@inproceedings{DigelDemirciTrzewiketal.2004, author = {Digel, Ilya and Demirci, Taylan and Trzewik, J{\"u}rgen and Linder, Peter and Temiz Artmann, Ayseg{\"u}l}, title = {Fibroblast response to mechanical stress: role of the adhesion substrate : [abstract]}, year = {2004}, abstract = {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.}, subject = {Fibroblast}, language = {en} } @inproceedings{HafnerOchsWeickertetal.2016, author = {Hafner, David and Ochs, Peter and Weickert, Joachim and Reißel, Martin}, title = {FSI Schemes : Fast Semi-Iterative Solvers for PDEs and Optimisation Methods}, series = {Pattern Recognition : 38th German Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings}, booktitle = {Pattern Recognition : 38th German Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings}, editor = {Rosenhahn, Bodo}, publisher = {Springer}, isbn = {978-3-319-45886-1}, doi = {10.1007/978-3-319-45886-1_8}, pages = {91 -- 102}, year = {2016}, language = {de} } @inproceedings{SchreiberKraftZuendorf2018, author = {Schreiber, Marc and Kraft, Bodo and Z{\"u}ndorf, Albert}, title = {NLP Lean Programming Framework: Developing NLP Applications More Effectively}, series = {Proceedings of NAACL-HLT 2018: Demonstrations, New Orleans, Louisiana, June 2 - 4, 2018}, booktitle = {Proceedings of NAACL-HLT 2018: Demonstrations, New Orleans, Louisiana, June 2 - 4, 2018}, doi = {10.18653/v1/N18-5001 }, pages = {5 Seiten}, year = {2018}, abstract = {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.}, language = {en} } @inproceedings{SchmidtsKraftSiebigterothetal.2019, author = {Schmidts, Oliver and Kraft, Bodo and Siebigteroth, Ines and Z{\"u}ndorf, Albert}, title = {Schema Matching with Frequent Changes on Semi-Structured Input Files: A Machine Learning Approach on Biological Product Data}, series = {Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS}, booktitle = {Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS}, isbn = {978-989-758-372-8}, doi = {10.5220/0007723602080215}, pages = {208 -- 215}, year = {2019}, language = {en} } @inproceedings{EschlerWozniakRichteretal.2019, author = {Eschler, Eric and Wozniak, Felix and Richter, Christoph and Drechsler, Klaus}, title = {Materialanalyse an lokal verst{\"a}rkten Triaxialgeflechten}, series = {Leichtbau in Forschung und industrieller Anwendung von der Nano- bis zur Makroebene, LLC, Landshuter Leichtbau-Colloquium, 9}, booktitle = {Leichtbau in Forschung und industrieller Anwendung von der Nano- bis zur Makroebene, LLC, Landshuter Leichtbau-Colloquium, 9}, publisher = {Leichtbau Cluster}, address = {Landshut}, isbn = {978-3-9818439-2-7}, pages = {120 -- 131}, year = {2019}, language = {de} } @inproceedings{OlderogMohrBegingetal.2021, author = {Olderog, M. and Mohr, P. and Beging, Stefan and Tsoumpas, C. and Ziemons, Karl}, title = {Simulation study on the role of tissue-scattered events in improving sensitivity for a compact time of flight compton positron emission tomograph}, series = {2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)}, booktitle = {2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)}, publisher = {IEEE}, address = {New York, NY}, isbn = {978-1-7281-7693-2}, doi = {10.1109/NSS/MIC42677.2020.9507901}, pages = {4 Seiten}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{KolditzAlbinAlbrachtetal.2016, author = {Kolditz, Melanie and Albin, Thivaharan and Albracht, Kirsten and Br{\"u}ggemann, Gert-Peter and Abel, Dirk}, title = {Isokinematic leg extension training with an industrial robot}, series = {6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) June 26-29, 2016. UTown, Singapore}, booktitle = {6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) June 26-29, 2016. UTown, Singapore}, doi = {10.1109/BIOROB.2016.7523750}, pages = {950 -- 955}, year = {2016}, language = {de} } @inproceedings{SchreiberKraftZuendorf2017, author = {Schreiber, Marc and Kraft, Bodo and Z{\"u}ndorf, Albert}, title = {Metrics Driven Research Collaboration: Focusing on Common Project Goals Continuously}, series = {39th International Conference on Software Engineering, May 20-28, 2017 - Buenos Aires, Argentina}, booktitle = {39th International Conference on Software Engineering, May 20-28, 2017 - Buenos Aires, Argentina}, pages = {8 Seiten}, year = {2017}, abstract = {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.