The Effect of SIFT Features as Content Descriptors in the Context of Automatic Writer Identification in Malayalam Language

The span of writer identification extends to broad domes like digital rights administration, forensic expert decisionmaking systems, and document analysis systems and so on. As the success rate of a writer identification scheme is highly dependent on the features extracted from the documents, the phase of feature extraction and therefore selection is highly significant for writer identification schemes. In this paper, the writer identification in Malayalam language is sought for by utilizing feature extraction technique such as Scale Invariant Features Transform (SIFT).The schemes are tested on a test bed of 280 writers and performance evaluated

SUBKAVYA: KATHYA KE VIBHINNA AYAM (POETRY OF SURDAS-DIFFERENT DIMENSIONS OF POETIC CONTENT)

HINDI

Content aggregation on knowledge bases using graph clustering

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.

Determination of the silvo-melliferous regions of Benin: a nationwide categorisation of the land based on melliferous plants suitable for timber production

Perennial plants are the main pollen and nectar sources for bees in the tropical areas where most of the annual flora are burned in dry seasons. Therefore perennial plants constitute the most reliable bio materials for determining and evaluating the beekeeping regions of the Republic of Benin. A silvo-melliferous region (S-MR) is a geographical area characterised by a particular set of homogenous melliferous plants that can produce timber. Using both the prevailing climatic and the agro-ecological conditions six S-MRs could be identified, i.e. the South region, the Common Central region, the Central West region, the Central North region, the Middle North region and the Extreme North region. At the country level, the melliferous plants were dominated by Vitellaria paradoxa which is common to all regions. The most diversified family was the Caesalpiniaceae (12 species) followed by the Combretaceae (10 species) and Combretum being the richest genus. The effect of dominance is particularly high in the South region where Elaeis guineensis alone represented 72.6% of the tree density and 140% of the total plant importance. The total melliferous plant density varied from 99.3 plants ha^(−1) in the Common Central region to 178.0 plants ha^(−1) in the Central West region. On the basis of nectar and pollen source, the best region for beekeeping is the CentralWest region with 46.7% of nectar producing trees, 9.4% of pollen producing trees and 40.6% of plants that issue both, this in opposition to the South region which was characterised by an unbalanced distribution of melliferous trees.

COMP6218 Web Architecture - Web Content Formats

Plain Text - ASCII, Unicode, UTF-8 Content Formats - XML-based formats (RSS, MathML, SVG, Office) + PDF Text based data formats: CSV, JSON

iTunesU - open educational content in audio and video formats available via iTunes

There is a wealth of open educational content in audio and video formats available via iTunes U, one of the services offered especially for education via iTunes. There are details of how to get started as well as an informative video to help you. Details of how to get started with sharing content can be found for developers.

Part 1 - talk on using Creative Commons and opensource software to make Open Content (what is creative commons ?, what is open content ?)

This is the first part of a 2 part video from my talk in May 2008 on open source content creation.

Part 2 - talk on using Creative Commons and opensource software to make Open Content. (Making of Doljer)

This is the second part of a 2 part video from my talk in May 2008 on open source content creation. Here I am talking about the Making of Doljer

A-level chemistry content

This document outlines the material covered by the main UK exam board specifications at A-level in chemistry. This is for the A-level taught up until and including June 2009 (i.e. relevant to undergraduates arriving at university in October 2009).

Review of A-level Chemistry content 2010

This document is a review of the content of the A-level Chemistry specifications from the main UK exam boards (Scottish highers not included - sorry!). These A-level specifications commenced teaching in September 2008. Students entering university in 2010 will have studied the new A-levels, and this document is intended to help academics to identify what students will have covered. The document also contains a summary of discussions which took place between teachers and academics at our annual Post-16 teachers' day in June 2010 regarding the nature of the 2010 intake and their capabilities in chemistry. Please inform us of any errors or typos that you spot and we'll update the document. LAST UPDATE at 13:15 on Aug 27th 2010.

Creating a Table of Contents to cover only part of a file's content using MS Word 2011 for Apple computers

A Table of Contents can be tweaked so that it picks up the content from only part of a file (such as an Appendix). This video shows you how to make such a change to a Table of Contents that is based upon Heading Styles. For best viewing Download the video.

Sustaining Success Week 4 Task: Student Generated Content

Description of student generated content which you can choose to submit

Caches and Content Delivery

Getting content from server to client can be more complicated than we have discussed so far. This lecture discusses how caching and content delivery networks help to make the Web work.