@inproceedings{SchreiberKraftZuendorf2018,
  author    = {Schreiber, Marc and Kraft, Bodo and Z{\"u}ndorf, Albert},
  title     = {NLP Lean Programming Framework: Developing NLP Applications More Effectively},
  series = {Proceedings of NAACL-HLT 2018: Demonstrations, New Orleans, Louisiana, June 2 - 4, 2018},
  booktitle = {Proceedings of NAACL-HLT 2018: Demonstrations, New Orleans, Louisiana, June 2 - 4, 2018},
  doi       = {10.18653/v1/N18-5001 },
  pages     = {5 Seiten},
  year      = {2018},
  abstract  = {This paper presents NLP Lean Programming framework (NLPf), a new framework for creating custom natural language processing (NLP) models and pipelines by utilizing common software development build systems. This approach allows developers to train and integrate domain-specific NLP pipelines into their applications seamlessly. Additionally, NLPf provides an annotation tool which improves the annotation process significantly by providing a well-designed GUI and sophisticated way of using input devices. Due to NLPf's properties developers and domain experts are able to build domain-specific NLP applications more efficiently. NLPf is Opensource software and available at https:// gitlab.com/schrieveslaach/NLPf.},
  language  = {en}
}
@inproceedings{SchulzeMuehleisenFeyerl2018,
  author    = {Schulze, Sven and M{\"u}hleisen, M. and Feyerl, G{\"u}nter},
  title     = {Adaptive energy management strategy for a heavy-duty truck with a P2-hybrid topology},
  series = {18. Internationales Stuttgarter Symposium. Proceedings},
  booktitle = {18. Internationales Stuttgarter Symposium. Proceedings},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  doi       = {10.1007/978-3-658-21194-3},
  pages     = {75 -- 89},
  year      = {2018},
  language  = {en}
}
@article{SchwabedalSippelBrandtetal.2018,
  author    = {Schwabedal, Justus T. C. and Sippel, Daniel and Brandt, Moritz D. and Bialonski, Stephan},
  title     = {Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning},
  doi       = {10.48550/arXiv.1809.08443},
  year      = {2018},
  abstract  = {Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle.},
  language  = {en}
}
@incollection{SchoeningPoghossian2018,
  author    = {Sch{\"o}ning, Michael Josef and Poghossian, Arshak},
  title     = {Enzyme und Biosensorik},
  series = {Einf{\"u}hrung in die Enzymtechnologie},
  booktitle = {Einf{\"u}hrung in die Enzymtechnologie},
  publisher = {Springer Spektrum},
  address   = {Berlin},
  isbn      = {978-3-662-57619-9},
  doi       = {10.1007/978-3-662-57619-9_18},
  pages     = {323 -- 347},
  year      = {2018},
  abstract  = {Enzymbasierte Biosensoren finden seit mehr als f{\"u}nf Jahrzehnten einen prosperierenden Wachstumsmarkt und werden zunehmend auch in biotechnologischen Prozessen eingesetzt. In diesem Kapitel werden, ausgehend vom Sensorbegriff und typischen Kenngr{\"o}ßen f{\"u}r Biosensoren (Abschn. 18.1), elektrochemische Enzym-Biosensoren vorgestellt und deren typischen Einsatzgebiete diskutiert (Abschn. 18.2). Ein Blick {\"u}ber den „Tellerrand" hinaus zeigt alternative Transduktorprinzipien (Abschn. 18.3) und f{\"u}hrt abschließend in aktuelle Forschungstrends ein (Abschn. 18.4).},
  language  = {de}
}
@book{SchoeningPoghossian2018,
  author    = {Sch{\"o}ning, Michael Josef and Poghossian, Arshak},
  title     = {Label-free biosensing: advanced materials, devices and applications},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-75219-8},
  pages     = {xii, 480 Seiten ; Illustrationen, Diagramme},
  year      = {2018},
  language  = {en}
}
@incollection{SchoeningWagnerPoghossianetal.2018,
  author    = {Sch{\"o}ning, Michael Josef and Wagner, Torsten and Poghossian, Arshak and Miyamoto, K.I. and Werner, C.F. and Krause, S. and Yoshinobu, T.},
  title     = {Light-addressable potentiometric sensors for (bio-)chemical sensing and imaging},
  series = {Encyclopedia of Interfacial Chemistry: Surface Science and Electrochemistry. Vol. 7},
