Informatics Publishing Limited

Savita Ahlawat ¹, Promila Batra ², Anirudh Sharma ²

Affiliations
1 Department of Psychology, F. C. College for Women, Hisar, IN
2 Department of Psychology, M.D.U. Rohtak, IN

Abstract

Music has been found to increase the productivity as well performance in industrial sectors. The studies in relation to academics are however, very sparse yet. In day to day life music is common and often unavoidable. The students are fond of playing music while studying. But the effects cannot be the same for everyone. Keeping such factors in mind, it was felt highly relevant to study the effect of music on arithmatic task amongst different personality types, i.e., extroverts and introverts. The present study was a 3x2 factorial (repeated measure) design to investigate the effect of music on arithmetic performance amongst extroverts and introverts having an age range of 14-16 years. The sample of 27 students (18 extroverts and 9 introverts) was screened out from a school of Nangloi (Delhi) after administering the introversion and extroversion inventory by Aziz and Agnihotry. After this, 3 different sets of arithmetic ability tasks were standardized and administered on these subjects in three different musical conditions (silence, instrumental and vocal). Errors and time taken were recorded. The results were analyzed by 2-way ANOVA followed by DRT indicated that music enhanced the performance in terms of speed much more than in terms of errors. Regarding speed, the type of music did not affect the extroverts and introverts differently, but regarding the errors, introverts were the gainer i.e. they committed lesser errors. It was also found that any type of music was better than silence condition. So music can be used as a facilitating agent in different domains of life.

Keywords

Personality, Music, Arithmatic Performance.

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Anirudh Sharma , Pranshu Sharma

Abstract

To get more interactive with virtual reality systems, hand gesture recognition appears as a suitable mean. Gesture recognition are of different types making use of other types has been a research topic for many years. However, the use of cameras technology for automatic gesture recognition is in its infant stage. Cameras, with its potential of simultaneously capturing a full 3D point with a sensor in video rates, this provides us with a great potential for real-time measurement of dynamic scenes. With the help of camera the aim is to build a man - machine interface, this will be done using a range in camera for identifying hand gestures.  In the near future, gesture recognition technology will routinely add yet another dimension to human interactions with consumer electronic devices such as PCs, media tablets and Smartphones. Gesture recognition is a very exciting prospect, particularly for Smartphones and tablets. Camera-based tracking for gesture recognition has actually been in use for some time. Leading video game consoles Microsoft’s Xbox and Sony’s PlayStation both have gesture recognition built-in.

There are certain limitations related to gesture recognition like adverse light conditions, variations in the background, and high power consumption. Gesture recognition will likely become a useful feature for all media tablets, portable media players, and portable game players. Over time, it is anticipated that a higher percentage of media tablets will have the technology, rather than Smartphones  This research demonstrates the capability of a range camera for real-time gesture recognition applications.

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