Bauhaus University, Weimar

About: Bauhaus University, Weimar is a education organization based out in Weimar, Thüringen, Germany. It is known for research contribution in the topics: Finite element method & Isogeometric analysis. The organization has 1421 authors who have published 2998 publications receiving 104454 citations. The organization is also known as: Bauhaus-Universität Weimar & Hochschule für Architektur und Bauwesen.

Combining optical holograms with interactive computer graphics

Abstract: Holograms can reconstruct complete optical wavefronts, capturing images that have a three-dimensional appearance and can be observed from different perspectives. Museum exhibits often use optical hologram technology because it permits presentation of 3D objects with almost no loss in visual quality. Optical holograms are static, however, and lack interactivity. Combining 3D computer graphical elements with stereoscopic presentation techniques provides an alternative that allows interactivity.

Predicting undrained static response of sand with non-plastic fines in terms of equivalent granular state parameter

Abstract: The influence of non-plastic fines on undrained monotonic behaviour of sand was investigated over a wide range of fines content (FC = 0–40%), global void ratio and initial mean effective stress ($$ p_{0}^{\prime } $$ = 100 kPa to 500 kPa), by performing triaxial compression tests with isotropic and anisotropic consolidation. For the sand–silt mixtures, steady-state line in the e − log(p′) space was found to be dependent on fines content with the existence of a limiting fines content, which defines the transition from a “fines in sand” to a “sand in fines” soil fabric. It is demonstrated that by means of the concept of equivalent granular void ratio, e*, all steady-state/critical state data points can be well described by a unique relationship in the e* − log(p′) space called the equivalent steady-state line (EG-SSL), regardless of fines content. The equivalent granular state parameter (ψ*), defined in terms of e*, and the EG-SSL can be effectively adopted for predicting the undrained monotonic behaviour of sand–silt mixtures and the onset of static instability, irrespective of fines content and initial state of the sand–silt mixtures.

Celebrity Profiling

Abstract: Celebrities are among the most prolific users of social media, promoting their personas and rallying followers. This activity is closely tied to genuine writing samples, which makes them worthy research subjects in many respects, not least profiling. With this paper we introduce the Webis Celebrity Corpus 2019. For its construction the Twitter feeds of 71,706 verified accounts have been carefully linked with their respective Wikidata items, crawling both. After cleansing, the resulting profiles contain an average of 29,968 words per profile and up to 239 pieces of personal information. A cross-evaluation that checked the correct association of Twitter account and Wikidata item revealed an error rate of only 0.6%, rendering the profiles highly reliable. Our corpus comprises a wide cross-section of local and global celebrities, forming a unique combination of scale, profile comprehensiveness, and label reliability. We further establish the state of the art’s profiling performance by evaluating the winning approaches submitted to the PAN gender prediction tasks in a transfer learning experiment. They are only outperformed by our own deep learning approach, which we also use to exemplify celebrity occupation prediction for the first time.

Report on the Evaluation-as-a-Service (EaaS) Expert Workshop

Abstract: In this report, we summarize the outcome of the "Evaluation-as-a-Service" workshop that was held on the 5th and 6th March 2015 in Sierre, Switzerland. The objective of the meeting was to bring together initiatives that use cloud infrastructures, virtual machines, APIs (Application Programming Interface) and related projects that provide evaluation of information retrieval or machine learning tools as a service.