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Faculty of Business and Law

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Abstracts

Arraut, I. (2023). The solution to the Hardy’s paradox (No. arXiv:2106.06397). arXiv. https://doi.org/10.48550/arXiv.2106.06397

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Iong, K. Y., & Phillips, J. O. L. (2023). The transformation of government employees’ behavioural intention towards the adoption of E-government services: An empirical study. Social Sciences & Humanities Open, 7(1), 100485. https://doi.org/10.1016/j.ssaho.2023.100485

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Bernardo Gois, F. N., & Lobo Marques, J. A. (2023). Segmentation of CT-Scan Images Using UNet Network for Patients Diagnosed with COVID-19. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 29–44). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_3

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Bernardo Gois, F. N., Lobo Marques, J. A., & Fong, S. J. (2023). Classification of COVID-19 CT Scans Using Convolutional Neural Networks and Transformers. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 79–97). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_6

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Bernardo Gois, F. N., Lobo Marques, J. A., & Fong, S. J. (2023). TPOT Automated Machine Learning Approach for Multiple Diagnostic Classification of Lung Radiography and Feature Extraction. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 117–135). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_8

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Caldas, W. L., do Vale Madeiro, J. P., Pedrosa, R. C., Gomes, J. P. P., Du, W., & Marques, J. A. L. (2023). Noise Detection and Classification in Chagasic ECG Signals Based on One-Dimensional Convolutional Neural Networks. In R. Lee (Ed.), Computer and Information Science (pp. 117–129). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_8

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Cavalcante, C. H. L., Primo, P. E. O., Sales, C. A. F., Caldas, W. L., Silva, J. H. M., Souza, A. H., Marinho, E. S., Pedrosa, R. C., Marques, J. A. L., Santos, H. S., Madeiro, J. P. V., Cavalcante, C. H. L., Primo, P. E. O., Sales, C. A. F., Caldas, W. L., Silva, J. H. M., Souza, A. H., Marinho, E. S., Pedrosa, R. C., … Madeiro, J. P. V. (2023). Sudden cardiac death multiparametric classification system for Chagas heart disease’s patients based on clinical data and 24-hours ECG monitoring. Mathematical Biosciences and Engineering, 20(5), 9159–9178. https://doi.org/10.3934/mbe.2023402

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dos Santos Silva, B. R., Cesar Cortez, P., Crosara Motta, P., & Lobo Marques, J. A. (2023). Covid-19 Detection Based on Chest X-Ray Images Using Multiple Transfer Learning CNN Models. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 45–63). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_4

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dos Santos Silva, B. R., Cesar Cortez, P., Gomes Aguiar, R., Rodrigues Ribeiro, T., Pereira Teixeira, A., Bernardo Gois, F. N., & Lobo Marques, J. A. (2023). Lung Segmentation of Chest X-Rays Using Unet Convolutional Networks. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 15–28). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_2

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dos Santos Silva, B. R., Cortez, P. C., da Silva Neto, M. G., & Lobo Marques, J. A. (2023). X-Ray Machine Learning Classification with VGG-16 for Feature Extraction. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 65–78). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_5

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Gois, F. N. B., Marques, J. A. L., de Oliveira Dantas, A. B., Santos, M. C., Neto, J. V. S., de Macêdo, J. A. F., Du, W., & Li, Y. (2023). Malaria Blood Smears Object Detection Based on Convolutional DCGAN and CNN Deep Learning Architectures. In R. Lee (Ed.), Computer and Information Science (pp. 197–212). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_14

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Lei, W. C., & Wang, X. (2023). Digital Renminbi: Impacts on Economic Integration of the Greater Bay Area. In E. Lau, R. K. Brahmana, & L. M. Tan (Eds.), Economics and Finance Readings (pp. 1–14). Springer Nature. https://doi.org/10.1007/978-981-99-1979-6_1
Lobo Marques. (2023). The (non) standardized classroom - the analysis of three different cultures in the higher education systems - Angola, Brazil and Macau SAR, China. In Disentangled Vision on Higher Education: Preparing the Generation Next (pp. 329–351). Peter Lang. https://www.peterlang.com/document/1266828

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Lobo Marques, J. A., & Fong, S. J. (Eds.). (2023). Computerized Systems for Diagnosis and Treatment of COVID-19. Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1

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Lobo Marques, J. A., & Fong, S. J. (2023). Technology Developments to Face the COVID-19 Pandemic: Advances, Challenges, and Trends. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 1–13). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_1

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Lobo Marques, J. A., Macedo, D. S., Motta, P., dos Santos Silva, B. R., Carvalho, F. H. C., Kehdi, R. C., Cavalcante, L. R. L., da Silva Viana, M., Lós, D., & Fiorenza, N. G. (2023). Exploratory Data Analysis on Clinical and Emotional Parameters of Pregnant Women with COVID-19 Symptoms. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 179–209). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_11

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Motta, P. C., Cesar Cortez, P., & Lobo Marques, J. A. (2023). COVID-19 Classification Using CT Scans with Convolutional Neural Networks. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 99–116). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_7

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Pordeus, D., Ribeiro, P., Zacarias, L., de Oliveira, A., Marques, J. A. L., Rodrigues, P. M., Leite, C., Neto, M. A., Peixoto, A. A., & do Vale Madeiro, J. P. (2023). Training Strategies for Covid-19 Severity Classification. In I. Rojas, O. Valenzuela, F. Rojas Ruiz, L. J. Herrera, & F. Ortuño (Eds.), Bioinformatics and Biomedical Engineering (pp. 514–527). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-34953-9_40
Pordeus, D., Ribeiro, P., Zacarias, L., Paulo Madeiro, J., Lobo Marques, J. A., Miguel Rodrigues, P., Leite, C., Alves Neto, M., Aires Peixoto Jr, A., & de Oliveira, A. (2023). Classification of Severity of COVID-19 Patients Based on the Heart Rate Variability. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 155–177). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_10

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Ribeiro, P., Pordeus, D., Zacarias, L., Leite, C., Alves Neto, M., Aires Peixoto Jr, A., de Oliveira, A., Paulo Madeiro, J., Lobo Marques, J. A., & Miguel Rodrigues, P. (2023). Evaluation of ECG Non-linear Features in Time-Frequency Domain for the Discrimination of COVID-19 Severity Stages. In J. A. Lobo Marques & S. J. Fong (Eds.), Computerized Systems for Diagnosis and Treatment of COVID-19 (pp. 137–154). Springer International Publishing. https://doi.org/10.1007/978-3-031-30788-1_9

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Last update from database: 5/20/25, 1:01 PM (UTC)