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Suche nach „[Digital]“ hat 541 Publikationen gefunden
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    DigitalMaschinenbau und Mechatronik

    Zeitschriftenartikel

    F. Heilmeier, R. Koos, Peter Hornberger, Jochen Hiller, et al.

    Calibration of cast-in Fibre-Bragg-Gratings for internal strain measurements in cast aluminium by using neutron diffraction

    [Submitted for publication]

    Measurement

    2020

    DigitalAngewandte InformatikTC Grafenau

    Zeitschriftenartikel

    Ali Fallah Tehrani, M. Strickert, Diane Ahrens

    Class of Monotone Kernelized Classifiers on the basis of the Choquet Integral

    Expert Systems, vol. 37, no. First published: 21 January 2020, pp. 1-15

    2020

    DOI: 10.1111/exsy.12506

    Abstract anzeigen

    The key property of monotone classifiers is that increasing (decreasing) input values lead to increasing (decreasing) the output value. Preserving monotonicity for a classifier typically requires many constraints to be respected by modeling approaches such as artificial intelligence techniques. The type of constraints strongly depends on the modeling assumptions. Of course, for sophisticated models such conditions might be very complex. In this study we present a new family of kernels that we call it Choquet kernels. Henceforth it allows for employing popular kernel‐based methods such as support vector machines. Instead of a naïve approach with exponential computational complexity we propose an equivalent formulation with quadratic time in the number of attributes. Furthermore, since coefficients derived from kernel solutions are not necessarily monotone in the dual form, different approaches are proposed to monotonize coefficients. Finally experiments illustrate beneficial properties of the Choquet kernels.

    DigitalAngewandte InformatikTC Freyung

    Beitrag (Sammelband oder Tagungsband)

    Wolfgang Dorner, Mariann Juha

    Museumsapps - Individualität versus Plattformstrategie

    Digital Humanities Austria 2018

    2020

    ISBN: 978-3-7001-8668-7

    DigitalAngewandte InformatikAngewandte Wirtschaftswissenschaften

    Zeitschriftenartikel

    M. Kretschmann, Andreas Fischer, Benedikt Elser

    Extracting Keywords from Publication Abstracts for an Automated Researcher Recommendation System

    Digitale Welt, vol. 4, no. 1, pp. 20-25

    2020

    DOI: 10.1007/s42354-019-0227-2

    Abstract anzeigen

    This paper presents an automated keyword assignment system for scientific abstracts. That system is applied to paper abstracts collected in a local publication database and used to drive a researcher recommendation system. Problems like low data volume and missing keywords are discussed. For remediation, training is performed on an extended data set based on large online publication databases. Additionally a closer look at label imbalance in the dataset is taken. Ten multi-label classification algorithms for assigning keywords from a given catalogue to a scientific abstract are compared. The usage of binary relevance as transformation method with LightGBM as classifier yields the best results. Random oversampling before the training phase additionally increases the F1-Score by around 5-6%.

    DigitalAngewandte InformatikTC Grafenau

    Zeitschriftenartikel

    Ali Fallah Tehrani, M. Strickert, Diane Ahrens

    A Class of Monotone Kernelized Classifiers on the Basis of the Chopuet Integral

    [Accepted for publication]

    Expert Systems

    2020

    DigitalAngewandte Wirtschaftswissenschaften

    Beitrag (Sammelband oder Tagungsband)

    Monica I. Ciolacu, Leon Binder, P. M. Svasta, D. Stoichescu, I. Tache

    Education 4.0 - Jump to Innovation IoT in Higher Education

    Proceedings of the 2019 IEEE 25th International Symposium for Design and Technology in Electronic Packaging (SIITME) [Oct 23-26, 2019; Cluj-Napoca, Romania], New York, NY, USA

    2020

    DOI: 10.1109/SIITME47687.2019.8990825

    Abstract anzeigen

    Artificial Intelligence (AI) will play a key role in Higher Education. Our contribution leads the road to innovation within IoT for Education 4.0, using a system comprising smartwatch data, health data, learning analytics and Artificial Intelligence. By using embedded sensors from wearable devices, we can add value to Education 4.0. Smartwatches are IoT devices, equipped with a multitude of embedded sensors collecting distraction-free huge amounts of real-time data during students’ learning. In our paper we highlight advantages of wrist-based wearables like smartwatches for Education 4.0. We develop a User Experience Questionnaire for the measurement of acceptance of advanced electronic technology in Higher Education. We identify as experiment’s results the most important sensors and protocols for Education 4.0.

