@phdthesis{Lincke2014,
  author    = {Lincke, Jens},
  title     = {Evolving Tools in a Collaborative Self-supporting Development Environment},
  school      = {Universit{\"a}t Potsdam},
  pages     = {164},
  year      = {2014},
  language  = {en}
}
@phdthesis{Lindauer2014,
  author    = {Lindauer, T. Marius},
  title     = {Algorithm selection, scheduling and configuration of Boolean constraint solvers},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-71260},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ii, 130},
  year      = {2014},
  abstract  = {Boolean constraint solving technology has made tremendous progress over the last decade, leading to industrial-strength solvers, for example, in the areas of answer set programming (ASP), the constraint satisfaction problem (CSP), propositional satisfiability (SAT) and satisfiability of quantified Boolean formulas (QBF). However, in all these areas, there exist multiple solving strategies that work well on different applications; no strategy dominates all other strategies. Therefore, no individual solver shows robust state-of-the-art performance in all kinds of applications. Additionally, the question arises how to choose a well-performing solving strategy for a given application; this is a challenging question even for solver and domain experts. One way to address this issue is the use of portfolio solvers, that is, a set of different solvers or solver configurations. We present three new automatic portfolio methods: (i) automatic construction of parallel portfolio solvers (ACPP) via algorithm configuration,(ii) solving the \$NP\$-hard problem of finding effective algorithm schedules with Answer Set Programming (aspeed), and (iii) a flexible algorithm selection framework (claspfolio2) allowing for fair comparison of different selection approaches. All three methods show improved performance and robustness in comparison to individual solvers on heterogeneous instance sets from many different applications. Since parallel solvers are important to effectively solve hard problems on parallel computation systems (e.g., multi-core processors), we extend all three approaches to be effectively applicable in parallel settings. We conducted extensive experimental studies different instance sets from ASP, CSP, MAXSAT, Operation Research (OR), SAT and QBF that indicate an improvement in the state-of-the-art solving heterogeneous instance sets. Last but not least, from our experimental studies, we deduce practical advice regarding the question when to apply which of our methods.},
  language  = {en}
}
@phdthesis{Krueger2014,
  author    = {Kr{\"u}ger, Jens},
  title     = {Enterprise-specific in-memory data managment : HYRISEc - an in-memory column store engine for OLXP},
  publisher = {Hasso-Plattner-Insitut},
  address   = {Potsdam},
  pages     = {201 S.},
  year      = {2014},
  language  = {en}
}
@phdthesis{Rafiee2014,
  author    = {Rafiee, Hosnieh},
  title     = {Privacy and security issues in IPv6 networks},
  address   = {Potsdam},
  pages     = {141 S.},
  year      = {2014},
  language  = {en}
}
@phdthesis{Fudickar2014,
  author    = {Fudickar, Sebastian},
  title     = {Sub Ghz transceiver for indoor localisation of smartphones},
  school      = {Universit{\"a}t Potsdam},
  pages     = {IV, 167},
  year      = {2014},
  language  = {en}
}
@phdthesis{Videla2014,
  author    = {Videla, Santiago},
  title     = {Reasoning on the response of logical signaling networks with answer set programming},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-71890},
  school      = {Universit{\"a}t Potsdam},
  year      = {2014},
  abstract  = {Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks.},
  language  = {en}
}
@phdthesis{Gericke2014,
  author    = {Gericke, Lutz},
  title     = {Tele-Board - Supporting and analyzing creative collaboration in synchronous and asynchronous scenario},
  pages     = {186},
  year      = {2014},
  language  = {en}
}