@inproceedings{KromeSander2018,
  author    = {Krome, Cornelia and Sander, Volker},
  title     = {Time series analysis with apache spark and its applications to energy informatics},
  series = {Proceedings of the 7th DACH+ Conference on Energy Informatics},
  booktitle = {Proceedings of the 7th DACH+ Conference on Energy Informatics},
  doi       = {10.1186/s42162-018-0043-1},
  year      = {2018},
  abstract  = {In energy economy forecasts of different time series are rudimentary. In this study, a prediction for the German day-ahead spot market is created with Apache Spark and R. It is just an example for many different applications in virtual power plant environments. Other examples of use as intraday price processes, load processes of machines or electric vehicles, real time energy loads of photovoltaic systems and many more time series need to be analysed and predicted. This work gives a short introduction into the project where this study is settled. It describes the time series methods that are used in energy industry for forecasts shortly. As programming technique Apache Spark, which is a strong cluster computing technology, is utilised. Today, single time series can be predicted. The focus of this work is on developing a method to parallel forecasting, to process multiple time series simultaneously with R and Apache Spark.},
  language  = {en}
}
@inproceedings{PohleFroehlichDalitzRichteretal.2020,
  author    = {Pohle-Fr{\"o}hlich, Regina and Dalitz, Christoph and Richter, Charlotte and Hahnen, Tobias and St{\"a}udle, Benjamin and Albracht, Kirsten},
  title     = {Estimation of muscle fascicle orientation in ultrasonic images},
  series = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5},
  booktitle = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5},
  publisher = {SciTePress},
  address   = {Set{\´u}bal, Portugal},
  isbn      = {978-989-758-402-2},
  doi       = {10.5220/0008933900790086},
  pages     = {79 -- 86},
  year      = {2020},
  abstract  = {We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.},
  language  = {en}
}
@inproceedings{HingleyDikta2019,
  author    = {Hingley, Peter and Dikta, Gerhard},
  title     = {Finding a well performing box-jenkins forecasting model for annualised patent filings counts},
  series = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019},
  booktitle = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019},
  pages     = {24 Folien},
  year      = {2019},
  language  = {en}
}
@inproceedings{BuesgenKloeserKohletal.2022,
  author    = {B{\"u}sgen, Andr{\´e} and Kl{\"o}ser, Lars and Kohl, Philipp and Schmidts, Oliver and Kraft, Bodo and Z{\"u}ndorf, Albert},
  title     = {Exploratory analysis of chat-based black market profiles with natural language processing},
  series = {Proceedings of the 11th International Conference on Data Science, Technology and Applications},
  booktitle = {Proceedings of the 11th International Conference on Data Science, Technology and Applications},
  isbn      = {978-989-758-583-8},
  issn      = {2184-285X},
  doi       = {10.5220/0011271400003269},
  pages     = {83 -- 94},
  year      = {2022},
  abstract  = {Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.},
  language  = {en}
}
@inproceedings{StaatDuong2016,
  author    = {Staat, Manfred and Duong, Minh Tuan},
  title     = {Smoothed Finite Element Methods for Nonlinear Solid Mechanics Problems: 2D and 3D Case Studies},
  series = {Proceedings of the National Science and Technology Conference on Mechanical - Transportation Engineering (NSCMET 2016), 13th October 2016, Hanoi, Vietnam, Vol.2},
  booktitle = {Proceedings of the National Science and Technology Conference on Mechanical - Transportation Engineering (NSCMET 2016), 13th October 2016, Hanoi, Vietnam, Vol.2},
  pages     = {440 -- 445},
  year      = {2016},
