REFERENCES
- Bronstein, A. C., Buscema, M., Esfahani, A., Lodwick, W. A., & Grossi, E. (2013). Locating the source of public health events using intelligent adaptive systems: 2011 United States listeriosis outbreak linked to whole cantaloupes. Clinical Toxicology, 51(7), 625–626.
- Bruzzone, R., & Rossmo, K. (2005). Case study: UNABOMBER. Rome: International Crime Analysis Association (ICAA), RACIS.
- Buchholz, U., Bernard, H., Werber, D., Bohmer, M. M., Remschmidt, C., Wilking, H., … Kühne, M. (2011). German outbreak of Escherichia coli O104:H4 associated with sprouts. The New England Journal of Medicine, 365, 1763–1770.
- Buscema, M. (2006–2014). TWC and hidden point of Unabomber case, classified document, Semeion, Rome.
- Buscema, M. (2010). The general philosophy of the artificial adaptive systems. In V. Capecchi, B. Buscema, P. Contucci, & B. D'Amore (Eds.), Applications of mathematics in models, artificial neural networks and arts (pp. 197–226). Springer Science+Business Media.
- Buscema, M., Breda, M., & Catzola, G. (2009). The topological weighted centroid, and the semantic of the physical space—Theory. In M. Buscema & E. Grossi (Eds.), Artificial adaptive systems in medicine (pp. 69–78). London: Bentham.
- Buscema, M., Grossi, E., Breda, M., & Jefferson, T. (2009). Outbreaks source: A new mathematical approach to identify their possible location. Physica A, 388, 4736–4762.
- Buscema, M., Grossi, E., Bronstein, A. C., Lodwick, W. A., Asadi-Zeydabadi, M., Benzi, R., & Newman, F. (2013). A new algorithm for identifying possible epidemic sources with application to the German Escherichia coli outbreak, in a special issue “Spatial Analysis and Data Mining”. ISPRS International Journal of Geo-Information, 2(1), 155–200.
- Buscema, M., Sacco, P. L., Ferilli, G., Breda, M., & Grossi, E. (2014). Analyzing the semantics of point spaces through the topological weighted centroid and other mathematical quantities: The hidden geometry of the global economic order. Computational Intelligence, doi:10.1111/coin.12040.
- Buscema, M., Sacco, P. L., Grossi, E., & Lodwick, W. A. (2013). Spatiotemporal mining: A systematic approach to discrete diffusion models for time and space extrapolation, Chapter 8, In W. J. Tastle (Ed.), Data mining applications using artificial adaptive systems (pp. 231–275,) New York: Springer Science+Business Media.
- Buscema, M., & Tastle, W. J., (Eds.) (2013). Intelligent data mining in law enforcement analytics, New York: Springer Scienze+Business Media.
- Ferreira, M. C. (2005). Spatial diffusion maps of dengue fever epidemics occurring in southeast of Brazil: A methodology for cartographic modeling in GIS. In: XXIII International Cartographic Conference, La Corunã, Espanha.
- Ferreira, M. C. (2010). Spatial diffusion maps of dengue fever epidemics occurring in southeastern Brazil: A methodology for cartographic modeling in GIS. Unpublished, UNICAMP, Campinas.
- Frank, C., Faber, M. S., Askar, M., Bernard, H., Fruth, A., Gilsdorf, A.Werber, D. (2011). On behalf of the HUS investigation team, large and ongoing outbreak of haemolytic uraemic syndrome, Germany, May 2011. Eurosurveillance, 16(21), 2–4.
- Grossi, E., Buscema, M., & Jefferson, T. (2009). The topological weighted centroid, and the semantic of the physical space—Application. In M. Buscema & E. Grossi (Eds.), Artificial adaptive systems in medicine (pp. 79–89). London: Bentham.
- Massini, G. (2014). The land of fires, Conference on the Hidden Point in Geographic Profiling, Semeion Research Centre, Rome, Italy.