Documents clustering are an important task in digital data base of textual documents. Manual clustering of text documents is very tedious and time consuming and labour intensive as well. The keywords vector set determine the vicinity of documents among each other in a given data base. In the presented algorithm, the keywords are extracted from the documents based on the font style, frequency of...

Objective-The main purpose of this paper is to construct a distributed clustering algorithm such that each distributed cluster can perform the data accuracy at their respective cluster head node before data aggregation and transmit the data to the sink node. Design approach/Procedure – We investigate that the data are spatially correlated among the sensor nodes which form the clusters in the sp...

To identify potential genotypes for location specific breeding programmes of Andhra Pradesh, genetic diversity among 537 chickpea germplasm accessions was assessed yield attributing traits during rabi 2020-21 at Regional Agricultural Research Station, Acharya N.G. Ranga University, Nandyal, Pradesh. K-means clustering utilised to ascertain distances which were grouped into 12 different clusters...

Introduction: The Co-word analysis has the ability to identify the intellectual structure of knowledge ‎in a research domain and reveal its subsurface research aspects.‎ Objective: This study examines the intellectual structure of knowledge in the field of nanomedicine ‎during the period of 2009 to 2018 by using Co-word analysis.‎ Materials and Methods: This paper develops a sciento...

BACKGROUND: Giardia lamblia is the most frequently identified human intestinal parasite in Canada with prevalence estimates of 4-10%. However, infection rates vary by geographical area and localized 'pockets' of high or low infection rates are thought to exist. Water-borne transmission is one of the major routes of infection. Sources of contamination of drinking water include humans, domestic a...