Related papers: piHyFlow Operational Semantics
Recent advancements in video generation models have significantly improved their ability to follow text prompts. However, the customization of dynamic visual effects, defined as temporally evolving and appearance-driven visual phenomena…
Conceptual modeling (CM) applies abstraction to reduce the complexity of a system under study (e.g., an excerpt of reality). As a result of the conceptual modeling process a human interpretable, formalized representation (i.e., a conceptual…
Large Language Models (LLMs) have facilitated the definition of autonomous intelligent agents. Such agents have already demonstrated their potential in solving complex tasks in different domains. And they can further increase their…
This paper is based on a case study of an IT organization in a large, US-based healthcare provider, and develops simluation models to identify areas for performance improvement. These organizations are often grouped into departments by…
Large general-purpose transformer models have recently become the mainstay in the realm of speech analysis. In particular, Whisper achieves state-of-the-art results in relevant tasks such as speech recognition, translation, language…
Business process management (BPM) has been widely used to discover, model, analyze, and optimize organizational processes. BPM looks at these processes with analysis techniques that assume a clearly defined start and end. However, not all…
Speech foundation models, such as OpenAI's Whisper, become the state of the art in speech understanding due to their strong accuracy and generalizability. Yet, their applications are mostly limited to processing pre-recorded speech, whereas…
Multimodal foundation models that can holistically process text alongside images, video, audio, and other sensory modalities are increasingly used in a variety of real-world applications. However, it is challenging to characterize and study…
This paper proposes an introduction to one of the newest modelling methods, an executable model based on workflows. We present the terminology for some basic workflow patterns, as described in the Workflow Management Coalition Terminology…
We employ supervisory controllers to safely coordinate high-level discrete(-event) behavior of distributed components of complex systems. Supervisory controllers observe discrete-event system behavior, make a decision on allowed activities,…
Business process simulation is a versatile technique to predict the impact of one or more changes on the performance of a process. Mainstream approaches in this space suffer from various limitations, some stemming from the fact that they…
New trends towards multiple core processors imply using standard programming models to develop efficient, reliable and portable programs for distributed memory multiprocessors and workstation PC clusters. Message passing using MPI is widely…
Message Sequence Charts & Sequence Diagrams are graphical models that represent the behavior of distributed and concurrent systems via the scheduling of discrete and local emission and reception events. We propose an Interaction Language…
Simulations play important and diverse roles in statistical workflows, for example, in model specification, checking, validation, and even directly in model inference. Over the past decades, the application areas and overall potential of…
BIP is a component framework for constructing systems by superposing three layers of modeling: Behavior, Interaction, and Priority. Behavior is represented by labeled transition systems communicating through ports. Interactions are sets of…
In this paper, we argue that simulation platforms enable a novel type of embodied spatial reasoning, one facilitated by a formal model of object and event semantics that renders the continuous quantitative search space of an open-world,…
Python is a popular high-level general-purpose programming language also heavily used by the scientific community. It supports a variety of different programming paradigms and is preferred by many for its ease of use. With the vision of…
Problems in modeling and simulation require significantly different workflow management technologies than standard grid-based workflow management systems. Computational scientists typically interact with simulation software in a feedback…
We present Probabilistic Structure Integration (PSI), a system for learning richly controllable and flexibly promptable world models from data. PSI consists of a three-step cycle. The first step, Probabilistic prediction, involves building…
The sliding mode approach is recognized as an efficient tool for treating the chattering behavior in hybrid systems. However, the amplitude of chattering, by its nature, is proportional to magnitude of discontinuous control. A possible…