}, language = {en} } @inproceedings{SchmidtsBoltesKraftetal.2017, author = {Schmidts, Oliver and Boltes, Maik and Kraft, Bodo and Schreiber, Marc}, title = {Multi-pedestrian tracking by moving Bluetooth-LE beacons and stationary receivers}, series = {2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 18-21 September 2017, Sapporo, Japan}, booktitle = {2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 18-21 September 2017, Sapporo, Japan}, pages = {1 -- 4}, year = {2017}, language = {en} } @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{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} } @inproceedings{OberlaenderArreolaHansenetal.2017, author = {Oberl{\"a}nder, Jan and Arreola, Julio and Hansen, Christina and Greeff, Anton and Mayer, Marlena and Keusgen, Michael and Sch{\"o}ning, Michael Josef}, title = {Impedimetric Biosensor to Enable Fast Evaluation of Gaseous Sterilization Processes}, series = {MDPI Proceedings}, volume = {1}, booktitle = {MDPI Proceedings}, number = {4}, doi = {10.3390/proceedings1040435}, pages = {4 Seiten}, year = {2017}, language = {en} } @inproceedings{BreuerGuthmannSchoeningetal.2017, author = {Breuer, Lars and Guthmann, Eric and Sch{\"o}ning, Michael Josef and Thoelen, Ronald and Wagner, Torsten}, title = {Light-Stimulated Hydrogels with Incorporated Graphene Oxide as Actuator Material for Flow Control in Microfluidic Applications}, series = {Proceedings Eurosensors 2017 Conference, Paris, France, 3-6 September 2017}, booktitle = {Proceedings Eurosensors 2017 Conference, Paris, France, 3-6 September 2017}, doi = {10.3390/proceedings1040524}, pages = {1 -- 4}, year = {2017}, language = {en} } @inproceedings{SiebigterothKraftSchmidtsetal.2019, author = {Siebigteroth, Ines and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert}, title = {A Study on Improving Corpus Creation by Pair Annotation}, series = {Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019)}, booktitle = {Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019)}, issn = {1613-0073}, pages = {40 -- 44}, year = {2019}, language = {en} } @inproceedings{SchmidtsKraftWinkensetal.2020, author = {Schmidts, Oliver and Kraft, Bodo and Winkens, Marvin and Z{\"u}ndorf, Albert}, title = {Catalog integration of low-quality product data by attribute label ranking}, series = {Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1}, booktitle = {Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1}, publisher = {SciTePress}, address = {Set{\´u}bal, Portugal}, isbn = {978-989-758-440-4}, doi = {10.5220/0009831000900101}, pages = {90 -- 101}, year = {2020}, abstract = {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.}, language = {en} } @inproceedings{MandekarJentschLutzetal.2021, author = {Mandekar, Swati and Jentsch, Lina and Lutz, Kai and Behbahani, Mehdi and Melnykowycz, Mark}, title = {Earable design analysis for sleep EEG measurements}, series = {UbiComp '21}, booktitle = {UbiComp '21}, doi = {10.1145/3460418.3479328}, pages = {171 -- 175}, year = {2021}, abstract = {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).}, language = {en} } @inproceedings{KloeserKohlKraftetal.2021, author = {Kl{\"o}ser, Lars and Kohl, Philipp and Kraft, Bodo and Z{\"u}ndorf, Albert}, title = {Multi-attribute relation extraction (MARE): simplifying the application of relation extraction}, series = {Proceedings of the 2nd International Conference on Deep Learning Theory and Applications DeLTA - Volume 1}, booktitle = {Proceedings of the 2nd International Conference on Deep Learning Theory and Applications DeLTA - Volume 1}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-526-5}, doi = {10.5220/0010559201480156}, pages = {148 -- 156}, year = {2021}, abstract = {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.}, language = {en} }