Detalhes

TÓPICOS ESPECIAIS III - E-COMMERCE, ARTIFICIAL INTELLIGENCE & MACHINE LEARNING, METAVERSE, AND CYBERSECURITY

Nome da Disciplina: TÓPICOS ESPECIAIS III - E-COMMERCE, ARTIFICIAL INTELLIGENCE & MACHINE LEARNING, METAVERSE, AND CYBERSECURITY
Carga Horária: 60
Créditos: 3
Obrigatória: Não
EMENTA
A disciplina será conduzida individualmente, em inglês, remotamente, realizando pesquisas customizadas com cada aluno e nos dias e horários flexíveis combinados entre o respectivo aluno e o professor. This discipline seeks to encourage the students to study and to develop research studies, involving the e-commerce, the artificial intelligence & the machine learning, the metaverse, and the cybersecurity. The COVID-19 pandemic brought the need and consequently the strengthening of the e-commerce to the world. On the one hand, the online access to the banks and the online purchases have allowed for the maintenance of the business and a new supply chain model. On the other hand, the security issues had been reinforced with cybersecurity. In this way, the artificial intelligence & the machine learning have added value to the topic. At this time, the virtual landscape is expanding globally, with the metaverse being introduced in the daily lives of the Global population. The main topics to be studied in this discipline involve:  the development and the improvement of the e-commerce concepts;  the industry 4.0 applications in order to enhance the artificial intelligence & the machine learning;  the concepts and the management of the cybersecurity;  the metaverse concepts, the analyses, and the impacts;  the production in English of five top journal papers, one conference paper, and ten essays.
BIBLIOGRAFIA
Carley, K.M. (2020) “Social cybersecurity: an emerging science,” Computational and mathematical organization theory, 26(4), pp. 365–381. Escursell, S., Llorach-Massana, P. and Roncero, M.B. (2021) “Sustainability in e-commerce packaging: A review,” Journal of cleaner production, 280, p. 124314. Gritzalis, D.A., Pantziou, G. and Román-Castro, R. (2021) “Sensors Cybersecurity,” Sensors (Basel, Switzerland), 21(5), p. 1762. Janiesch, C., Zschech, P. and Heinrich, K. (2021) “Machine learning and deep learning,” Electronic markets, 31(3), pp. 685–695. C:\Formularios\FORMDISC.DOC MacEachern, S.J. and Forkert, N.D. (2021) “Machine learning for precision medicine,” Genome, 64(4), pp. 416–425. Mei, X. et al. (2020) “Artificial intelligence-enabled rapid diagnosis of patients with COVID19,” Nature medicine, 26(8), pp. 1224–1228. Puntoni, S. et al. (2021) “Consumers and Artificial Intelligence: An Experiential Perspective,” Journal of marketing, 85(1), pp. 131–151. Wang, H. et al. (2022) “Can e-commerce alleviate agricultural non-point source pollution? -- A quasinatural experiment based on a China's E-Commerce Demonstration City,” The Science of the total environment, 846, p. 157423. Wiederhold, B.K. (2022) “Metaverse Games: Game Changer for Healthcare?,” Cyberpsychology, behavior and social networking, 25(5), pp. 267–269. Yang, D. et al. (2022) “Metaverse in medicine,” Clinical eHealth, 5, pp. 39–43. And other papers.


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