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 - http://dx.doi.org/10.1186/s42162-018-0043-1 N1 - Energy Informatics 2018, Volume 1 Supplement 1 ER - TY - CHAP A1 - Kremers, Alexander A1 - Pieper, Martin T1 - Simulation and Verification of Bionic Heat Exchangers with COMSOL Multiphysics® Software T2 - COMSOL Conference 2015 User Presentations ; COMSOL Conference 2015 Grenoble October 14 - 16, 2015 - World Trade Center, Grenoble, France Y1 - 2015 PB - COMSOL CY - Göttingen ; Berlin ER - TY - CHAP A1 - Kolditz, Melanie A1 - Albracht, Kirsten A1 - Fasse, Alessandro A1 - Albin, Thivaharan A1 - Brüggemann, Gert-Peter A1 - Abel, Dirk T1 - Evaluation of an industrial robot as a leg press training device T2 - XV International Symposium on Computer Simulation in Biomechanics July 9th – 11th 2015, Edinburgh, UK Y1 - 2015 SP - 41 EP - 42 ER - TY - CHAP A1 - Kolditz, Melanie A1 - Albin, Thivaharan A1 - Fasse, Alessandro A1 - Brüggemann, Gert-Peter A1 - Abel, Dirk A1 - Albracht, Kirsten T1 - Simulative Analysis of Joint Loading During Leg Press Exercise for Control Applications T2 - IFAC-PapersOnLine Y1 - 2015 U6 - http://dx.doi.org/10.1016/j.ifacol.2015.10.179 N1 - IFAC-PapersOnLine 48-20; Conference Paper Archive VL - 48 IS - 20 SP - 435 EP - 440 ER - TY - CHAP A1 - Kolditz, Melanie A1 - Albin, Thivaharan A1 - Albracht, Kirsten A1 - Brüggemann, Gert-Peter A1 - Abel, Dirk T1 - Isokinematic leg extension training with an industrial robot T2 - 6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) June 26-29, 2016. UTown, Singapore Y1 - 2016 U6 - http://dx.doi.org/10.1109/BIOROB.2016.7523750 SP - 950 EP - 955 ER - TY - CHAP A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Klöser, Lars A1 - Werth, Henri A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - STAMP 4 NLP – an agile framework for rapid quality-driven NLP applications development T2 - Quality of Information and Communications Technology. QUATIC 2021 N2 - The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments. KW - Machine learning KW - Process model KW - Natural language processing Y1 - 2021 SN - 978-3-030-85346-4 SN - 978-3-030-85347-1 U6 - http://dx.doi.org/10.1007/978-3-030-85347-1_12 N1 - International Conference on the Quality of Information and Communications Technology, QUATIC 2021, 8-11 September, Algarve, Portugal SP - 156 EP - 166 PB - Springer CY - Cham ER - TY - CHAP A1 - Kohl, Philipp A1 - Freyer, Nils A1 - Krämer, Yoka A1 - Werth, Henri A1 - Wolf, Steffen A1 - Kraft, Bodo A1 - Meinecke, Matthias A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP T2 - Deep Learning Theory and Applications. DeLTA 2023. Communications in Computer and Information Science N2 - Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance. However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP. The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework. KW - Active learning KW - Query learning KW - Natural language processing KW - Deep learning KW - Reproducible research Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/978-3-031-39059-3 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER - TY - CHAP A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Multi-attribute relation extraction (MARE): simplifying the application of relation extraction T2 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications - DeLTA N2 - Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations. Y1 - 2021 SN - 978-989-758-526-5 U6 - http://dx.doi.org/10.5220/0010559201480156 N1 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications, DeLTA2021, July 7-9, 2021 SP - 148 EP - 156 ER - TY - CHAP A1 - Klöser, Lars A1 - Büsgen, André A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - Explaining relation classification models with semantic extents T2 - DeLTA 2023: Deep Learning Theory and Applications N2 - In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions. We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models. KW - Relation classification KW - Natural language processing KW - Natural language understanding KW - Information