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Adaptive and reflective training support for improving search behaviour in industry 4.0 9

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Adaptive and reflective training support for improving searc...

2017 Tagungsband der 9. Konferenz Professionelles Wissensmanagement (Professional Knowledge Management), WM 2017 - 9th Conference on Professional Knowledge Management, WM 2017

作者： Fessl, Angela Thalmann, Stefan Schindler, Viktoria Pammer Know-Center Inffeldgasse 13 GrazA-8010 Austria Graz University of Technology Institute of Interactive Systems and Data Science Inffeldgasse 13 Graz8010 Austria

Fairness literacy: The achilles’ heel of applying fair principles

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data science Journal 2020年第1期19卷 1-11页

作者： David, Romain Mabile, Laurence Specht, Alison Stryeck, Sarah Thomsen, Mogens Yahia, Mohamed Jonquet, Clement Dollé, Laurent Jacob, Daniel Bailo, Daniele Bravo, Elena Gachet, Sophie Gunderman, Hannah Hollebecq, Jean-Eudes Ioannidis, Vassilios Bras, Yvan Le Lerigoleur, Emilie Cambon-Thomsen, Anne MISTEA INRAE Montpellier SupAgro University of Montpellier Montpellier France AISBL Paris France INSERM-Université Paul Sabatier Toulouse III Toulouse France SEES-TERN the University of Queensland St Lucia Australia Graz University of Technology Institute for Interactive Systems and Data Science Graz Austria INIST-CNRS Nancy France LIRMM University of Montpellier CNRS Montpellier France Erasme Hospital Brussels Belgium INRAE UMR BFP Université de Bordeaux Villenave d’Ornon France EPOS-ERIC/Istituto Nazionale di Geofisica e Vulcanologia Rome Italy Istituto Superiore Sanità Rome Italy Aix Marseille Université CNRS Avignon Université IRD IMBE Marseille France Carnegie Mellon University Pittsburgh Pittsburgh United States MISTEA INRAE Montpellier SupAgro Université de Montpellier Montpellier France SIB Swiss Institute of Bioinformatics Lausanne Switzerland DGD-REVE UMS PatriNat MNHN Paris France CNRS UMR GEODE Université Toulouse 2 Toulouse France

The SHARC Interest Group of the Research data Alliance was established to improve research crediting and rewarding mechanisms for scientists who wish to organise their data (and material resources) for community sharing. This requires that data are findable and accessible on the Web, and comply with shared standards making them interoperable and reusable in alignment with the FAIR principles. It takes considerable time, energy, expertise and motivation. It is imperative to facilitate the processes to encourage scientists to share their data. To that aim, supporting FAIR principles compliance processes and increasing the human understanding of FAIRness criteria – i.e., promoting FAIRness literacy – and not only the machine-readability of the criteria, are critical steps in the data sharing process. Appropriate human-understandable criteria must be the first identified in the FAIRness assessment processes and roadmap. This paper reports on the lessons learned from the RDA SHARC Interest Group on identifying the processes required to prepare FAIR implementation in various communities not specifically data skilled, and on the procedures and training that must be deployed and adapted to each practice and level of understanding. These are essential milestones in developing adapted support and credit back mechanisms not yet in place. © 2020 The Author(s).

关键词： FAIR assessment, Research data sharing FAIR principles FAIRification FAIRness literacy Pre-FAIRification

iLCM - A virtual research infrastructure for large-scale qualitative data

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arXiv 2018年

作者： Niekler, Andreas Bleier, Arnim Kahmann, Christian Posch, Lisa Wiedemann, Gregor Erdogan, Kenan Heyer, Gerhard Strohmaier, Markus Faculty of Mathematics and Computer Science University Leipzig Augustusplatz 10 Leipzig04109 Germany Department of Computational Social Science GESIS Leibniz Institute for the Social Sciences Unter Sachsenhausen 6-8 Cologne50667 Germany Institute of Interactive Systems and Data Science Graz University of Technology Inffeldgasse 16c Graz8010 Austria HumTec Institute RWTH Aachen University Theaterplatz 14 Aachen52062 Germany

The iLCM project pursues the development of an integrated research environment for the analysis of structured and unstructured data in a "Software as a Service" architecture (SaaS). The research environment addresses requirements for the quantitative evaluation of large amounts of qualitative data with text mining methods as well as requirements for the reproducibility of data-driven research designs in the social sciences. For this, the iLCM research environment comprises two central components. First, the Leipzig Corpus Miner (LCM), a decentralized SaaS application for the analysis of large amounts of news texts developed in a previous Digital Humanities project. Second, the text mining tools implemented in the LCM are extended by an "Open Research Computing" (ORC) environment for executable script documents, so-called "notebooks". This novel integration allows to combine generic, high-performance methods to process large amounts of unstructured text data and with individual program scripts to address specific research requirements in computational social science and digital humanities. ***. Copyright © 2018, The Authors. All rights reserved.

