@phdthesis{Grum2021,
  author    = {Grum, Marcus},
  title     = {Construction of a concept of neuronal modeling},
  year      = {2021},
  abstract  = {The business problem of having inefficient processes, imprecise process analyses, and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating, and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS), and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes.},
  language  = {en}
}
@article{Hildebrandt2016,
  author    = {Hildebrandt, Dieter},
  title     = {Image-based styling},
  series = {The Visual Computer},
  volume    = {32},
  journal   = {The Visual Computer},
  publisher = {Springer},
  address   = {New York},
  issn      = {0178-2789},
  doi       = {10.1007/s00371-015-1073-3},
  pages     = {445 -- 463},
  year      = {2016},
  abstract  = {The same data can be visualized using various visual styles that each is suitable for specific requirements, e.g., 3D geodata visualized using photorealistic, cartographic, or illustrative styles. In contrast to feature-based styling, image-based styling performed in image space at image resolution allows decoupling styling from image generation and output-sensitive, expressive styling. However, leveraging image-based styling is still impeded. No previous approach allows specifying image-based styling expressively with an extensive inventory of composable operators, while providing styling functionality in a service-oriented, interoperable manner. In this article, we present an interactive system for specifying and providing the functionality of image-based styling. As key characteristics, it separates concerns of styling from image generation and facilitates specifying styling as algebraic compositions of high-level operators using a unified 3D model representation. We propose a generalized visualization model, an image-based styling algebra, two declarative DSLs, an operator taxonomy, an operational model, and a standards-based service interface. The approach facilitates expressive specifications of image-based styling for design, description, and analysis and leveraging the functionality of image-based styling in a service-oriented, interoperable, reusable, and composable manner.},
  language  = {en}
}
@article{GautamZhangLandwehretal.2021,
  author    = {Gautam, Khem Raj and Zhang, Guoqiang and Landwehr, Niels and Adolphs, Julian},
  title     = {Machine learning for improvement of thermal conditions inside a hybrid ventilated animal building},
  series = {Computers and electronics in agriculture : COMPAG online ; an international journal},
  volume    = {187},
  journal   = {Computers and electronics in agriculture : COMPAG online ; an international journal},
  publisher = {Elsevier Science},
  address   = {Amsterdam [u.a.]},
  issn      = {0168-1699},
  doi       = {10.1016/j.compag.2021.106259},
  pages     = {10},
  year      = {2021},
  abstract  = {In buildings with hybrid ventilation, natural ventilation opening positions (windows), mechanical ventilation rates, heating, and cooling are manipulated to maintain desired thermal conditions. The indoor temperature is regulated solely by ventilation (natural and mechanical) when the external conditions are favorable to save external heating and cooling energy. The ventilation parameters are determined by a rule-based control scheme, which is not optimal. This study proposes a methodology to enable real-time optimum control of ventilation parameters. We developed offline prediction models to estimate future thermal conditions from the data collected from building in operation. The developed offline model is then used to find the optimal controllable ventilation parameters in real-time to minimize the setpoint deviation in the building. With the proposed methodology, the experimental building's setpoint deviation improved for 87\% of time, on average, by 0.53 degrees C compared to the current deviations.},
  language  = {en}
}
@article{KraemerGelbrechtPavithranetal.2022,
  author    = {Kr{\"a}mer, Hauke Kai and Gelbrecht, Maximilian and Pavithran, Induja and Sujith, Ravindran and Marwan, Norbert},
  title     = {Optimal state space reconstruction via Monte Carlo decision tree search},
  series = {Nonlinear Dynamics},
  volume    = {108},
  journal   = {Nonlinear Dynamics},
  number    = {2},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0924-090X},
  doi       = {10.1007/s11071-022-07280-2},
  pages     = {1525 -- 1545},
  year      = {2022},
  abstract  = {A novel idea for an optimal time delay state space reconstruction from uni- and multivariate time series is presented. The entire embedding process is considered as a game, in which each move corresponds to an embedding cycle and is subject to an evaluation through an objective function. This way the embedding procedure can be modeled as a tree, in which each leaf holds a specific value of the objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path, which ends at the leaf with the lowest achieved value of the objective function. The method aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way, enabling practitioners to choose a statistic for possible delays in each embedding cycle as well as a suitable objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. As a proof of concept, we demonstrate the superiority of the proposed method over the classical time delay embedding methods using a variety of application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. Finally, we utilize state space reconstruction for the detection of causality and its strength between observables of a gas turbine type thermoacoustic combustor.},
  language  = {en}
}
@article{BaslerGrimbsNikoloski2012,
  author    = {Basler, Georg and Grimbs, Sergio and Nikoloski, Zoran},
  title     = {Optimizing metabolic pathways by screening for feasible synthetic reactions},
  series = {Biosystems : journal of biological and information processing sciences},
  volume    = {109},
  journal   = {Biosystems : journal of biological and information processing sciences},
  number    = {2},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0303-2647},
  doi       = {10.1016/j.biosystems.2012.04.007},
  pages     = {186 -- 191},
  year      = {2012},
  abstract  = {Background: Reconstruction of genome-scale metabolic networks has resulted in models capable of reproducing experimentally observed biomass yield/growth rates and predicting the effect of alterations in metabolism for biotechnological applications. The existing studies rely on modifying the metabolic network of an investigated organism by removing or inserting reactions taken either from evolutionary similar organisms or from databases of biochemical reactions (e.g., KEGG). A potential disadvantage of these knowledge-driven approaches is that the result is biased towards known reactions, as such approaches do not account for the possibility of including novel enzymes, together with the reactions they catalyze. Results: Here, we explore the alternative of increasing biomass yield in three model organisms, namely Bacillus subtilis, Escherichia coil, and Hordeum vulgare, by applying small, chemically feasible network modifications. We use the predicted and experimentally confirmed growth rates of the wild-type networks as reference values and determine the effect of inserting mass-balanced, thermodynamically feasible reactions on predictions of growth rate by using flux balance analysis. Conclusions: While many replacements of existing reactions naturally lead to a decrease or complete loss of biomass production ability, in all three investigated organisms we find feasible modifications which facilitate a significant increase in this biological function. We focus on modifications with feasible chemical properties and a significant increase in biomass yield. The results demonstrate that small modifications are sufficient to substantially alter biomass yield in the three organisms. The method can be used to predict the effect of targeted modifications on the yield of any set of metabolites (e.g., ethanol), thus providing a computational framework for synthetic metabolic engineering.},
  language  = {en}
}