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Academic Units

Faculty of Business and Law
- Alexandre Lobo

Publication year

Between 2000 and 2024

Results 90 resources

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Abstracts

Chong, K. Y., & Lobo Marques, J. A. (2021). A Prospective analysis about employee retention strategies for Macao Hotel Industry. The 2021 12th International Conference on E-Business, Management and Economics, 533–537. https://doi.org/10.1145/3481127.3481251
J.P.P. Santos, E., Lobo Marques, J., & Phyllips, J. O. L. (2021). Sustainable Buildings’ Projects – A Perspective from Consultants and Contractors based in Macau SAR, China. The 2021 12th International Conference on E-Business, Management and Economics, 865–870. https://doi.org/10.1145/3481127.3481252
Nguyen Van, S., Lobo Marques, J. A., Biala, T. A., & Li, Y. (2021). Identification of Latent Risk Clinical Attributes for Children Born Under IUGR Condition Using Machine Learning Techniques. Computer Methods and Programs in Biomedicine, 200, 105842. https://doi.org/10.1016/j.cmpb.2020.105842
Bernardo Gois, F. N., Lima, A., Santos, K., Oliveira, R., Santiago, V., Melo, S., Costa, R., Oliveira, M., Henrique, F. das C. D. M., Neto, J. X., Martins Rodrigues Sobrinho, C. R., & Lôbo Marques, J. A. (2021). Predictive models to the COVID-19. In U. Kose, D. Gupta, V. H. C. de Albuquerque, & A. Khanna (Eds.), Data Science for COVID-19 (pp. 1–24). Academic Press. https://doi.org/10.1016/B978-0-12-824536-1.00023-X
Arraut, I., Lobo Marques, J. A., & Gomes, S. (2021). The Probability Flow in the Stock Market and Spontaneous Symmetry Breaking in Quantum Finance. Mathematics, 9(21), 2777. https://doi.org/10.3390/math9212777
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2021). Predictive Models for Decision Support in the COVID-19 Crisis. Springer International Publishing. https://doi.org/10.1007/978-3-030-61913-8
Silva, S. C. e, Machado, J. C., Martins, C., Duarte, P., & Marques, J. A. L. (2021). Modelling the barriers that are preventing e-commerce to thrive – a case study from Portugal, international journal of business excellence. International Journal of Business Excellence.
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2020). Artificial Intelligence Prediction for the COVID-19 Data Based on LSTM Neural Networks and H2O AutoML. In Predictive Models for Decision Support in the COVID-19 Crisis (pp. 69–87). Springer International Publishing. https://doi.org/10.1007%2F978-3-030-61913-8_5
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2020). Epidemiology Compartmental Models—SIR, SEIR, and SEIR with Intervention. In Predictive Models for Decision Support in the COVID-19 Crisis (pp. 15–39). Springer International Publishing. https://doi.org/10.1007%2F978-3-030-61913-8_2
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2020). Forecasting COVID-19 Time Series Based on an Autoregressive Model. In Predictive Models for Decision Support in the COVID-19 Crisis (pp. 41–54). Springer International Publishing. https://doi.org/10.1007%2F978-3-030-61913-8_3
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2020). Nonlinear Prediction for the COVID-19 Data Based on Quadratic Kalman Filtering. In Predictive Models for Decision Support in the COVID-19 Crisis (pp. 55–68). Springer International Publishing. https://doi.org/10.1007%2F978-3-030-61913-8_4
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2020). Predicting the Geographic Spread of the COVID-19 Pandemic: A Case Study from Brazil. In Predictive Models for Decision Support in the COVID-19 Crisis (pp. 89–98). Springer International Publishing. https://doi.org/10.1007%2F978-3-030-61913-8_6
Marques, J. A. L., Gois, F. N. B., Xavier-Neto, J., & Fong, S. J. (2020). Prediction for Decision Support During the COVID-19 Pandemic. In Predictive Models for Decision Support in the COVID-19 Crisis (pp. 1–13). Springer International Publishing. https://doi.org/10.1007%2F978-3-030-61913-8_1
Li, T., Marques, J. A. L., & Fong, S. (2020). Health and Well-Being Education: Extending the SCARF Learning Analytics Model for Identifying the Learner Happiness Indicators. International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH), 2(2), 42–53. https://doi.org/10.4018/IJEACH.2020070105
Luo, R., Marques, J. A. L., Ong, K.-L., & Fong, S. (2020). Crowdsensing-Based Gamification for Collective Assistance for Post-Era of Coronavirus Epidemic in Community Living. International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH), 2(2), 54–64. https://doi.org/10.4018/IJEACH.2020070106
do Vale Madeiro, J. P., Lobo Marques, J. A., Han, T., & Coury Pedrosa, R. (2020). Evaluation of mathematical models for QRS feature extraction and QRS morphology classification in ECG signals. Measurement, 156, 107580. https://doi.org/10.1016/j.measurement.2020.107580
Marques, J., Reis, J., Phillips, J. O. L., & Diakite, A. (2020). The Importance of Readiness for Change, a Leadership Perspective Based on a Case Study in Macau, SAR China. Journal of Advanced Management Science, 116–120. https://doi.org/10.18178/joams.8.4.116-120
Arraut, I., Au, A., Tse, A. C., & Marques, J. A. L. (2020). On the probability flow in the Stock market I: The Black-Scholes case. ArXiv.Org, 1, 1–10. https://search.proquest.com/docview/2332255379?pq-origsite=primo
Lan, K., Liu, L., Li, T., Chen, Y., Fong, S., Marques, J. A. L., Wong, R. K., & Tang, R. (2020). Multi-view convolutional neural network with leader and long-tail particle swarm optimizer for enhancing heart disease and breast cancer detection. Neural Computing and Applications. https://doi.org/10.1007/s00521-020-04769-y
Marques, J. A. L., Cortez, P. C., Madeiro, J. P. V., Albuquerque, V. H. C., Fong, S. J., & Schlindwein, F. S. (2020). Nonlinear characterization and complexity analysis of cardiotocographic examinations using entropy measures. Journal of Supercomputing, 76(2), 1305–1320. https://doi.org/10.1007/s11227-018-2570-8

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