Using open source software for digital libraries A case study of CUSAT

The purpose of this paper is to describe the design and development of a digital library at Cochin University of Science and Technology (CUSAT), India, using DSpace open source software. The study covers the structure, contents and usage of CUSAT digital library. Design/methodology/approach – This paper examines the possibilities of applying open source in libraries. An evaluative approach is carried out to explore the features of the CUSAT digital library. The Google Analytics service is employed to measure the amount of use of digital library by users across the world. Findings – CUSAT has successfully applied DSpace open source software for building a digital library. The digital library has had visits from 78 countries, with the major share from India. The distribution of documents in the digital library is uneven. Past exam question papers share the major part of the collection. The number of research papers, articles and rare documents is less. Originality/value – The study is the first of its type that tries to understand digital library design and development using DSpace open source software in a university environment with a focus on the analysis of distribution of items and measuring the value by usage statistics employing the Google Analytics service. The digital library model can be useful for designing similar systems

Jitter measurements for Performance enhancement in the Service Sector

In a leading service economy like India, services lie at the very center of economic activity. Competitive organizations now look not only at the skills and knowledge, but also at the behavior required by an employee to be successful on the job. Emotionally competent employees can effectively deal with occupational stress and maintain psychological well-being. This study explores the scope of the first two formants and jitter to assess seven common emotional states present in the natural speech in English. The k-means method was used to classify emotional speech as neutral, happy, surprised, angry, disgusted and sad. The accuracy of classification obtained using raw jitter was more than 65 percent for happy and sad but less accurate for the others. The overall classification accuracy was 72% in the case of preprocessed jitter. The experimental study was done on 1664 English utterances of 6 females. This is a simple, interesting and more proactive method for employees from varied backgrounds to become aware of their own communication styles as well as that of their colleagues' and customers and is therefore socially beneficial. It is a cheap method also as it requires only a computer. Since knowledge of sophisticated software or signal processing is not necessary, it is easy to analyze