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.

Ultrasonic NDE of concrete

Abstract: In this contribution an overview of ultrasonic non-destructive evaluation (NDE) of concrete is given. The intention is to provide insight into the specific features of concrete testing, and to build a picture of this rapidly developing field by presenting examples of research results and applications. After introducing concrete as a construction material and inhomogeneous propagation medium, common inspection tasks at civil structures are identified. Characteristics of ultrasonic wave propagation in concrete are explained together with measurement and modeling methods. A short presentation of measurement systems precedes the description of research and applications examples. This subjective selection comprises measurement and signal processing techniques including imaging. The list encompasses well-tried methods as well as topics of current research. Finally, the current state of development is discussed in view of demanded testing objectives.

The cuetable: cooperative and competitive multi-touch interaction on a tabletop

Abstract: In this paper we explain how we built cueTable, a multi-touch interactive tabletop, as a base technology to explore new interaction concepts for cooperative and competitive multi-touch applications. We present the Puh game application. And most of all we report on user feedback to the cueTable and the Puh game.

Boron Monochalcogenides; Stable and Strong Two-Dimensional Wide Band-Gap Semiconductors

Abstract: In this short communication, we conducted first-principles calculations to explore the stability of boron monochalcogenides (BX, X = S, Se or Te), as a new class of two-dimensional (2D) materials. We predicted BX monolayers with two different atomic stacking sequences of ABBA and ABBC, referred in this work to 2H and 1T, respectively. Analysis of phonon dispersions confirm the dynamical stability of BX nanosheets with both 2H and 1T atomic lattices. Ab initio molecular dynamics simulations reveal the outstanding thermal stability of all predicted monolayers at high temperatures over 1500 K. BX structures were found to exhibit high elastic modulus and tensile strengths. It was found that BS and BTe nanosheets can show high stretchability, comparable to that of graphene. It was found that all predicted monolayers exhibit semiconducting electronic character, in which 2H structures present lower band gaps as compared with 1T lattices. The band-gap values were found to decrease from BS to BTe. According to the HSE06 results, 1T-BS and 2H-BTe show, respectively, the maximum (4.0 eV) and minimum (2.06 eV) electronic band gaps. This investigation introduces boron monochalcogenides as a class of 2D semiconductors with remarkable thermal, dynamical, and mechanical stability.

A multiphase micromechanical model for unsaturated concrete repaired by electrochemical deposition method with the bonding effects

Abstract: Most concrete structures repaired by the electrochemical deposition method are not fully saturated and the healing interfaces are not always perfect in reality. To demonstrate these issues, microme...

Application of Sentiment Analysis to Language Learning

Abstract: Emotion vocabulary has been studied in various disciplines, such as psychology, linguistics, and computational linguistics. Recently, it plays a requisite role in sentiment analysis or opinion mining. However, emotion vocabulary has not received considerable attention in second or foreign language learning. The insufficient pedagogical materials and inefficient tool support seem to provide little help for learners to master emotion words. The current study considers the application of sentiment analysis to language learning. To achieve this goal, we developed RESOLVE, a context-aware emotion synonym suggestion system, for educational purposes. Utilizing machine-learning techniques, the system is capable of suggesting synonymous emotion words appropriate to learners’ contexts. Importantly, the usage information of each emotion word, including scenario descriptions, definitions, and example sentences, is provided in order to help develop language learners’ vocabulary knowledge as well as help facilitate their word use. A pedagogical evaluation of the system’s effectiveness was conducted using a writing task and a survey questionnaire. The results indicate that the participants achieved substantial progress on emotion word use with the help of the proposed system. In particular, less proficient participants demonstrated greater improvements. Meanwhile, participants showed positive attitudes toward the tool support, as it helps them to have a better command of emotion words in their writings.