Refine
Year of publication
- 2022 (18) (remove)
Document Type
- Article (6)
- Conference Proceeding (6)
- Master's Thesis (4)
- Bachelor Thesis (2)
Language
- English (18) (remove)
Keywords
- virtual reality (4)
- Augmented Reality (2)
- Business Process Management Systems (2)
- Fuzzy Logic (2)
- visualization (2)
- Assignment Automation (1)
- Average corneal radius (1)
- Axial eye length (1)
- Blinking (1)
- Blinzeln (1)
Comparing axial eye length to other physiological properties of the eye, body height and the head
(2022)
Purpose: To find, if there is any relationship between axial eye length and other physiological properties of the eye (horizontal corneal diameter, average corneal radius, central corneal thickness, objective spherical equivalent, pupillary distance), body height, and head size. Can any of these correlations eventually complement models in myopia progression or be the model for further research.
Telemedicine assisted non-mydriatic Fundus imaging for detection of Diabetic Retinopathy in Colombia
(2022)
Diabetic retinopathy (DR) is a well-recognized complication of diabetes mellitus where retinal function is compromised. It is considered a public health disease and is the fifth leading cause of visual impairment worldwide. But although the worldwide prevalence is continually increasing, little is known about the frequency of this disease in Colombia, South America. On the other hand, telemedicine is presented as a tool that has the potential to improve access to health care services, for remote or rural populations, and for those who have limited access due to physical or other disabilities. Recent technological advances in telecommunication and digital imaging, including fundus photography, telemedicine represents a valuable clinical aid for the documentation and diagnosis of ocular pathologies, and therefore helps to minimize adverse outcomes associated with chronic disease such as diabetes mellitus.
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.
A Context and Augmented Reality BPMN and BPMS Extension for Industrial Internet of Things Processes
(2022)
In the context of Industry 4.0, smart factories enable a new level of highly individualized and very efficient production, driven by highly automated processes and connected Industrial Internet of Things (IIoT) devices. Yet the IIoT process context, crucial for operational process enactment, cannot be readily represented in processes as currently modeled. Despite automation progress, manual tasks performed by humans (such as maintenance) remain, and while complicated tasks can be supported by Augmented Reality (AR) devices, they remain insufficiently integrated into global production processes. To seamlessly integrate process automation, IIoT context, and AR, this paper contributes BPMN-CARX, a Context and Augmented Reality eXtension (CARX) for BPMN (Business Process Model and Notation) and the CARX Framework, which enables AR and IIoT context integration with existing Business Process Management Systems (BPMSs). An Industry 4.0 case study demonstrates its feasibility and applicability.
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.
Feedback management in hearing aids and its challenges have been there for over 60 years. The basic principles of feedback management are still in use to prevent the hearing aids from oscillation. This work focusses on the feedback management in custom style hearing aids by comparing four different Invisible-In-the-Canal (IIC) hearing aids. Four test set-ups were created to find valid and reli-able methods and set-ups to test custom hearing aids for their feedback management. The goal was to find out if they could provide 1) stable gain, 2) good sound quality, 3) indicate specific frequencies audible feedback occurs and 4) to test the clinical robustness through subjective experience rating. The principle was: matched gain – matched acoustics.
The purpose of this master’s thesis is to evaluate the efficiency of state-provided eye exams as part of regular health check-ups for children aged between 6 and 18. This paper examines how capable these eye exams are at detecting reduced visual acuity and other vision related problems. It also investigates whether older children are better at noticing vision related problems then their younger peers. The results are obtained by a comprehensive questionnaire.
The purpose of this master thesis is to make a manual on cataracts so that optometrists in the Republic of Croatia have in one place everything about the causes, diagnosis, and treatment of cataracts. According to the World Health Organization cataract is one of the leading causes of vision impairment in the world. By properly diagnosing the type of cataract, we provide patients with a better quality of life and a visual aid with which they will achieve maximum visual acuity. This master’s thesis will summarize all the knowledge from the master's degree in Aalen in order to get a broader picture of the formation of cataracts. On daily basis optometrists encounter cataract pathology, the goal is to better understand what affects cataract formation, from drugs to systemic diseases, and to ultimately help the client see better after resolving cataract pathology.
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.
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.