Implementation and Feasibility of Electronic Patient-Reported Outcome (ePRO) Data Entry in the PRAEGNANT Real-Time Advanced and Metastatic Breast Cancer Registry
Wallwiener, Markus; Heindl, Felix; Brucker, Sara Y.; Taran, Florin-Andrei; Hartkopf, Andreas D.; Overkamp, Friedrich; et al., ..; Volz, Bernhard; et al., ..; Gass, Paul (2017)
Wallwiener, Markus; Heindl, Felix; Brucker, Sara Y.; Taran, Florin-Andrei...
Geburtshilfe und Frauenheilkunde 2017, 77 (08), 870-878.
DOI: 10.1055/s-0043-116223
Open Access
Emotions and fashion recommendations: evaluating the predictive power of affective information for the prediction of fashion product preferences in cold-start scenarios
Piazza, Alexander; Kröckel, Pavlina; Bodendorf, Freimut (2017)
WI '17: Proceedings of the International Conference on Web Intelligence, 1234-1240.
DOI: 10.1145/3106426.3109441
Peer Reviewed
Emotions have a significant impact on the purchasing process. Due to novel affective computing approaches, affective information of users can be acquired in implicit and therefore non-intrusive manner. Recent research in the field of recommender systems indicates that the incorporation of affective user information in the prediction model has a positive impact on the recommender systems accuracy. Existing research mainly focused on product recommendations in the movie anfd music domain. Our paper investigates the impact of affective emotions on fashion products, which is one of the largest consumer industries. We integrate the users' mood and their emotion in the prediction model, and the results are compared to the baseline model using rating data only. For this, we generate a dataset with 337 participants, 64 products, and 10816 ratings. We determine the mood information using the PANAS questionnaire, and the emotion by using the SAM self-assessment method. The affective information is integrated leveraging Factorization Machines. The evaluation of the offline experiments reveals that in new item cold-start scenarios the mood information has a positive impact on the prediction accuracy, whereas the emotion information has a negative impact.
Body measure-aware fashion product recommendations: evaluating the predictive power of body scan data
Piazza, Alexander; Süßmuth, Jochen; Bodendorf, Freimut (2017)
Workshop on Recommendation in Complex Scenarios co-located with 11th ACM Conference on Recommender Systems (RecSys 2017) 1892, 5-8.
Peer Reviewed
Fashion product consumer are faced with large and fast changing product o erings. e fashion purchase decision process is complex, as the consumer has to consider various in uencing factors like current fashion trends, what fashion products t to their personality, and what products t to their physical appearance like hair colors or body measures. Based on novel technologies, 3D body avatars can be reconstructed from 3D or 2D data. From these avatars, body measures can be determined. e objective of this research is to investigate the predictive performance of body measures extracted from a 3D body scanner for predicting fashion item preferences. erefore, item preferences and body scans from 200 users were collected. From the body scans, 11 body measures are extracted and integrated into a prediction model using Factorization Machines. e results from a cross-validation show, that including body measurements signi cantly improves the prediction performance of the recommendation model, especially in new user scenarios, when no information about the fashion product preferences of the active user is known.
Direct metallization by a plasma coating process on thermal conductive polyamide
Sover, Alexandru; Amend, Jonas (2017)
MATEC Web of Conferences 178, 03005.
DOI: 10.1051/matecconf/201817803005
Open Access Peer Reviewed
A First Step towards Industry 4.0 in Melting and Die-Casting Industries. Networking and Prototypical Utilization of Machine Data.
Krieg, Jakob; Schlüter, Wolfgang (2017)
Applied Research Conference 2017. ARC 2017. München, 07.07.2017. Herzogenrath: Shaker Verlag, 565–569.
Sciencomat: A gamified research platform for evaluating visual attractiveness
Zagel, Christian; Piazza, Alexander; Petrov, Yoan; Bodendorf, Freimut (2017)
In: Freund, L., Cellary, W. (eds) Advances in The Human Side of Service Engineering. AHFE 2017. Advances in Intelligent Systems and Computing, vol 601. Springer, Cham 601, 50-60.
DOI: 10.1007/978-3-319-60486-2_5
Peer Reviewed
There are many platforms on the market that support researchers and practitioners to create surveys and market studies. Nevertheless, nearly all of them focus on providing answers to textual questions. In contrast to existing systems this paper presents the concept, prototype, and evaluation of a new mobile platform for quantitative research strictly focusing on images: the SciencOmat. This platform uses pictures to evaluate products, marketing content, and other elements based on their visual attractiveness. Particular emphasis was placed on a high level of usability and user experience. The system integrates methods known from popular online dating applications (e.g., liking/disliking a product by swiping left or right) and also applies gamification elements to further drive user motivation. Next to the application and its evaluation using the User Experience Questionnaire provided by Schrepp et al. we also present the results of two exemplary image data sets.
Do you like according to your lifestyle? a quantitative analysis of the relation between individual facebook likes and the users’ lifestyle
Piazza, Alexander; Zagel, Christian; Haeske, Julia; Bodendorf, Freimut (2017)
In: Freund, L., Cellary, W. (eds) Advances in The Human Side of Service Engineering. AHFE 2017. Advances in Intelligent Systems and Computing, vol 601. Springer, Cham 601.
