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This paper describes an application analysis of one important topic of diversity
marketing – gender marketing. With the help of two surveys and content analyses
in two different media sectors – television and print media – the general trend of
gender representation in advertising could be located. While most survey
respondents are still using characteristics for males and females which were
shaped by traditional gender roles, most of them believe that the roles from the
1950s are outdated and that the media should adapt to the changes in societies in
regard to gender roles. However, the content analyses have shown that the
marketers have already adapted and are primarily presenting the viewers
contemporary images of men and women instead of the stereotyped ones from the
1950s. The only issue that has not changed yet is the color coding which starts to
differentiate between males and females since childhood. The findings of this
paper suggest that the perception and the reality do not always correspond with
each other and that, although the adoption of the change of gender roles is
advancing, it is still not completed yet.
Application of a robotic THz imaging system for sub-surface analysis of ancient human remains
(2019)
We used a robotic-based THz imaging system to investigate the sub-surface structure of an artificially mummified ancient Egyptian human left hand. The results obtained are compared to the results of a conventional CT and a micro-CT scan. Using such a robotic THz system promises new insights into the sub-surface structure of human remains. The depth resolution of the THz images exceeds the resolution of a conventional CT scan and is comparable with a micro-CT scan. The advantage of THz measurements over micro-CT scans is the fact that even comparatively large samples, like complete bodies, can be scanned. These would not fit into a conventional micro-CT scanner.
Although production processes in Industry 4.0 set- tings are highly automated, many complicated tasks, such as machine maintenance, continue to be executed by human workers. While smart factories can provide these workers with some digitalization support via Augmented Reality (AR) devices, these AR tasks depend on many contextual factors, such as live data feeds from machines in view, or current work safety conditions. Although currently feasible, these localized contextual factors are mostly not well-integrated into the global production process, which can result in various problems such as suboptimal task assignment, over-exposure of workers to hazards such as noise or heat, or delays in the production process. Current Business Process Management (BPM) Systems (BPMS) were not particularly designed to consider and integrate context-aware factors during planning and execution. This paper describes the AR-Process Framework (ARPF) for extending a BPMS to support context-integrated modeling and execution of processes with AR tasks in industrial use cases. Our realization shows how the ARPF can be easily integrated with prevalent BPMS. Our evaluation findings from a simulation scenario indicate that ARPF can improve Industry 4.0 processes with regard to AR task execution quality and cost savings.
This research looks into the question of where and how Artificial Intelligence and Big Data can be usefully implemented into Affiliate Marketing. By consulting relevant literature and qualified experts, this work identifies 6 areas, where Artificial Intelligence can be beneficial. These areas were found to be Affiliate Recruitment, Affiliate Management, Product Data Feed Optimization, Tracking, Attribution and Forecasting.
The implementation of Artificial Intelligence in these areas revealed 3 advantages to the Affiliate Marketing channel: Saving of time, support of decision-making, and incentivizing of publishers. While a more detailed study of this research topic would be necessary for validating the results, the findings show that the implementation of Artificial Intelligence technology can help a business gain competitive advantage.