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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1950s are outdated and that the media should adapt to the changes in societies in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.
Purpose: Although the frequency in which practitioners are fitting scleral
contact lenses is increasing, the recommendation for proper tear layer depth
(thickness) varies amongst experts. The main goal of this paper is to clinically
verify the effect of varying tear layer depths on induced corneal edema during
lens wear.
Methods: Ten subjects with healthy eyes were fitted with scleral lenses on their
right eye. Each of them was fit with two different lenses: one with an apical
clearance of 200 μm and another with an apical clearance of 600 μm. They wore
the lenses for 8 hours on two different days, with at least a one week wash-out
period. Lenses were applied at 8 a.m. on each of the testing days. Pachymetry
measurements were taken one day prior to lens wear at 4 p.m., on the day of
wear prior to lens application, and after removal of the lenses at 4 p.m.
Measurements were collected using both the Pentacam® HR Corneal
Tomographer, as well as the Visante Anterior Segment Optical Coherence
Tomographer (OCT). The apical clearance was measured using the
Visante OCT at two intervals during the test day: immediately after application of
the lens and immediately prior to the removal of the lens.
Results: In this study, there was found to be no significant difference in corneal
edematous response during lens wear between the two test groups. The study
shows that the eyes with the lenses have a statistically significantly thicker
cornea compared to the non-lens-wearing eye after wearing either lens for 8
hours, lying within clinically and physiologically acceptable limits.
Conclusion: Our clinical results do not correlate with current theoretical
calculations, which predict a greater amount of corneal swelling with increasing
tear layer thickness. It has to be evaluated if the effect on corneal edema
changes with longer wearing periods, larger samples or other influences.
Key words: scleral (contact) lens, corneal edema, pachymetry, tear layer
thickness, vaulting, apical clearance
Pharmaceutical agents or drugs often have a pronounced impact on protein-protein interactions in cells, and in particular, cell membranes. Changes of molecular conformations as well as of intermolecular interactions may affect dipole-dipole interaction between chromophoric groups, which can be proven by measuring the Förster resonance energy transfer (FRET). If these chromophores are located within or in close proximity to the plasma membrane, they are excited preferentially by an evanescent electromagnetic wave upon total internal reflection (TIR) of an incident laser beam. For the TIR-FRET screening of larger cell collectives, we performed three separate steps: (1) setting up of a membrane associated test system for probing the interaction between the epidermal growth factor receptor (EGFR) and the growth factor receptor-bound protein 2; (2) use of the Epac-SH188 sensor for quantitative evaluation under the microscope; and (3) application of a TIR fluorescence reader to probe the interaction of GFP with Nile Red. In the first two steps, we measured FRET from cyan (CFP) to yellow fluorescent protein (YFP) by spectral analysis and fluorescence lifetime imaging (FLIM) upon illumination of whole cells (epi-illumination) as well as selective illumination of their plasma membranes by TIR. In particular, TIR excitation permitted FRET measurements with high sensitivity and low background. The Epac sensor showed a more rapid response to pharmaceutical agents, e.g., Forskolin or the A2B adenosine receptor agonist NECA, in close proximity to the plasma membrane compared to the cytosol. Finally, FRET from a membrane associated GFP to Nile Red was used to test a multi-well TIR fluorescence reader with simultaneous detection of a larger number of samples.
The surface topography of biodegradable polymer foils is modified by mechanical imprinting on a submillimeter length scale. The created patterns strongly influence the wetting behavior and allow the preparation of hydrophobic surfaces with controlled solid-liquid interaction. A detailed analysis of anisotropic surface patterns reveals that the observed effect arises from a combination of topographical and compositional changes that are introduced to the surface. As a main result it is found that an individual combination of material and structure is required for the production of water-repellent biopolymer foils that are highly attractive for packaging applications.
Creation of Liquid‐Air Dispersions in Oil and Water: Comparison of Calculations and Measurements
(2021)
The present study deals with the topic how a town can use its cultural heritage or,
more precisely, its industrial culture as a means to market itself as an innovative
business location and to foster a more pronounced sense of civic cohesion among
residents. Economic theory suggests that, nowadays, traditional location factors
such as access to resources and a performant infrastructure are less important than
in the industrial age. Recently, factors like a city’s potential to generate and retain
human and creative capital have emerged. Accordingly, the economic and social
role of cities has shifted – from a place where workers lived and manufactured
goods towards a deeply interwoven ecosystem of knowledge-intense value creation.
