arXiv subjects

C. Balasubramanian

Publications and source records attributed to C. Balasubramanian.

4 recordsLinked to original sources

arXiv2014

X-ray absorption spectroscopy characterization of iron-oxide nanoparticles synthesized by high temperature plasma processing

Iron-oxide nanoparticles have been synthesized by high temperature arc plasma route with different plasma currents and characterized for their structure, morphology and local atomic order. Fe K-edge x-ray absorption spectra reveal distinct local structure of the samples grown with different plasma currents. We have shown that the local disorder is higher for the higher plasma current grown samples that also have a larger average particle-size. The results provide useful information to control structural and morphological properties of nanoparticles grown by high temperature plasma synthesis process.

cond-mat.mtrl-sci↗

arXiv2010

Similarity Data Item Set Approach: An Encoded Temporal Data Base Technique

Data mining has been widely recognized as a powerful tool to explore added value from large-scale databases. Finding frequent item sets in databases is a crucial in data mining process of extracting association rules. Many algorithms were developed to find the frequent item sets. This paper presents a summary and a comparative study of the available FP-growth algorithm variations produced for mining frequent item sets showing their capabilities and efficiency in terms of time and memory consumption on association rule mining by taking application of specific information into account. It proposes pattern growth mining paradigm based FP-tree growth algorithm, which employs a tree structure to compress the database. The performance study shows that the anti- FP-growth method is efficient and scalable for mining both long and short frequent patterns and is about an order of magnitude faster than the Apriority algorithm and also faster than some recently reported new frequent-pattern mining.

cs.DB↗

arXiv2009

An Application of Bayesian classification to Interval Encoded Temporal mining with prioritized items

In real life, media information has time attributes either implicitly or explicitly known as temporal data. This paper investigates the usefulness of applying Bayesian classification to an interval encoded temporal database with prioritized items. The proposed method performs temporal mining by encoding the database with weighted items which prioritizes the items according to their importance from the user perspective. Naive Bayesian classification helps in making the resulting temporal rules more effective. The proposed priority based temporal mining (PBTM) method added with classification aids in solving problems in a well informed and systematic manner. The experimental results are obtained from the complaints database of the telecommunications system, which shows the feasibility of this method of classification based temporal mining.

cs.DB↗

arXiv2004

Accelerator Tests of Crystal Undulators

A series of Silicon crystal undulator samples were produced based on the approach presented in PRL 90 (2003) 034801, with the periods of undulation from 0.1 mm to 1 mm, and the number of periods on the order of 10. The samples were characterized by X-rays, revealing the sine-like shape of the crystal lattice in the bulk. Next step in the characterization has been the channeling tests done with 70 GeV protons, where good channeling properties of the undulated Silicon lattice have been observed. The photon radiation tests of crystal undulators with high energy positrons are in progress on several locations: IHEP Protvino, LNF Frascati, and CERN SPS. The progress in the experimental activities and the predictions from detailed simulations are reported.

physics.acc-ph↗