@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} } @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{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{BlumAlbannaBenninghausetal.2019, author = {Blum, Yannik and Albanna, Walid and Benninghaus, Anne and Kotliar, Konstantin}, title = {Vasomotion in retinal vessels of patients presenting post hemorrhagic hydrocephalus following subarachnoid hemorrhage}, series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen}, booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen}, editor = {Staat, Manfred and Erni, Daniel}, publisher = {Universit{\"a}t Duisburg-Essen}, address = {Duisburg}, organization = {MedTech Symposium}, isbn = {978-3-940402-22-6}, doi = {10.17185/duepublico/48750}, pages = {38 -- 39}, year = {2019}, abstract = {Clearance of blood components and fluid drainage play a crucial role in subarachnoid hemorrhage (SAH) and post hemorrhagic hydrocephalus (PHH). With the involvement of interstitial fluid (ISF) and cerebrospinal fluid (CSF), two pathways for the clearance of fluid and solutes in the brain are proposed. Starting at the level of capillaries, flow of ISF follows along the basement membranes in the walls of cerebral arteries out of the parenchyma to drain into the lymphatics and CSF [1]-[3]. Conversely, it is shown that CSF enters the parenchyma between glial and pial basement membranes of penetrating arteries [4]-[6]. Nevertheless, the involved structures and the contribution of either flow pathway to fluid balance between the subarachnoid space and interstitial space remains controversial. Low frequency oscillations in vascular tone are referred to as vasomotion and corresponding vasomotion waves are modeled as the driving force for flow of ISF out of the parenchyma [7]. Retinal vessel analysis (RVA) allows non-invasive measurement of retinal vessel vasomotion with respect to diameter changes [8]. Thus, the aim of the study is to investigate vasomotion in RVA signals of SAH and PHH patients.}, language = {en} } @inproceedings{ZingsheimGrimmerOrtneretal.2019, author = {Zingsheim, Jonas and Grimmer, Timo and Ortner, Marion and Schmaderer, Christoph and Hauser, Christine and Kotliar, Konstantin}, title = {Recognition of subjects with mild cognitive impairment (MCI) by the use of retinal arterial vessels.}, series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen}, booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen}, editor = {Staat, Manfred and Erni, Daniel}, publisher = {Universit{\"a}t Duisburg-Essen}, address = {Duisburg}, organization = {MedTech Symposium}, isbn = {978-3-940402-22-6}, doi = {10.17185/duepublico/48750}, pages = {36 -- 37}, year = {2019}, language = {en} } @inproceedings{AzarDigel2019, author = {Azar, Fouad and Digel, Ilya}, title = {Utilization of fluorescence spectroscopy and neural networks in clinical analysis}, series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen}, booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen}, editor = {Staat, Manfred and Erni, Daniel}, publisher = {Universit{\"a}t Duisburg-Essen}, address = {Duisburg}, organization = {MedTech Symposium}, isbn = {978-3-940402-22-6}, doi = {10.17185/duepublico/48750}, pages = {40 -- 41}, year = {2019}, abstract = {Fluorescence topography of human urine in combination with learning algorithms can provide a variant pattern recognition method in analytical clinical chemistry and, eventually, diagnosis.}, language = {en} }