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VR-V&V
(2023)
To build quality into a software (SW) system necessitates supporting quality-related lifecycle activities during the software development. In software engineering, software Verification and Validation (V&V) processes constitute an inherent part of Software Quality Assurance (SQA) processes. A subset of the V&V activities involved are: 1) bidirectional traceability analysis of requirements to design model elements, and 2) software testing. Yet the complex nature of large SW systems and the dependencies involved in both design models and testing present a challenge to current V&V tools and methods regarding support for trace analysis. One of software’s essential challenges remains its invisibility, which also affects V&V activities. This paper contributes VR-V&V, a Virtual Reality (VR) solution concept towards supporting immersive V&V activities. By visualizing requirements, models, and testing artifacts with dependencies and trace relations immersively, they are intuitively accessible to a larger stakeholder audience such as SQA personnel while supporting digital cognition. Our prototype realization shows the feasibility of supporting immersive bidirectional traceability as well as immersive software test coverage and analysis. The evaluation results are based on a case study demonstrating its capabilities, in particular traceability support was performed with ReqIF, ArchiMate models, test results, test coverage, and test source to test target dependencies.
With the increasing pressure to deliver additional software functionality, software engineers and developers are often confronted with the dilemma of sufficient software testing. One aspect to avoid is test redundancy, and measuring test (or code or statement) coverage can help focus test development on those areas that are not yet sufficiently tested. As software projects grow, it can be difficult to visualize both the software product and the software testing area and their dependencies. This paper contributes VR-TestCoverage, a Virtual Reality (VR) solution concept for visualizing and interacting with test coverage, test results, and test dependency data in VR. Our VR implementation shows its feasibility. The evaluation results based on a case study show its support for three testing-related scenarios.
As systems grow in complexity, the interdisciplinary nature of systems engineering makes the visualization and comprehension of the underlying system models challenging for the various stakeholders. This, in turn, can affect validation and realization correctness. Furthermore, stakeholder collaboration is often hindered due to the lack of a common medium to access and convey these models, which are often partitioned across multiple 2D diagrams. This paper contributes VR-SysML, a solution concept for visualizing and interacting with SysML models in Virtual Reality (VR). Our prototype realization shows its feasibility, and our evaluation results based on a case study shows its support for the various SysML diagram types in VR, cross-diagram element recognition via our backplane followers concept, and depicting further related (SysML and non-SysML) models side-by-side in VR.
VR-SysML+Traceability
(2023)
As systems grow in complexity, the interdisciplinary nature of systems engineering makes the visualization and comprehension of the underlying system models challenging for the various stakeholders. This, in turn, can affect validation and realization correctness. Furthermore, stakeholder collaboration is often hindered due to the lack of a common medium to access and convey these models, which are often partitioned across multiple 2D diagrams. This paper contributes VR-SysML, a solution concept for visualizing and interacting with Systems Modeling Language (SysML) models in Virtual Reality (VR). Our prototype realization shows its feasibility, and our evaluation results based on a case study shows its support for the various SysML diagram types in VR, cross-diagram element recognition via our Backplane Followers concept, and depicting further related (SysML and non-SysML) models side-by-side in VR.
Repeatable processes are fundamental for describing how enterprises and organizations operate, for production, for Industry 4.0, etc. As digitalization and automation progresses across all organizations and industries, including enterprises, business, government, manufacturing, and IT, evidence-based comprehension and analysis of the processes involved, including their variations, anomalies, and performance, becomes vital for an increasing set of stakeholders. Process Mining (PM) relies on logs or processes (as such evidence-based) to provide process-centric analysis data, yet insights are not necessarily visually accessible for a larger set of stakeholders (who may not be process or data analysts). Towards addressing certain challenges described in the Process Mining Manifesto, this paper contributes VR-ProcessMine, a solution for visualizing and interacting with PM results in Virtual Reality (VR). Our realization shows its feasibility, and a case-based evaluation provides insights into its capabilities.
VR-GitCity
(2023)
The increasing demand for software functionality necessitates an increasing amount of program source code that is retained and managed in version control systems, such as Git. As the number, size, and complexity of Git repositories increases, so does the number of collaborating developers, maintainers, and other stakeholders over a repository’s lifetime. In particular, visual limitations of command line or two- dimensional graphical Git tooling can hamper repository comprehension, analysis, and collaboration across one or multiple repositories when a larger stakeholder spectrum is involved. This is especially true for depicting repository evolution over time. This paper contributes VR-GitCity, a Virtual Reality (VR) solution concept for visualizing and interacting with Git repositories in VR. The evolution of the code base is depicted via a 3D treemap utilizing a city metaphor, while the commit history is visualized as vertical planes. Our prototype realization shows its feasibility, and our evaluation results based on a case study show its depiction, comprehension, analysis, and collaboration capabilities for evolution, branch, commit, and multi-repository analysis scenarios.