DOI: 10.1007/978-3-319-60486-2_12
Peer Reviewed
The performance of companies depends on the ability to leverage data to create insights and to target consumers with personalized messages Like marketing content or product offerings. One key element for personalized targeting are expressive user profiles, which are the basis for predictive models to estimate individual consumers’ preferences. Traditionally user profiles are mainly based on demographic attributes like age, gender, or occupation. Due to changes in society, consumers’ behaviors are less stable, and therefore these demographic factors are less effective. Alternatively, the consumers’ lifestyle has a significant impact on their purchase and consumption behavior. This paper investigates the relationship between Facebook Likes and the lifestyle of individuals based on the activity, interests, and opinion (AIO) model. Therefore, 14482 user-Like combinations from 214 participants were collected together with lifestyle information and a correlation analysis is conducted. The results indicate weak monotonic correlations between the AIO and the Like information.
A Material Flow Simulation of a Melting and Die Casting Plant with the Simulation Software Simio
Müller, Stefan; Schlüter, Wolfgang (2017)
Applied Research Conference 2017. Hochschule München.
Digital Direct Metallization (DDM) by a plasma coating process on polymeric components and its applications
Sover, Alexandru; Popp, Pilipp; Tamer, Aydin (2017)
MATEC Web of Conferences 112 (2017), 04003.
DOI: 10.1051/matecconf/201711204003
Open Access Peer Reviewed
Prediction of outcome in internet-delivered cognitive behaviour therapy for paediatric obsessive-compulsive disorder: A machine learning approach
Lenhard, Fabian; Sauer, Sebastian; Andersson, Erik; Månsson, Kristoffer N. T.; Mataix-Cols, David; Rück, Christian; Serlachius, Eva (2017)
Lenhard, Fabian; Sauer, Sebastian; Andersson, Erik; Månsson, Kristoffer N. T....
International Journal of Methods in Psychiatric Research 27 (1), e1576.
Open Access
Teilprojekt Effizienz: Online-Energiekennzahlen für Aluminium-Schmelz- und Druckgussbetriebe
Krieg, Jakob; Schlüter, Wolfgang (2017)
ENCN Jahreskonferenz 2017. Energiecampus Nürnberg. Nürnberg, 13.12.2017.
Smart Melting: Energiekennzahlen der Nichteisen-Schmelz- und Druckgussindustrie
Krieg, Jakob; Schlüter, Wolfgang (2017)
GFB Kolloquium 2017. Fraunhofer IGCV. Augsburg, 21.09.2017.
Das signalgesteuerte Percussion-Interface MOMENTUM
Holzmayr, Marcus; Pöpel, Cornelius (2017)
Mensch Computer 2017 - Workshopband. Regensburg, 10.-13.09.2017: Books on Demand, 515-518.
DOI: 10.18420/muc2017-ws15-0323
Peer Reviewed
WELLENFORMATION: Eine gestengesteuerte Installation zum neuen Erleben alter Musik
Holzmayr, Marcus; Pöpel, Cornelius (2017)
Mensch Computer 2017 - Workshopband. Regensburg, 10.-13.09.2017: Books on Demand, 519-523.
DOI: 10.18420/muc2017-ws15-0324
Peer Reviewed
AV Kleinststeuereinheit für den Kontext interaktiver Klanginstallationen
Kirschner, Michael; Pöpel, Cornelius (2017)
Mensch Computer 2017 - Workshopband. Regensburg, 10.-13.09.2017: Books on Demand Online verfügbar unter , 525-528.
DOI: 10.18420/muc2017-ws15-0327
Peer Reviewed
Parameterschätzung nicht-linearer Differentialgleichungsmodelle via globaler Optimierung
Adamski, Dennis; Seifert, Bastian; Uhl, Christian (2017)
MATLAB EXPO 2017. MathWorks. München, 27.06.2017.
Ein erster Schritt hin zu Industrie 4.0 mit MATLAB - Vernetzung und Verwendung von Maschinendaten in der Schmelz- und Druckgussindustrie
Krieg, Jakob; Müller, Stefan; Schlüter, Wolfgang (2017)
MATLAB EXPO 2017. MathWorks. München, 27.06.2017.
Potentiale zur Reichweitenerhöhung eines Serien-Elektrofahrzeuges durch die Nutzung regenerativer Energien
Haas, Tiffany; Walter, Michael S. J.; Weiherer, Stefan (2017)
Biomass to Power and Heat. Beiträge zum Fachkolloquium, 31.05-01.06.2017. Hochschule Zittau/Görlitz, 191-203.
Software-based Analysis and Visualization of Process Data in Melting and Die Casting Industry
Krieg, Jakob; Schlüter, Wolfgang (2017)
M-APR-Seminar (Konferenz im Forschungsmaster - Master of Applied Research, MAPRby). Ansbach, 20.01.2017.
Public Perception and Acceptance of CO2 Capture and Utilisation
Arning, Katrin; Ziefle, Martina (2017)
CO2 Utilisation Today. Report 2017, 19-23.
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