  abstract  = {The Smoothed Finite Element Method (SFEM) is presented as an edge-based and a facebased techniques for 2D and 3D boundary value problems, respectively. SFEMs avoid shortcomings of the standard Finite Element Method (FEM) with lower order elements such as overly stiff behavior, poor stress solution, and locking effects. Based on the idea of averaging spatially the standard strain field of the FEM over so-called smoothing domains SFEM calculates the stiffness matrix for the same number of degrees of freedom (DOFs) as those of the FEM. However, the SFEMs significantly improve accuracy and convergence even for distorted meshes and/or nearly incompressible materials. Numerical results of the SFEMs for a cardiac tissue membrane (thin plate inflation) and an artery (tension of 3D tube) show clearly their advantageous properties in improving accuracy particularly for the distorted meshes and avoiding shear locking effects.},
  language  = {en}
}
@inproceedings{TranTranMatthiesetal.2016,
  author    = {Tran, Ngoc Trinh and Tran, Thanh Ngoc and Matthies, Hermann G. and Stavroulakis, Georgios Eleftherios and Staat, Manfred},
  title     = {FEM Shakedown of uncertain structures by chance constrained programming},
  series = {PAMM Proceedings in Applied Mathematics and Mechanics},
  volume    = {16},
  booktitle = {PAMM Proceedings in Applied Mathematics and Mechanics},
  number    = {1},
  issn      = {1617-7061},
  doi       = {10.1002/pamm.201610346},
  pages     = {715 -- 716},
  year      = {2016},
  language  = {en}
}
@inproceedings{BlaneckBornheimGriegeretal.2022,
  author    = {Blaneck, Patrick Gustav and Bornheim, Tobias and Grieger, Niklas and Bialonski, Stephan},
  title     = {Automatic readability assessment of german sentences with transformer ensembles},
  series = {Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text},
  booktitle = {Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text},
  publisher = {Association for Computational Linguistics},
  address   = {Potsdam},
  doi       = {10.48550/arXiv.2209.04299},
  pages     = {57 -- 62},
  year      = {2022},
  abstract  = {Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435.},
  language  = {en}
}
@inproceedings{StaatTran2022,
  author    = {Staat, Manfred and Tran, Ngoc Trinh},
  title     = {Strain based brittle failure criteria for rocks},
  series = {Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training},
  booktitle = {Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training},
  publisher = {Nha xuat ban Khoa hoc tu nhien va Cong nghe (Verlag Naturwissenschaft und Technik)},
  address   = {Hanoi},
  isbn      = {978-604-357-084-7},
  pages     = {500 -- 509},
  year      = {2022},
  abstract  = {When confining pressure is low or absent, extensional fractures are typical, with fractures occurring on unloaded planes in rock. These "paradox" fractures can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. But this criterion makes unrealistic strength predictions in biaxial compression and tension. A new extension strain criterion overcomes this limitation by adding a weighted principal shear component. The weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr-Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting failure modes, which are unexpected in the understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak P. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.},
  language  = {en}
}
@inproceedings{JablonskiKochBronderetal.2017,
  author    = {Jablonski, Melanie and Koch, Claudia and Bronder, Thomas and Poghossian, Arshak and Wege, Christina and Sch{\"o}ning, Michael Josef},
  title     = {Field-Effect Biosensors Modified with Tobacco Mosaic Virus Nanotubes as Enzyme Nanocarrier},
  series = {MDPI Proceeding},
  volume    = {1},
  booktitle = {MDPI Proceeding},
  number    = {4},
  doi       = {10.3390/proceedings1040505},
  pages     = {4},
  year      = {2017},
  language  = {en}
}
@inproceedings{MiyamotoSutoWerneretal.2017,
  author    = {Miyamoto, Ko-ichiro and Suto, Takeyuki and Werner, Frederik and Wagner, Torsten and Sch{\"o}ning, Michael Josef and Yoshinobu, Tatsuo},
  title     = {Restraining the Diffusion of Photocarriers to Improve the Spatial Resolution of the Chemical Imaging Sensor},
  series = {MDPI Proceedings},
  volume    = {1},
  booktitle = {MDPI Proceedings},
  number    = {4},
  doi       = {10.3390/proceedings1040477},
  pages     = {4 Seiten},
  year      = {2017},
  language  = {en}
}