No abstract

The COVID-19 pandemic, is also known as the coronavirus pandemic, is an ongoing serious global problem all over the world. The outbreak first came to light in December 2019 in Wuhan, China. This was declared pandemic by the World Health Organization on 11th March 2020. COVID-19 virus infected on people and killed hundreds of thousands of people in the United States, Brazil, Russia, India and several other countries. Since this pandemic continues to affect millions of lives, and a number of countries have resorted to either partial or full lockdown. People took social media platforms to share their emotions, and opinions during this lockdown to find a way to relax and calm down. In this research work, sentiment analysis on the tweets of people from top ten infected countries has been conducted. The experiments have been conducted on the collected data related to the tweets of people from top ten infected countries with the addition of one more country chosen from Gulf region, i.e.

Injection in SQL (structure query language) is one of the threats to web-based apps, mobile apps and even desktop applications associated to the database. An effective SQL Injection Attacks (SQLIA) could have severe implications for the victimized organization including economic loss, loss of reputation, enforcement and infringement of regulations. Systems which do not validate the input of the user correctly make them susceptible to SQL injection. SQLIA happens once an attacker can incorporate a sequence of harmful SQL commands into a request by changing back-end database through user information. To use this sort of attacks may readily hack applications and grab the private information by the attacker. In this article we introduce deferential sort of process to safeguard against current SQLIA method and instruments that are used in ASP.NET apps to detect or stop these attacks.

Information Retrieval (IR) deals with searching, retrieving and presenting information within the WWW and online databases and also searches the web documents. Genetic Algorithms (GA) are robust and efficient search and optimization techniques inspired by the Darwin's theory of natural evolution. In this paper, the applicability of Genetic algorithm (GA) in the field of information retrieval and a review on how a Genetic Algorithm is applied to different problem domains in information retrieval is discussed.

Large amounts of data are generated every moment by connected objects creating Internet of Things (IoT). IoT isn’t about things; it’s about the data those things create and collect. Organizations rely on this data to provide better user experiences, to make smarter business decisions, and ultimately fuel their growth. However, none of this is possible without a reliable database that is able to handle the massive amounts of data generated by IoT devices. Relational databases are known for being flexible, easy to work with, and mature but they aren’t particularly known for is scale, which prompted the creation of NoSQL databases. Another thing to note is that IoT data is time-series in nature. In this paper we are discussed and compare about top five time-series database like InfluxDB, Kdb+, Graphite, Prometheus and RRDtool.