Abstract

A semiconductor ring laser is designed so as to work as an inverted integrator coupling three of such integrators an all-optical Delta Sigma Modulator is designed. The phenomenon of injection locking and switching is used.

Abstract

On the run towards making a photonic processor, which uses the photons of visible light rather than electric current to perform digital computations we propose all optical digital logic gate library consisting of NOR, OR, AND, XOR, and two compound gates. These gates which are designed using semiconductor ring lasers (SRL) are analyzed and modeled by developing rate equations. This digital library can be used in any CAD tool developed to design integrated photonics components. The phenomenon of injection locking is used for the realization of logic gates.

Abstract

A set of tools that demostrate the concept of a re-narration web, that aims to add alternative, target specific narrations of web documents as an extension of the web protocol with the intent of assisting a process of content dissemination and access that is inclusive of non-literate people.

Abstract

We propose Alipi, a distributed and participatory approach for re-narrating web pages for the purpose of rendering the content more accessible. This model supports alternative descriptions for a web page or parts of it via rewriting or re-narration for a given target audience by volunteers. The goal is to render the Web accessible to people across varied abilities, age, economic situation, language and geographic locations. We present the motivation, architecture and prototype implementation of Alipi.

Abstract

The astonishing diversity in folding patterns of RNA three-dimensional (3D) structures is crafted by myriads of noncovalent contacts, of which base pairing and stacking are the most prominent. A systematic and comprehensive classification and annotation of these interactions is necessary for a molecular-level understanding of their roles. However, unlike in the case of base pairing, where a widely accepted nomenclature and classification scheme exists in the public domain, currently available classification schemes for base–base stacking need major enhancements to comprehensively capture the necessary features underlying the rich stacking diversity in RNA. Here, we extend the previous stacking classification based on nucleobase interacting faces by introducing a structurally intuitive geometry-cum topology-based scheme. Specifically, a stack is first classified in terms of the geometry described by the relative orientation of the glycosidic bonds, which generates eight basic stacking geometric families for heterodimeric stacks and six of those for homodimeric stacks. Further annotation in terms of the identity of the bases and the region of involvement of purines (five-membered, six-membered, or both rings) leads to the enumeration of 384 distinct RNA base stacks. Based on our classification scheme, we present an algorithm for automated identification of stacks in RNA crystal structures and analyze the stacking context in selected RNA structures. Overall, the work described here is expected to greatly facilitate the structure-based RNA research.

Abstract

The AXES project participated in the interactive known-item search task (KIS) and the interactive instance search task (INS) for TRECVid 2011. We used the same system architecture and a nearly identical user interface for both the KIS and INS tasks. Both systems made use of text search on ASR, visual concept detectors, and visual similarity search. The user experiments were carried out with media professionals and media students at the Netherlands Institute for Sound and Vision, with media professionals performing the KIS task and media students participating in the INS task. This paper describes the results and findings of our experiments.

Abstract

We have applied genetic algorithm optimization for the design of laser pulses to control dissociation process in the ground electronic state of HF molecule, within the mathematical framework of optimal control theory. In order to design the experimentally feasible laser fields, we coded the small set of selected field parameters in the GA parameter space. Two types of pulses, one with fixed frequency components and the other having non-deterministic components have been designed. Optimized laser field obtained using this approach, possesses simple time and frequency structures. We show that the fields having non-deterministic frequency components lead to greater dissociation probability compared to the ones having deterministic frequency components.

Abstract

This paper presents integration and testing scheme for managing a large Multilingual OCR Project. The project is an attempt to implement an integrated platform for OCR of different Indian languages. Software engineering, workflow management and testing processes have been discussed in this paper. The OCR has now been experimentally deployed for some specific applications and currently is being enhanced for handling the space and time constraints, achieving higher recognition accuracies and adding new functionalities.

Abstract

Page segmentation is a basic step in any character recognition system. Its failure is one of the major causes for deteriorating overall accuracy of the current Indian language OCR engines. Many segmentation algorithms are proposed in literature. Often these algorithms fail to adapt dynamically to a given page and thus tend to yield poor segmentation for some specific regions or some specific pages. Given the ground truth, locating page segmentation errors is a straight foreword problem and merely useful for comparing segmentation algorithms. In this work, we locate segmentation errors without directly using the ground truth. Such automatic localization of page segmentation errors can be considered a major step towards improving page segmentation errors. In this work, we focus on localizing line level segmentation errors. We perform experiments on more than 18000 scanned pages of 109 books belonging to four prominent south Indian languages.

Abstract

Inspired by the success of MRF models for solving object segmentation problems, we formulate the binarization problem in this framework. We represent the pixels in a document image as random variables in an MRF, and introduce a new energy (or cost) function on these variables. Each variable takes a foreground or background label, and the quality of the binarization (or labelling) is determined by the value of the energy function. We minimize the energy function, i.e. find the optimal binarization, using an iterative graph cut scheme. Our model is robust to variations in foreground and background colours as we use a Gaussian Mixture Model in the energy function. In addition, our algorithm is efficient to compute, and adapts to a variety of document images. We show results on word images from the challenging ICDAR 2003 dataset, and compare our performance with previously reported methods. Our approach shows significant improvement in pixel level accuracy as well as OCR accuracy.