In today's world, the social media is everywhere, and everybody come in contact with it every day. With social media datas, we are able to do a lot of analysis and statistics nowdays. Within this scope of article, we conclude and analyse the sentiments and manifestations (comments, hastags, posts, tweets) of the users of the Twitter social media platform, based on the main trends (by keyword, which is mostly the 'covid' and coronavirus theme in this article) with Natural Language Processing and with Sentiment Classification using Recurrent Neural Network. Where we analyse, compile, visualize statistics, and summarize for further processing. The trained model works much more accurately, with a smaller margin of error, in determining emotional polarity in today's 'modern' often with ambiguous tweets. Especially with RNN. We use this fresh scraped data collections (by the keyword's theme) with our RNN model what we have created and trained to determine what emotional manifestations occurred on a given topic in a given time interval.

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This paper presents a framework suitable for the de nition of a Generic Enterprise Reference Architecture and Methodology to readers interested in architectures-and methodology development.The Generic Enterprise Reference Architecture and Methodology is about those methods, models and tools which are needed to build the integrated enterprise. The architecture is generic because it applies to most, potentially all types of enterprise.The coverage of the framework spans Products, Enterprises, Enterprise Integration and Strategic Enterprise Management, with the emphasis being on the middle two. The proposal for the architecture follows the architecture itself improving the quality of the presentation and of the outcome.De nitions of Generic Enterprise Reference Architecture, Enterprise Engineering/ Integration Methodology, E n terprise Modelling Languages, Enterprise Models, and Enterprise Modules are given. It is proposed how the above could be developed on the basis of previously analysed architectures (and other results too), such as the Purdue Enterprise Reference Architecture 3], the GRAI Integrated Methodology 8], CIM-OSA 7], and TOVIE 5].

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A variational quantum mechanical protocol is presented for the computation of rovibrational energy levels of semirigid molecules using discrete variable representation of the Eckart-Watson Hamiltonian, a complete, "exact" inclusion of the potential energy surface, and selection of a vibrational subspace. Molecular symmetry is exploited via a symmetry-adapted Lanczos algorithm. Besides symmetry labels, zeroth-order rigid-rotor and harmonic-oscillator quantum numbers are employed to characterize the computed rovibrational states. Using the computational molecular spectroscopy algorithm presented, a large number of rovibrational states, up to J = 50, of the ground electronic state of the parent isotopologue of ketene, H(2) (12)C=(12)C=(16)O, were computed and characterized. Based on 12 references, altogether 3982 measured and assigned rovibrational transitions of H(2) (12)C=(12)C=(16)O have been collected, from which 3194 were validated. These transitions form two spectroscopic networks (SN). The ortho and the para SNs contain 2489 and 705 validated transitions and 1251 and 471 validated energy levels, respectively. The computed energy levels are compared with energy levels obtained, up to J = 41, via an inversion protocol based on this collection of validated measured rovibrational transitions. The accurate inverted energy levels allow new assignments to be proposed. Some regularities and irregularities in the rovibrational spectrum of ketene are elucidated.