    DigitalAngewandte WirtschaftswissenschaftenTC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    Monica I. Ciolacu, Leon Binder, Heribert Popp

    Enabling IoT in Education 4.0 with Biosensors from Wearables and Artificial Intelligence

    Proceedings of the 2019 IEEE 25th International Symposium for Design and Technology in Electronic Packaging (SIITME) [Oct 23-26, 2019; Cluj-Napoca, Romania], New York, NY, USA

    2020

    DOI: 10.1109/SIITME47687.2019.8990763

    Abstract anzeigen

    A major challenge for Education 4.0 is to make use of wearable devices for helping students in monitoring their learning behavior and their activities (steps, heart rate variability, and heart rate) in real-time. The first aim of this paper is to present our implementation of adaptivity and Artificial Intelligence (AI) methods within the Education 4.0 process. In this work, we investigate embedded biosensors (noninvasive, low-cost, and distraction-free) used in smartphones and smartwatches. The next objective is to enable IoT for Higher Education, i.e. a novel system assisted by AI that takes embedded biosensor data and environmental data into account in order to estimate students’ wellbeing and health. In this regard, we propose a framework that uses wearable devices to collect data with biofeedback methods to support students’ academic success.

    DigitalTC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    T. Wimmer, Michael Scholz

    Online Product Descriptions - Boost for your Sales?

    14. Internationale Tagung Wirtschaftsinformatik, Siegen

    2019

    DigitalTC Grafenau

    Zeitschriftenartikel

    Michael Scholz, C. Brenner, O. Hinz

    AKEGIS: automatic keyword generation for sponsored search advertising in online retailing

    Decision Support Systems, vol. 119, no. April, pp. 96-106

    2019

    DOI: 10.1016/j.dss.2019.02.001

    Abstract anzeigen

    Sponsored search advertisers face several complex decisions when planning and implementing a new sponsored search advertising campaign. These decisions include the selection of keywords, the definition of landing pages, and the formulation of bidding strategies. Relatively low attention has been paid on supporting the selection of keywords in recent research and most studies on sponsored search advertising focus on the formulation of bidding strategies and strategies for budget planning. We present a novel approach for automatically generating sponsored search keywords that relies on the theory of consumer search behavior. Our approach uses an online store's internal search log to extract keywords used by consumers within their search process, because recent research has shown that especially consumers with a high conversion probability that exhibit goal-directed instead of exploratory search patterns use an online store's internal search engine. We empirically test our approach based on a store's internal search engine and identify the effects of this approach by comparing it to a state-of-the-art approach. Our analysis reveals that our approach substantially increased the number of profitable keywords, improved the store's conversion rate by approximately 41%, and decreased the average cost per click by more than 70%.

    DigitalTC Grafenau

    Beitrag (Sammelband oder Tagungsband)

    A. Keller, Michael Scholz

    Trading on Cryptocurrency Markets: Analyzing the Behavior of Bitcoin Investors

    Proceedings of the 40th International Conference on Information Systems

    2019

    DigitalAngewandte WirtschaftswissenschaftenGMRC

    Buch (Monographie)

    Josef Scherer

    Das interessiert Kapitalgeber: Antifragilität und der „Achilleskörper“ des Ordentlichen Kaufmanns

    Vermeidung der persönlichen Haftung für Missmanagement am Beispiel „Governance, Risk und Compliance („GRC“)“ und Geschäftsprozessdigitalisierung

    2019

    DigitalDEG-DLM2IQW

    Buch (Monographie)

    Matthias Vollroth

    Technisches Konzept Automatisierte Vorlesungsaufzeichnungen für das Projekt DEG-DLM2

    2019

    DigitalDEG-DLM2IQW

    Buch (Monographie)

    Andreas Gegenfurtner, Christian Ebner

    Langfristige Transfereffekte wissenschaftlicher Weiterbildung für nicht-traditionell Studierende im Blended Learning-Design