  booktitle = {Encyclopedia of Interfacial Chemistry: Surface Science and Electrochemistry. Vol. 7},
  publisher = {Elsevier},
  address   = {Amsterdam},
  isbn      = {9780128097397},
  pages     = {295 -- 308},
  year      = {2018},
  language  = {en}
}
@inproceedings{SerrorHenzeHacketal.2018,
  author    = {Serror, Martin and Henze, Martin and Hack, Sacha and Schuba, Marko and Wehrle, Klaus},
  title     = {Towards in-network security for smart homes},
  series = {13th International Conference on Availability, Reliability and Security, ARES 2018; Hamburg; Germany; 27 August 2018 through 30 August 2018},
  booktitle = {13th International Conference on Availability, Reliability and Security, ARES 2018; Hamburg; Germany; 27 August 2018 through 30 August 2018},
  isbn      = {978-145036448-5},
  doi       = {10.1145/3230833.3232802},
  pages     = {Article numer 3232802},
  year      = {2018},
  language  = {en}
}
@incollection{StengerAltherrMuelleretal.2018,
  author    = {Stenger, David and Altherr, Lena and M{\"u}ller, Tankred and Pelz, Peter F.},
  title     = {Product family design optimization using model-based engineering techniques},
  series = {Operations Research Proceedings 2017},
  booktitle = {Operations Research Proceedings 2017},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-89919-0},
  doi       = {10.1007/978-3-319-89920-6_66},
  pages     = {495 -- 502},
  year      = {2018},
  abstract  = {Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.},
  language  = {en}
}
@article{SunAltherrPeietal.2018,
  author    = {Sun, Hui and Altherr, Lena and Pei, Ji and Pelz, Peter F. and Yuan, Shouqi},
  title     = {Optimal booster station design and operation under uncertain load},
  series = {Applied Mechanics and Materials},
  volume    = {885},
  journal   = {Applied Mechanics and Materials},
  publisher = {Trans Tech Publications},
  address   = {B{\"a}ch},
  issn      = {1662-7482},
  doi       = {10.4028/www.scientific.net/AMM.885.102},
  pages     = {102 -- 115},
  year      = {2018},
  abstract  = {Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the system's resilience can be engineered},
  language  = {en}
}
@article{SvaneborgKarimiVarzanehHojdisetal.2018,
  author    = {Svaneborg, Carsten and Karimi-Varzaneh, Hossein Ali and Hojdis, Nils and Fleck, Franz and Everaers, Ralf},
  title     = {Kremer-Grest Models for Universal Properties of Specific Common Polymer Species},
  series = {Soft Condensed Matter},
  journal   = {Soft Condensed Matter},
  number    = {1606.05008},
  year      = {2018},
  abstract  = {The Kremer-Grest (KG) bead-spring model is a near standard in Molecular Dynamic simulations of generic polymer properties. It owes its popularity to its computational efficiency, rather than its ability to represent specific polymer species and conditions. Here we investigate how to adapt the model to match the universal properties of a wide range of chemical polymers species. For this purpose we vary a single parameter originally introduced by Faller and M{\"u}ller-Plathe, the chain stiffness. Examples include polystyrene, polyethylene, polypropylene, cis-polyisoprene, polydimethylsiloxane, polyethyleneoxide and styrene-butadiene rubber. We do this by matching the number of Kuhn segments per chain and the number of Kuhn segments per cubic Kuhn volume for the polymer species and for the Kremer-Grest model. We also derive mapping relations for converting KG model units back to physical units, in particular we obtain the entanglement time for the KG model as function of stiffness allowing for a time mapping. To test these relations, we generate large equilibrated well entangled polymer melts, and measure the entanglement moduli using a static primitive-path analysis of the entangled melt structure as well as by simulations of step-strain deformation of the model melts. The obtained moduli for our model polymer melts are in good agreement with the experimentally expected moduli.},
  language  = {en}
}