DATA MINING ON CRUDE, PARTIALLY PURIFIED AND DOPED SILVER NANOPARTICLES OF TWO PLANT SPECIES AGAINST DENGUE VECTOR, Aedes aegypti
RAJMOHAN DEVADASS *
Department of Zoology, PG and Research, Kongunadu Arts and Science College, Coimbatore, Tamilnadu, India
HALDURAI LINGARAJ
Department of Computer Science (PG), Kongunadu Arts and Science College, Coimbatore, Tamilnadu, India
RANJITHKUMAR RAJAMANI
Department of Biotechnology, Dr. N. G. P. Arts and Science College, Coimbatore, Tamilnadu, India
LOGANKUMAR KANDASAMY
Department of Zoology, PG and Research, Kongunadu Arts and Science College, Coimbatore, Tamilnadu, India
CHANDAR SHEKAR BELLAN
Department of Physics, Nanotechnology Research Lab, Kongunadu Arts and Science College, Coimbatore, Tamilnadu, India
*Author to whom correspondence should be addressed.
Abstract
Data mining is one of the essential steps in knowledge discovery from databases process to understand comparative analysis of specific value. The raw data are extracted from the database and preprocessed to clean the data which is inconsistent. Intelligent methods are implemented to extract data patterns from the database is the main process of data mining to identify with accurate assessment. The present study focused on evaluating the crude, partially purified and doped silver nanoparticles of two plant species, Tridax procumbens and Annona squamosa against the developmental stages of Dengue vector, Aedes aegypti. This paper elucidates the process of extracting the clean data from the actual (raw) data against the developmental stages of Dengue vector, A. aegypti using TANAGRA tool. This comparative analysis clearly shows that the experimental plants doped silver nanoparticles showed maximum efficacy on various stages of the Dengue vector, A. aegypti.
Keywords: Data mining, AgNPs, Aedes aegypti, Tridax procumbens, Annona squamosa, LC50