Abstract

The method of calibrated simulation has been used to estimate the energy savings by application of cool roof for the building of Satyam Learning Centre (SLC) at Hyderabad (India). Energy simulation model of the building was created using ‘DesignBuilder v. 1.95’and the building was monitored for few months. Mismatch between the simulation results and actual energy consumption has been reduced to obtain the calibrated model of the building using the method suggested in IPMVP Option-D. The calibrated model is then used to predict energy saving from the cool roof; the annual cooling energy savings were 19.4 kWh/m2. This saving corresponds to 9% reduction in annual air conditioning load and 5% reduction in overall annual energy consumption. Cost/benefit analysis for cool roof at SLC showed a 2.4 year financial payback period.

Abstract

This paper explores the area of creating smart spaces using mobile Internet devices to develop intelligent classrooms. We propose a suite of applications that leverage the recent progress made in the domains of mobile computers and information access, resulting in a richer classroom experience where knowledge is dispensed with greater efficiency while also making it possible to access it efficiently from the Internet as well as peers. We attempt to achieve this by introducing novel means of classroom teaching and management and an intelligent information access system while harnessing the computational capabilities of mobile Internet devices. Though the current work is still in progress, this paper elaborates on our attempts in reducing the gap between technological progress in various domains and the existing pedagogy.

Abstract

EnergyPlus is an energy simulation tool which models heating, cooling, lighting, ventilation, and other energy flows in buildings. It is based on the popular features of BLAST and DOE-2. Though EnergyPlus is more advanced than DOE-2, it comes with a drawback of larger simulation runtime. A decrease in the simulation runtime of EnergyPlus would increase the usability of the software. In this paper, a concept has been proposed which uses data parallelization to speed up EnergyPlus simulation. Data parallelization is a form of parallelization for computing across multiple processors or multiple computers in a cluster, run under a suitable environment. Data parallelism focuses on distributing the data across different parallel computing nodes by breaking it into smaller chunks, each of which is processed on by the same function, running in parallel on different cores/machines. In the proposed concept, this is …

Abstract

By extending information and communication technologies, a personalizedagricultural advisory system called eSaguTMhas been developed in which the farmersreceive agricultural expert advice for each of their farms at regular intervals. The expertadvice is prepared by agricultural experts based on the crop status information receivedin the form of both digital photographs and text. During 2004-05, the eSaguTMsystemwas operated for 1051 cotton farms covering three villages in the state of AndhraPradesh, India. In eSaguTM, the expert advice had been delivered to every cottonfarm, once in a week. As a result, the data set consisting of about 20,000 such advicetexts had been generated. In this paper, we have carried out the cluster/textualanalysis experiments on the data set and reported interesting results concerning thedynamics of crop problems. Normally, all are cotton farms and belonging to nearbyarea/region should have faced similar problems. However, the cluster analysis of theadvices delivered on each day shows that significant number of farms are suffering fromdistinct crop production problems. The results also indicate that, a cluster of farmswhich face the same crop problem during one week face distinct crop problems duringthe subsequent weeks. Based on the results, we can conclude that it is necessaryto deliver agricultural expert advice to each farm by building agricultural advisorysystems which deliver farm-specific agricultural advices to reduce crop failures andimprove crop productivity.

Abstract

The effect of variation of the water model on the temperature dependence of protein and hydration water dynamics is examined by performing molecular dynamics simulations of myoglobin with the TIP3P, TIP4P, and TIP5P water models and the CHARMM protein force field at temperatures between 20 and 300 K. The atomic mean-square displacements, solvent reorientational relaxation times, pair angular correlations between surface water molecules, and time-averaged structures of the protein are all found to be similar, and the protein dynamical transition is described almost indistinguishably for the three water potentials. The results provide evidence that for some purposes changing the water model in protein simulations without a loss of accuracy may be possible.

Abstract

Gold nanostars provide high sensitivity for single nanoparticle label-free biosensing. The nanostars present multiple plasmon resonances of which the lower energy ones, corresponding to the nanostar tips and core−tip interactions, are the most sensitive to environmental changes. Streptavidin molecules are detected upon binding to individual, biotin-modified gold nanostars by spectral shifts in the plasmon resonances. Concentrations as low as 0.1 nM produce a shift of the tip related plasmon resonances of about 2.3 nm (5.3 meV).

Abstract

The present invention provides a method for manufacture of supported noble metal based alloy catalysts with a high degree of alloying and a small crystallite size. The method is based on the use of polyol solvents as reaction medium and comprises of a two-step reduction process in the presence of a support material. In the first step, the first metal (M1= 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 (M2= noble metal; eg Pt, Pd, Au and mixtures thereof) is added and the slurry is heated to the boiling point of the polyol solvent in a range of 160 to 300 C. Due to this two-step method, an uniform reduction occurs, resulting in noble metal based catalysts with a high degree of alloying and a small crystallite size of less than 3 nm. Due to the high degree of alloying, the lattice constants are lowered. The catalysts manufactured …

Abstract

Analysis of human reference summaries of broadcast news showed that humans give preference to anchor speaker segments while constructing a summary. Therefore, we exploit the role of anchor speaker in a news show by tracking his/her speech to construct indicative/informative extractive audio summaries. Speaker tracking is done by Bayesian information criterion (BIC) technique. The proposed technique does not require Automatic Speech Recognition (ASR) transcripts or human reference summaries for training. The objective evaluation by ROUGE showed that summaries generated by the proposed technique are as good as summaries generated by a baseline text summarization system taking manual transcripts as input and summaries generated by a supervised speech summarization system trained using human summaries. The subjective evaluation of audio summaries by humans showed that they prefer summaries generated by proposed technique to summaries generated by supervised speech summarization system.

Abstract

The problem of measuring semantic relatedness between social tags remains largely open. Given the structure of social bookmarking systems, similarity measures need to be addressed from a social bookmarking systems perspective. We address the fundamental problem of weight model for tags over which every similarity measure is based. We propose a weight model for tagging systems that considers the user dimension unlike existing measures based on tag frequency. Visual analysis of tag clouds depicts that the proposed model provides intuitively better scores for weights than tag frequency. We also propose weighted similarity model that is conceptually different from the contemporary frequency based similarity measures. Based on the weighted similarity model, we present weighted variations of several existing measures like Dice and Cosine similarity measures. We evaluate the proposed similarity model using Spearman's correlation coefficient, with WordNet as the gold standard. Our method achieves 20% improvement over the traditional similarity measures like dice and cosine similarity and also over the most recent tag similarity measures like mutual information with distributional aggregation. Finally, we show the practical effectiveness of the proposed weighted similarity measures by performing search over tagged documents using Social SimRank over a large real world dataset.

Abstract

The problem of extracting bilingual dictionaries from Wikipedia is well known and well researched. Given the structural and rich multilingual content of Wikipedia, a language independent approach is necessary for extracting dictionaries for various languages more so for under-resourced languages. In our attempt to mine dictionaries for under-resourced languages, we developed an iterative approach to construct parallel corpus for building a dictionary, for which we consider several kinds of Wikipedia article information like title, infobox information, category, article text and dictionaries already built at each phase. The average precision over various datasets is encouraging with maximum precision of 76.7%, performing better than existing systems. As no language-specific resources are used, our method is applicable to any pair of language with special focus on under-resourced languages and hence breaking the language barrier.