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.

The MUSETECH Model: A Comprehensive Evaluation Framework for Museum Technology

Abstract: Digital technologies are being introduced in museums and other informal learning environments alongside more traditional interpretive and communication media. An increasing number of studies has proved the potential of digitally mediated cultural heritage experiences. However, there is still a lot of controversy as to the advantages and disadvantages of introducing the digital into museum settings, primarily related to the risks and investment in terms of time and human and financial resources required. This work introduces the MUSETECH model, a comprehensive framework for evaluating museum technology before and after its introduction into a museum setting. One of the unique features of our framework is to consider the evaluation of digital technologies from three different perspectives: the cultural heritage professional, cultural heritage institution, and museum visitor. The framework benefited from an extensive review of the current state of the art and from inputs from cultural heritage professionals, designers, and engineers. MUSETECH can be used as a tool for reflection before, during, and after introducing novel digital media resources. The model covers technologies as diverse as mobile museum guides, Augmented and Virtual Reality applications, hands-on museum interactives, edutainment applications, digitally mediated tangible and embodied experiences, or online approaches used for museum education and learning.

Computational machine learning representation for the flexoelectricity effect in truncated pyramid structures

Abstract: In this study, machine learning representation is introduced to evaluate the flexoelectricity effect in truncated pyramid nanostructure under compression. A NonUniform Rational B-spline (NURBS) based IGA formulation is employed to model the flexoelectricity. We investigate 2D system with an isotropic linear elastic material under plane strain conditions discretized by 45×30 grid of B-spline elements. Six input parameters are selected to construct a deep neural network (DNN) model. They are the Young's modulus, two dielectric permittivity constants, the longitudinal and transversal flexoelectric coefficients and the order of the shape function. The outputs of interest are the strain in the stress direction and the electric potential due flexoelectricity. The dataset are generated from the forward analysis of the flexoelectric model. 80% of the dataset is used for training purpose while the remaining is used for validation by checking the mean squared error. In addition to the input and output layers, the developed DNN model is composed of four hidden layers. The results showed high predictions capabilities of the proposed method with much lower computational time in comparison to the numerical model.

Evaluation-as-a-Service for the Computational Sciences: Overview and Outlook

Abstract: Evaluation in empirical computer science is essential to show progress and assess technologies developed Several research domains such as information retrieval have long relied on systematic evaluation to measure progress: here, the Cranfield paradigm of creating shared test collections, defining search tasks, and collecting ground truth for these tasks has persisted up until now In recent years, however, several new challenges have emerged that do not fit this paradigm very well: extremely large data sets, confidential data sets as found in the medical domain, and rapidly changing data sets as often encountered in industry Crowdsourcing has also changed the way in which industry approaches problem-solving with companies now organizing challenges and handing out monetary awards to incentivize people to work on their challenges, particularly in the field of machine learningThis article is based on discussions at a workshop on Evaluation-as-a-Service (EaaS) EaaS is the paradigm of not providing data sets to participants and have them work on the data locally, but keeping the data central and allowing access via Application Programming Interfaces (API), Virtual Machines (VM), or other possibilities to ship executables The objectives of this article are to summarize and compare the current approaches and consolidate the experiences of these approaches to outline the next steps of EaaS, particularly toward sustainable research infrastructuresThe article summarizes several existing approaches to EaaS and analyzes their usage scenarios and also the advantages and disadvantages The many factors influencing EaaS are summarized, and the environment in terms of motivations for the various stakeholders, from funding agencies to challenge organizers, researchers and participants, to industry interested in supplying real-world problems for which they require solutionsEaaS solves many problems of the current research environment, where data sets are often not accessible to many researchers Executables of published tools are equally often not available making the reproducibility of results impossible EaaS, however, creates reusable/citable data sets as well as available executables Many challenges remain, but such a framework for research can also foster more collaboration between researchers, potentially increasing the speed of obtaining research results

An inverted personalization effect when learning with multimedia

Abstract: The personalization principle states that students learn better with a personalized message than a nonpersonalized message. Whether the personalization principle holds true for instructional material that is emotionally aversive (in this case, content concerning cerebral hemorrhages) was investigated in two experiments (N=77 in Experiment 1 and N=71 in Experiment 2). The text for the nonpersonalized version was in a formal style, whereas the text for the personalized version was in a conversational style, where personal pronouns such as you and your were used. The results in both experiments showed that students experienced a general increase in state anxiety after learning with both instructional materials, but state anxiety was not significantly different between the experimental conditions. Concerning our main research question and regarding our expectations, the personalization principle did not hold true in either experiment for the emotionally aversive topic used in this study and was even inverted for transfer tasks, where students showed better performance when they learned with a nonpersonalized message compared to a personalized message. The personalization principle was tested for emotionally aversive content.Results showed in 2 experiments an inverted personalization effect for transfer tasks.There was a general increase of state-anxiety when learning with the aversive content.State-anxiety was however not differently pronounced between experimental conditions.

Parallels between wind and crowd loading of bridges

Abstract: Parallels between the dynamic response of flexible bridges under the action of wind and under the forces induced by crowds allow each field to inform the other. Wind-induced behaviour has been traditionally classified into categories such as flutter, galloping, vortex-induced vibration and buffeting. However, computational advances such as the vortex particle method have led to a more general picture where effects may occur simultaneously and interact, such that the simple semantic demarcations break down. Similarly, the modelling of individual pedestrians has progressed the understanding of human-structure interaction, particularly for large-amplitude lateral oscillations under crowd loading. In this paper, guided by the interaction of flutter and vortex-induced vibration in wind engineering, a framework is presented, which allows various human-structure interaction effects to coexist and interact, thereby providing a possible synthesis of previously disparate experimental and theoretical results. Language: en