TY - CHAP A1 - Poghossian, Arshak A1 - Abouzar, Maryam H. A1 - Schöning, Michael Josef ED - Abdelghani, Adnane ED - Schöning, Michael Josef T1 - (Bio-­)chemical sensor array based on nanoplate SOI capacitors T2 - Nanoscale Science and Technology (NS&T´12) : Proceedings Book Humboldt Kolleg ; Tunisia, 17-19 March, 2012 Y1 - 2012 SP - 31 EP - 31 ER - TY - CHAP A1 - Ermelenko, Y. A1 - Yoshinobu, T. A1 - Mourzina, Y. A1 - Schöning, Michael Josef A1 - Vlasov, Y. A1 - Iwasaki, H. T1 - A multisensor based on laser scanned silicon transducer (LSST): development and properties T2 - Eurosensors XVII : the 17th European Conference on Solid-State Transducers ; University of Minho, Guimarães, Portugal, September 21 - 24, 2003 Y1 - 2003 SP - 72 EP - 73 ER - TY - CHAP A1 - Bäcker, Matthias A1 - Koch, C. A1 - Geiger, F. A1 - Eber, F. A1 - Gliemann, H. A1 - Poghossian, Arshak A1 - Schöning, Michael Josef T1 - A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier T2 - Procedia Engineering Y1 - 2016 U6 - http://dx.doi.org/10.1016/j.proeng.2016.11.228 SN - 1877-7058 N1 - Proceedings of the 30th anniversary Eurosensors Conference – Eurosensors 2016, 4-7. Sepember 2016, Budapest, Hungary VL - Vol. 168 SP - 618 EP - 621 ER - TY - CHAP A1 - Tran, Thanh Ngoc A1 - Staat, Manfred ED - Eberhardsteiner, J. T1 - A primal-dual shakedown analysis of 3D structures using the face-based smoothed finite element method T2 - Proceedings European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012) Y1 - 2012 N1 - 6th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012) Vienna, Austria, September 10-14, 2012 ER - TY - CHAP A1 - de Honde, Lukas A1 - Porst, Dariusz A1 - Digel, Ilya ED - Fischerauer, Alice T1 - A randomized, observational thermographic study of the neck region before and after a physiotherapeutic intervention 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 - 122 EP - 123 PB - Universität Duisburg-Essen CY - Duisburg ER - TY - CHAP A1 - Schöning, Michael Josef A1 - Abouzar, Maryam H. A1 - Wagner, Torsten A1 - Näther, Niko A1 - Rolka, David A1 - Yoshinobu, Tatsuo A1 - Kloock, Joachim P. A1 - Turek, Monika A1 - Ingebrandt, Sven A1 - Poghossian, Arshak T1 - A semiconductor-based field-effect platform for (bio-)chemical and physical sensors: From capacitive EIS sensors and LAPS over ISFETs to nano-scale devices T2 - MRS Proceedings Y1 - 2006 U6 - http://dx.doi.org/10.1557/PROC-0952-F08-02 N1 - Vol. 952 - Symposium F - Integrated Nanosensors SP - 1 EP - 9 ER - TY - CHAP A1 - Pham, Phu Tinh A1 - Staat, Manfred T1 - A simplification for shakedown analysis of hardening structures T2 - Conference proceedings of the YIC GACM 2015 : 3rd ECCOMAS Young Investigators Conference and 6th GACM Colloquium on Computational Mechanics , Aachen , Germany, 20.07.2015 - 23.07.2015 / ed.: Stefanie Elgeti ; Jaan-Willem Simon Y1 - 2015 SP - 1 EP - 4 PB - RWTH Aachen University CY - Aachen ER - TY - CHAP A1 - Siebigteroth, Ines A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - A Study on Improving Corpus Creation by Pair Annotation T2 - Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019) Y1 - 2019 SN - 1613-0073 SP - 40 EP - 44 ER - TY - CHAP A1 - Gerhards, Michael A1 - Sander, Volker A1 - Belloum, Adam ED - Zimmermann, Wolf ED - Lee, Yong Woo ED - Demchenko, Yuri T1 - About the flexible Migration of Workflow Tasks to Clouds : Combining on- and off-premise Executions of Applications T2 - CLOUD COMPUTING 2012 : The Third International Conference on Cloud Computing, GRIDs, and Virtualization ; July 22-27, 2012 - Nice, France N2 - An increasing number of applications target their executions on specific hardware like general purpose Graphics Processing Units. Some Cloud Computing providers offer this specific hardware so that organizations can rent such resources. However, outsourcing the whole application to the Cloud causes avoidable costs if only some parts of the application benefit from the specific expensive hardware. A partial execution of applications in the Cloud is a tradeoff between costs and efficiency. This paper addresses the demand for a consistent framework that allows for a mixture of on- and off-premise calculations by migrating only specific parts to a Cloud. It uses the concept of workflows to present how individual workflow tasks can be migrated to the Cloud whereas the remaining tasks are executed on-premise. KW - Workflow Orchestration KW - Workflow KW - Grid Computing KW - Cloud Service Broker KW - Cloud Computing Y1 - 2012 SN - 978-1-61208-216-5 SP - 82 EP - 87 PB - IARIA Journals 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 -