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2021 Winter Simulation Conference, WSC 2021

作者： Wilsdorf, Pia Fischer, Nadine Haack, Fiete Uhrmacher, Adelinde M. Institute for Visual and Analytic Computing University of Rostock Rostock18059 Germany

ISBN: (纸本)9781665433112

Simulation studies are intricate processes and user support for conducting more consistent, systematic, and efficient simulation studies is needed. Simulation experiments as one crucial part of a simulation study can benefit from semi-automatic method selection, parameterization, and execution. However, this largely depends on the context in which the experiment is conducted. Context information about a simulation study can be provided in form of provenance that documents which artifacts contributed in developing a simulation model. We present an approach that exploits provenance to support best practices for simulation experiments. The approach relies on 1) explicitly specified provenance information, 2) an ontology of methods, 3) best practices rules, and 4) integration with a previously developed experiment generation pipeline. We demonstrate our approach by conducting a sensitivity analysis experiment within a cell biological simulation study. © 2021 IEEE.

关键词： Ontology

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Validation Without Data - Formalizing Stylized Facts of Time Series 23

Validation Without Data - Formalizing Stylized Facts of Time...

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Proceedings of the Winter Simulation Conference

作者： Pia Wilsdorf Marian Zuska Philipp Andelfinger Adelinde M. Uhrmacher Florian Peters Institute for Visual and Analytic Computing University of Rostock Rostock Germany Department of Economics University of Rostock Rostock Germany

ISBN: (纸本)9798350369663

A stylized fact is a simplified presentation of an empirical finding. When modeling and simulating complex systems and real data are sparse, stylized facts have become a key instrument for building trust in a model as they represent important requirements regarding the model's behavior. However, automatically validating stylized facts has remained limited as they are usually expressed in natural language. Therefore, we develop a formal language with a custom syntax and tailored predicates allowing modelers to unambiguously and succinctly describe important (temporal) characteristics of simulation traces or relationships between multiple traces via statistical tests. The proposed formal language is able to express numerous facts from the literature in different application domains, as well as to automatically check stylized facts. If stylized facts are defined at the beginning of a simulation study, formally expressing and checking them can streamline and guide the development of simulation models and their successive revisions.

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Potential and Challenges of Assurance Cases for Simulation Validation 24

Potential and Challenges of Assurance Cases for Simulation V...

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Proceedings of the Winter Simulation Conference

作者： Pia Wilsdorf Steffen Zschaler Fiete Haack Adelinde M. Uhrmacher Institute for Visual and Analytic Computing University of Rostock Rostock GERMANY Department of Informatics King's College London London UK

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.

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A Tool for Automated Generation of Domain Specific Symbolic Models From Texts

A Tool for Automated Generation of Domain Specific Symbolic ...

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2023 IEEE International Conference on Pervasive computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023

作者： Stoev, Teodor Sosnowski, Tomasz Yordanova, Kristina Institute for Data Science University of Greifswald Felix-Hausdorff-Stra e 18 Greifswald17489 Germany Institute for Visual and Analytic Computing University of Rostock Albert-Einstein-Str. 22 Rostock18059 Germany

ISBN: (纸本)9781665453813

Recent studies in the area of pervasive computing have shown that it is possible to create systems which combine symbolic models incorporating domain knowledge and sensor observations in order to perform tasks such as activity recog-nition in health monitoring use-cases. Creating symbolic models manually can, however, be a very time consuming endeavour and in some cases it also requires experts in the domain of interest. In this work, we showcase a tool for automatic generation of symbolic models from texts written in natural language. The output of our tool is a model description in Planning Domain Definition Language (PDDL). We concentrate on instructional texts in the cooking domain (cooking recipes), but our tool can be also applied in other areas of interest. © 2023 IEEE.

关键词： Ubiquitous computing

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GPU-Accelerated Simulation Ensembles of Stochastic Reaction Networks

GPU-Accelerated Simulation Ensembles of Stochastic Reaction ...

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Simulation Winter Conference

作者： Till Köster Leon Herrmann Philipp Andelfinger Adelinde Uhrmacher Institute for Visual and Analytic Computing University of Rostock Rostock GERMANY

ISBN: (纸本)9781665476621

Stochastic Simulation Algorithms are widely used for simulating reaction networks in cellular biology. Due to the stochastic nature of models and the large parameter spaces involved, many simulation runs are frequently needed. We approach the computational challenge by expanding the hardware used for execution by massively parallel graphical processing units (GPUs) to execute these ensembles of runs concurrently in a form of coarse-grained parallelization. Such computing infrastructure in the form of GPUs is readily available in desktop workstations and clusters but is not commonly exploited as part of stochastic simulation studies. Building on the existing literature in the field, we employ state-of-the-art algorithms to study the degree to which GPUs can augment the computation resources available for ensemble studies. Furthermore, the challenge of efficient work assignment given the GPU's synchronous mode of execution is explored. There are several algorithmic tradeoffs to consider for models with different execution characteristics, which we investigate in a performance study across four different models. To explore the limitations of the GPU-based simulators, the performance characteristics when executing large models are compared to those of highly optimized CPU simulators. Our results indicate that for some models adding a typical desktop GPU has a similar effect on performance as up to 40 added CPU cores.