The increasing demand for software functionality necessitates an increasing amount of program source code that is retained and managed in version control systems, such as Git. As the number, size, and complexity of Git repositories increases, so does the number of collaborating developers, maintainers, and other stakeholders over a repository’s lifetime. In particular, visual limitations of Git tooling hampers repository comprehension, analysis, and collaboration across one or multiple repositories with a larger stakeholder spectrum. This paper contributes VR-Git, a Virtual Reality (VR) solution concept for visualizing and interacting with Git repositories in VR. Our prototype realization shows its feasibility, and our evaluation results based on a case study show its support for repository comprehension, analysis, and collaboration via branch, commit, and multi-repository scenarios.
VR-EDStream+EDA
(2023)
With increasing digitalization, the importance of data and events, which comprise its most fundamental level, cannot be overemphasized. All types of organizations, including enterprises, business, government, manufacturing, and the supporting IT, are dependent on these fundamental building blocks. Thus, evidence-based comprehension and analysis of the underlying data and events, their stream processing, and correlation with enterprise events and activities becomes vital for an increasing set of (grassroot or citizen) stakeholders. Thus, further investigation of accessible alternatives to visually support analysis of data and events is needed. This paper contributes VR-EDStream+EDA, a solution for immersively visualizing and interacting with data and event streams or pipelines and generically visualizing Event-Driven Architecture (EDA) in Virtual Reality (VR). Our realization shows its feasibility, and a case-based evaluation provides insights into its capabilities.
Purpose: The purpose of this thesis is to provide a comprehensive literature review about albinism as an inherited metabolic disorder of melanin synthesis along with those related conditions impacting the visual system. As such, it addresses eye care emphasizing the visual consequences of albinism along with diagnostic and treatment options.
Methods: Background knowledge about ocular development is given as well as information about etiological biochemical and genetic processes. The current classification, clinical findings and their assessment and management options are presented based on recent results of research. In conclusion, two case reports are described as examples of visual care options.
Results: Melanin plays a big role in the retinal and chiasmal development. Melanin biosynthesis can be disrupted by different genes in various ways which leads to the current classification of albinism. Clinical findings include fundus hypopigmenta-tion, nystagmus, iris transillumination, photophobia, foveal hypoplasia, excessive chiasmal decussation, reduced visual acuity, high astigmatism (with-the-rule), strabismus and decreased stereopsis. Treatment options to improve visual acuity, fixation and binocularity are (tinted) prescription lenses and contact lenses, low vision aids, surgical procedures and vision therapy. Medication and supplementa-tion for increased pigmentation are currently being tested on mice.
Conclusions: Albinism is caused by genetic mutations resulting in ocular and cutaneous hypopigmentation. It establishes various phenotypes that require different therapy approaches in order to improve vision and therefore quality of life.
Ophthalmic lenses are ideally measured in accordance with the center of rotation of the eye. Therefore a measuring device was constructed due to this principle to measure lenses with a focimeter. In this work that measuring device was validated. Lenses of ± 4 dpt in spherical and aspherical design were measured across a field of 9x9 measuring points being at 5° distance from each other. This corresponds to a field of view of 40°. The measurement points in x- and y- direction were theoretically calculated to validate the measurement results. Regarding angles of incidence up to 20° it was supposed that the main optical aberration depends on a change in the sagittal and tangential sphere powers which is also defined as astigmatism. Therefore the calculation presents the tangential and sagittal oblique sphere powers depending on the different angles of the line of vision. On average the measurement results and the calculated data of the spherical designed lenses coincide quite good (correlation at 0,98), the systematic deviation of both values on average is 0.01 dpt and the random error (standard deviation) amounts 0.03 dpt on average. The minimum deviation is -0.06 dpt and the maximum is 0.09 dpt. Common focimeters have a measuring inaccuracy of up to 0.06 dpt (Diepes, Blendowske 2002). Therefore the quality of the measured data should be reliable. The aspherical designed lenses were compared to the spherical designed lenses. With increased angles of incidence the astigmatism of the aspherical lenses leads to lower values than the astigmatism of the spherical lenses
Today’s Industry 4.0 Smart Factories involve complicated and highly automated processes. Nevertheless, certain crucial activities such as machine maintenance remain that require human involvement. For such activities, many factors have to be taken into account, like worker safety or worker qualification. This adds to the complexity of selection and assignment of optimal human resources to the processes and overall coordination. Contemporary Business Process Management (BPM) Systems only provide limited facilities regarding activity resource assignment. To overcome these, this contribution pro- poses a BPM-integrated approach that applies fuzzy sets and rule processing for activity assignment. Our findings suggest that our approach has the potential for improved work distribution and cost savings for Industry 4.0 production processes. Furthermore, the scalability of the approach provides efficient performance even with a large number of concurrent activity assignment requests and can be applied to complex production scenarios with minimal effort.
Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets. Preclinical imaging, such as micro-magnetic resonance imaging (μMRI) can produce tomographic datasets of murine vasculature across length scales and organs, which is of outmost importance to study tumor progression, angiogenesis, or vascular risk factors for diseases such as Alzheimer’s. Training a neural network capable of accurate segmentation results requires a sufficiently large amount of labelled data, which takes a long time to compile. Recently, several reasonably automated approaches have emerged in the preclinical context but still require significant manual input and are less accurate than the deep learning approach presented in this paper—quantified by the Dice score. In this work, the implementation of a shallow, three-dimensional U-Net architecture for the segmentation of vessels in murine brains is presented, which is (1) open-source, (2) can be achieved with a small dataset (in this work only 8 μMRI imaging stacks of mouse brains were available), and (3) requires only a small subset of labelled training data. The presented model is evaluated together with two post-processing methodologies using a cross-validation, which results in an average Dice score of 61.34% in its best setup. The results show, that the methodology is able to detect blood vessels faster and more reliably compared to state-of-the-art vesselness filters with an average Dice score of 43.88% for the used dataset.
The direct ophthalmoscope is a retinal screening tool that has been in existence and development for more than 150 years, yet, the rapid influence of technological evolution in screening tools, has left the direct ophthalmoscope untouched. The main purpose of this master thesis is to determine if the direct ophthalmoscope has reached its maximum potential of development and, additionally, to determine if a further development, including a more electronic input, would be feasible.
Soft magnetic Fe-Al alloys have been a subject of research in the past. However, they never saw the same reception in technical applications as the Fe-Si or Fe-Ni alloys, which is, to some extent, due to a low ductility level and difficulties in manufacturing. Additive manufacturing (AM) technology could be a way to avoid issues in conventional manufacturing and produce soft magnetic components from these alloys, as has already been shown with similarly brittle Fe-Si alloys. While AM has already been applied to certain Fe-Al alloys, no magnetic properties of AM Fe-Al alloys have been reported in the literature so far. Therefore, in this work, a Fe-12Al alloy was additively manufactured through laser powder bed fusion (L-PBF) and characterized regarding its microstructure and magnetic properties. A comparison was made with the materials produced by casting and rolling, prepared from melts with an identical chemical composition. In order to improve the magnetic properties, a heat treatment at a higher temperature (1300 °C) than typically applied for conventionally manufactured materials (850–1150 °C) is proposed for the AM material. The specially heat-treated AM material reached values (HC: 11.3 A/m; µmax: 13.1 × 103) that were close to the heat-treated cast material (HC: 12.4 A/m; µmax: 20.3 × 103). While the DC magnetic values of hot- and cold-rolled materials (HC: 3.2 to 4.1 A/m; µmax: 36.6 to 40.4 × 103) were not met, the AM material actually showed fewer losses than the rolled material under AC conditions. One explanation for this effect can be domain refinement effects. This study shows that it is possible to additively manufacture Fe-Al alloys with good soft magnetic behavior. With optimized manufacturing and post-processing, further improvements of the magnetic properties of AM L-PBF Fe-12Al may still be possible.
Purpose: The aim is to be able to advise patients on the choice of sports and exercises regarding the effects on the intraocular pressure.
Methods: The search engines Google Scholar and PubMed were used to search for suitable studies. The studies were summarized, and the most important data were collected in one table for each study. The effect on the IOP was extracted or, if not given in the article, calculated by the difference of means of the IOP after or during exercise, and the baseline IOP before, whenever these values were available.
Findings: A total of 47 studies out of the years 1990 to 2020 that investigated the influence on the IOP of the most popular sports actively practiced in Germany were reviewed and summarized: twelve for running, sixteen for fitness/ weight training, one for swimming/diving, twelve for cycling, four for hiking, and two for yoga.
Conclusions: Throughout all studies and sports it was seen that physical fitness stabilized the IOP. Higher
intensity of exercise led to higher fluctuations of the IOP. Moderate endurance training keeps the IOP fluctuations low and may lead to a lower baseline IOP if practiced on a regular base. Fitness and weight training lead to fluctuations of the IOP in a pronounced manner when performed at moderate and high intensity. Therefore, only a moderate training can be recommended if there is need to keep the IOP stable. Isometric exercise is not recommended as it provokes a rise of the IOP even when performed with light loads. The Valsalva Maneuver should always be avoided as it leads to additional fluctuations of the IOP. Also, the IOP behaved more stable during resistance training when higher fitness was present.