The question at the root of the present study is how Heidenheim’s rich industrial
cultural heritage can be used as a future-pointing source of power for rebranding
the town. This rebranding concept has to be developed according to the town’s role
in past, present and future, thus creating actual economic and societal value.
Industrial culture bears branding potential and is closely related to various aspects
of modern life and work. The study examines possibilities to create awareness for
these relations connecting past, present and future. Their relevance shall be
emphasized in order to establish both points of orientation and authenticity of place
in times when macroeconomic and societal trends are difficult to predict. Ideally,
residents shall be given a sort of local identification to hold on to, and potential
investors and entrepreneurs shall be encouraged to sustainably experience the
innovation-based DNA of Heidenheim. Therefore, the study searches for a value
proposition that takes into account the points mentioned above on terms of an
innovative theoretic framework. As a result of this thesis, precise suggestions for
the implementation of a new branding strategy based on the conceptual guidelines
developed in this study will be proposed to the municipality of Heidenheim and, in
addition, an interface using principles of virtual and augmented reality will be
introduced.
Cyber security in family businesses - empirical assessments from the perspective of German SMEs
(2020)
Databases are becoming an ubiquitous and integral part of most software as the data era and the Internet of Everything unfolds. Alternative database types such as NoSQL grow in popularity and allow data to be stored and accessed more simply or in new ways. Thus, software developers, not just database specialists, are more likely to encounter and need to deal with databases. Virtual Reality (VR) technology has grown in popularity, yet its integration in the software development tool chain has been limited. One potential application area for VR technology that has not been sufficiently explored is database-model visualization. This paper describes Virtual Reality Immersion in Data Models (VRiDaM), a generic database-model approach for visualizing, navigating, and conveying database-model information interactively. It describes and explores both native VR and WebVR solution concepts, with prototypes showing the viability of the approach.
Based on a data-driven approach, a computer-assisted workflow for the quantitative analysis of optical Kerr microscopy images of sintered FeNdB-type permanent magnets was developed. By analyzing the domain patterns visible in the Kerr image with data-driven approaches such as traditional machine learning and advanced deep learning, we can quantify grain orientation and size with a better trade-off between accuracy and higher throughput than electron backscatter diffraction (EBSD). The key distinction between traditional machine learning and advanced deep learning lies in feature extraction. Traditional methods require manual, user-dependent feature extraction from input data, while advanced deep learning achieves this automatically. The predictions from the trained models were compared to the measurements from EBSD for performance evaluation. The proposed data-driven model is trained on the dataset created from the correlative microscopy technique, which requires the images of grains extracted from the Kerr microscopy and corresponding EBSD grain orientation data (Euler angles). The fine-tuned deep learning model shows better generalization ability than the traditional machine learning models trained on the manually extracted features and resulted in a mean absolute error of less than 5° for grain orientation of the anisotropic magnet samples when evaluated against the measured EBSD values. The developed approach has reduced the measurement effort for grain orientation by 5 times and have sufficient accuracy when compared to the EBSD.
DEKXTROSE: An Education 4.0 Mobile Learning Approach and Object-Aware App Based on a Knowledge Nexus
(2020)
The exponential growth in knowledge coupled with the decreasing knowledge half-life creates a challenging situation for educational programs - particularly those preparing software engineers for their very dynamic high-technology field. Teachers in high technology education areas are challenged in selecting and making relevant knowledge intuitively accessible to students, especially with regard the highly dynamic digital and software technologies. This paper contributes a knowledge nexus-based multimedia approach aligned with Higher Education 4.0 for creating learning apps on mobile devices that support multiple didactic models, leverage intrinsic curiosity and motivation, support gamification, and enable digital collaboration. Object recognition is used to trigger learning paths, and various didactic methods are supported via workflow-like learning flows to support group or team-based learning. A prototype app was realized to demonstrate its feasibility and an empirical evaluation in software engineering shows the didactic potential and advantages of the approach, which can be readily generalized and applied to the arts, sciences, etc.
