2026
Autores
Almeida, F; Okon, E;
Publicação
Knowledge and Process Management
Abstract
2025
Autores
Almeida, F;
Publicação
Examining the Intersection of Technology, Media, and Social Innovation
Abstract
2025
Autores
Matos, M; Gomes, F; Nogueira, F; Almeida, F;
Publicação
INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS
Abstract
PurposeDetecting anomalous access to electronic health records (EHRs) is critical for safeguarding patient privacy and ensuring compliance with healthcare regulations. Traditional anomaly detection methods often struggle in this domain due to extreme class imbalance, limited labelled data and the subtlety of insider threats. This study proposes a lightweight, hybrid anomaly detection framework that integrates unsupervised, supervised and rule-based approaches using a meta-classifier architecture.Design/methodology/approachAn experimental and model-development approach is employed, combining machine learning techniques with domain-inspired rule modelling to construct a hybrid anomaly detection framework for healthcare access logs. Performance of the algorithm is measured using standard classification metrics such as precision, recall, F1-score and accuracy.FindingsEvaluated on a synthetic but realistic dataset of 50.000 normal and 500 labelled anomalous healthcare access events, the proposed framework achieved superior performance compared to standalone models as well as other hybrid models, with an F1-score of 0.8989 and recall of 0.8180. It also maintained low inference latency (0.028 ms) and energy consumption (4.03e-07 kg CO2), making it suitable for deployment in resource-constrained clinical environments.Originality/valueThis study highlights the potential of a hybrid meta-classifier to enhance anomaly detection in healthcare access logs, capturing both subtle and obvious anomalies while outperforming conventional models and remaining efficient, scalable and practical for real-time monitoring.
2025
Autores
Almeida, FL;
Publicação
Information Security Journal: A Global Perspective
Abstract
2025
Autores
Kurteshi, R; Almeida, F;
Publicação
INTERNATIONAL JOURNAL OF ENTREPRENEURIAL BEHAVIOR & RESEARCH
Abstract
Purpose - The objective of this study is to integrate various theories of identity within entrepreneurship and derive insights and propositions that enhance the understanding of how an incubation program influences the formation and development of entrepreneurial team identity. Design/methodology/approach - This study adopts a qualitative multiple case study design to explore how entrepreneurial team identity develops within ventures incubated at CEU iLab. The analysis is based primarily on interviews with individual entrepreneurs from five selected ventures, complemented by secondary data to enrich and contextualize the findings. Findings - The findings revealed the interconnections between entrepreneurial team formation processes, social interactions, networking, entrepreneurial team stability, feedback mechanisms, team dynamics and intrateam trust and legitimacy. Moreover, the cultivation of a culture defined by trust, open communication and the active integration of feedback mechanisms played a pivotal role in the creation of collaborative team environments. Furthermore, the process of building an entrepreneurial team is heavily reliant on shared vision, common values, complementary skill sets, intrateam trust and pre-existing relationships. Originality/value - This study addresses a notable gap in the existing literature by studying how entrepreneurial teams and individual entrepreneurial team members manage to form and develop their entrepreneurial identity. By focusing on the dynamic processes behind identity formation within teams, this research provides novel insights into the motivations that drive individuals and teams to engage in entrepreneurial activities. This focus on the interplay between identity and team processes represents a distinctive and timely addition to the field.
2025
Autores
Almeida, F;
Publicação
Environment, Innovation and Management
Abstract
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.