Objectives: To propose a crawler to visit websites for collecting information and create a search engine index for reference; To compare various crawler License, language used for creation, effectiveness with proposed DHEKTS crawler; To compare various characteristics, tasks and functions with proposed DHEKTS crawler; To identify the merits of the DHEKTS Crawler. Methods: A new Crawler called DHEKTS is developed to filter and synchronize documents like Images, Link, and HTML code from a given website. This Crawler is unique in nature since it returns all the details of a particular website having Images, Links, html code and contents. It can crawl through links in a specified website and crawl further to other links on the website. The DHEKTS Crawler is designed for Depth and Relevance crawling. The entire DHEKTS crawler has a few crawling mechanism supporting variety of information. The requirements are Operating System: Win 7 and higher, Front End: PHP, BackEnd: MySQL, RAM: Minimum 4GB and SERVER: High Speed Server with good storage Capacity. Findings: The DHEKTS Crawler has brought web related Links, Images, HTML Code, Information about to fifth level of crawling and Relevance Search giving relevant information. Multiple crawlers fulfill the major functions of crawling but DHEKTS CRAWLER is built to execute all functions in one crawler. Applications: This is applied in Crawling of various Websites and to retrieve valuable data.

In this present study, biosynthesis of AgNp’s from methanolic extracts of H. Colorata and its wound healing activity was documented. The synthesis of AgNp’s was done by treating AgNO3 solution with an aqueous extract of H. colorata. The production of AgNp’s was confirmed by a color change of the solution from clear to brown color. The reduced AgNp’s were characterized by Scanning Electron Microscope (SEM), UV–vis spectroscopy. From UV analysis peak was observed at 415nm and spherical shaped AgNp’s were observed. The antibacterial activity and Minimum inhibitory Concentration (MIC) of the silver nanoparticles were determined. The results suggest that biosynthesized AgNp’s from aqueous extracts ofH.coloratashowed a significant antibacterial activity against wound pathogens.

This research paper explores a variety of strategies for performing classification with missing feature values. The classification setting is particularly affected by the presence of missing feature values since most discriminative learning approaches including logistic regression, support vector machines, and neural networks have no natural ability to deal with missing input features. Our main interest is in classification methods that can both learn from data cases with missing features, and make predictions for data cases with missing features.