关键词： Behavioral research

Salt polygons and porous media convection

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arXiv 2019年

作者： Lasser, Jana Nield, Joanna M. Ernst, Marcel Karius, Volker Wiggs, Giles F.S. Threadgold, Matthew R. Beaume, Cédric Goehring, Lucas Graz University of Technology Institute for Interactive Systems and Data Science Inffeldgasse 16c Graz8010 Austria Max Planck Institute for Dynamics and Self-Organization Am Fassberg 17 Göttingen37077 Germany Geography and Environmental Science University of Southampton Highfield SouthamptonSO17 1BJ United Kingdom Geowissenschaftliches Zentrum Georg-August-University Goldschmidtstrasse 3 Göttingen37077 Germany School of Geography and the Environment University of Oxford South Parks Road OxfordOX1 3QY United Kingdom School of Mathematics University of Leeds LeedsLS2 9JT United Kingdom School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom

From fairy circles to patterned ground and columnar joints, natural patterns spontaneously appear in many complex geophysical settings. Here, we investigate the origins of polygonally patterned crusts of salt playa and salt pans. These beautifully regular features, approximately a meter in diameter, are found worldwide and are fundamentally important to the transport of salt and dust in arid regions. We show that they are consistent with the surface expression of buoyancy-driven convection in the porous soil beneath a salt crust. By combining quantitative results from direct field observations, analogue experiments and numerical simulations, we further determine the conditions under which salt polygons should form, as well as how their characteristic size emerges. Copyright © 2019, The Authors. All rights reserved.

关键词： Porous materials

Improving search strategies of auditors - A focus group on reflection interventions 7

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Improving search strategies of auditors - A focus group on r...

7th Workshop on Awareness and Reflection in Technology Enhanced Learning, ARTEL 2017

作者： Fessl, Angela Pammer, Viktoria Wiese, Michael Thalmann, Stefan Know-Center Inffeldgasse 13 GrazA-8010 Austria Institute of Interactive Systems and Data Science Graz University of Technology Inffeldgasse 13 Graz8010 Austria Ernst and Young Wirtschaftsprufungsgesellschaft Wittekindstraße 1a Essen45131 Germany

Financial auditors routinely search internal as well as public knowledge bases as part of the auditing process. Efficient search strategies are crucial for knowledge workers in general and for auditors in particular. Modern search technology quickly evolves;and features beyond keyword search like fac-etted search or visual overview of knowledge bases like graph visualisations emerge. It is therefore desirable for auditors to learn about new innovations and to explore and experiment with such technologies. In this paper, we present a reflection intervention concept that intends to nudge auditors to reflect on their search behaviour and to trigger informal learning in terms of by trying out new or less frequently used search features. The reflection intervention concept has been tested in a focus group with six auditors using a mockup. Foremost, the discussion centred on the timing of reflection interventions and how to raise mo-tivation to achieve a change in search behaviour.

关键词： Search engines

Varying the Stiffness and Diffusivity of Rod-Shaped Microgels Independently through Their Molecular Building Blocks

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Angewandte Chemie 2023年第44期135卷

作者： Yonca Kittel Luis P. B. Guerzoni Carolina Itzin Dirk Rommel Matthias Mork Céline Bastard Bernhard Häßel Abdolrahman Omidinia-Anarkoli Silvia P. Centeno Tamás Haraszti Kyoohyun Kim Jochen Guck Alexander J. C. Kuehne Laura De Laporte DWI-Leibniz Institute for Interactive Materials e. V. Forckenbeckstraße 50 52074 Aachen Germany Institute of Technical and Macromolecular Chemistry RWTH Aachen University Worringerweg 1–2 52074 Aachen Germany Institute of Organic and Macromolecular Chemistry Ulm University Albert-Einstein Allee 11 89081 Ulm Germany Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (lead) Investigation (lead) Project administration (lead) Visualization (lead) Writing - original draft (lead) Contribution: Conceptualization (equal) Investigation (supporting) Supervision (supporting) Writing - review & editing (supporting) Contribution: Investigation (supporting) Validation (supporting) Visualization (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Investigation (supporting) Validation (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Formal analysis (supporting) Investigation (supporting) Visualization (supporting) Writing - review & editing (equal) Center for Biohybrid Medical Systems (CBMS) Advanced Materials for Biomedicine (AMB) Institute of Applied Medical Engineering (AME) Forckenbeckstraße 55 52074 Aachen Germany Contribution: Conceptualization (supporting) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Contribution: Formal analysis (equal) Software (lead) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Max Planck Institute for the Science of Light and Max-Planck-Zentrum für Physik und Medizin Staudtstraße 2 91058 Erlangen Germany Contribution: Conceptualization (supporting) Investigation (supporting) Software (supporting) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Writing - review

