Music Similarity Estimation

Music is a complicated form of communication, where creators and culture communicate and expose their individuality. After music digitalization took place, recommendation systems and other online services have become indispensable in the field of Music Information Retrieval (MIR). To build these systems and recommend the right choice of song to the user, classification of songs is required. In this paper, we propose an approach for finding similarity between music based on mid-level attributes like pitch, midi value corresponding to pitch, interval, contour and duration and applying text based classification techniques. Our system predicts jazz, metal and ragtime for western music. The experiment to predict the genre of music is conducted based on 450 music files and maximum accuracy achieved is 95.8% across different n-grams. We have also analyzed the Indian classical Carnatic music and are classifying them based on its raga. Our system predicts Sankarabharam, Mohanam and Sindhubhairavi ragas. The experiment to predict the raga of the song is conducted based on 95 music files and the maximum accuracy achieved is 90.3% across different n-grams. Performance evaluation is done by using the accuracy score of scikit-learn

Is That Twitter Hashtag Worth Reading

Online social media such as Twitter, Facebook, Wikis and Linkedin have made a great impact on the way we consume information in our day to day life. Now it has become increasingly important that we come across appropriate content from the social media to avoid information explosion. In case of Twitter, popular information can be tracked using hashtags. Studying the characteristics of tweets containing hashtags becomes important for a number of tasks, such as breaking news detection, personalized message recommendation, friends recommendation, and sentiment analysis among others. In this paper, we have analyzed Twitter data based on trending hashtags, which is widely used nowadays. We have used event based hashtags to know users' thoughts on those events and to decide whether the rest of the users might find it interesting or not. We have used topic modeling, which reveals the hidden thematic structure of the documents (tweets in this case) in addition to sentiment analysis in exploring and summarizing the content of the documents. A technique to find the interestingness of event based twitter hashtag and the associated sentiment has been proposed. The proposed technique helps twitter follower to read, relevant and interesting hashtag.Comment: 10 pages, 6 figures, Presented at the Third International Symposium on Women in Computing and Informatics (WCI-2015

Functional Renormalization Description of the Roughening Transition

We reconsider the problem of the static thermal roughening of an elastic manifold at the critical dimension $d=2$ in a periodic potential, using a perturbative Functional Renormalization Group approach. Our aim is to describe the effective potential seen by the manifold below the roughening temperature on large length scales. We obtain analytically a flow equation for the potential and surface tension of the manifold, valid at all temperatures. On a length scale $L$, the renormalized potential is made up of a succession of quasi parabolic wells, matching onto one another in a singular region of width $\sim L^{-6/5}$ for large $L$. We also obtain numerically the step energy as a function of temperature, and relate our results to the existing experimental data on $^4$He. Finally, we sketch the scenario expected for an arbitrary dimension $d<2$ and examine the case of a non local elasticity which is realized physically for the contact line.Comment: 21 pages, 2 .ps figures. Submitted to E.P.J.

Firm-Specific Information and the Efficiency of Investment

We use a new firm-level dataset to examine the efficiency of investment in emerging economies. In the three-year period following stock market liberalizations, the growth rate of the typical firm's capital stock exceeds its pre-liberalization mean by an average of 5.4 percentage points. Cross-sectional changes in investment are significantly correlated with the signals about fundamentals embedded in the stock price changes that occur upon liberalization. Panel data estimations show that a 1-percentage point increase in a firm's expected future sales growth predicts a 4.1-percentage point increase in its investment; country-specific changes in the cost of capital predict a 2.3-percentage point increase in investment; firm-specific changes in risk premia do not affect investment.

Capital Account Liberalization, Risk Sharing and Asset Prices

In the month that the capital account is liberalized, all publicly traded firms experience a 7 percent stock price revaluation. Firms whose shares become eligible for purchase by foreigners experience and additional revaluation that is directly proportional to their firm specific reduction in aggregate risk -- the covariance of the typical firm's stock return with the local market is on average 30 times larger than its covariance with the world market. The statistical significance of this proportionality persists after controlling for the firm-specific effects of liberalization on expected future profits in this sample of of 411 firms from 11 countries. These findings suggest that capital account liberalization facilitates risk sharing.