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  <doc>
    <id>6505</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>81</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>masterthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2017-02-01</thesisDateAccepted>
    <title language="eng">Optimal Experimental Design to Estimate the Time of Death in a Bayesian Context</title>
    <abstract language="eng">This thesis is devoted to the interdisciplinary work between mathematicians and forensic&#13;
experts: the modeling of the human body cooling process after death laying the&#13;
foundation for the estimation of the time of death. An inverse problem needs to be&#13;
solved. In this thesis the inverse problem computes the time of death given the measured&#13;
body temperature and the Forward Model that simulates the body cooling&#13;
process. The Forward Model is based on the heat equation established by Fourier.&#13;
This differential equation is numerically solved by the discretization over space by the&#13;
Finite Element Method and the discretization over time by the Implicit Euler Method.&#13;
The applications in this thesis demand a fast computation time. A model reduction is&#13;
achieved by the Proper Orthogonal Decomposition in combination with the Galerkin&#13;
Method. For reasons of simplification the computations and the measurements are&#13;
restricted to a cylindrical phantom that is made out of homogeneous polyethylene.&#13;
The estimate of the time of death is accompanied by an uncertainty. The inverse problem&#13;
is incorporated by Bayesian inference to interpret the quality of the estimate and&#13;
the effciency of the experiment. The uncertainty of the estimate of the time of death&#13;
is minimized by approaching the Optimal Design of the Experiment. An objective&#13;
function measures the certainty of the data and lays the foundation of the optimization&#13;
problem. Solving the optimization problem is successfully done by relaxing the&#13;
complex discrete NP-hard problem and applying a gradient-based method.&#13;
&#13;
The results of this thesis clearly show that the design of an experiment has a great in-&#13;
uence on the outcome of the quality of the estimate. The comparison of the estimate&#13;
and its properties based on different designs and conditions reveals the effciency of&#13;
the Design of Experiment in the context of the estimation of the time of death.</abstract>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-62475</enrichment>
    <advisor>Martin Weiser</advisor>
    <author>Yvonne Freytag</author>
    <submitter>Bodo Erdmann</submitter>
    <advisor>Dietmar Hömberg</advisor>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="institutes" number="compmed">Computational Medicine</collection>
    <collection role="projects" number="UJena-Forensic">UJena-Forensic</collection>
    <thesisPublisher>Zuse Institute Berlin (ZIB)</thesisPublisher>
    <thesisGrantor>Technische Universität Berlin</thesisGrantor>
  </doc>
</export-example>