    2019

    DigitalAngewandte Gesundheitswissenschaften

    Vortrag

    Thomas Bartscher

    People Analytics: Personalsteuerung in Echtzeit & mit Zukunftsbezug

    2019

    DigitalAngewandte Gesundheitswissenschaften

    Vortrag

    Thomas Bartscher

    Corporate Culture & Digitale Transformation

    Forum Personalleitung, Berlin

    2019

    DigitalAngewandte Gesundheitswissenschaften

    Vortrag

    Thomas Bartscher

    Personalgewinnung heute – flexibler Personaleinsatz morgen: Auswirkungen der digitalen Arbeitswelt auf das Personalmanagement

    2019

    DigitalMaschinenbau und Mechatronik

    Beitrag (Sammelband oder Tagungsband)

    Peter Landstorfer, Gabriel Herl, Jochen Hiller

    Investigation of Non-circular Scanning Trajectories in Robot-based Industrial X-ray Computed Tomography of Multi-material Objects

    16th International Conference on Informatics in Control, Automation and Robotics (ICINCO) [29-31 July, 2019; Prague, Czech Republic]

    2019

    DigitalMaschinenbau und Mechatronik

    Beitrag (Sammelband oder Tagungsband)

    Peter Landstorfer, Jochen Hiller, Matthias Herbst

    Investigation of positioning accuracy of industrial robots for robotic-based X-ray computed tomography

    iCT 2019 9th Conference on Industrial Computed Tomography (iCT) [13-15 February, 2019; Padua, Italy]

    2019

    Abstract anzeigen

    In this research work we investigated the accuracy of a standard industrial robot. We wanted to find out, how accurate an X-RayComputed Tomography (CT) scan can be performed when using such a robot as a manipulator. The accuracy was measuredusing a laser-interferometer. The measured deviations were used to run an X-Ray simulation via Fraunhofer EZRT’s ScorpiusX-Lab. Metrological analysis was performed as a measure for the quality of the simulated CT-scan. The metrological deviationsreflect the feasible accuracy of a CT-scan in a real CT-setup.

    DigitalMaschinenbau und Mechatronik

    Beitrag (Sammelband oder Tagungsband)

    Gabriel Herl, Jochen Hiller, T. Sauer

    Artifact reduction in X-ray computed tomography by multipositional data fusion using local image quality measures

    iCT 2019 9th Conference on Industrial Computed Tomography (iCT) [13-15 February, 2019; Padua, Italy]

    2019

    Abstract anzeigen

    Metal artifacts are still a major problem in X-ray industrial computed tomography. In order to reduce metal artifacts and increase the image quality of X-ray CT-scans, we suggest using projection data from multiple scans with differently positioned object orientations. We present two different approaches for multipositional CT, which are especially effective for multimaterial objects with high absorbing metal parts. On one hand, we reconstruct the different scans separatly, estimate the local quality of the resulting volumes and then fuse these volumes to an optimized volume. On the other hand, we introduce smART (shrinking merged Algebraic Reconstruction Technique) and merge sinograms of different scans, estimate the reliability of each projection pixel and then reconstruct the merged sinogram with an adapted SART reconstruction method. We demonstrate our approaches on simulations and on measurement data and are able to show a significant reduction of image artifacts qualitatively and quantitatively with the help of dimensional measurement results.

    DigitalMaschinenbau und Mechatronik

    Zeitschriftenartikel

    Gabriel Herl, Jochen Hiller, Kasperl, S. Maier, A.

    Reduktion von Metallartefakten durch multipositionale Datenfusion in der industriellen Röntgen-Computertomographie

    tm - Technisches Messen, vol. 87, no. 2

    2019

    DOI: 10.1515/teme-2019-0137

    Abstract anzeigen

    Metallartefakte stellen eine große Herausforderung für das Messen mit Röntgen-Computertomographie dar. Dieser Beitrag stellt die Methode der multipositionalen Datenfusion zur Reduktion von Metallartefakten vor. Dazu werden mehrere Scans desselben Objekts bei unterschiedlicher Objekt-positionierung durchgeführt, aufeinander registriert und zur Fusion gemeinsam unter Betrachtung eines lokalen Gütemaßes rekonstruiert. In praxisnahen Experimenten wird der Mehrwert der Methode gezeigt. Insbesondere wird dargestellt, wie mit wenig Aufwand und ohne Vorwissen Kunststoffstrukturen trotz starker Metallartefakte sichtbar gemacht werden können, womit das Verfahren ein Alleinstellungsmerkmal gegenüber den existierenden Metallartefaktreduktionsverfahren aufweist.