关键词： Computational modeling Biological system modeling Instruction sets Layout Graphics processing units Stochastic processes Hardware

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Potential and Challenges of Assurance Cases for Simulation Validation

Potential and Challenges of Assurance Cases for Simulation V...

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Simulation Winter Conference

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

关键词： Accuracy Computational modeling Safety Reliability Context modeling Computational biology

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Seamless Simulation-Based Verification and Validation of Event-Driven Software Systems

Seamless Simulation-Based Verification and Validation of Eve...

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Simulation Winter Conference

作者： Tom Meyer Philipp Andelfinger Andreas Ruscheinski Adelinde M. Uhrmacher Institute for Visual and Analytic Computing University of Rostock Rostock GERMANY

ISBN: (纸本)9781665476621

Verification and validation (V&V) are essential concerns in the development of safety-critical distributed software systems. V&V efforts targeting full system implementations rely on testing, which requires real-world deployments and cumbersome analysis to track down issues across distributed software components. Here, we propose a simulation-based development and testing framework for distributed systems following the event-driven architecture (EDA) paradigm. During development, unmodified software components can be executed in their interaction with a simulated environment, allowing for early testing under envisioned deployments. After introducing the interplay of EDA and discrete-event simulation, we present our framework's architecture and the API offered to software components, which closely follows accepted EDA principles. We demonstrate the use of our framework on a medical software system used in the diagnosis of rare genetic diseases. By observing the system's interaction with simulated laboratories, the feedback loop between diagnoses by laboratories and classifications from the software system is evaluated.

关键词： Target tracking Laboratories Computer architecture Quality of service Production Software systems Middleware

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Validation Without Data - Formalizing Stylized Facts Of Time Series

Validation Without Data - Formalizing Stylized Facts Of Time...

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Simulation Winter Conference

A stylized fact is a simplified presentation of an empirical finding. When modeling and simulating complex systems and real data are sparse, stylized facts have become a key instrument for building trust in a model as they represent important requirements regarding the model’s behavior. However, automatically validating stylized facts has remained limited as they are usually expressed in natural language. Therefore, we develop a formal language with a custom syntax and tailored predicates allowing modelers to unambiguously and succinctly describe important (temporal) characteristics of simulation traces or relationships between multiple traces via statistical tests. The proposed formal language is able to express numerous facts from the literature in different application domains, as well as to automatically check stylized facts. If stylized facts are defined at the beginning of a simulation study, formally expressing and checking them can streamline and guide the development of simulation models and their successive revisions.

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Creating PROV-DM Graphs from Model Databases

Creating PROV-DM Graphs from Model Databases

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Simulation Winter Conference

作者： Pia Wilsdorf Adelinde M. Uhrmacher Institute for Visual and Analytic Computing University of Rostock Rostock GERMANY

ISBN: (纸本)9781665476621

Documenting the provenance of the main products of a simulation study plays a crucial role in improving the understanding of mechanistic, biological models as well as their reproducibility and credibility. With model databases already an ample collection of simulation models, including metainformation and source files, exists. In this paper, we bridge the gap between the information contained in model databases and the PROV-DM provenance standard, which allows making the diverse products and their relationships formally explicit. We present a procedure for creating PROV-DM graphs from model database entries, and illustrate the approach based on ten different models from the BioModels database. These case studies demonstrate the advantages of having a standardized provenance view in addition to the regular database entries, i.e., enhanced means for visualizing the structure of the simulation study and the curation process.

关键词： visualization Biological system modeling Reproducibility of results visual databases Standards

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Towards Machine Learning-based Fish Stock Assessment

arXiv

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arXiv 2023年

作者： Lüdtke, Stefan Pierce, Maria E. Institute for Visual & Analytic Computing University of Rostock Germany Thünen Institute of Baltic Sea Fisheries Rostock Germany

The accurate assessment of fish stocks is crucial for sustainable fisheries management. However, existing statistical stock assessment models can have low forecast performance of relevant stock parameters like recruitment or spawning stock biomass, especially in ecosystems that are changing due to global warming and other anthropogenic stressors. In this paper, we investigate the use of machine learning models to improve the estimation and forecast of such stock parameters. We propose a hybrid model that combines classical statistical stock assessment models with supervised ML, specifically gradient boosted trees. Our hybrid model leverages the initial estimate provided by the classical model and uses the ML model to make a post-hoc correction to improve accuracy. We experiment with five different stocks and find that the forecast accuracy of recruitment and spawning stock biomass improves considerably in most cases. © 2023, CC BY.

关键词： Global warming

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