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 - http://dx.doi.org/10.5220/0011271400003269 SN - 2184-285X SP - 83 EP - 94 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 - http://dx.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 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 - http://dx.doi.org/10.5220/0010559201480156 N1 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications, DeLTA2021, July 7-9, 2021 SP - 148 EP - 156 ER - TY - CHAP A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Winkens, Marvin A1 - Zündorf, Albert T1 - Catalog integration of heterogeneous and volatile product data T2 - DATA 2020: Data Management Technologies and Applications N2 - 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. Y1 - 2021 SN - 978-3-030-83013-7 U6 - http://dx.doi.org/10.1007/978-3-030-83014-4_7 N1 - International Conference on Data Management Technologies and Applications, DATA 2020, 7-9 July SP - 134 EP - 153 PB - Springer CY - Cham ER - TY - CHAP A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Klöser, Lars A1 - Werth, Henri A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - STAMP 4 NLP – an agile framework for rapid quality-driven NLP applications development T2 - Quality of Information and Communications Technology. QUATIC 2021 N2 - The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments. KW - Machine learning KW - Process model KW - Natural language processing Y1 - 2021 SN - 978-3-030-85346-4 SN - 978-3-030-85347-1 U6 - http://dx.doi.org/10.1007/978-3-030-85347-1_12 N1 - International Conference on the Quality of Information and Communications Technology, QUATIC 2021, 8-11 September, Algarve, Portugal SP - 156 EP - 166 PB - Springer CY - Cham ER - TY - CHAP A1 - Bornheim, Tobias A1 - Grieger, Niklas A1 - Bialonski, Stephan T1 - FHAC at GermEval 2021: Identifying German toxic, engaging, and fact-claiming comments with ensemble learning T2 - Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021 Y1 - 2021 U6 - http://dx.doi.org/10.48415/2021/fhw5-x128 N1 - SP - 105 EP - 111 PB - Heinrich Heine University CY - Düsseldorf 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 - http://dx.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 ER - TY - CHAP A1 - Tran, Ngoc Trinh A1 - Staat, Manfred T1 - FEM shakedown analysis of Kirchhoff-Love plates under uncertainty of strength T2 - Proceedings of UNCECOMP 2021 N2 - 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. Y1 - 2021 SN - 978-618-85072-6-5 U6 - http://dx.doi.org/10.7712/120221.8041.19047 N1 - Proceedings of UNCECOMP 2021, 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering, streamed from Athens, Greece, 28–30 June 2021. SP - 323 EP - 338 ER - TY - CHAP A1 - Iomdina, Elena N. A1 - Kiseleva, Anna A. A1 - Kotliar, Konstantin A1 - Luzhnov, Petr V. T1 - Quantification of Choroidal Blood Flow Using the OCT-A System Based on Voxel Scan Processing T2 - 2020 International Conference on Biomedical Innovations and Applications (BIA) Y1 - 2020 SN - 978-1-7281-7073-2 U6 - http://dx.doi.org/10.1109/BIA50171.2020.9244511 SP - 41 EP - 44 ER - TY - CHAP A1 - Sildatke, Michael A1 - Karwanni, Hendrik A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - Automated Software Quality Monitoring in Research Collaboration Projects T2 - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Y1 - 2020 U6 - http://dx.doi.org/10.1145/3387940.3391478 SP - 603 EP - 610 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 - Volume 1: DATA Y1 - 2020 SN - 978-989-758-440-4 U6 - http://dx.doi.org/10.5220/0009831000900101 SP - 90 EP - 101 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 - VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 5 Y1 - 2020 SP - 79 EP - 86 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 - 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 - Savitskaya, Irina S. A1 - Kistaubayeva, Aida S. A1 - Akimbekov, Nuraly S. A1 - Digel, Ilya A1 - Zhubanova, Azhar A. T1 - Performance of Bio-Composite Carbonized Materials in Probiotic Applications T2 - World Academy of Science, Engineering and Technology International Journal of Biotechnology and Bioengineering Y1 - 2013 VL - 7 IS - 7 SP - 685 EP - 689 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 - http://dx.doi.org/10.1186/s42162-018-0043-1 N1 - Energy Informatics 2018, Volume 1 Supplement 1 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 - Blum, Yannik A1 - Albanna, Walid A1 - Benninghaus, Anne A1 - Kotliar, Konstantin ED - Staat, Manfred ED - Erni, Daniel T1 - Vasomotion in retinal vessels of patients presenting post hemorrhagic hydrocephalus following subarachnoid hemorrhage T2 - 3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen N2 - 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. Y1 - 2019 SN - 978-3-940402-22-6 U6 - http://dx.doi.org/10.17185/duepublico/48750 SP - 38 EP - 39 PB - Universität Duisburg-Essen CY - Duisburg ER - TY - CHAP A1 - Zingsheim, Jonas A1 - Grimmer, Timo A1 - Ortner, Marion A1 - Schmaderer, Christoph A1 - Hauser, Christine A1 - Kotliar, Konstantin ED - Staat, Manfred ED - Erni, Daniel T1 - Recognition of subjects with mild cognitive impairment (MCI) by the use of retinal arterial vessels. T2 - 3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen Y1 - 2019 SN - 978-3-940402-22-6 U6 - http://dx.doi.org/10.17185/duepublico/48750 SP - 36 EP - 37 PB - Universität Duisburg-Essen CY - Duisburg ER - TY - CHAP A1 - Azar, Fouad A1 - Digel, Ilya ED - Staat, Manfred ED - Erni, Daniel T1 - Utilization of fluorescence spectroscopy and neural networks in clinical analysis T2 - 3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen N2 - Fluorescence topography of human urine in combination with learning algorithms can provide a variant pattern recognition method in analytical clinical chemistry and, eventually, diagnosis. Y1 - 2019 SN - 978-3-940402-22-6 U6 - http://dx.doi.org/10.17185/duepublico/48750 SP - 40 EP - 41 PB - Universität Duisburg-Essen CY - Duisburg ER -