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Abstract: This paper gives an overview of the software engineering activities of Siemens Healthineers that are related to education and learning. Our training activities have a long history and are done globally throughout the company. We expect that experience and lessons learned are useful for others. Our software engineering education activities range from onboarding of new employees to approaches for co...
Abstract: Deep learning (DL) based software systems are difficult to develop and maintain in industrial settings due to several challenges. Data management is one of the most prominent challenges which complicates DL in industrial deployments. DL models are data-hungry and require high-quality data. Therefore, the volume, variety, velocity, and quality of data cannot be compromised. This study aims to explo...
Abstract: This paper gives an overview of the software engineering activities of Siemens Healthineers that are related to education and learning. Our training activities have a long history and are done globally throughout the company. We expect that experience and lessons learned are useful for others. Our software engineering education activities range from onboarding of new employees to approaches for co...
Abstract: Wireless sensor and actuator networks (WSAN) are real-time systems which demand timing requirements. To ensure this level of requirements, different timing analysis approaches have been proposed for WSAN systems. Among different alternatives, analytical analysis and model checking approaches are two common ones which are widely used for the timing analysis of WSAN systems. Analytical approaches ap...
Abstract: Modern industrial robots are increasingly deployed in dynamic environments, where unpredictable events are expected to impact the robot’s operation. Under these conditions, runtime task replanning is required to avoid failures and unnecessary stops, while keeping up productivity. Task replanning is a long-sighted complement to path replanning, which is mostly concerned with avoiding unexpected obs...
Abstract: Time Sensitive Networking (TSN) is a set of IEEE standards based on switched Ethernet that aim at meeting high-bandwidth and low-latency requirements in wired communication. TSN implementations typically do not support integration of wireless networks, which limits their applicability to many industrial applications that need both wired and wire-less communication. The development of 5G and its pr...
Abstract: Time Sensitive Networking (TSN) is a set of IEEE standards based on switched Ethernet that aim at meeting high-bandwidth and low-latency requirements in wired communication. TSN implementations typically do not support integration of wireless networks, which limits their applicability to many industrial applications that need both wired and wire-less communication. The development of 5G and its pr...
Abstract: Design and development of domain-specific modeling languages are crucial activities in model-driven engineering. At the core of these languages we find metamodels, i.e. descriptions of concepts and rules to combine those concepts in order to build valid models. Both in research and practice, metamodels are created and updated more or less frequently to meet certain business requirements. Although ...
Abstract: In general, trains are referred to as environment-friendly transportation means when compared e.g. to cars, busses, or aircraft, being modern trains electrified systems. Unfortunately, the costs due to creation and maintenance of railway infrastructures, notably the overhead lines to power the trains, impose boundaries to their expansion potentials. In this respect, the advances in battery technol...
Abstract: The ubiquity of internet connections has made web applications one of the most widespread means of contents delivery. Indeed, very often they are preferred to applications run locally due to their flexibility, portability, maintainability, and so forth. However, the growth of web contents, and correspondingly of users, has raised critical issues that can be reduced to the required communications b...
Abstract: With the increased availability of new and better computer processing units (CPUs) as well as graphical processing units (GPUs), the interest in statistical learning and deep learning algorithms for classification tasks has grown exponentially. These classification algorithms often require the presence of fully labeled instances during the training period for maximum classification accuracy. Howev...
Abstract: Randomized field experiments are the gold standard for evaluating the impact of software changes on customers. In the online domain, randomization has been the main tool to ensure exchangeability. However, due to the different deployment conditions and the high dependence on the surrounding environment, designing experiments for automotive software needs to consider a higher number of restricted v...
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