Web scraping is a technique to extract information from various web documents automatically. It retrieves the related contents based on the query, aggregates and transforms the data from an unstructured format into a structured representation. Text classification becomes a vital phase to summarize the data and in categorizing the webpages adequately. In this article, using effective web scraping methodologies, the data is initially extracted from websites, then transformed into a structured form. Based on the keywords from the data, the documents are classified and labeled. A recursive feature elimination technique is applied to the data to select the best candidate feature subset. The final data-set trained with standard machine learning algorithms. The proposed model performs well on classifying the documents from the extracted data with a better accuracy rate.

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In recent years, WiFi offloading provides a potential solution for improving ad hoc network performance along with cellular network. This paper reviews the different offloading techniques that are implemented in various applications. In disaster management applications, the cellular network is not optimal for existing case studies because the lack of infrastructure. MANET Wi-Fi offloading (MWO) is one of the potential solutions for offloading cellular traffic. This word combines the cellular network with mobile ad hoc network by implementing the technique of Wi-Fi offloading. Based on the applications requirements the offloading techniques implemented into mobile-to-mobile (M-M), mobile-to-cellular (M-C), mobile-to-AP (M-AP). It serves more reliability, congestion eliminated, increasing data rate, and high network performance. The authors also identified the issue while implementing the offloading techniques in network. Finally, this paper achieved the better performance results compared to existing approaches implemented in disaster management.

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Over 200 million yearly reports of diseases identified with scarce water and sanitation conditions, 5-10 million deaths occurred worldwide. Water quality checking has subsequently gotten important to supply clean and safe water. This survey work depicts the fundamental explanation behind the requirement for robust and productive Water level, Drought, and water quality control in the level framework, which will keep human assets healthy, sustainable and diminish water use for household purposes. Climate change and variability have so many significant impacts caused by the natural environment’s water system. Incredible methods, collection of water samples are tested alone and analyzed in water laboratories. However, it is not always easy to capture, analyze, and rapidly disseminate information to relevant users to make timely and well-informed decisions. The review work encompasses traditional methods based on Machine Learning (ML), and Deep Learning (DL) approaches.