Open Access
Refine
Year of publication
Document Type
- Article (24)
- Bachelor Thesis (12)
- Master's Thesis (12)
- Conference Proceeding (11)
- Doctoral Thesis (1)
Language
- English (60) (remove)
Has Fulltext
- yes (60) (remove)
Keywords
- virtual reality (9)
- Business Process Management Systems (4)
- Fuzzy Logic (4)
- visualization (4)
- Myopia (3)
- Assignment Automation (2)
- Augmented Reality (2)
- Business Process Modeling Notation (2)
- Git (2)
- Studie (2)
Institute
The volume of program source code created, reused, and maintained worldwide is rapidly increasing, yet code comprehension remains a limiting productivity factor. For developers and maintainers, well known common software design patterns and the abstractions they offer can help support program comprehension. However, manual pattern documentation techniques in code and code-related assets such as comments, documents, or models are not necessarily consistent or dependable and are cost-prohibitive. To address this situation, we propose the Hybrid Design Pattern Detection (HyDPD), a generalized approach for detecting patterns that is programming-language-agnostic and combines graph analysis (GA) and Machine Learning (ML) to automate the detection of design patterns via source code analysis. Our realization demonstrates its feasibility. An evaluation compared each technique and their combination for three common patterns across a set of 75 single pattern Java and C# public sample pattern projects. The GA component was also used to detect the 23 Gang of Four design patterns across 258 sample C# and Java projects as well as in a large Java project. Performance and scalability were measured. The results show the advantages and potential of a hybrid approach for combining GA with artificial neural networks (ANN) for automated design pattern detection, providing compensating advantages such as reduced false negatives and improved F1 scores.
As the amount of software source code increases, manual approaches for documentation or detection of software design patterns in source code become inefficient relative to the value. Furthermore, typical automatic pattern detection tools are limited to a single programming language. To address this, our Design Pattern Detection using Machine Learning (DPDML) offers a generalized and programming language agnostic approach for automated design pattern detection based on machine learning (ML). The focus of our evaluation was on ensuring DPDML can reasonably detect one design pattern in the structural, creational, and behavioral category for two popular programming languages (Java and C#). 60 unique Java and C# code projects were used to train the artificial neural network (ANN) and 15 projects were then used to test pattern detection. The results show the feasibility and potential for pursuing an ANN approach for automated design pattern detection.
Strategy development is one of the crucial factors for a firm's performance. For it
to be developed, a strategic analysis has to be conducted first. It enables
companies to gain a deeper understanding of their internal and external
environment. In the present work, the specialty coffee market is closely analyzed through a strategic analysis. The focus of this study is the young company Tikuna, a coffee producer that aims to enter the German market. In this context, Tikuna's possible entry into the German market and the companies competitive capacities are analyzed. In order to implement the different tools of the analysis, extensive literature research, as well as one expert interview and a survey were conducted.
It was found that Tikuna possesses all characteristics to enter the German
market. However, due to the lack of a differentiation factor in Tikuna's value
proposition, its competitive capacity is limited to a short period of time. In this
sense, different recommendations are given in order to ensure long term success
in the market. The central one being that Tikuna has to use its main strength and
bring innovation to the market.
Forming complex parts out of high and ultra-high strength aluminium alloys has proved to be more challenging in comparison to the currently used deep drawing steels. Nevertheless, aluminium alloys show a limited formability in contrast with, for example, deep drawing steels. Novel processes like Warm-forming, W-Temper or Hotforming, offer the potential to produce light and highly integrated one-piece components from such aluminium alloys at elevated temperatures. When considering aluminium alloys of the 7000 group, which can reach strength values (UTS) of about 600 MPa, crash components such as side impact bars would offer a suitable field of application.
Forming at elevated temperatures, in particular with the Hotforming process, offers high potential in the production of complex structural components on the one hand and in the use of existing press hardening equipment on the other. To date, the material behaviour of aluminium alloys in the 7000 group, applied in such processes and in the later final state after forming, is not sufficiently known.
Therefore, in this study, systematic investigations on the formability and the final strength during and after forming at elevated temperature of the EN AW-7075 aluminium wrought alloy from different suppliers are conducted. In general, material- and damage/ failure models were created and implemented into simulation in order to make predictions. Characterisation of the plastic material properties on the basis of various tensile specimens as shear-, notched-, tensile- and Erichsen tests are carried out to adapt the complex material- and failure models such as Barlat YLD2000 and GISSMO to the experimental values using a parameter optimisation. These were made for the material conditions during forming, i.e. after solution heat treatment, the final condition after artificial ageing at 180°C for 20 minutes, which corresponds to the cathodic dip coating, and the T6 condition, which is the highest strength condition.
