No abstract

The most well-known cryptocurrency, Bitcoin, is one of many that are sweeping the globe. Along with them, fungible tokens traded on numerous centralised or decentralised exchanges are different from non-fungible tokens traded on NFT marketplaces. The majority of NFTs are currently digital, and in the future, producers may innovate in this area to allow for more innovative user experiences. The blockchain and its NFTs can provide fantastic chances for artists and content producers to profit from their work. The NFT Marketplace intends to be at the centre of all these fantastic use cases for NFTs by giving users a platform to produce and exchange non-fungible tokens. NFTs offer a wide range of application cases. Automated Market Makers, which are essentially decentralised markets for crypto-tokens and offer users three core operations—depositing crypto tokens in exchange for AMM shares, performing a dual operation in which shares are obtained in exchange for base tokens, and exchanging two tokens for one another—are some of the main applications of DeFi. This conceptual research discusses AMMs that are already in existence on the Ethereum blockchain and their developments, including the AMM that is now being created on the Tezos blockchain. The goal of this study is to present a thorough understanding of blockchain technology and all of its practical uses, including voting, trading NFTs, etc. It then focuses on how NFTs are traded on various platforms before aiming for improved NFT trading marketplaces, namely Automated Market Makers on various blockchains like Ethereum and Tezos.

Both computers and the internet have ingratiated themselves deeply into daily lives, freeing one from a lot of paperwork. The assessment of a student is also an essential component of the work because it shows how well-versed and knowledgeable a student is in a certain area. Students who employ traditional methods of assessment may do it in an unfair manner. The assessment of students' response sheets would be handled by various universities and institutes with the use of automatic agents that evaluate the answers. The study outlines a method for assessing students' descriptive responses. The suggested approach will automatically compare students' responses to expected responses. Therefore, the inference process necessary for the construction of such a system is the subject of this paper. For one word and one-sentence-based answers, this system is workable. For implementation, WordNet and WordNet handling APIs like RiTa are employed along with Java.