@phdthesis{Glasser2001,
  author    = {Glaßer, Christian},
  title     = {Forbidden-Patterns and Word Extensions for Concatenation Hierarchies},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-1179153},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2001},
  abstract  = {Starfree regular languages can be build up from alphabet letters by using only Boolean operations and concatenation. The complexity of these languages can be measured with the so-called dot-depth. This measure leads to concatenation hierarchies like the dot-depth hierarchy (DDH) and the closely related Straubing-Th{\´e}rien hierarchy (STH). The question whether the single levels of these hierarchies are decidable is still open and is known as the dot-depth problem. In this thesis we prove/reprove the decidability of some lower levels of both hierarchies. More precisely, we characterize these levels in terms of patterns in finite automata (subgraphs in the transition graph) that are not allowed. Therefore, such characterizations are called forbidden-pattern characterizations. The main results of the thesis are as follows: forbidden-pattern characterization for level 3/2 of the DDH (this implies the decidability of this level) decidability of the Boolean hierarchy over level 1/2 of the DDH definition of decidable hierarchies having close relations to the DDH and STH Moreover, we prove/reprove the decidability of the levels 1/2 and 3/2 of both hierarchies in terms of forbidden-pattern characterizations. We show the decidability of the Boolean hierarchies over level 1/2 of the DDH and over level 1/2 of the STH. A technique which uses word extensions plays the central role in the proofs of these results. With this technique it is possible to treat the levels 1/2 and 3/2 of both hierarchies in a uniform way. Furthermore, it can be used to prove the decidability of the mentioned Boolean hierarchies. Among other things we provide a combinatorial tool that allows to partition words of arbitrary length into factors of bounded length such that every second factor u leads to a loop with label u in a given finite automaton.},
  subject      = {Automatentheorie},
  language  = {en}
}
@phdthesis{Schmitz2000,
  author    = {Schmitz, Heinz},
  title     = {The Forbidden Pattern Approach to Concatenation Hierarchies},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-2832},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2000},
  abstract  = {The thesis looks at the question asking for the computability of the dot-depth of star-free regular languages. Here one has to determine for a given star-free regular language the minimal number of alternations between concatenation on one hand, and intersection, union, complement on the other hand. This question was first raised in 1971 (Brzozowski/Cohen) and besides the extended star-heights problem usually refered to as one of the most difficult open questions on regular languages. The dot-depth problem can be captured formally by hierarchies of classes of star-free regular languages B(0), B(1/2), B(1), B(3/2),... and L(0), L(1/2), L(1), L(3/2),.... which are defined via alternating the closure under concatenation and Boolean operations, beginning with single alphabet letters. Now the question of dot-depth is the question whether these hierarchy classes have decidable membership problems. The thesis makes progress on this question using the so-called forbidden pattern approach: Classes of regular languages are characterized in terms of patterns in finite automata (subgraphs in the transition graph) that are not allowed. Such a characterization immediately implies the decidability of the respective class, since the absence of a certain pattern in a given automaton can be effectively verified. Before this work, the decidability of B(0), B(1/2), B(1) and L(0), L(1/2), L(1), L(3/2) were known. Here a detailed study of these classes with help of forbidden patterns is given which leads to new insights into their inner structure. Furthermore, the decidability of B(3/2) is proven. Based on these results a theory of pattern iteration is developed which leads to the introduction of two new hierarchies of star-free regular languages. These hierarchies are decidable on one hand, on the other hand they are in close connection to the classes B(n) and L(n). It remains an open question here whether they may in fact coincide. Some evidence is given in favour of this conjecture which opens a new way to attack the dot-depth problem. Moreover, it is shown that the class L(5/2) is decidable in the restricted case of a two-letter alphabet.},
  subject      = {Sternfreie Sprache},
  language  = {en}
}
@phdthesis{Kluegl2000,
  author    = {Kl{\"u}gl, Franziska},
  title     = {Aktivit{\"a}tsbasierte Verhaltensmodellierung und ihre Unterst{\"u}tzung bei Multiagentensimulationen},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-2874},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2000},
