Mass Fatality Incident Identification based on nuclear DNA evidence

Fabio Corradi
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, PMLR 9:105-112, 2010.

Abstract

This paper focuses on the use of nuclear DNA Short Tandem Repeat traits for the identification of the victims of a Mass Fatality Incident. The goal of the analysis is the assessment of the identification probabilities concerning the recovered victims. Identification hypotheses are evaluated conditionally to the DNA evidence observed both on the recovered victims and on the relatives of the missing persons disappeared in the tragical event. After specifying a set of conditional independence assertions suitable for the problem, an inference strategy is provided, treating some points to achieve computational efficiency. Finally, the proposal is tested through the simulation of a Mass Fatality Incident and the results are examined in details.

Cite this Paper

BibTeX
@InProceedings{pmlr-v9-corradi10a, title = {Mass Fatality Incident Identification based on nuclear DNA evidence}, author = {Corradi, Fabio}, booktitle = {Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics}, pages = {105--112}, year = {2010}, editor = {Teh, Yee Whye and Titterington, Mike}, volume = {9}, series = {Proceedings of Machine Learning Research}, address = {Chia Laguna Resort, Sardinia, Italy}, month = {13--15 May}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v9/corradi10a/corradi10a.pdf}, url = {https://proceedings.mlr.press/v9/corradi10a.html}, abstract = {This paper focuses on the use of nuclear DNA Short Tandem Repeat traits for the identification of the victims of a Mass Fatality Incident. The goal of the analysis is the assessment of the identification probabilities concerning the recovered victims. Identification hypotheses are evaluated conditionally to the DNA evidence observed both on the recovered victims and on the relatives of the missing persons disappeared in the tragical event. After specifying a set of conditional independence assertions suitable for the problem, an inference strategy is provided, treating some points to achieve computational efficiency. Finally, the proposal is tested through the simulation of a Mass Fatality Incident and the results are examined in details.} }
Endnote
%0 Conference Paper %T Mass Fatality Incident Identification based on nuclear DNA evidence %A Fabio Corradi %B Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics %C Proceedings of Machine Learning Research %D 2010 %E Yee Whye Teh %E Mike Titterington %F pmlr-v9-corradi10a %I PMLR %P 105--112 %U https://proceedings.mlr.press/v9/corradi10a.html %V 9 %X This paper focuses on the use of nuclear DNA Short Tandem Repeat traits for the identification of the victims of a Mass Fatality Incident. The goal of the analysis is the assessment of the identification probabilities concerning the recovered victims. Identification hypotheses are evaluated conditionally to the DNA evidence observed both on the recovered victims and on the relatives of the missing persons disappeared in the tragical event. After specifying a set of conditional independence assertions suitable for the problem, an inference strategy is provided, treating some points to achieve computational efficiency. Finally, the proposal is tested through the simulation of a Mass Fatality Incident and the results are examined in details.
RIS
TY - CPAPER TI - Mass Fatality Incident Identification based on nuclear DNA evidence AU - Fabio Corradi BT - Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics DA - 2010/03/31 ED - Yee Whye Teh ED - Mike Titterington ID - pmlr-v9-corradi10a PB - PMLR DP - Proceedings of Machine Learning Research VL - 9 SP - 105 EP - 112 L1 - http://proceedings.mlr.press/v9/corradi10a/corradi10a.pdf UR - https://proceedings.mlr.press/v9/corradi10a.html AB - This paper focuses on the use of nuclear DNA Short Tandem Repeat traits for the identification of the victims of a Mass Fatality Incident. The goal of the analysis is the assessment of the identification probabilities concerning the recovered victims. Identification hypotheses are evaluated conditionally to the DNA evidence observed both on the recovered victims and on the relatives of the missing persons disappeared in the tragical event. After specifying a set of conditional independence assertions suitable for the problem, an inference strategy is provided, treating some points to achieve computational efficiency. Finally, the proposal is tested through the simulation of a Mass Fatality Incident and the results are examined in details. ER -
APA
Corradi, F.. (2010). Mass Fatality Incident Identification based on nuclear DNA evidence. Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, in Proceedings of Machine Learning Research 9:105-112 Available from https://proceedings.mlr.press/v9/corradi10a.html.

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