, a recent study has shown that around half of the images on the web have no ALT text. So, predicting the ALT text of an image in a web page would be of great use in web image retrieval. We propose an approach on top of term cooccurrence approach proposed in the literature to ALT text prediction. Our results show that our approach and the simple term co-occurrence approach produce almost the same results. We analyze both the methods and describe the usage of the methods in different situations. We build an image annotation system on top of our proposed approach and compare the results with the image annotation system built on top of the term co-occurrence approach. Preliminary experiments on a set of 1000 images show that our proposed approach performs well over the simple term co-occurrence approach for web image annotation.