@inproceedings{BornheimGriegerBialonski2021,
  author    = {Bornheim, Tobias and Grieger, Niklas and Bialonski, Stephan},
  title     = {FHAC at GermEval 2021: Identifying German toxic, engaging, and fact-claiming comments with ensemble learning},
  series = {Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021},
  booktitle = {Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021},
  publisher = {Heinrich Heine University},
  address   = {D{\"u}sseldorf},
  doi       = {10.48415/2021/fhw5-x128},
  pages     = {105 -- 111},
  year      = {2021},
  language  = {en}
}
@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{TranStaat2021,
  author    = {Tran, Ngoc Trinh and Staat, Manfred},
  title     = {FEM shakedown analysis of Kirchhoff-Love plates under uncertainty of strength},
  series = {Proceedings of UNCECOMP 2021},
  booktitle = {Proceedings of UNCECOMP 2021},
  isbn      = {978-618-85072-6-5},
  doi       = {10.7712/120221.8041.19047},
  pages     = {323 -- 338},
  year      = {2021},
  abstract  = {A new formulation to calculate the shakedown limit load of Kirchhoff plates under stochastic conditions of strength is developed. Direct structural reliability design by chance con-strained programming is based on the prescribed failure probabilities, which is an effective approach of stochastic programming if it can be formulated as an equivalent deterministic optimization problem. We restrict uncertainty to strength, the loading is still deterministic. A new formulation is derived in case of random strength with lognormal distribution. Upper bound and lower bound shakedown load factors are calculated simultaneously by a dual algorithm.},
  language  = {en}
}
@inproceedings{IomdinaKiselevaKotliaretal.2020,
  author    = {Iomdina, Elena N. and Kiseleva, Anna A. and Kotliar, Konstantin and Luzhnov, Petr V.},
  title     = {Quantification of Choroidal Blood Flow Using the OCT-A System Based on Voxel Scan Processing},
  series = {Proceedings of the International Conference on Biomedical Innovations and Applications- BIA 2020},
  booktitle = {Proceedings of the International Conference on Biomedical Innovations and Applications- BIA 2020},
  publisher = {IEEE},
  address   = {New York, NY},
  isbn      = {978-1-7281-7073-2},
  doi       = {10.1109/BIA50171.2020.9244511},
  pages     = {41 -- 44},
  year      = {2020},
  abstract  = {The paper presents a method for the quantitative assessment of choroidal blood flow using an OCT-A system. The developed technique for processing of OCT-A scans is divided into two stages. At the first stage, the identification of the boundaries in the selected portion was performed. At the second stage, each pixel mark on the selected layer was represented as a volume unit, a voxel, which characterizes the region of moving blood. Three geometric shapes were considered to represent the voxel. On the example of one OCT-A scan, this work presents a quantitative assessment of the blood flow index. A possible modification of two-stage algorithm based on voxel scan processing is presented.},
  language  = {en}
}
@inproceedings{SildatkeKarwanniKraftetal.2020,
  author    = {Sildatke, Michael and Karwanni, Hendrik and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert},
  title     = {Automated Software Quality Monitoring in Research Collaboration Projects},
  series = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops},
  booktitle = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1145/3387940.3391478},
  pages     = {603 -- 610},
  year      = {2020},
  abstract  = {In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem. Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ. Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible. In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production. Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.},
  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{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{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{SavitskayaKistaubayevaAkimbekovetal.2013,
  author    = {Savitskaya, Irina S. and Kistaubayeva, Aida S. and Akimbekov, Nuraly S. and Digel, Ilya and Zhubanova, Azhar A.},
  title     = {Performance of Bio-Composite Carbonized Materials in Probiotic Applications},
  series = {World Academy of Science, Engineering and Technology International Journal of Biotechnology and Bioengineering},
  volume    = {7},
  booktitle = {World Academy of Science, Engineering and Technology International Journal of Biotechnology and Bioengineering},
  number    = {7},
  pages     = {685 -- 689},
  year      = {2013},
  language  = {en}
}