TY - CHAP A1 - Schmidts, Oliver A1 - Boltes, Maik A1 - Kraft, Bodo A1 - Schreiber, Marc T1 - Multi-pedestrian tracking by moving Bluetooth-LE beacons and stationary receivers T2 - 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 18-21 September 2017, Sapporo, Japan Y1 - 2017 N1 - International Conference on Indoor Positioning and Indoor Navigation <8, 2017, Sapporo, Japan> SP - 1 EP - 4 ER - TY - CHAP A1 - Krome, Cornelia A1 - Sander, Volker T1 - Time series analysis with apache spark and its applications to energy informatics T2 - Proceedings of the 7th DACH+ Conference on Energy Informatics N2 - 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. Y1 - 2018 U6 - https://doi.org/10.1186/s42162-018-0043-1 N1 - Energy Informatics 2018, Volume 1 Supplement 1 ER - TY - CHAP A1 - Pohle-Fröhlich, Regina A1 - Dalitz, Christoph A1 - Richter, Charlotte A1 - Hahnen, Tobias A1 - Stäudle, Benjamin A1 - Albracht, Kirsten T1 - Estimation of muscle fascicle orientation in ultrasonic images T2 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 N2 - 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. Y1 - 2020 SN - 978-989-758-402-2 U6 - https://doi.org/10.5220/0008933900790086 N1 - 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISAPP 2020, Valletta, Malta SP - 79 EP - 86 PB - SciTePress CY - Setúbal, Portugal ER - TY - CHAP A1 - Hingley, Peter A1 - Dikta, Gerhard T1 - Finding a well performing box-jenkins forecasting model for annualised patent filings counts T2 - International Symposium on Forecasting, Thessaloniki, Greece, June 2019 Y1 - 2019 ER - TY - CHAP A1 - Büsgen, André A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Exploratory analysis of chat-based black market profiles with natural language processing T2 - Proceedings of the 11th International Conference on Data Science, Technology and Applications N2 - 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. KW - Clustering KW - Natural Language Processing KW - Information Extraction KW - Profile Extraction KW - Text Mining Y1 - 2022 SN - 978-989-758-583-8 U6 - https://doi.org/10.5220/0011271400003269 SN - 2184-285X N1 - 11th International Conference on Data Science, Technology and Applications DATA - Volume 1, 83-94, 2022, Lisbon, Portugal SP - 83 EP - 94 ER - TY - CHAP A1 - Tran, Ngoc Trinh A1 - Tran, Thanh Ngoc A1 - Matthies, Hermann G. A1 - Stavroulakis, Georgios Eleftherios A1 - Staat, Manfred T1 - FEM Shakedown of uncertain structures by chance constrained programming T2 - PAMM Proceedings in Applied Mathematics and Mechanics Y1 - 2016 U6 - https://doi.org/10.1002/pamm.201610346 SN - 1617-7061 N1 - Special Issue: Joint 87th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM) and Deutsche Mathematiker-Vereinigung VL - 16 IS - 1 SP - 715 EP - 716 ER - TY - CHAP A1 - Blaneck, Patrick Gustav A1 - Bornheim, Tobias A1 - Grieger, Niklas A1 - Bialonski, Stephan T1 - Automatic readability assessment of german sentences with transformer ensembles T2 - Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text N2 - 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. Y1 - 2022 U6 - https://doi.org/10.48550/arXiv.2209.04299 N1 - Proceedings of the 18th Conference on Natural Language Processing / Konferenz zur Verarbeitung natürlicher Sprache (KONVENS 2022), 12-15 September, 2022, University of Potsdam, Potsdam, Germany SP - 57 EP - 62 PB - Association for Computational Linguistics CY - Potsdam ER - TY - CHAP A1 - Staat, Manfred A1 - Tran, Ngoc Trinh T1 - Strain based brittle failure criteria for rocks T2 - Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training N2 - 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. KW - Extension fracture KW - Extension strain criterion KW - Mohr–Coulomb criterion KW - Evolution of damage Y1 - 2023 SN - 978-604-357-084-7 N1 - 11th National Conference on Mechanics (NACOME 2022), December 2-3, 2022, VNU University of Engineering and Technology, Hanoi, Vietnam SP - 500 EP - 509 PB - Nha xuat ban Khoa hoc tu nhien va Cong nghe (Verlag Naturwissenschaft und Technik) CY - Hanoi ER - TY - CHAP A1 - Jablonski, Melanie A1 - Koch, Claudia A1 - Bronder, Thomas A1 - Poghossian, Arshak A1 - Wege, Christina A1 - Schöning, Michael Josef T1 - Field-Effect Biosensors Modified with Tobacco Mosaic Virus Nanotubes as Enzyme Nanocarrier T2 - MDPI Proceeding Y1 - 2017 U6 - https://doi.org/10.3390/proceedings1040505 N1 - Eurosensors 2017 Conference, Paris, France, 3–6 September 2017 VL - 1 IS - 4 ER - TY - CHAP A1 - Miyamoto, Ko-ichiro A1 - Suto, Takeyuki A1 - Werner, Frederik A1 - Wagner, Torsten A1 - Schöning, Michael Josef A1 - Yoshinobu, Tatsuo T1 - Restraining the Diffusion of Photocarriers to Improve the Spatial Resolution of the Chemical Imaging Sensor T2 - MDPI Proceedings Y1 - 2017 U6 - https://doi.org/10.3390/proceedings1040477 N1 - Eurosensors 2017 Conference, Paris, France, 3–6 September 2017 VL - 1 IS - 4 ER -