DEKXTROSE: An Education 4.0 Mobile Learning Approach and Object-Aware App Based on a Knowledge Nexus
(2020)
The exponential growth in knowledge coupled with the decreasing knowledge half-life creates a challenging situation for educational programs - particularly those preparing software engineers for their very dynamic high-technology field. Teachers in high technology education areas are challenged in selecting and making relevant knowledge intuitively accessible to students, especially with regard the highly dynamic digital and software technologies. This paper contributes a knowledge nexus-based multimedia approach aligned with Higher Education 4.0 for creating learning apps on mobile devices that support multiple didactic models, leverage intrinsic curiosity and motivation, support gamification, and enable digital collaboration. Object recognition is used to trigger learning paths, and various didactic methods are supported via workflow-like learning flows to support group or team-based learning. A prototype app was realized to demonstrate its feasibility and an empirical evaluation in software engineering shows the didactic potential and advantages of the approach, which can be readily generalized and applied to the arts, sciences, etc.
Software design patterns and the abstractions they offer can support developers and maintainers with program code comprehension. Yet manually-created pattern documentation within code or code-related assets, such as documents or models, can be unreliable, incomplete, and labor-intensive. While various Design Pattern Detection (DPD) techniques have been proposed, industrial adoption of automated DPD remains limited. This paper contributes a hybrid DPD solution approach that leverages a Bayesian network integrating developer expertise via rule-based micropatterns with our machine learning subsystem that utilizes graph embeddings. The prototype shows its feasibility, and the evaluation using three design patterns shows its potential for detecting both design patterns and variations.
Designing a Randomized Trial with an Age Simulation Suit-Representing People with Health Impairments
(2020)
Purpose
To determine the stereo threshold and inherent variability with a monitor-based two-rod test at various eccentricities of the visual field. Additionally, to evaluate the duration of this procedure.
Subjects and methods
A pilot trial was conducted in five ophthalmologically normal subjects (2 male and 3 female) aged 21 – 23 years. Two black rods on white background, which appeared under an angle of 1° were presented in a viewing distance of 5.0 meters. The right rod was stationary, whilst the left rod appeared under a stereoscopic parallax, with an either proximal or distal displacement to the image plane. Threshold determination was assessed at seven eccentricities of the visual field by a staircase method. Eccentricities were 0° centrally, 5° to the right and left, 10° to the right and left and 15° to the right and left of the visual field. Proximal and distal displacement as well as the sequence of eccentricities were presented in random order. Stereo acuity was measured in two different sessions for four subjects and in five different sessions for one subject. For all sessions the duration was recorded. All sessions were separated by a time interval of at least 24 hours and no longer than 7 days. Evaluation was made by Wilcoxon test and Kruskal Wallis test at the 95% confidence level (CI) and the median was assessed for all thresholds.
Results
Stereo acuity declines with increasing eccentricities of the retina similar to visual acuity. While at 0° eccentricity thresholds were found to be lowest with (median) 5.0 seconds of arc (‘’) and the CI (0.5’’, 30.5’’) for all measurements, they increased to 112.2’’ at 15° eccentricity to the left in proximal displacement. Distal it was 19.9’’ centrally and 112.2’’ to the right at 15° eccentricity with CI (0.5’’, 30.5’’) for all measurements.
Repeatability of the threshold determination was found to be best at 0° eccentricity with proximal displacement showing the exact same result in the repetitive session and poorest repetition was found at 15° eccentricity to the left with distal displacement. Distal repeatability was worse than proximal. Median and CI of duration time was 5.3 (3.2, 8.3) minutes.
Conclusion
Stereo acuity thresholds are repeatable however increase with increasing eccentricity. Repetitions of the threshold determination do not vary considerably. The duration of these measurements indicates the monitor-based two-rod test as a fast procedure, that can be applied in future studies. The test program is limited by an imperfect algorithm and the stereoscopic images evoke cues, this should be reworked.
Development and trial of a blended learning concept for students in engineering study courses
(2018)