@inproceedings{SchmidtsKraftWinkensetal.2021, author = {Schmidts, Oliver and Kraft, Bodo and Winkens, Marvin and Z{\"u}ndorf, Albert}, title = {Catalog integration of heterogeneous and volatile product data}, series = {DATA 2020: Data Management Technologies and Applications}, booktitle = {DATA 2020: Data Management Technologies and Applications}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-83013-7}, doi = {10.1007/978-3-030-83014-4_7}, pages = {134 -- 153}, year = {2021}, abstract = {The integration of frequently changing, volatile product data from different manufacturers into a single catalog is a significant challenge for small and medium-sized e-commerce companies. They rely on timely integrating product data to present them aggregated in an online shop without knowing format specifications, concept understanding of manufacturers, and data quality. Furthermore, format, concepts, and data quality may change at any time. Consequently, integrating product catalogs into a single standardized catalog is often a laborious manual task. Current strategies to streamline or automate catalog integration use techniques based on machine learning, word vectorization, or semantic similarity. However, most approaches struggle with low-quality or real-world data. We propose Attribute Label Ranking (ALR) as a recommendation engine to simplify the integration process of previously unknown, proprietary tabular format into a standardized catalog for practitioners. We evaluate ALR by focusing on the impact of different neural network architectures, language features, and semantic similarity. Additionally, we consider metrics for industrial application and present the impact of ALR in production and its limitations.}, language = {en} } @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{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{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{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{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{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{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{KetelhutGoellBraunsteinetal.2019, author = {Ketelhut, Maike and G{\"o}ll, Fabian and Braunstein, Bjoern and Albracht, Kirsten and Abel, Dirk}, title = {Iterative learning control of an industrial robot for neuromuscular training}, series = {2019 IEEE Conference on Control Technology and Applications}, booktitle = {2019 IEEE Conference on Control Technology and Applications}, publisher = {IEEE}, address = {New York}, isbn = {978-1-7281-2767-5 (ePub)}, doi = {10.1109/CCTA.2019.8920659}, pages = {7 Seiten}, year = {2019}, abstract = {Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.}, language = {en} } @inproceedings{HunkerJungGossmannetal.2019, author = {Hunker, Jan and Jung, Alexander and Goßmann, Matthias and Linder, Peter and Staat, Manfred}, title = {Development of a tool to analyze the conduction speed in microelectrode array measurements of cardiac tissue}, 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 = {7 -- 8}, year = {2019}, abstract = {The discovery of human induced pluripotent stem cells reprogrammed from somatic cells [1] and their ability to differentiate into cardiomyocytes (hiPSC-CMs) has provided a robust platform for drug screening [2]. Drug screenings are essential in the development of new components, particularly for evaluating the potential of drugs to induce life-threatening pro-arrhythmias. Between 1988 and 2009, 14 drugs have been removed from the market for this reason [3]. The microelectrode array (MEA) technique is a robust tool for drug screening as it detects the field potentials (FPs) for the entire cell culture. Furthermore, the propagation of the field potential can be examined on an electrode basis. To analyze MEA measurements in detail, we have developed an open-source tool.}, 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} } @inproceedings{RamanJungHorvathetal.2019, author = {Raman, Aravind Hariharan and Jung, Alexander and Horv{\´a}th, Andr{\´a}s and Becker, Nadine and Staat, Manfred}, title = {Modification of a computer model of human stem cell-derived cardiomyocyte electrophysiology based on Patch-Clamp measurements}, 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 = {10 -- 11}, year = {2019}, abstract = {Human induced pluripotent stem cells (hiPSCs) have shown to be promising in disease studies and drug screenings [1]. Cardiomyocytes derived from hiPSCs have been extensively investigated using patch-clamping and optical methods to compare their electromechanical behaviour relative to fully matured adult cells. Mathematical models can be used for translating findings on hiPSCCMs to adult cells [2] or to better understand the mechanisms of various ion channels when a drug is applied [3,4]. Paci et al. (2013) [3] developed the first model of hiPSC-CMs, which they later refined based on new data [3]. The model is based on iCells® (Fujifilm Cellular Dynamics, Inc. (FCDI), Madison WI, USA) but major differences among several cell lines and even within a single cell line have been found and motivate an approach for creating sample-specific models. We have developed an optimisation algorithm that parameterises the conductances (in S/F=Siemens/Farad) of the latest Paci et al. model (2018) [5] using current-voltage data obtained in individual patch-clamp experiments derived from an automated patch clamp system (Patchliner, Nanion Technologies GmbH, Munich).}, language = {en} } @inproceedings{BayerHeschelerArtmannetal.2019, author = {Bayer, Robin and Hescheler, J{\"u}rgen and Artmann, Gerhard and Temiz Artmann, Ayseg{\"u}l}, title = {Treating arterial hypertension in a cell culture well}, series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH AachenW}, booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH AachenW}, 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 = {5 -- 6}, year = {2019}, abstract = {Hypertension describes the pathological increase of blood pressure, which is most commonly associated with the increase of vascular wall stiffness [1]. Referring to the "Deutsche Bluthochdruck Liga" this pathology shows a growing trend in our aging society. In order to find novel pharmacological and probably personalized treatments, we want to present a functional approach to study biomechanical properties of a human aortic vascular model. In this method review we will give an overview of recent studies which were carried out with the CellDrum technology [2] and underline the added value to already existing standard procedures known from the field of physiology. Herein described CellDrum technology is a system to measure functional mechanical properties of cell monolayers and thin tissue constructs in-vitro. Additionally, the CellDrum enables to elucidate the mechanical response of cells to pharmacological drugs, toxins and vasoactive agents. Due to its highly flexible polymer support, cells can also be mechanically stimulated by steady and cyclic biaxial stretching.}, 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{BhattaraiStaat2018, author = {Bhattarai, Aroj and Staat, Manfred}, title = {Pectopexy to repair vaginal vault prolapse: a finite element approach}, series = {Proceedings CMBBE 2018}, booktitle = {Proceedings CMBBE 2018}, editor = {Fernandes, P.R. and Tavares, J. M.}, year = {2018}, abstract = {The vaginal prolapse after hysterectomy (removal of the uterus) is often associated with the prolapse of the vaginal vault, rectum, bladder, urethra or small bowel. Minimally invasive surgery such as laparoscopic sacrocolpopexy and pectopexy are widely performed for the treatment of the vaginal prolapse with weakly supported vaginal vault after hysterectomy using prosthetic mesh implants to support (or strengthen) lax apical ligaments. Implants of different shape, size and polymers are selected depending on the patient's anatomy and the surgeon's preference. In this computational study on pectopexy, DynaMesh®-PRP soft, GYNECARE GYNEMESH® PS Nonabsorbable PROLENE® soft and Ultrapro® are tested in a 3D finite element model of the female pelvic floor. The mesh model is implanted into the extraperitoneal space and sutured to the vaginal stump with a bilateral fixation to the iliopectineal ligament at both sides. Numerical simulations are conducted at rest, after surgery and during Valsalva maneuver with weakened tissues modeled by reduced tissue stiffness. Tissues and prosthetic meshes are modeled as incompressible, isotropic hyperelastic materials. The positions of the organs are calculated with respect to the pubococcygeal line (PCL) for female pelvic floor at rest, after repair and during Valsalva maneuver using the three meshes.}, language = {en} } @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{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} }