检索结果-内蒙古大学图书馆

POTENTIAL AND CHALLENGES OF ASSURANCE CASES FOR SIMULATION VALIDATION

学校读者我要写书评

暂无评论

POTENTIAL AND CHALLENGES OF ASSURANCE CASES FOR SIMULATION V...

2024 Winter Simulation Conference, WSC 2024

作者： Wilsdorf, Pia Zschaler, Steffen Haack, Fiete Uhrmacher, Adelinde M. Institute for Visual and Analytic Computing University of Rostock Rostock Germany Department of Informatics King’s College London London United Kingdom

ISBN: (纸本)9798331534202

Simulation studies require thorough validation to ensure model accuracy, reliability, and credibility. While validation typically focuses on the simulation model itself, additional artifacts also influence study outcomes. Conceptual models, comprising research questions, requirements, inputs and outputs, model content, assumptions, and simplifications, provide context information for interpreting results and assessing model suitability. Validating other simulation artifacts for their fitness-for-purpose is complex, necessitating structured arguments to increase confidence. This paper explores when and how validation arguments should be constructed throughout the modeling and simulation lifecycle. Drawing on concepts from safety assurance cases, it defines key claims for the various artifacts, discusses validation arguments from different perspectives – including process, product, people, and project – and illustrates them through a computational biology case study. We conclude with a discussion of the suitability of such structured arguments for the comprehensive validation of simulation studies. © 2024 IEEE.

关键词： Digital elevation model

NBSIMGEN: Jupyter Notebook Extension for Generating Simulation Experiments

学校读者我要写书评

暂无评论

NBSIMGEN: Jupyter Notebook Extension for Generating Simulati...

2023 Winter Simulation Conference, WSC 2023

作者： Wilsdorf, Pia Kirchhübel, Anton Willy Uhrmacher, Adelinde M. University of Rostock Institute for Visual and Analytic Computing Albert-Einstein-Str. 22 Rostock18059 Germany

ISBN: (纸本)9798350369663

Simulation experiments are crucial in conducting simulation studies. With simulation studies growing increasingly complex, simulation experiments are intertwined with steps of conceptual modeling, model building, analyzing data, and visualizing and interpreting results. Making the products of these various steps (assumptions, requirements, data, model components, and experiments) explicit has been shown to increase the reproducibility of simulation studies. Moreover, using an integrated environment that allows developing, organizing and documenting those products can facilitate their automatic reuse and exploitation. We explore Jupyter Notebook as an all-in-one solution for conducting and documenting a simulation study, and we present nbSimGen. This Jupyter Notebook extension lends support to modelers by automatically specifying and running suitable simulation experiments. It is based on an annotation vocabulary that, during the development of the conceptual model and the simulation model, allows users to mark portions of their notebook deemed relevant to the various simulation experiments to come. © 2023 IEEE.

关键词：

A Symmetric Petri Net Model of Generic Publish-Subscribe Systems for Verification and Business Process Conformance Checking

学校读者我要写书评

暂无评论

A Symmetric Petri Net Model of Generic Publish-Subscribe Sys...

2023 International Workshop on Petri Nets and Software Engineering, PNSE 2023

作者： Meyer, Tom Institute for Visual and Analytic Computing University of Rostock Albert-Einstein-Straße 22 Rostock18059 Germany

The highly decoupled nature of distributed systems can greatly simplify modular development. However, it is easy to lose track of component interactions and emerging system behavior. To inspect the behavior of the aggregated system, an abstract model and analysis tools can be of great help. In this paper, we present such a model that follows the Event-Driven Architecture paradigm. We argue that a Petri net model that captures the event flow, without modeling event data, is a useful abstraction to give insight into a system composed of distributed components. We present a symmetric Petri net model with publish-subscribe middleware and a generic abstraction of components. The model was designed with the intention to produce a finite P/T net to be compatible with current Petri net model checking tools. To build such a model, information about component behavior is necessary. We show that this information is encoded in the system implementation, and we describe potential means for automatic extraction. With the formal Petri net model, we enable the use of established verification methods. We discuss ideas from business process conformance checking and other verification properties that may deepen the system understanding. The proposed methods can be used either for static analysis during design time or to automatically signal issues at runtime. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Abstracting

Using (Not so) Large Language Models for Generating Simulation Models in a Formal DSL - A Study on Reaction Networks

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Kreikemeyer, Justin N. Jankowski, Milosz Wilsdorf, Pia Uhrmacher, Adelinde M. Institute for Visual and Analytic Computing University of Rostock Rostock Germany

Formal languages are an integral part of modeling and simulation. They allow the distillation of knowledge into concise simulation models amenable to automatic execution, interpretation, and analysis. However, the arguably most humanly accessible means of expressing models is through natural language, which is not easily interpretable by computers. Here, we evaluate how a Large Language Model (LLM) might be used for formalizing natural language into simulation models. Existing studies only explored using very large LLMs, like the commercial GPT models, without fine-tuning model weights. To close this gap, we show how an open-weights, 7B-parameter Mistral model can be fine-tuned to translate natural language descriptions to reaction network models in a domain-specific language, offering a self-hostable, compute-, and memory efficient alternative. To this end, we develop a synthetic data generator to serve as the basis for fine-tuning and evaluation. Our quantitative evaluation shows that our fine-tuned Mistral model can recover the ground truth simulation model in up to 84.5% of cases. In addition, our small-scale user study demonstrates the model’s practical potential for one-time generation as well as interactive modeling in various domains. While promising, in its current form, the fine-tuned small LLM cannot catch up with large LLMs. We conclude that higher-quality training data are required, and expect future small and open-source LLMs to offer new opportunities. © 2025, CC BY.

