Elektronik und Informatik
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The digital transformation occurring in enterprises results in an in- creasingly dynamic and complex IT landscape that in turn impacts enterprise architecture (EA) and its artefacts. New approaches for dealing with more com- plex and dynamic models and conveying EA structural and relational insights are needed. As EA tools attempt to address these challenges, virtual reality (VR) can potentially enhance EA tool capabilities and user insight but further investigation is needed in how this can be achieved. This paper contributes a VR solution concept for visualizing, navigating, and interacting with EA tool dynamically-generated diagrams and models using the EA tool Atlas. An im- plementation shows its feasibility and a case study using EA scenarios is used to demonstrate its potential.
Two-Level Classification of Chronic Stress Using Machine Learning on Resting-State EEG Recordings
(2020)
Speichereinsatz versus Netzausbau - Methoden der Bürgerkommunikation am Beispiel des Projekts NEOS
(2020)
Self-Management of Diabetes Mellitus Patients Using mHealth Applications: A Systematic Review
(2020)
Linking Intrusion Detection System Information and System Model to Redesign Security Architecture
(2020)
Learning for E-Learning
(2020)
Nowadays, businesses with focus on consumer-products are challenged by short production cycles, high pricing pressure, and the need to deliver new features and services in a regular interval. Currently, businesses are tackling these challenges by automating their business pro- cesses, while yet trying to be flexible by introducing methods for process variability modeling. However, for larger processes and variability models, it becomes difficult to consider, maintain, and optimize all process variations in the various execution contexts. In software development, highly agile requirements are usually tackled with a flexible microservice architecture. Nonetheless, the fast-changing service landscape is often not fully reflected in the underlying business processes, leading to inefficiency and loss of profit. With this work, we extend our framework for process variability modeling with concepts of Microflows, allowing agile business process modeling and orchestration while utilizing the full flexibility of underlying microservices. In addition, we present a case study, showing how this approach is used in the context of an IoT application