extraction KW - Trustworthy artificial intelligence Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-39059-3_13 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 189 EP - 208 PB - Springer CY - Cham ER - TY - CHAP A1 - Kloock, Joachim P. A1 - Schöning, Michael Josef T1 - Heavy metal detection with semiconductor devices based on PLD-prepared chalcogenide glass thin films T2 - Armenian Journal of Physics Y1 - 2007 SN - 1829-1171 SP - 95 EP - 98 ER - TY - CHAP A1 - Kloock, Joachim P. A1 - Schubert, J. A1 - Ermelenko, Y. A1 - Vlasov, Y. G. A1 - Bratov, A. A1 - Schöning, Michael Josef T1 - Thin-film sensors with chalcogenide glass materials – a general survey T2 - Biochemical sensing utilisation of micro- and nanotechnologies : Warsaw, [23rd - 26th] November 2005 / ed. by M. Mascini ... Y1 - 2006 SP - 92 EP - 97 CY - Warsaw ER - TY - CHAP A1 - Kloock, Joachim P. A1 - Moreno, Lia A1 - Huachupoma, S. A1 - Xu, J. A1 - Wagner, Torsten A1 - Bratov, A. A1 - Doll, T. A1 - Vlasov, Y. A1 - Schöning, Michael Josef ED - Gerlach, Gerald T1 - Halbleiterbasierte Schwermetallsensorik auf der Basis von Chalkogenidgläsern für zukünftige „Lab on Chip“-Anwendungen T2 - 7. Dresdner Sensor-Symposium - Neue Herausforderungen und Anwendungen in der Sensortechnik Y1 - 2005 SN - 3-938863-29-3 SP - 221 EP - 224 PB - TUDpress, Verl. der Wissenschaften CY - Dresden ER - TY - CHAP A1 - Kirchner, Patrick A1 - Henkel, H. A1 - Näther, Niko A1 - Spelthahn, H. A1 - Schneider, A. A1 - Berger, J. A1 - Kolstad, J. A1 - Friedrich, P. A1 - Schöning, Michael Josef T1 - RFID-basiertes Sensorsystem zur Realisierung intelligenter Verpackungen für die Nahrungsmittelindustrie T2 - KMU - innovativ: IKT 2008. CD-ROM : BMBF-Statustagung KMU - innovativ: IKT, Darmstadt, 17. - 18. Nov. 2008 Y1 - 2008 IS - CD-ROM-Ausg. PB - BMBF CY - Berlin ER - TY - CHAP A1 - Ketelhut, Maike A1 - Göll, Fabian A1 - Braunstein, Bjoern A1 - Albracht, Kirsten A1 - Abel, Dirk T1 - Iterative learning control of an industrial robot for neuromuscular training T2 - 2019 IEEE Conference on Control Technology and Applications N2 - Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations. KW - Knee KW - Training KW - Load modeling KW - Force KW - Iterative learning control Y1 - 2019 SN - 978-1-7281-2767-5 (ePub) SN - 978-1-7281-2766-8 (USB) SN - 978-1-7281-2768-2 (PoD) U6 - http://dx.doi.org/10.1109/CCTA.2019.8920659 N1 - 2019 IEEE Conference on Control Technology and Applications (CCTA) Hong Kong, China, August 19-21, 2019 PB - IEEE CY - New York ER - TY - CHAP A1 - Kahmann, Stephanie Lucina A1 - Uschok, Stephan A1 - Wegmann, Kilian A1 - Müller, Lars-P. A1 - Staat, Manfred T1 - Biomechanical multibody model with refined kinematics of the elbow T2 - 6th European Conference on Computational Mechanics (ECCM 6), 7th European Conference on Computational Fluid Dynamics (ECFD 7), 11-15 June 2018, Glasgow, UK N2 - The overall objective of this study is to develop a new external fixator, which closely maps the native kinematics of the elbow to decrease the joint force resulting in reduced rehabilitation time and pain. An experimental setup was designed to determine the native kinematics of the elbow during flexion of cadaveric arms. As a preliminary study, data from literature was used to modify a published biomechanical model for the calculation of the joint and muscle forces. They were compared to the original model and the effect of the kinematic refinement was evaluated. Furthermore, the obtained muscle forces were determined in order to apply them in the experimental setup. The joint forces in the modified model differed slightly from the forces in the original model. The muscle force curves changed particularly for small flexion angles but their magnitude for larger angles was consistent. Y1 - 2018 ER - TY - CHAP A1 - Kahmann, Stephanie A1 - Hackl, Michael A1 - Wegmann, Kilian A1 - Müller, Lars-Peter A1 - Staat, Manfred ED - Erni, Daniel T1 - Impact of a proximal radial shortening osteotomy on the distribution of forces and the stability of the elbow T2 - 1st YRA MedTech Symposium 2016 : April 8th / 2016 / University of Duisburg-Essen N2 - The human arm consists of the humerus (upper arm), the medial ulna and the lateral radius (forearm). The joint between the humerus and the ulna is called humeroulnar joint and the joint between the humerus and the radius is called humeroradial joint. Lateral and medial collateral ligaments stabilize the elbow. Statistically, 2.5 out of 10,000 people suffer from radial head fractures [1]. In these fractures the cartilage is often affected. Caused by the injured cartilage, degenerative diseases like posttraumatic arthrosis may occur. The resulting pain and reduced range of motion have an impact on the patient’s quality of life. Until now, there has not been a treatment which allows typical loads in daily life activities and offers good long-term results. A new surgical approach was developed with the motivation to reduce the progress of the posttraumatic arthrosis. Here, the radius is shortened by 3 mm in the proximal part [2]. By this means, the load of the radius is intended to be reduced due to a load shift to the ulna. Since the radius is the most important stabilizer of the elbow it has to be confirmed that the stability is not affected. In the first test (Fig. 1 left), pressure distributions within the humeroulnar and humeroradial joints a native and a shortened radius were measured using resistive pressure sensors (I5076 and I5027, Tekscan, USA). The humerus was loaded axially in a tension testing machine (Z010, Zwick Roell, Germany) in 50 N steps up to 400 N. From the humerus the load is transmitted through both the radius and the ulna into the hand which is fixed on the ground. In the second test (Fig. 1 right), the joint stability was investigated using a digital image correlation system to measure the displacement of the ulna. Here, the humerus is fixed with a desired flexion angle and the unconstrained forearm lies on the ground. A rope connects the load actuator with a hook fixed in the ulna. A guide roller is used so that the rope pulls the ulna horizontally when a tensile load is applied. This creates a moment about the elbow joint with a maximum value of 7.5 Nm. Measurements were performed with varying flexion angles (0°, 30°, 60°, 90°, 120°). For both tests and each measurement, seven specimens were used. Student ́s t-test was employed to determine whether the mean values of the measurements in native specimen and operated specimens differ significantly. Y1 - 2016 U6 - http://dx.doi.org/10.17185/duepublico/40821 SP - 7 EP - 8 PB - Universität Duisburg-Essen CY - Duisburg ER - TY - CHAP A1 - Jung, Alexander A1 - Staat, Manfred A1 - Müller, Wolfram T1 - Effect of wind on flight style optimisation in ski jumping T2 - 15th International Symposium on Computer Simulation in Biomechanics ; July 9th-11th 2015, Edinburgh, UK Y1 - 2016 SP - 53 EP - 54 PB - The University of Edinburgh ; Loughborough University CY - Edinburgh ER - TY - CHAP A1 - Jung, Alexander A1 - Staat, Manfred ED - Erni, Daniel T1 - Computing olympic gold: Ski jumping as an example T2 - 1st YRA MedTech Symposium 2016 : April 8th / 2016 / University of Duisburg-Essen Y1 - 2016 SN - 978-3-940402-06-6 U6 - http://dx.doi.org/10.17185/duepublico/40821 SP - 54 EP - 55 PB - Universität Duisburg-Essen CY - Duisburg 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 - http://dx.doi.org/10.3390/proceedings1040505 N1 - Eurosensors 2017 Conference, Paris, France, 3–6 September 2017 VL - 1 IS - 4 ER - TY - CHAP A1 - Jabbari, Medisa A1 - Bhattarai, Aroj A1 - Anding, Ralf A1 - Staat, Manfred ED - Erni, Daniel ED - Fischerauer, Alice ED - Himmel, Jörg ED - Seeger, Thomas ED - Thelen, Klaus T1 - Biomechanical simulation of different prosthetic meshes for repairing uterine/vaginal vault prolapse T2 - 2nd YRA MedTech Symposium 2017 : June 8th - 9th / 2017 / Hochschule Ruhr-West Y1 - 2017 SN - 978-3-9814801-9-1 U6 - http://dx.doi.org/10.17185/duepublico/43984 N1 - A young researchers track of the 7th IEEE Workshop & SENSORICA 2017 SP - 118 EP - 119 PB - Universität Duisburg-Essen CY - Duisburg ER -