More than just a propagandist for tea: religious argument and advice on a healthy life in the work of the Dutch physician Cornelis Bontekoe (1647-1685).

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Constant Delay Enumeration with FPT-Preprocessing for Conjunctive Queries of Bounded Submodular Width

Marx (STOC 2010, J. ACM 2013) introduced the notion of submodular width of a conjunctive query (CQ) and showed that for any class Phi of Boolean CQs of bounded submodular width, the model-checking problem for Phi on the class of all finite structures is fixed-parameter tractable (FPT). Note that for non-Boolean queries, the size of the query result may be far too large to be computed entirely within FPT time. We investigate the free-connex variant of submodular width and generalise Marx\u27s result to non-Boolean queries as follows: For every class Phi of CQs of bounded free-connex submodular width, within FPT-preprocessing time we can build a data structure that allows to enumerate, without repetition and with constant delay, all tuples of the query result. Our proof builds upon Marx\u27s splitting routine to decompose the query result into a union of results; but we have to tackle the additional technical difficulty to ensure that these can be enumerated efficiently

Answering FO+MOD Queries Under Updates on Bounded Degree Databases

We investigate the query evaluation problem for fixed queries over fully dynamic databases, where tuples can be inserted or deleted. The task is to design a dynamic algorithm that immediately reports the new result of a fixed query after every database update. We consider queries in first-order logic (FO) and its extension with modulo-counting quantifiers (FO+MOD), and show that they can be efficiently evaluated under updates, provided that the dynamic database does not exceed a certain degree bound. In particular, we construct a data structure that allows to answer a Boolean FO+MOD query and to compute the size of the query result within constant time after every database update. Furthermore, after every update we are able to immediately enumerate the new query result with constant delay between the output tuples. The time needed to build the data structure is linear in the size of the database. Our results extend earlier work on the evaluation of first-order queries on static databases of bounded degree and rely on an effective Hanf normal form for FO+MOD recently obtained by [Heimberg, Kuske, and Schweikardt, LICS, 2016]

Answering UCQs under Updates and in the Presence of Integrity Constraints

We investigate the query evaluation problem for fixed queries over fully dynamic databases where tuples can be inserted or deleted. The task is to design a dynamic data structure that can immediately report the new result of a fixed query after every database update. We consider unions of conjunctive queries (UCQs) and focus on the query evaluation tasks testing (decide whether an input tuple belongs to the query result), enumeration (enumerate, without repetition, all tuples in the query result), and counting (output the number of tuples in the query result). We identify three increasingly restrictive classes of UCQs which we call t-hierarchical, q-hierarchical, and exhaustively q-hierarchical UCQs. Our main results provide the following dichotomies: If the query\u27s homomorphic core is t-hierarchical (q-hierarchical, exhaustively q-hierarchical), then the testing (enumeration, counting) problem can be solved with constant update time and constant testing time (delay, counting time). Otherwise, it cannot be solved with sublinear update time and sublinear testing time (delay, counting time), unless the OV-conjecture and/or the OMv-conjecture fails. We also study the complexity of query evaluation in the dynamic setting in the presence of integrity constraints, and we obtain similar dichotomy results for the special case of small domain constraints (i.e., constraints which state that all values in a particular column of a relation belong to a fixed domain of constant size)

Untersuchung der Altersabhängigkeit von grauer und weißer Hirnsubstanz mit Hilfe von 3D-MR-Datensätzen von gesunden Probanden

In dieser Arbeit sollte untersucht werden, ob die Segmentierung von Gehirngewebe aus MRT-Bildern zur Detektion von Volumenunterschieden verbessert werden kann, wenn statt der üblichen Methode, bei der nur T1-Bilder verwendet werden, noch zusätzliche Daten aus T2- und T2-Flair-Bildern genutzt werden. Die multispektrale Segmentierung ist der alleinigen T1-Segmentierung in den meisten Fällen überlegen, da sie die Gyri und Gewebegrenzen genauer darstellt. Bezüglich der Volumina wurden signifikante Unterschiede festgestellt, wobei jedoch alle Segmentierungen die altersabhängigen Volumenänderungen zeigen. Das Volumen der grauen Substanz scheint durch eine alleinige T1-Segmentierung überschätzt. Zusammenfassend konnte in dieser Arbeit gezeigt werden, dass die etablierte T1-Segmentierung die Anatomie zum Teil fehlerhaft abbildet. Es wurde jedoch keine Segmentierung gefunden, die alle Bereiche des Gehirns gleich gut abbildet. Zukünftige Studien sollten je nach untersuchter Gehirnregion die hierfür optimale Kombination aus den Segmentierungen wählen

Tight lower bounds for query processing on streaming and external memory data

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