TY - CHAP A1 - Digel, Ilya A1 - Demirci, Taylan A1 - Trzewik, Jürgen A1 - Linder, Peter A1 - Temiz Artmann, Aysegül T1 - Fibroblast response to mechanical stress: role of the adhesion substrate : [abstract] N2 - Mechanical stimulation of the cells resulted in evident changes in the cell morphology, protein composition and gene expression. Microscopically, additional formation of stress fibers accompanied by cell re-arrangements in a monolayer was observed. Also, significant activation of p53 gene was revealed as compared to control. Interestingly, the use of CellTech membrane coating induced cell death after mechanical stress had been applied. Such an effect was not detected when fibronectin had been used as an adhesion substrate. KW - Fibroblast KW - Mechanische Beanspruchung KW - celldrum technology Y1 - 2004 ER - TY - CHAP A1 - Hafner, David A1 - Ochs, Peter A1 - Weickert, Joachim A1 - Reißel, Martin ED - Rosenhahn, Bodo T1 - FSI Schemes : Fast Semi-Iterative Solvers for PDEs and Optimisation Methods T2 - Pattern Recognition : 38th German Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings Y1 - 2016 SN - 978-3-319-45886-1 U6 - https://doi.org/10.1007/978-3-319-45886-1_8 N1 - Lecture Notes in Computer Science; Vol. 9796 SP - 91 EP - 102 PB - Springer ER - TY - CHAP A1 - Schreiber, Marc A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - NLP Lean Programming Framework: Developing NLP Applications More Effectively T2 - Proceedings of NAACL-HLT 2018: Demonstrations, New Orleans, Louisiana, June 2 - 4, 2018 N2 - This paper presents NLP Lean Programming framework (NLPf), a new framework for creating custom natural language processing (NLP) models and pipelines by utilizing common software development build systems. This approach allows developers to train and integrate domain-specific NLP pipelines into their applications seamlessly. Additionally, NLPf provides an annotation tool which improves the annotation process significantly by providing a well-designed GUI and sophisticated way of using input devices. Due to NLPf’s properties developers and domain experts are able to build domain-specific NLP applications more efficiently. NLPf is Opensource software and available at https:// gitlab.com/schrieveslaach/NLPf. Y1 - 2018 U6 - https://doi.org/10.18653/v1/N18-5001  ER - TY - CHAP A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Siebigteroth, Ines A1 - Zündorf, Albert T1 - Schema Matching with Frequent Changes on Semi-Structured Input Files: A Machine Learning Approach on Biological Product Data T2 - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS Y1 - 2019 SN - 978-989-758-372-8 U6 - https://doi.org/10.5220/0007723602080215 SP - 208 EP - 215 ER - TY - CHAP A1 - Eschler, Eric A1 - Wozniak, Felix A1 - Richter, Christoph A1 - Drechsler, Klaus T1 - Materialanalyse an lokal verstärkten Triaxialgeflechten T2 - Leichtbau in Forschung und industrieller Anwendung von der Nano- bis zur Makroebene, LLC, Landshuter Leichtbau-Colloquium, 9 Y1 - 2019 SN - 978-3-9818439-2-7 SP - 120 EP - 131 PB - Leichtbau Cluster CY - Landshut ER - TY - CHAP A1 - Olderog, M. A1 - Mohr, P. A1 - Beging, Stefan A1 - Tsoumpas, C. A1 - Ziemons, Karl T1 - Simulation study on the role of tissue-scattered events in improving sensitivity for a compact time of flight compton positron emission tomograph T2 - 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) N2 - In positron emission tomography improving time, energy and spatial detector resolutions and using Compton kinematics introduces the possibility to reconstruct a radioactivity distribution image from scatter coincidences, thereby enhancing image quality. The number of single scattered coincidences alone is in the same order of magnitude as true coincidences. In this work, a compact Compton camera module based on monolithic scintillation material is investigated as a detector ring module. The detector interactions are simulated with Monte Carlo package GATE. The scattering angle inside the tissue is derived from the energy of the scattered photon, which results in a set of possible scattering trajectories or broken line of response. The Compton kinematics collimation reduces the number of solutions. Additionally, the time of flight information helps localize the position of the annihilation. One of the questions of this investigation is related to how the energy, spatial and temporal resolutions help confine the possible annihilation volume. A comparison of currently technically feasible detector resolutions (under laboratory conditions) demonstrates the influence on this annihilation volume and shows that energy and coincidence time resolution have a significant impact. An enhancement of the latter from 400 ps to 100 ps leads to a smaller annihilation volume of around 50%, while a change of the energy resolution in the absorber layer from 12% to 4.5% results in a reduction of 60%. The inclusion of single tissue-scattered data has the potential to increase the sensitivity of a scanner by a factor of 2 to 3 times. The concept can be further optimized and extended for multiple scatter coincidences and subsequently validated by a reconstruction algorithm. Y1 - 2021 SN - 978-1-7281-7693-2 U6 - https://doi.org/10.1109/NSS/MIC42677.2020.9507901 N1 - 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 31 Oct.