Purpose
The purpose of this study was to evaluate the validity of the iPad Aniseikonia Test for
measurement size lens-induced aniseikonia. The iPad Aniseikonia Test is a new
computer-based test designed for measuring aniseikonia in vertical direction. The iPad
Test uses red-green anaglyphs.
Methods
Aniseikonia was induced in 21 subjects by means of afocal size lenses. Resulting
aniseikonia was measured in vertical direction by the iPad Aniseikonia Test. The
measurement was performed in dark condition with appropriate correction of refractive
error. All subject were patients with normal vision with no anisometropia or other
ocular problem.
Results:
Afocal size lenses of known magnification were used to induce aniseikonia. 5
measurements were taken in each subject, ranging from zero to 7 % magnification.
When using the regression analysis, the slope of the fitted line significantly differs from
1. The average slope of regression line is 0,58.
Conclusions:
Only moderate accuracy was found for tested target size and orientation. In all cases the
iPad Aniseikonia Test underestimates the level of aniseikonia. However for gross
assessment of anisometropia in clinical practice it could be successfully used. Further
study with different target size should be addressed.
Purpose: Recent studies found a reduction of myopia progression with multifocal contact lenses, however, with yet unclear mechanism. This raises the hypothesis that the addition zones of the multifocal contact lenses induce myopic defocus on the retina, which consequentially leads to choroidal thickening and therefore inhibited eye growth. We tested the effect of the optical design of multifocal contact lenses on choroidal thickness.
Methods: 18 myopic students wore four different contact lenses ((1) single-vision lens corrected for distance, (2) single-vision lens with +2.50 D full-field defocus, (3) “Multifocal center-distance” design, addition +2.50 D, (4) “Multifocal center-near” design, addition +2.50 D) for each 30 minutes on their right eye. Automated analysis of the macular choroidal thickness, vitreous chamber depth and eccentric photorefraction were performed before and after each contact lens.
Results: Choroidal thickness and vitreous chamber depth showed no significant differences to baseline with none of the contact lenses. Choroidal thickness increased the most with the “Multifocal center-distance” and the full-field defocus lens, followed by the “Multifocal center-near” and the single-vision contact lens (+2.1 ± 11.1 μm, +2.0 ± 11.1 μm, +1.6 ± 11.3 μm, +0.9 ± 11.2 μm, respectively). The “Multifocal center-distance” design showed an overall more myopic refractive profile than the other lenses. Changes of vitreous chamber depth occurred in anti-phase to these of choroidal thickness.
Conclusion: Multifocal contact lenses have no significant influence on choroidal thickness and after short-term wear. Therefore, it is assumed that it is not the main contributor to the protective effect of multifocal contact lenses in myopia control.
In this study, we investigate the use of artificial neural networks as a potentially efficient method to determine the rate capability of electrodes for lithium-ion batteries with different porosities. The performance of a lithium-ion battery is, to a large extent, determined by the microstructure (i.e., layer thickness and porosity) of its electrodes. Tailoring the microstructure to a specific application is a crucial process in battery development. However, unravelling the complex correlations between microstructure and rate performance using either experiments or simulations is time-consuming and costly. Our approach provides a swift method for predicting the rate capability of battery electrodes by using machine learning on microstructural images of electrode cross-sections. We train multiple models in order to predict the specific capacity based on the batteries’ microstructure and investigate the decisive parts of the microstructure through the use of explainable artificial intelligence (XAI) methods. Our study shows that even comparably small neural network architectures are capable of providing state-of-the-art prediction results. In addition to this, our XAI studies demonstrate that the models are using understandable human features while ignoring present artefacts.
Production processes in Industry 4.0 settings are usually highly automated. However, many complicated tasks, such as machine maintenance, must be executed by human workers. In current smart factories, such tasks can be supported by Augmented Reality (AR) devices. These AR tasks rely on high numbers of contextual factors like live data from machines or work safety conditions and are mostly not well integrated into the global production process. This can lead to various problems like suboptimal task assignment, over-exposure of workers to hazards like noise or heat, or delays in the production process. Current Business Process Management (BPM) Systems (BPMS) are not capable of readily taking such factors into account. There- fore, this contribution proposes a novel approach for context- integrated modeling and execution of processes with AR tasks. Our practical evaluations show that our AR Process Framework can be easily integrated with prevalent BPMS. Furthermore, we have created a comprehensive simulation scenario and our findings suggest that the application of this system can lead to various benefits, like better quality of AR task execution and cost savings regarding the overall Industry 4.0 processes.