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Diakité, A. D. (2010). Aid to Infrastructure Development in Sub Saharan Africa: An Assessment of China Financing Approaches. In China-Africa: New Types of Exchange, Cultural Identity and Emerging Relations in a Globalized World (pp. 205–227). Saint Joseph Academic Press.
Porschitz, E. T., Guo, C., & Alves, J. (2012). “Going through the mist”: early career transitions of Chinese Millennial returnees. In E. Ng, S. Lyons, & L. Schweitzer, Managing the New Workforce (pp. 86–106). Edward Elgar Publishing. https://doi.org/10.4337/9780857933010.00010
Rato, R., & Davey, G. (2012). Quality of Work Life in Macau. In H. Selin & G. Davey (Eds.), Happiness Across Cultures: Views of Happiness and Quality of Life in Non-Western Cultures (pp. 95–106). Springer Netherlands. https://doi.org/10.1007/978-94-007-2700-7_7
Davey, G., & Rato, R. (2014). Macau, Quality of Life. In A. C. Michalos (Ed.), Encyclopedia of Quality of Life and Well-Being Research (pp. 3737–3740). Springer Netherlands. https://doi.org/10.1007/978-94-007-0753-5_3953
Carreiras, H., & Leandro, F. J. (2018). Obediência militar, liberdade e consciência, Ética Aplicada: Política, Edições 70, (pp. 339–364).
Leandro, F. J. (2018). The OBOR Global Geopolitical Drive: The Chinese Access Security Strategy -. In Julien Chaisse and Jędrzej Górski (Ed.), Law, Economics, and Politics (pp. 83–106). Brill. https://brill.com/view/ti-tle/38740
Leandro, F. J. B. S. (2018). The OBOR geopolitical drive: the Chinese access security Strategy. In J. C. and L. Nottage (Ed.), The Belt and Road Initiative Law, Economics, and Politics. Brill.
Lobo-Marques, J. Al. (2018). Artificial intelligence and forensic computing. In Forensic Computing.
Lei, W. C. (2020). The Road to Service Export Diversification: Gambling and Convention in Macao. In E. Lau, B. Simonetti, I. Trinugroho, & L. M. Tan (Eds.), Economics and Finance Readings: Selected Papers from Asia-Pacific Conference on Economics & Finance, 2019. Springer Singapore. https://doi.org/10.1007/978-981-15-2906-1
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
Phillips, J. O. L. (2021). Ritual and the Sacred in Peter Shaffer’s Theatre. In Sacred and the Everyday: Comparative approaches to literature, religious and secular (pp. 137–150). University of Saint Joseph.
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., Marques, J. A. L., Fong, S. J., Li, G., Gois, F. N. B., & Neto, J. X. (2022). A Quantum Field Formulation for a Pandemic Propagation. In J. A. L. Marques & S. J. Fong (Eds.), Epidemic Analytics for Decision Supports in COVID19 Crisis (pp. 141–158). Springer International Publishing. https://doi.org/10.1007/978-3-030-95281-5_6
Fong, S. J., Marques, J. A. L., Li, G., Dey, N., Crespo, R. G., Herrera-Viedma, E., Gois, F. N. B., & Neto, J. X. (2022). Analysis of the COVID19 Pandemic Behaviour Based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models. In J. A. L. Marques & S. J. Fong (Eds.), Epidemic Analytics for Decision Supports in COVID19 Crisis (pp. 17–64). Springer International Publishing. https://doi.org/10.1007/978-3-030-95281-5_2
Fong, S. J., Marques, J. A. L., Li, G., Dey, N., Crespo, R. G., Herrera-Viedma, E., Gois, F. N. B., & Neto, J. X. (2022). The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak. In J. A. L. Marques & S. J. Fong (Eds.), Epidemic Analytics for Decision Supports in COVID19 Crisis (pp. 65–81). Springer International Publishing. https://doi.org/10.1007/978-3-030-95281-5_3

Last update from database: 4/20/24, 5:28 AM (UTC)

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