To evaluate a suitable friction coefficient for high temperature forming processes, anti-friction agents are screened, and the potential applicability evaluated by strip-drawing tests. Thereby, using an analytical relationship, friction coefficients are determined at room temperature and 180°C, which are used as corresponding friction model for the finite element forming simulation.
Crash simulations using the nonlinear finite element method (FEM) of side impact protection beams are used to demonstrate the weight saving potential of high and ultra-high strength aluminium alloys compared to a beam made of press hardened steel. A weight saving of about 20 % could be achieved with the same crash performance. This can be significantly increased to around 30 % - 40 % by using local reinforcements such as CFRP or GFRP (carbon/ glass fibre reinforced plastic) patch. For this reason, a novel process was developed which is based on the conventional Hotforming process with an integrated thermal direct joining step called “Extended Hotforming”.
Subsequently, a heatable forming tool for the production of a serial like sheet metal side impact beam was developed to validate the finite element simulation and to demonstrate the potential of the forming processes at elevated temperatures for aluminium sheet metal components.
This paper aims to provide essential information about the formal aspects of the adjustment process companies in Southern Germany utilize to adjust their employees to new surroundings. In particular, it shall be investigated and defined what formal aspects are and when firms apply them. Literature shows that companies do implement language courses, intercultural trainings or provide further information about the host country before a stay abroad. Nevertheless, the phases during and after the assignment are not taken into account with the required importance. Additionally, since national culture can be broken down into different layers, the organizational culture as one layer was analyzed, too.By conducting a quantitative research among companies in Baden-Württemberg, this paper shows the different approaches for dealing with a stay abroad. Scientific literature about the topic of adjustment of globally assigned workers shall help emphasizing the need of a deeper cultural insight. Furthermore, by attempting to explain the organizations’ culture, a better understanding of the chosen training methods shall be created. Definitions in the beginning helped to understand the concept of culture, the notion and the phases of adjustment. Almost all collected data has been accessed either through JSTOR (a digital library founded to help academic libraries or publishers) or similar databases, through the companies’ websites or through the survey results it selves.The results of this research show that the phase before the stay abroad is organized well. Companies offer pre-departure training, but during and after the expatriate time a lack of support is being observed. The firms obviously underestimate the necessary help needed during the assignment and in the return phase, which is why the thesis attempts to fill this gap. Through the organizational culture, described on the companies’ webpages the author was able to draw a conclusion to the applied training methods, which results in a consistent overall picture of the described firms. Companies from the automotive sector had the highest return rate in the survey, which is why particular attention was paid to it.
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.
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
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.
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.
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.
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.
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.
Transformations in the work–nonwork interface highlight the importance of effectively managing the boundaries between life domains. However, do the ways individuals manage the boundaries between work and nonwork life change from one day to the next? If so, which antecedents may explain these intra-individual fluctuations in boundary management? Drawing on boundary management, spillover, and resource theories, we investigate daily changes in segmentation preferences and integration enactments as a function of experiencing strain in work and nonwork life. Assuming that changes in segmentation preferences reflect an individual’s strategy to regulate negative cross-role spillover, we suppose that strain increases individuals’ segmentation preferences; at the same time, however, it could force individuals to enact more integration.
The present thesis deals with alternative powertrains, focusing on electric vehicles
and hybrid vehicles and which of those alternative powertrains is considered as
sustainable for the future. It explores the question, which alternative powertrain is
worthwhile investing in for German automotive suppliers. The aim is to clarify
which of the two powertrains is already established on the market and what the
future prospects of those powertrains are. The question here is evaluated based on
the analysis of current literature as well as through the use of a SWOT analysis
and the use of the scoring model.
As a result it is clear that there is a need for alternative powertrains and the entire
automotive industry invests a lot in the development and research of alternative
powertrains. According to the German Federal Government, one million electric
vehicles should be on German roads by 2020. With pure electric vehicles, however,
the goal will be difficult to reach. Therefore, there is a lot of vested interest in
the development of hybrid vehicles on the market. It shows that the hybrid vehicle
has considerable advantages over the electric vehicle and the hybrid vehicle is
already seen as a transitional solution for pure electric vehicles. The hybrid vehicle
is also already established in the market and has better chances on the market
in the future. Therefore, it makes sense for German automotive suppliers to invest
in hybrid vehicles and to focus on this market, since there the chances of success
are greater and the future potential of this market is higher.