Related papers: Higher-Order Process Modeling: Product-Lining, Var…
Reduced-order models that accurately abstract high fidelity models and enable faster simulation is vital for real-time, model-based diagnosis applications. In this paper, we outline a novel hybrid modeling approach that combines machine…
Networks are a fundamental tool for understanding and modeling complex systems in physics, biology, neuroscience, engineering, and social science. Many networks are known to exhibit rich, lower-order connectivity patterns that can be…
Process mining has matured as analysis instrument for process-oriented data in recent years. Manufacturing is a challenging domain that craves for process-oriented technologies to address digitalization challenges. We found that process…
This experience report presents a model-driven approach to legacy system modernization that inserts an enriched, technology-agnostic intermediate model between the legacy codebase and the modern target platform, and reports on its…
An established trend in software engineering insists on using components (sometimes also called services or packages) to encapsulate a set of related functionalities or data. By defining interfaces specifying what functionalities they…
A complex business process demands adaptability as it has been highly influenced by the contextual information. The contextual information declares the underlying semantics on which the process logic depends. Thus one of the challenges of a…
Supply and manufacturing networks in the chemical industry involve diverse processing steps across different locations, rendering their operation vulnerable to disruptions from unplanned events. Optimal responses should consider factors…
The Web 2.0 paradigm has radically changed the way businesses are run all around the world. Moreover, e-Commerce has overcome in daily shopping activities. For management teams, the assessment, evaluation, and forecasting of online incomes…
In this work we propose and analyze a novel Hybrid High-Order discretization of a class of (linear and) nonlinear elasticity models in the small deformation regime which are of common use in solid mechanics. The proposed method is valid in…
Modeling interactive driving behaviors in complex scenarios remains a fundamental challenge for autonomous driving planning. Learning-based approaches attempt to address this challenge with advanced generative models, removing the…
With the continuous development of business process management technology, the increasing business process models are usually owned by large enterprises. In large enterprises, different stakeholders may modify the same business process…
In large-scale projects operated in regulated environments, standard development processes are employed to meet strict compliance demands. Since such processes are usually complex, providing process users with access to their required…
To improve the quality of programs we provide an approach to guidance in the process of program development. At the higher level the various activities and their dependencies to structure the process are identified. At the lower level,…
In computer science, models are made explicit to provide formality and a precise understanding of small, contingent universes (e.g., an organization), as constructed from stakeholder requirements. Conceptual modeling is a fundamental…
We present a design through analysis workflow that enables virtual prototyping of electric devices. A CAD plugin establishes the interaction between design and analysis, allowing the preparation of analysis models and the visualization of…
Supply chain operations traditionally involve a variety of complex decision making problems. Over the last few decades, supply chains greatly benefited from advances in computation, which allowed the transition from manual processing to…
Many modern applications require real-time processing of large volumes of high-speed data. Such data processing needs can be modeled as a streaming computation. A streaming computation is specified as a dataflow graph that exposes multiple…
The stability and the predictability of a computer network algorithm's performance are as important as the main functional purpose of networking software. However, asserting or deriving such properties from the finite state machine…
To ensure the correctness of network analysis methods, the network (as the input) has to be a sufficiently accurate representation of the underlying data. However, when representing sequential data from complex systems such as global…
As more and more devices connect to Internet of Things, unbounded streams of data will be generated, which have to be processed "on the fly" in order to trigger automated actions and deliver real-time services. Spark Streaming is a popular…