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Publicações

Publicações por Ana Pereira

2021

Deep Learning in Biomedical and Health Informatics

Autores
Jabbar, M; Abraham, A; Dogan, O; Madureira, A; Tiwari, S;

Publicação

Abstract

2020

Hybrid Intelligent Systems

Autores
Madureira, AM; Abraham, A; Gandhi, N; Varela, ML;

Publicação
Advances in Intelligent Systems and Computing

Abstract

2021

Intelligent Systems Design and Applications

Autores
Abraham, A; Piuri, V; Gandhi, N; Siarry, P; Kaklauskas, A; Madureira, A;

Publicação
Advances in Intelligent Systems and Computing

Abstract

2024

Navigating the Future of Enterprises: Insights into Digital Transformation, Virtual Reality, and the Metaverse

Autores
Silva, R; Pereira, I; Nicola, S; Madureira, A; Bettencourt, N; Reis, JL; Santos, JP; de Oliveira, DA;

Publicação
2024 IEEE 22ND MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, MELECON 2024

Abstract
Over the past two decades, Digital Transformation (DT) has been focused on improving businesses, industries, and the general public through significant breakthroughs. This paper examines the significant developments brought forth by DT and how they impact organizations. This analysis explores the impact of Virtual Reality (VR) and the Metaverse on global businesses, taking inspiration from successful case studies such as Netflix, Amazon, and Meta. This study emphasizes the potential of virtual reality and the Metaverse in facilitating remote meetings, training employees, engaging with consumers, and gathering data. Case studies and strategic recommendations are offered for overcoming barriers to the adoption of these digital technologies. The study finishes by addressing the future trajectory of DT and emphasizing the significance of devoting time, commitment, and resources to effectively utilize the range of potential offered by VR and the Metaverse. It highlights the importance for organizations to comprehend and handle this ever-changing environment to remain at the forefront of the digital frontier.

2024

A Systematic Review on Responsible Multimodal Sentiment Analysis in Marketing Applications

Autores
César, I; Pereira, I; Rodrigues, F; Miguéis, VL; Nicola, S; Madureira, A; Reis, JL; Dos Santos, JPM; De Oliveira, DA;

Publicação
IEEE ACCESS

Abstract
The intrinsic challenges of contemporary marketing encourage discovering new approaches to engage and retain customers effectively. As the main channels of interactions between customers and brands pivot between the physical and the digital world, analyzing the outcome behavioral patterns must be achieved dynamically with the stimulus performed in both poles. This systematic review investigates the collaborative impact of adopting multidisciplinary fields of Affective Computing to evaluate current marketing strategies, upholding the process of using multimodal information from consumers to perform and integrate Sentiment Analysis tasks. The adjusted representation of modalities such as textual, visual, audio, or even psychological indicators enables prospecting a more precise assessment of the advantages and disadvantages of the proposed technique, glimpsing future applications of Multimodal Artificial Intelligence in Marketing. Embracing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as the research method to be applied, this article warrants a rigorous and sequential identification and interpretation of the synergies between the latest studies about affective computing and marketing. Furthermore, the robustness of the procedure is deepened in knowledge-gathering concerning the current state of Affective Computing in the Marketing area, their technical practices, ethical and legal considerations, and the potential upcoming applications, anticipating insights for the ongoing work of marketers and researchers.

2023

Windy Energy Production Planning Considering Local Marginal Prices

Autores
Guarezzi, P; Ferreira, M; Sica, T; Puga, J; Madureira, A;

Publicação
International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023

Abstract
This paper presents several case studies that show that it is possible to use clean energy to produce electricity, we have environmental benefits and benefits for the management of the electrical transmission network. In this case wind energy are used.For this work, software was developed in Matlab for the model we developed and the results of this were compared with the results obtained by the simulator Power World.To make the decision to replace generators fossil generators with wind generators, Local Marginal Prices (LMP) were used. Some case studies were created using a model system, with the objective of evaluating the benefits of this allocation based on the LMP.The test network presented in this paper is a 9 Bus network. However, the developed software was also tested on an IEEE 30 Bus network. © 2023 IEEE.

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