Open Access
Refine
Document Type
- Article (156) (remove)
Keywords
- virtual reality (4)
- Business Process Management Systems (2)
- Fuzzy Logic (2)
- software engineering (2)
- visualization (2)
- Assignment Automation (1)
- Augmented Reality (1)
- Business Process Modeling Notation (1)
- Git (1)
- Indusrie 4.0 (1)
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.
Adding evidence of the effects of treatments into relevant Wikipedia pages: a randomised trial
(2020)
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.
Die Begriffe künstliche Intelligenz und digitaler Zwilling sind prägende Themen der heutigen Zeit. Zwar beeinflussen beide Themen die Entwicklung der Gesellschaft auf verschiedene Arten und Weisen. Dennoch sind sie als Untersuchungsobjekt schlecht definiert und es herrschen etliche unterschiedliche Verständnisse dieser Begriffe.
Der vorliegende Aufsatz nähert sich dem Begriffen künstliche Intelligenz und digitaler Zwilling durch eine Literaturanalyse, um das Verständnis dieser Begriffe in ihrer Nutzung zu schärfen. Im Anschluss der Begriffsbetrachtung wird für jeden der zwei Begriffe betriebliche Anwendungsbereiche aufgezeigt. Folgend den Einzelbetrachtungen werden mögliche Forschungsrichtungen aufgezeigt und diskutiert.
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)
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.
Designing a Randomized Trial with an Age Simulation Suit-Representing People with Health Impairments
(2020)
Development and trial of a blended learning concept for students in engineering study courses
(2018)
Direct digital manufacturing – the role of cost accounting for online hubs to access industry 4.0
(2021)
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.
Fluorescence Microscopy-Based Quantitation of GLUT4 Translocation: High Throughput or High Content?
(2020)
Hardcore Gamer Profiling
(2018)
In the fast-growing but also highly competitive market of battery-powered power tools, cell-pack-cooling systems are of high importance, as they guarantee safety and short charging times. A simulation model of an 18 V power tool battery pack was developed to be able to evaluate four different pack-cooling systems (two heat-conductive polymers, one phase change material, and non-convective air as reference) in an application scenario of practical relevance (the intensive use of a power tool followed by cooling down and charging steps). The simulation comprises battery models of 21700 cells that are commercially available as well as heat transfer models. The study highlights the performance of the different cooling materials and their effect on the maximum pack temperature and total charging cycle time. Key material parameters and their influence on the battery pack temperature and temperature homogeneity are discussed. Using phase change materials and heat-conductive polymers, a significantly lower maximum temperature during discharge (up to 26%) and a high shortening potential of the use/charging cycle (up to 32%) were shown. In addition to the cooling material sweep, a parameter sweep was performed, varying the external temperature and air movement. The high importance of the conditions of use on the cooling system’s performance was illustrated.
Highlighting Thermal Post-Treatment for Improving Long-Term Media-Tightness of Polymer-Metal Hybrids
(2021)
While Virtual Reality (VR) has been applied to various domains to provide new visualization and interaction capabilities, enabling programmers to utilize VR for their software development and maintenance tasks has been insufficiently explored. In this paper, we present the Hyper-Display Environment (HyDE) in the form of a mixed-reality (HyDE-MR) or virtual reality (HyDE-VR) variant respectively, which provides simultaneous multiple operating system window visualization with integrated keyboard/mouse viewing and interaction using MR or in pure VR via a virtual keyboard. This paper applies HyDE in a software development case study as an alternative to typical non-VR Integrated Development Environments (IDEs), supporting software engineering tasks with multiple live screens in VR as an augmented virtuality. The MR solution concept enables programmers to benefit from VR visualization and virtually unlimited information displays while supporting their more natural keyboard interaction for basic code-centric tasks. Thus, developers can leverage VR paradigms and capabilities while directly interacting with their favorite tools to develop and maintain program code. A prototype implementation is described, with a case study demonstrating its feasibility and an initial empirical study showing its potential.
Integrated laser based pre‐tempering at laser welding of AISI 1045 steel by using 3D‐scanner optics
(2021)
Laser melting manufacturing of large elements of lunar regolith simulant for paving on the Moon
(2023)
The next steps for the expansion of the human presence in the solar system will be taken on the Moon. However, due to the low lunar gravity, the suspended dust generated when lunar rovers move across the lunar soil is a significant risk for lunar missions as it can affect the systems of the exploration vehicles. One solution to mitigate this problem is the construction of roads and landing pads on the Moon. In addition, to increase the sustainability of future lunar missions, in-situ resource utilization (ISRU) techniques must be developed. In this paper, the use of concentrated light for paving on the Moon by melting the lunar regolith is investigated. As a substitute of the concentrated sunlight, a high-power CO2 laser is used in the experiments. With this set-up, a maximum laser spot diameter of 100 mm can be achieved, which translates in high thicknesses of the consolidated layers. Furthermore, the lunar regolith simulant EAC-1A is used as a substitute of the actual lunar soil. At the end of the study, large samples (approximately 250 × 250 mm) with interlocking capabilities were fabricated by melting the lunar simulant with the laser directly on the powder bed. Large areas of lunar soil can be covered with these samples and serve as roads and landing pads, decreasing the propagation of lunar dust. These manufactured samples were analysed regarding their mineralogical composition, internal structure and mechanical properties.
Lower bounds on the sum of 25th-powers of univariates lead to complete derandomization of PIT
(2020)
Future lunar exploration will be based on in-situ resource utilization (ISRU) techniques. The most abundant raw material on the Moon is lunar regolith, which, however, is very scarce on Earth, making the study of simulants a necessity. The objective of this study is to characterize and investigate the sintering behavior of EAC-1A lunar regolith simulant. The characterization of the simulant included the determination of the phase assemblage, characteristic temperatures determination and water content analysis. The results are discussed in the context of sintering experiments of EAC-1A simulant, which showed that the material can be sintered to a relative density close to 90%, but only within a very narrow range of temperatures (20–30 °C). Sintering experiments were performed for sieved and unsieved, as well as for dried and non-dried specimens of EAC-1A. In addition, an analysis of the densification and mechanical properties of the sintered specimens was done. The sintering experiments at different temperatures showed that the finest fraction of sieved simulant can reach a higher maximum sintering temperature, and consequently a higher densification and biaxial strength. The non-dried powder exhibited higher densification and biaxial strength after sintering compared to the dried specimen. This difference was explained with a higher green density of the non-dried powder during pressing, rather than due to an actual influence on the sintering mechanism. Nevertheless, drying the powder prior to sintering is important to avoid the overestimation of the strength of specimens to be fabricated on the Moon.