Microgels are water-swollen, crosslinked polymers that are widely used as colloidal building blocks in scaffold materials for tissue engineering and regenerative medicine. Microgels can be controlled in their stiffness, degree of swelling, and mesh size depending on their polymer architecture, crosslink density, and fabrication method—all of which influence their function and interaction with the environment. Currently, there is a lack of understanding of how the polymer composition influences the internal structure of soft microgels and how this morphology affects specific biomedical applications. In this report, we systematically vary the architecture and molar mass of polyethylene glycol-acrylate (PEG-Ac) precursors, as well as their concentration and combination, to gain insight in the different parameters that affect the internal structure of rod-shaped microgels. We characterize the mechanical properties and diffusivity, as well as the conversion of acrylate groups during photopolymerization, in both bulk hydrogels and microgels produced from the PEG-Ac precursors. Furthermore, we investigate cell-microgel interaction, and we observe improved cell spreading on microgels with more accessible RGD peptide and with a stiffness in a range of 20 kPa to 50 kPa lead to better cell growth.

关键词： Diffusion Internal Structure Mechanical Properties Microfluidics PEG Microgels

Biomedical image analysis competitions: The state of current participation practice

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arXiv 2022年

作者： Eisenmann, Matthias Reinke, Annika Weru, Vivienn Tizabi, Minu Dietlinde Isensee, Fabian Adler, Tim J. Godau, Patrick Cheplygina, Veronika Kozubek, Michal Maier-Hein, Klaus Jäger, Paul F. Kopp-Schneider, Annette Maier-Hein, Lena Ali, Sharib Gupta, Anubha Kybic, Jan Noble, Alison de Solórzano, Carlos Ortiz Pachade, Samiksha Petitjean, Caroline Sage, Daniel Wei, Donglai Wilden, Elizabeth Alapatt, Deepak Andrearczyk, Vincent Baid, Ujjwal Bakas, Spyridon Balu, Niranjan Bano, Sophia Bawa, Vivek Singh Bernal, Jorge Bodenstedt, Sebastian Casella, Alessandro Choi, Jinwook Commowick, Olivier Daum, Marie Depeursinge, Adrien Dorent, Reuben Egger, Jan Eichhorn, Hannah Engelhardt, Sandy Ganz, Melanie Girard, Gabriel Hansen, Lasse Heinrich, Mattias Heller, Nicholas Hering, Alessa Huaulmé, Arnaud Kim, Hyunjeong Li, Hongwei Bran Landman, Bennett Li, Jianning Ma, Jun Martel, Anne Martín-Isla, Carlos Menze, Bjoern Nwoye, Chinedu Innocent Oreiller, Valentin Padoy, Nicolas Pati, Sarthak Payette, Kelly Sudre, Carole van Wijnen, Kimberlin Vardazaryan, Armine Vercauteren, Tom Wagner, Martin Wang, Chuanbo Yap, Moi Hoon Yu, Zeyun Yuan, Chun Zenk, Maximilian Zia, Aneeq Zimmerer, David Bao, Rina Choi, Chanyeol Cohen, Andrew Dzyubachyk, Oleh Galdran, Adrian Gan, Tianyuan Guo, Tianqi Gupta, Pradyumna Haithami, Mahmood Ho, Edward Jang, Ikbeom Li, Zhili Luo, Zhengbo Lux, Filip Makrogiannis, Sokratis Müller, Dominik Oh, Young-Tack Pang, Subeen Pape, Constantin Polat, Gorkem Reed, Charlotte Rosalie Ryu, Kanghyun Scherr, Tim Thambawita, Vajira Wang, Haoyu Wang, Xinliang Xu, Kele Yeh, Hung Yeo, Doyeob Yuan, Yixuan Zeng, Yan Zhao, Xin Abbing, Julian Adam, Jannes Adluru, Nagesh Agethen, Niklas Ahmed, Salman Al Khalil, Yasmina Alenyà, Mireia Alhoniemi, Esa An, Chengyang Arega, Tewodros Weldebirhan Avisdris, Netanell Aydogan, Dogu Baran Bai, Yingbin Calisto, Maria Baldeon Basaran, Berke Doga Beetz, Marcel Bian, Hao Blansit, Kevin Bloch, Louise Bohnsack, Robert Bosticardo, Sara Breen, Jack Brudfors, Mikael Brüngel, Raphael Cabezas, Mariano Cacciola, Alb Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Biostatistics Germany Heidelberg Division of Medical Image Computing Germany Heidelberg HI Applied Vision Lab Germany IT University of Copenhagen Copenhagen Denmark Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Heidelberg Interactive Machine Learning Group Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg DKFZ University Hospital Heidelberg Germany School of Computing University of Leeds Leeds United Kingdom SBILab Department of ECE IIIT-Delhi India Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Biomedical Engineering University of Oxford United Kingdom Center for Applied Medical Research Pamplona Spain Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Université de Rouen Normandie France Lausanne Switzerland School of Engineering and Applied Science Harvard University United States ICube University of Strasbourg CNRS France Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Techno-Pôle 3 Sierre3960 Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Rue du Bugnon 46 LausanneCH-1011 Switzerland University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington United States Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Visual Artificial Intelligence Lab Oxford Brookes University Oxford United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Spain Dresden Fetscherstraße 74 PF 64 Dresden01307 Germany

