Abstract

Rare association rules are the association rules consisting ofrare items. It is difficult to mine rare association rules withthe single minimum support based approaches such as Apri-ori and FP-growth as they suffer fromrare item problem. Inthe literature, efforts has been made to extract rare associa-tion rules with multiple minimum supports. It was observedthat the multiple minimum supports-based approach stillsuffers from performance problems. As a part of proposedwork, we have analyzed the multiple minimum supports-based approach and proposed improved approaches for ex-tracting rare association rules. Experimental results showthat the proposed approaches are efficient

Abstract

Speculative locking (SL) protocols have been proposed inthe literature for improving the performance of read-onlytransactions (ROTs) without correctness and data currencyissues. In these protocols, ROTs carry out speculative ex-ecutions and update transactions (UTs) follow two-phaselocking (2PL). In these protocols, UTs are blocked if theyconflict with ROTs. To reduce blocking of UTs, semantics-based protocol has been proposed in the literature by ex-ploiting the “compensatability” property of ROTs. In thatprotocol compensatable ROTs are processed without block-ing and non-compensatable ROTs are processed by usingsynchronous speculation method. In this paper, we haveproposed a semantics-based speculative locking protocol forROTs in which non-compensatable ROTs are processed withasynchronous speculation method. The simulation resultsshow that the proposed approach improves the performanceof ROTs over other protocols

Abstract

In the pervasive computing era, mobile phones and personaldigital assistants are widely used for data collection. The traditional userinterfaces which are employed for data collection in personal computerenvironments are to be modified appropriately for the mobile environ-ment. Because, it is difficult to display full interface on a single mobilescreen due to the limitation of the mobile phone screen size. Interfacetailoring methods are investigated in the literature for designing user in-terface for mobile screens. In the literature, temporality-based approachis proposed for designing efficient user interface for personal computerenvironment. In this paper, we extend the notion of attribute temporalityto interface tailoring methods and propose an improved user interface de-sign approach for small screens. The analysis on the real-world datasetsshows that the proposed approach can be used for better user interfacedesign for small screens.

Abstract

In the Internet era, the enterprises and companies receive thousands ofresumes from the job seekers. Currently available filtering techniques and searchservices help the recruiters to filter thousands of resumes to few hundred poten-tial ones. Since these filtered resumes are similar to each other, it is difficult toidentify the potential resumes by examining each resume. We are investigatingthe issues related to the development of approaches to improve the performanceof resume selection process. We have extended the notion of special features andproposed an approach to identify resumes with special skill information. In theliterature, the notion of special features have been applied to improve the pro-cess of product selection in E-commerce environment. However, extending thenotion of special features for the development of approach to process resumes isa complex task as resumes contain unformatted text or semi-formatted text. Inthis paper, we have proposed an approach by considering only skills related in-formation of the resumes. The experimental results on the real world data-set ofresumes show that the proposed approach has the potential to improve the processof resume selection.

Abstract

In the literature, speculation-based protocols have been pro-posed to improve the performance of read-only transactions(ROTs) over the existing two-phase locking (2PL) and snap-shot isolation(SI)-based protocols. In this paper, we havecompared the performance of asynchronous speculation-basedprotocol with 2PL and SI-based protocols through analyti-cal and simulation methods. The results show that asyn-chronous speculation-based protocol improves the perfor-mance over 2PL and SI-based protocols.

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.