REMIT - Research on Economics, Management and Information Technologies (UIDB/05105/2020)
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Description
Keywords
Innovation and creativity,Strategy and business models,Decision support systems,Territorial development,
Identifier
UIDB/05105/2020
Funding Stream
6817 - DCRRNI ID
Funder
Fundação para a Ciência e Tecnologia
A Fundação para a Ciência e Tecnologia (FCT) é uma entidade portuguesa responsável pela promoção e financiamento da investigação científica e tecnológica em Portugal. A FCT apoia projetos de investigação em diversas áreas, desde as ciências naturais e exatas até às ciências sociais e humanidades. Além disso, a FCT desempenha um papel importante na gestão de bolsas de estudo e no desenvolvimento de políticas para o avanço da ciência e tecnologia no país.
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6 results
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Publication Open Access Digital transformation, skills and education: A systematic literature review2023-10-23 - Rêgo, B.; Lourenço, D.; Moreira, Fernando; Santos-Pereira, CarlaDigital transformation (DT) is raising new challenges. This article seeks to understand how DT has changed business strategies, requiring a new profile of professionals, analyzing the most sought-after skills and identifying opportunities for future professionals. Also, it studies whether universities have incorporated in their training the new skills required by the labor market impacted by DT. To these ends, a systematic literature review dealing with digital transformation, competence, and education was conducted. The existing literature was categorized into seven main areas of investigation: digital literacy; skills identification; use of digital technologies in teaching; learning models; workforce qualification or re-skilling; digital technologies in the labor market; and undergraduate course analysis. This structuring then lays the groundwork for capturing gaps in the literature and proposing future research.Publication Restricted Access A study on sensors in Higher Education2024-06-01 - Sengupta, Sarthak; Bose, Anindya; Moreira, Fernando; Escudero, David Fonseca; García-Peñalvo, Francisco José; Collazos , CesarThe Coronavirus crisis affected the higher education system drastically. A rapid surge in the usage of sensors and wearable technologies was observed. So, a need to pursue further research on the implementation of sensors in higher education institutions has been witnessed. This research study revolves around exploring the relevant research studies on sensors and higher education. The study found that a notable number of global research studies have been pursued on sensors but very few were relevant to the context of higher education institutions. It was also observed that the number of relevant research studies on the topics increased during and after the COVID-19 pandemic. It was also observed that most of the relevant research studies were published by developed countries like the USA, China, and England but negligible studies were performed by other countries. So, this study can pave the foundation to formulate novel approaches in the strategic implementation of sensors in higher education institutions across the world.Publication Open Access Reliability on the Internet of Things with designing approach for exploratory analysis2024-06-04 - Singh, Khushwant; Yadav, Mohit; Singh, Yudhvir; Barak, Dheerdhwaj; Saini, Ashish; Moreira, FernandoThe Internet of Things (IoT) proposes to transform human civilization so that it is smart, practical, and highly efficient, with enormous potential for commercial as well as social and environmental advantages. Reliability is one of the major problems that must be resolved to enable this revolutionary change. The reliability issues raised with specific supporting technologies for each tier according to the layered IoT reliability are initially described in this research. The research then offers a complete review and assessment of IoT reliability. In this paper, various types of reliability on the IoT have been analyzed with each layer of IoT to solve the issues of failure rates, latency, MTTF, and MTBF. Each parameter has a certain classification and perception as well as enhancement in efficiency, accuracy, precision, timeliness, and completeness. Reliability models provide efficient solutions for different IoT problems, which are mirrored in the proposed study and classified with four types of reliabilities. The field of IoT reliability exploration is still in its initial phases, despite a sizable research record. Furthermore, the recent case study of CHISS is elaborated with discovered behaviors including brand-new aspects such as the multifaceted nature of evolving IoT systems, research opportunities, and difficulties.Publication Restricted Access Exploring the Nordic numbers: An analysis of price clustering in Scandinavian stocks2024-07-19 - Lobão, Júlio; Pacheco, Luís Miguel; Carvalho , DanielPurpose This paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland. Design/methodology/approach This paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland. Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering. Findings Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering. Results reveal pervasive clustering, strengthening with higher prices and turnover but weakening with larger trade volumes, firm size, and smaller tick sizes. These empirical findings support the theoretical expectations of price negotiation and resolution hypotheses. Practical implications The observed clustering presents an opportunity for investors to potentially capitalize on this market anomaly and achieve supra-normal returns. Originality/value Price clustering, the phenomenon where certain price levels are traded more frequently, challenges the efficient market hypothesis and has been extensively studied in financial markets. However, the Scandinavian stock markets, particularly those in the Nasdaq Nordic Exchange, remain unexplored in this context.Publication Restricted Access Anticipating tutoring demands based on students’ difficulties in Online Learning2024-06-01 - Pereira, Aluisio José; Gomes, Alex Sandro; Primo, Tiago Thompsen; Queiros, Leandro Marques; Moreira, FernandoAnticipating the tutoring needs in online learning is essential to provide adequate support to students. Feedback and even silence are valuable clues to reveal the level of engagement. Approaches based on Artificial Intelligence (AI) can process this information and alleviate the workload of human tutors. In this study, Natural Language Processing (NLP) techniques were used to assess the performance of classifying students’ difficulties in an Educational Social Network. Difficulties were classified into categories such as “personal”, “technical”, and “others”. The model's performance allows you to anticipate and direct tutoring.Publication Open Access Facial emotion recognition through artificial intelligence2024-01-31 - Ballesteros, Jesús A.; Ramírez V., Gabriel M.; Solano, Andrés; Pelaez, Carlos A.; Moreira, FernandoThis paper introduces a study employing artificial intelligence (AI) to utilize computer vision algorithms for detecting human emotions in video content during user interactions with diverse visual stimuli. The research aims to unveil the creation of software capable of emotion detection by leveraging AI algorithms and image processing pipelines to identify users' facial expressions. The process involves assessing users through images and facilitating the implementation of computer vision algorithms aligned with psychological theories defining emotions and their recognizable features. The study demonstrates the feasibility of emotion recognition through convolutional neural networks (CNN) and software development and training based on facial expressions. The results highlight successful emotion identification; however, precision improvement necessitates further training for contexts with more diverse images and additional algorithms to distinguish closely related emotional patterns. The discussion and conclusions emphasize the potential of A.I. and computer vision algorithms in emotion detection, providing insights into software development, ongoing training, and the evolving landscape of emotion recognition technology. Further training is necessary for contexts with more diverse images, alongside additional algorithms that can effectively distinguish between facial expressions depicting closely related emotional patterns, enhancing certainty and accuracy.