TY - JOUR A1 - Heel, Mareike van A1 - Dikta, Gerhard A1 - Braekers, Roel T1 - Bootstrap based goodness‑of‑fit tests for binary multivariate regression models JF - Journal of the Korean Statistical Society N2 - We consider a binary multivariate regression model where the conditional expectation of a binary variable given a higher-dimensional input variable belongs to a parametric family. Based on this, we introduce a model-based bootstrap (MBB) for higher-dimensional input variables. This test can be used to check whether a sequence of independent and identically distributed observations belongs to such a parametric family. The approach is based on the empirical residual process introduced by Stute (Ann Statist 25:613–641, 1997). In contrast to Stute and Zhu’s approach (2002) Stute & Zhu (Scandinavian J Statist 29:535–545, 2002), a transformation is not required. Thus, any problems associated with non-parametric regression estimation are avoided. As a result, the MBB method is much easier for users to implement. To illustrate the power of the MBB based tests, a small simulation study is performed. Compared to the approach of Stute & Zhu (Scandinavian J Statist 29:535–545, 2002), the simulations indicate a slightly improved power of the MBB based method. Finally, both methods are applied to a real data set. Y1 - 2021 U6 - https://doi.org/10.1007/s42952-021-00142-4 SN - 2005-2863 (Online) SN - 1226-3192 (Print) N1 - Corresponding author: Mareike van Heel VL - 51 PB - Springer Nature CY - Singapur 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 - Volume 1 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 - https://doi.org/10.5220/0010559201480156 N1 - 2nd International Conference on Deep Learning Theory and Applications, DeLTA2021, July 7-9, 2021 SP - 148 EP - 156 PB - SciTePress CY - Setúbal 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 - https://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 - 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 - https://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 - JOUR A1 - Jahnke, Siegfried A1 - Roussel, Johanna A1 - Hombach, Thomas A1 - Kochs, Johannes A1 - Fischbach, Andreas A1 - Huber, Gregor A1 - Scharr, Hanno T1 - phenoSeeder - A robot system for automated handling and phenotyping of individual seeds JF - Plant physiology N2 - The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently round-shaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality. Y1 - 2016 U6 - https://doi.org/10.1104/pp.16.01122 SN - 0032-0889 VL - 172 IS - 3 SP - 1358 EP - 1370 PB - Oxford University Press CY - Oxford ER - TY - JOUR A1 - Zange, Jochen A1 - Schopen, Kathrin A1 - Albracht, Kirsten A1 - Gerlach, Darius A. A1 - Frings-Meuthen, Petra A1 - Maffiuletti, Nicola A. A1 - Bloch, Wilhelm A1 - Rittweger, Jörn T1 - Using the Hephaistos orthotic device to study countermeasure effectiveness of neuromuscular electrical stimulation and dietary lupin protein supplementation, a randomised controlled trial JF - Plos one Y1 - 2017 U6 - https://doi.org/10.1371/journal.pone.0171562 VL - 12 IS - 2 ER - TY - CHAP A1 - Goldmann, Jan-Peter A1 - Braunstein, Bjoern A1 - Heinrich, Kai A1 - Sanno, Maximilian A1 - Stäudle, Benjamin A1 - Ritzdorf, Wolfgang A1 - Brüggemann, Gert-Peter A1 - Albracht, Kirsten T1 - Joint work of the take-off leg during elite high jump T2 - Proceedings of the 33th International Conference on Biomechanics in Sports (ISBS) Y1 - 2015 ER - TY - CHAP A1 - Droszez, Anna A1 - Sanno, Maximilian A1 - Goldmann, Jan-Peter A1 - Albracht, Kirsten A1 - Brüggemann, Gerd-Peter A1 - Braunstein, Bjoern T1 - Differences between take-off behavior during vertical jumps and two artistic elements T2 - 34th International Conference of Biomechanics in Sport, Tsukuba, Japan, July 18-22, 2016 Y1 - 2016 SN - 1999-4168 SP - 577 EP - 580 ER - TY - CHAP A1 - Abel, Thomas A1 - Bonin, Dominik A1 - Albracht, Kirsten A1 - Zeller, Sebastian A1 - Brüggemann, Gert-Peter A1 - Burkett, Brendan A1 - Strüder, Heiko K. T1 - Kinematic profile of the elite handcyclist T2 - 28th International Conference on Biomechanics in Sports, Marquette, Michigan, USA, July 19 – 23, 2010 Y1 - 2017 SN - 1999-4168 SP - 140 EP - 141 ER - TY - CHAP A1 - Braunstein, Bjoern A1 - Goldmann, Jan-Peter A1 - Albracht, Kirsten A1 - Sanno, Maximilian A1 - Willwacher, Steffen A1 - Heinrich, Kai A1 - Herrmann, Volker A1 - Brüggemann, Gert-Peter T1 - Joint specific contribution of mechanical power and work during acceleration and top speed in elite sprinters T2 - 31 International Conference on Biomechanics in Sports, Taipei, Taiwan, July 07 - July 22, 2013 Y1 - 2013 SN - 1999-4168 ER -