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.

Identifying featured articles in wikipedia: writing style matters

Abstract: Wikipedia provides an information quality assessment model with criteria for human peer reviewers to identify featured articles. For this classification task "Is an article featured or not?" we present a machine learning approach that exploits an article's character trigram distribution. Our approach differs from existing research in that it aims to writing style rather than evaluating meta features like the edit history. The approach is robust, straightforward to implement, and outperforms existing solutions. We underpin these claims by an experiment design where, among others, the domain transferability is analyzed. The achieved performances in terms of the F-measure for featured articles are 0.964 within a single Wikipedia domain and 0.880 in a domain transfer situation.

Use of key performance indicators for PPP transport projects to meet stakeholders’ performance objectives

Abstract: Purpose – The need for more efficient and effective public-private partnership (PPP) projects makes performance management of increasing importance, especially with respect to stakeholder expectations. This paper seeks to examine the use of key performances indicators (KPI) based on the analysis of critical success factors (CSF) for monitoring of PPP transport projects from the perspective of different stakeholders. Design/methodology/approach – The list of stakeholders’ performance objectives including CSF was defined using the brainstorming technique applied to group of experts in PPP transport sectors and refined through literature review. Input of the expert group was validated against a feedback from a respective survey. Three main groups of stakeholders were identified: public sector, private sector, and users. Finally, the review and comparative analysis of existing KPIs in PPP transport projects was performed based on stakeholders’ objectives and project attributes using the “frequency of mention”...

TL;DR: Mining Reddit to Learn Automatic Summarization

Abstract: Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data. We propose a new method for mining social media for author-provided summaries, taking advantage of the common practice of appending a “TL;DR” to long posts. A case study using a large Reddit crawl yields the Webis-TLDR-17 dataset, complementing existing corpora primarily from the news genre. Our technique is likely applicable to other social media sites and general web crawls.

Overview of the author identification task at PAN 2014

Abstract: The author identification task at PAN-2014 focuses on author verification. Similar to PAN-2013 we are given a set of documents by the same author along with exactly one document of questioned authorship, and the task is to determine whether the known and the questioned documents are by the same author or not. In comparison to PAN-2013, a significantly larger corpus was built comprising hundreds of documents in four natural languages (Dutch, English, Greek, and Spanish) and four genres (essays, reviews, novels, opinion articles). In addition, more suitable performance measures are used focusing on the accuracy and the confidence of the predictions as well as the ability of the submitted methods to leave some problems unanswered in case there is great uncertainty. To this end, we adopt the c@1 measure, originally proposed for the question answering task. We received 13 software submissions that were evaluated in the TIRA framework. Analytical evaluation results are presented where one language-independent approach serves as a challenging baseline. Moreover, we continue the successful practice of the PAN labs to examine meta-models based on the combination of all submitted systems. Last but not least, we provide statistical significance tests to demonstrate the important differences between the submitted approaches.

Topology optimization of flexoelectric structures

Abstract: We present a mixed finite element formulation for flexoelectric nanostructures that is coupled with topology optimization to maximize their intrinsic material performance with regards to their energy conversion potential. Using Barium Titanate (BTO) as the model flexoelectric material, we demonstrate the significant enhancement in energy conversion that can be obtained using topology optimization. We also demonstrate that non-smooth surfaces can play a key role in the energy conversion enhancements obtained through topology optimization. Finally, we examine the relative benefits of flexoelectricity, and surface piezoelectricity on the energy conversion efficiency of nanobeams. We find that the energy conversion efficiency of flexoelectric nanobeams is comparable to the energy conversion efficiency obtained from nanobeams whose electromechanical coupling occurs through surface piezoelectricity, but are ten times thinner. Overall, our results not only demonstrate the utility and efficiency of flexoelectricity as a nanoscale energy conversion mechanism, but also its relative superiority as compared to piezoelectric or surface piezoelectric effects.