-7 Nov. 2020, Boston, MA, USA PB - IEEE CY - New York, NY 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 - https://doi.org/10.1109/BIOROB.2016.7523750 SP - 950 EP - 955 ER - TY - CHAP A1 - Schreiber, Marc A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Metrics Driven Research Collaboration: Focusing on Common Project Goals Continuously T2 - 39th International Conference on Software Engineering, May 20-28, 2017 - Buenos Aires, Argentina N2 - Research collaborations provide opportunities for both practitioners and researchers: practitioners need solutions for difficult business challenges and researchers are looking for hard problems to solve and publish. Nevertheless, research collaborations carry the risk that practitioners focus on quick solutions too much and that researchers tackle theoretical problems, resulting in products which do not fulfill the project requirements. In this paper we introduce an approach extending the ideas of agile and lean software development. It helps practitioners and researchers keep track of their common research collaboration goal: a scientifically enriched software product which fulfills the needs of the practitioner’s business model. This approach gives first-class status to application-oriented metrics that measure progress and success of a research collaboration continuously. Those metrics are derived from the collaboration requirements and help to focus on a commonly defined goal. An appropriate tool set evaluates and visualizes those metrics with minimal effort, and all participants will be pushed to focus on their tasks with appropriate effort. Thus project status, challenges and progress are transparent to all research collaboration members at any time. Y1 - 2017 N1 - Software Engineering in Practice (SEIP). ICSE2017 Vorabversion der Autoren ER - 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 - 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 - TY - CHAP A1 - Oberländer, Jan A1 - Arreola, Julio A1 - Hansen, Christina A1 - Greeff, Anton A1 - Mayer, Marlena A1 - Keusgen, Michael A1 - Schöning, Michael Josef T1 - Impedimetric Biosensor to Enable Fast Evaluation of Gaseous Sterilization Processes T2 - MDPI Proceedings Y1 - 2017 U6 - https://doi.org/10.3390/proceedings1040435 N1 - Eurosensors 2017 Conference, Paris, France, 3–6 September 2017 VL - 1 IS - 4 ER - TY - CHAP A1 - Breuer, Lars A1 - Guthmann, Eric A1 - Schöning, Michael Josef A1 - Thoelen, Ronald A1 - Wagner, Torsten T1 - Light-Stimulated Hydrogels with Incorporated Graphene Oxide as Actuator Material for Flow Control in Microfluidic Applications T2 - Proceedings Eurosensors 2017 Conference, Paris, France, 3–6 September 2017 Y1 - 2017 U6 - https://doi.org/10.3390/proceedings1040524 SP - 1 EP - 4 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 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Winkens, Marvin A1 - Zündorf, Albert T1 - Catalog integration of low-quality product data by attribute label ranking T2 - Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1 N2 - The integration of product data from heterogeneous sources and manufacturers into a single catalog is often still a laborious, manual task. Especially small- and medium-sized enterprises face the challenge of timely integrating the data their business relies on to have an up-to-date product catalog, due to format specifications, low quality of data and the requirement of expert knowledge. Additionally, modern approaches to simplify catalog integration demand experience in machine learning, word vectorization, or semantic similarity that such enterprises do not have. Furthermore, most approaches struggle with low-quality data. We propose Attribute Label Ranking (ALR), an easy to understand and simple to adapt learning approach. ALR leverages a model trained on real-world integration data to identify the best possible schema mapping of previously unknown, proprietary, tabular format into a standardized catalog schema. Our approach predicts multiple labels for every attribute of an inpu t column. The whole column is taken into consideration to rank among these labels. We evaluate ALR regarding the correctness of predictions and compare the results on real-world data to state-of-the-art approaches. Additionally, we report findings during experiments and limitations of our approach. Y1 - 2020 SN - 978-989-758-440-4 U6 - https://doi.org/10.5220/0009831000900101 N1 - 9th International Conference on Data Science, Technologies and Applications (DATA 2020), 7 - 9 July 2020, online SP - 90 EP - 101 PB - SciTePress CY - Setúbal, Portugal ER - TY - CHAP A1 - Mandekar, Swati A1 - Jentsch, Lina A1 - Lutz, Kai A1 - Behbahani, Mehdi A1 - Melnykowycz, Mark T1 - Earable design analysis for sleep EEG measurements T2 - UbiComp '21 N2 - Conventional EEG devices cannot be used in everyday life and hence, past decade research has been focused on Ear-EEG for mobile, at-home monitoring for various applications ranging from emotion detection to sleep monitoring. As the area available for electrode contact in the ear is limited, the electrode size and location play a vital role for an Ear-EEG system. In this investigation, we present a quantitative study of ear-electrodes with two electrode sizes at different locations in a wet and dry configuration. Electrode impedance scales inversely with size and ranges from 450 kΩ to 1.29 MΩ for dry and from 22 kΩ to 42 kΩ for wet contact at 10 Hz. For any size, the location in the ear canal with the lowest impedance is ELE (Left Ear Superior), presumably due to increased contact pressure caused by the outer-ear anatomy. The results can be used to optimize signal pickup and SNR for specific applications. We demonstrate this by recording sleep spindles during sleep onset with high quality (5.27 μVrms). KW - EEG KW - sensors KW - Impedance Spectroscopy KW - Sleep EEG KW - biopotential electrodes Y1 - 2021 U6 - https://doi.org/10.1145/3460418.3479328 N1 - UbiComp '21: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers, September 21–26, 2021, Virtual, USA SP - 171 EP - 175 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 - Volume 1 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 - https://doi.org/10.5220/0010559201480156 N1 - 2nd International Conference on Deep Learning Theory and Applications, DeLTA2021, July 7-9, 2021 SP - 148 EP - 156 PB - SciTePress CY - Setúbal ER -