关键词： Modeling languages

Automatic Gradient Estimation for Calibrating Crowd Models with Discrete Decision Making

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Andelfinger, Philipp Kreikemeyer, Justin N. Institute for Visual and Analytic Computing University of Rostock Germany

Recently proposed gradient estimators enable gradient descent over stochastic programs with discrete jumps in the response surface, which are not covered by automatic differentiation (AD) alone. Although these estimators’ capability to guide a swift local search has been shown for certain problems, their applicability to models relevant to real-world applications remains largely unexplored. As the gradients governing the choice in candidate solutions are calculated from sampled simulation trajectories, the optimization procedure bears similarities to metaheuristics such as particle swarm optimization, which puts the focus on the different methods’ calibration progress per function evaluation. Here, we consider the calibration of force-based crowd evacuation models based on the popular Social Force model augmented by discrete decision making. After studying the ability of an AD-based estimator for branching programs to capture the simulation’s rugged response surface, calibration problems are tackled using gradient descent and two metaheuristics. As our main insights, we find 1) that the estimation’s fidelity benefits from disregarding jumps of large magnitude inherent to the Social Force model, and 2) that the common problem of calibration by adjusting a simulation input distribution obviates the need for AD across the Social Force calculations, allowing gradient descent to excel. © 2024, CC BY.

关键词： Calibration

Assessing Photorealism of Rendered Objects in Real-World Images: A Transparent and Reproducible User Study

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Kluge, S. Staadt, O. University of Rostock Institute for Visual and Analytic Computing Germany

In an era where numerous studies claim to achieve almost photorealism with real-time automated environment capture, there is a need for assessments and reproducibility in this domain. This paper presents a transparent and reproducible user study aimed at evaluating the photorealism of real-world images composed with virtual rendered objects, that have been generated using classical environment capturing and rendering techniques. We adopted a two-alternative forced choice methodology to compare pairs of images created by integrating virtual objects into real photographs, following a classic pipeline. A control group with defined directional light parameters was included to validate the study’s correctness. The findings revealed some insights, suggesting that observers experienced difficulties in differentiating between rendered and real objects. This work establishes the groundwork for future studies, aimed at enhancing the visual fidelity and realism of virtual objects in real-world environments. © 2024, CC BY.

关键词： Rendering (computer graphics)

Towards Accelerating Real-Time Path Tracing with Foveated Framework

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Mohanto, Bipul Kluge, Sven Staadt, Oliver University of Rostock Institute of Visual and Analytic Computing Germany

Path tracing is one of the most widespread rendering techniques for high-end graphics fidelity. However, the slow convergence time and presence of intensive noises make it infeasible for numerous real-time applications where physically corrected photorealistic effects are salient. Additionally, the increased demand for pixel density, geometric complexity, advanced material, and multiple lights hinder the algorithm from attaining an interactive frame rate for real-time applications. To address these issues, we developed a framework to accelerate path tracing through foveated rendering, a robust technique that leverages human vision. Our dynamic foveated path-tracing framework integrates fixation data and selectively lowers the rendering resolution towards the periphery. The framework is built on NVIDIA's OptiX 7.5 API with CUDA 12.1, serving as the base of future foveated path tracing research. Through comprehensive experimentation, we demonstrated the effectiveness of our framework in this paper. Depending on the scene complexity, our solution can significantly enhance rendering performance up to a factor of 25 without any notable visual differences. We further evaluated the framework using a structured error map algorithm with variable sample numbers and foveated area size. © 2024, CC BY.

关键词： Rendering (computer graphics)

nbSimGen: Jupyter Notebook Extension for Generating Simulation Experiments 23

学校读者我要写书评

暂无评论

nbSimGen: Jupyter Notebook Extension for Generating Simulati...

Proceedings of the Winter Simulation Conference

作者： Pia Wilsdorf Anton Willy Kirchhübel Adelinde M. Uhrmacher Institute for Visual and Analytic Computing University of Rostock Rostock Germany

ISBN: (纸本)9798350369663

关键词：

Towards Learning Stochastic Population Models by Gradient Descent

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Kreikemeyer, Justin N. Andelfinger, Philipp Uhrmacher, Adelinde M. Institute for Visual and Analytic Computing University of Rostock Rostock Germany

Increasing effort is put into the development of methods for learning mechanistic models from data. This task entails not only the accurate estimation of parameters but also a suitable model structure. Recent work on the discovery of dynamical systems formulates this problem as a linear equation system. Here, we explore several simulation-based optimization approaches, which allow much greater freedom in the objective formulation and weaker conditions on the available data. We show that even for relatively small stochastic population models, simultaneous estimation of parameters and structure poses major challenges for optimization procedures. Particularly, we investigate the application of the local stochastic gradient descent method, commonly used for training machine learning models. We demonstrate accurate estimation of models but find that enforcing the inference of parsimonious, interpretable models drastically increases the difficulty. We give an outlook on how this challenge can be overcome. © 2024, CC BY.

关键词： Stochastic models