Scrutiny of the stability, properties, and applications of 2D metals belonging to s-, p-, and d-block series has acquired intense research interest in the past few years. The present report is solely focused to systematically explore the stability and properties of 2D hexagonal (HX) lanthanides employing density functional theory calculations. To probe the dynamical stability of these materials, the phonon dispersion calculation is performed. The mechanical stability is analyzed on the basis of the 2D bulk modulus and elastic constant values. Further, to unravel the electronic properties of the 2D metals, electronic band structure, electron localization function, and the work function values are estimated. Moreover, en route to explore their magnetic properties, spin polarized density of states calculation is carried out and the ground state magnetic behavior is studied by considering ferromagnetic and antiferromagnetic spin configurations. Result explicitly demonstrates that 11 lanthanide metals are dynamically stable as an atomically thin 2D HX films. All of them are conducting in nature exhibiting ferromagnetic behavior in their ground state. These results offer the fundamentals of stability and properties of 2D HX lanthanides which can lay the foundation for exploring their diverse future applications.
Conversational agents or more universally known as the chatbot were industrialized to respond to user’s queries in a particular domain. Chatbot would serve as a software delegate which enables a computer to converse with human via natural language. A chatbot is a human-like conversational character (Shaikh et al. Int J Eng Sci Comput 6:3117–3119, 2016 [
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]. This technology was coined in 1960s, with the intention to impersonate a human (how he would reply to a particular situation) so that the user feels that he is talking to a real person and not a machine. Conversational agent that interacts with user’s turn by turn using natural language (Shawar A, Atwell E (2005) ICAME J Int Comput Arch Mod Med English J 29, 5–24, 2005 [
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]). The world of chatbot has seen much of the advance since the invention, and they have progressed from conventional rule-based chatbot to unorthodox AI-based chatbot. The chat agents are expert in their fields [
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]. The prime focus of this paper is to show implementation of a retrieval-based chabot with voice support, and we will investigate other standing chatbot and how it is useful in helping the patients fetching all the necessary details about COVID-19.
Future frame prediction project aims at predicting future frames of a video given previous frames. If ‘n’ frames are given into the model (n being 19 in our case) our model predicts the n+1th frame in the sequence (i.e., 20th frame). The model used for prediction is a deep learning model - GAN (Generative Adversarial Model). The Generative adversarial model has 2 components: the generator which generates the 20th frame and the adversary (Critic) which compares the outputs of the generator with real outputs. The purpose of this comparison is to train both the generator and the critic in a cyclic fashion to the point where the generator can create almost real-looking outputs. Complex systems like aiming machines,self-driving cars, etc require a good level of correct future prediction to make their outputs correct. We aim at creating a common prediction model which can be generalized for any task and can be used in any such machine.
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