Setting up Multilingual Information Repository: A case Study with EPrints.org Software

Today 80 % of the content on the Web is in English, which is spoken by only 8% of the World population and 5% of Indian population. There is wealth of useful content in the various languages of the world other than English, which can be made available on the Internet. But, to date, for various reasons most of it is not yet available on the Internet. India itself has 18 officially recognized languages and scores of dialects. Although the medium of instruction for most of the higher education and research in India is English, substantial amount of literature by way of novels, textbooks, scholarly information are being generated in the other languages in the country. Many of the e-governance initiatives are in the respective state languages. In the past, support for different languages by the operating systems and the software packages were not very encouraging. However, with the advent of Unicode technology, operating systems and software packages are supporting almost all the major languages of the world that have scripts. In the work reported in this paper, we have explained the configuration changes that are needed for Eprints.org software to store multilingual content and to create a multilingual user interface.

Comparison of North American universities with and without medical schools and their technology transfer initiatives

Empirical research available on technology transfer initiatives is either North American or European. Literature over the last two decades shows various research objectives such as identifying the variables to be measured and statistical methods to be used in the context of studying university based technology transfer initiatives. AUTM survey data from years 1996 to 2008 provides insightful patterns about the North American technology transfer initiatives, we use this data in our paper. This paper has three sections namely, a comparison of North American Universities with (n=1129) and without Medical Schools (n=786), an analysis of the top 75th percentile of these samples and a DEA analysis of these samples. We use 20 variables. Researchers have attempted to classify university based technology transfer initiative variables into multi-stages, namely, disclosures, patents and license agreements. Using the same approach, however with minor variations, three stages are defined in this paper. The first stage is to do with inputs from R&D expenditure and outputs namely, invention disclosures. The second stage is to do with invention disclosures being the input and patents issued being the output. The third stage is to do with patents issued as an input and technology transfers as outcomes.