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps. © 2022, CC BY.

关键词： Benchmarking

A cross-country comparison of crowdworker motivations

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arXiv 2017年

作者： Posch, Lisa Bleier, Arnim Flöck, Fabian Strohmaier, Markus Department of Computational Social Science GESIS - Leibniz Institute for the Social Sciences Germany Institute of Interactive Systems and Data Science Graz University of Technology Austria HumTec Institute RWTH Aachen University Germany

Crowd employment is a new form of short term employment that has been rapidly becoming a source of income for a vast number of people around the globe. It differs considerably from more traditional forms of work, yet similar ethical and optimization issues arise. One key to tackle such challenges is to understand what motivates the international crowd workforce. In this regard, we study one particularly prevalent type of crowd employment: micro-tasks. So far, the motivation of micro-task crowdworkers has mainly been investigated on Amazon Mechanical Turk (AMT) (e.g. [6, 7, 5]). Consequently, research has focused on workers from the USA and India, which constitute the main population on AMT [4]. This work, in contrast, addresses crowd employment as an increasingly international phenomenon by exploring the more workforce-diverse micro-task platform CrowdFlower1. Furthermore, questionnaires for measuring motivations should be carefully adapted and tested if they are to be used in these new and culturally diverse work environments, in order to produce interpretable results. To this end, we developed a novel scale that marks a major step in reliably measuring the motivations driving micro-task participation around the world, and we report on the results of applying this scale, which unveil significant international differences. Copyright © 2017, The Authors. All rights reserved.

关键词： Motivation

Learning analytics to improve writing skills for young children – an holistic approach

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Journal of Research in Innovative Teaching and Learning 2017年第2期10卷 143-159页

作者： Steinhauer, Nina Gros, Michael Ebner, Martin Ebner, Markus Huppertz, Anneliese Cormann, Mike Biermeier, Susanne Burk, Lena Edtstadler, Konstanze Gabriel, Sonja Wintschnig, Martina Aspalter, Christian Martich, Susanne Landesinstitut für Pädagogik und Medien Saarbrücken Germany Department of Educational Technology Graz University of Technology Graz Austria Institute for Interactive Systems and Data Science Faculty of Computer Science and Biomedical Engineering Technische Universitat Graz Graz Austria School of Raeren Raeren Belgium Albert-Weisgerber School St Ingbert Germany Institute of Professionalisation in Early Childhood and Primary Teacher Education University College of Teacher Education Steiermark Graz Austria University College of Teacher Education Vienna/Krems Vienna Austria

Purpose: Due to the important role of orthography in society, the project called IDeRBlog presented in this paper created a web-based tool to motivate pupils to write text as well as to read and to comment on texts written by fellow students. In addition, IDeRBlog aims to improve student’s German orthography skills and supports teachers and parents with training materials for their students. The paper aims to discuss these issues. Design/methodology/approach: With the aid of learning analytics, the submitted text is analyzed and special feedback is given to the students so that they can try to correct the misspelled words themselves. The teachers as well as the parents are benefiting from the analysis and exercises suggested by the system. Findings: A recent study showed the efficiency of the system in form of an improvement of the students’ orthographic skills. Over a period of four months 70 percent of the students achieved a significant reduction of their spelling mistakes. Originality/value: IDeRBlog is an innovative approach to improving orthography skills combining blogging and new media with writing and practice. © 2017, Nina Steinhauer, Michael Gros, Martin Ebner, Markus Ebner, Anneliese Huppertz, Mike Cormann, Susanne Biermeier, Lena Burk, Konstanze Edtstadler, Sonja Gabriel, Martina Wintschnig, Christian Aspalter and Susanne Martich.

关键词： German orthography German spelling acquisition Learning analytics Technology enhanced learning