  abstract  = {Durch Zusammenf{\"u}hrung traditioneller Methoden zur individuenbasierten Simulation und dem Konzept der Multiagentensysteme steht mit der Multiagentensimulation eine Methodik zur Verf{\"u}gung, die es erm{\"o}glicht, sowohl technisch als auch konzeptionell eine neue Ebene an Detaillierung bei Modellbildung und Simulation zu erreichen. Ein Modell beruht dabei auf dem Konzept einer Gesellschaft: Es besteht aus einer Menge interagierender, aber in ihren Entscheidungen autonomen Einheiten, den Agenten. Diese {\"a}ndern durch ihre Aktionen ihre Umwelt und reagieren ebenso auf die f{\"u}r sie wahrnehmbaren {\"A}nderungen in der Umwelt. Durch die Simulation jedes Agenten zusammen mit der Umwelt, in der er "lebt", wird die Dynamik im Gesamtsystem beobachtbar. In der vorliegenden Dissertation wurde ein Repr{\"a}sentationsschema f{\"u}r Multiagentensimulationen entwickelt werden, das es Fachexperten, wie zum Beispiel Biologen, erm{\"o}glicht, selbst{\"a}ndig ohne traditionelles Programmieren Multiagentenmodelle zu implementieren und mit diesen Experimente durchzuf{\"u}hren. Dieses deklarative Schema beruht auf zwei Basiskonzepten: Der K{\"o}rper eines Agenten besteht aus Zustandsvariablen. Das Verhalten des Agenten kann mit Regeln beschrieben werden. Ausgehend davon werden verschiedene Strukturierungsans{\"a}tze behandelt. Das wichtigste Konzept ist das der "Aktivit{\"a}t", einer Art "Verhaltenszustand": W{\"a}hrend der Agent in einer Aktivit{\"a}t A verweilt, f{\"u}hrt er die zugeh{\"o}rigen Aktionen aus und dies solange, bis eine Regel feuert, die diese Aktivit{\"a}t beendet und eine neue Aktivit{\"a}t ausw{\"a}hlt. Durch Indizierung dieser Regeln bei den zugeh{\"o}rigen Aktivit{\"a}ten und Einf{\"u}hrung von abstrakten Aktivit{\"a}ten entsteht ein Schema f{\"u}r eine vielf{\"a}ltig strukturierbare Verhaltensbeschreibung. Zu diesem Schema wurde ein Interpreter entwickelt, der ein derartig repr{\"a}sentiertes Modell ausf{\"u}hrt und so Simulationsexperimente mit dem Multiagentenmodell erlaubt. Auf dieser Basis wurde die Modellierungs- und Experimentierumgebung SeSAm ("Shell f{\"u}r Simulierte Agentensysteme") entwickelt. Sie verwendet vorhandene Konzepte aus dem visuellen Programmieren. Mit dieser Umgebung wurden Anwendungsmodelle aus verschiedenen Dom{\"a}nen realisiert: Neben abstrakten Spielbeispielen waren dies vor allem Fragestellungen zu sozialen Insekten, z.B. zum Verhalten von Ameisen, Bienen oder der Interaktion zwischen Bienenv{\"o}lkern und Milbenpopulationen.},
  subject      = {Agent <Informatik>},
  language  = {de}
}
@phdthesis{Baier1998,
  author    = {Baier, Herbert},
  title     = {Operators of Higher Order},
  publisher = {Shaker Verlag},
  isbn      = {3-8265-4008-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-140799},
  school      = {Universit{\"a}t W{\"u}rzburg},
  pages     = {V, 95},
  year      = {1998},
  abstract  = {Motivated by results on interactive proof systems we investigate the computational power of quantifiers applied to well-known complexity classes. In special, we are interested in existential, universal and probabilistic bounded error quantifiers ranging over words and sets of words, i.e. oracles if we think in a Turing machine model. In addition to the standard oracle access mechanism, we also consider quantifiers ranging over oracles to which access is restricted in a certain way.},
  subject      = {Komplexit{\"a}tstheorie},
  language  = {en}
}
@article{KrenzerHeilFittingetal.,
  author    = {Krenzer, Adrian and Heil, Stefan and Fitting, Daniel and Matti, Safa and Zoller, Wolfram G. and Hann, Alexander and Puppe, Frank},
  title     = {Automated classification of polyps using deep learning architectures and few-shot learning},
  series = {BMC Medical Imaging},
  volume    = {23},
  journal   = {BMC Medical Imaging},
  doi       = {10.1186/s12880-023-01007-4},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357465},
  abstract  = {Background Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous. Therefore, polyps are classified using different classification systems. After the classification, further treatment and procedures are based on the classification of the polyp. Nevertheless, classification is not easy. Therefore, we suggest two novel automated classifications system assisting gastroenterologists in classifying polyps based on the NICE and Paris classification. Methods We build two classification systems. One is classifying polyps based on their shape (Paris). The other classifies polyps based on their texture and surface patterns (NICE). A two-step process for the Paris classification is introduced: First, detecting and cropping the polyp on the image, and secondly, classifying the polyp based on the cropped area with a transformer network. For the NICE classification, we design a few-shot learning algorithm based on the Deep Metric Learning approach. The algorithm creates an embedding space for polyps, which allows classification from a few examples to account for the data scarcity of NICE annotated images in our database. Results For the Paris classification, we achieve an accuracy of 89.35 \%, surpassing all papers in the literature and establishing a new state-of-the-art and baseline accuracy for other publications on a public data set. For the NICE classification, we achieve a competitive accuracy of 81.13 \% and demonstrate thereby the viability of the few-shot learning paradigm in polyp classification in data-scarce environments. Additionally, we show different ablations of the algorithms. Finally, we further elaborate on the explainability of the system by showing heat maps of the neural network explaining neural activations. Conclusion Overall we introduce two polyp classification systems to assist gastroenterologists. We achieve state-of-the-art performance in the Paris classification and demonstrate the viability of the few-shot learning paradigm in the NICE classification, addressing the prevalent data scarcity issues faced in medical machine learning.},
  language  = {en}
}