Related papers: Discrete Event Simulation: It's Easy with SimPy!
Simulation was launched in the 1950s, nicknamed a tool of "last resort." Over the years, this Operations Research (OR) method has made significant progress, and utilizing the accelerated advances in computer science (hardware and software,…
Virtual reality (VR) has emerged as a powerful tool for evaluating school security measures in high-risk scenarios such as school shootings, offering experimental control and high behavioral fidelity. However, assessing new interventions in…
RidePy enables fast computer simulations of on-demand mobility modes such as ridehailing or ridepooling. It strongly focuses on modeling the mobility service itself, rather than its customers or the environment. Through a combination of…
This paper focuses on the study of a practical management problem faced by a healthcare {\it emergency department} (ED) located in the north of Italy. The objective of our study was to propose organisational changes in the selected ED,…
Timed discrete-event systems (TDES), which is a modelling formalism proposed by Brandin and Wonham, can be used for modelling scheduling and production planning problems. This paper aims to show that TDES are essentially synchronous product…
Integrated information theory provides a mathematical framework to fully characterize the cause-effect structure of a physical system. Here, we introduce PyPhi, a Python software package that implements this framework for causal analysis…
This paper describes the algorithms, features and implementation of PyDEC, a Python library for computations related to the discretization of exterior calculus. PyDEC facilitates inquiry into both physical problems on manifolds as well as…
Time-to-event (survival) analysis models the time until a pre-specified event occurs. When time is measured in discrete units or rounded into intervals, standard continuous-time models can yield biased estimators. In addition, the event of…
Discrete Event Modelling of Embedded Systems (DEMES) is a development methodology based on the Discrete Event Systems (DEVS) specification that improves the time -to-market by simplifying the development and testing of embedded systems.…
Discrete Event Simulation (DES) is a widely used technique in which the state of the simulator is updated by events happening at discrete points in time (hence the name). DES is used to model and analyze many kinds of systems, including…
We introduce PrivPy, a practical privacy-preserving collaborative computation framework, especially optimized for machine learning tasks. PrivPy provides an easy-to-use and highly compatible Python programming front-end which supports…
Quantum cloud computing is an emerging computing paradigm that allows seamless access to quantum hardware as cloud-based services. However, effective use of quantum resources is challenging and necessitates robust simulation frameworks for…
Distribution grid operation faces new challenges caused by a rising share of renewable energy sources and the introduction of additional types of loads to the grid. With the increasing adoption of distributed generation and emerging…
The study of complex many-body systems via analysis of the trajectories of the units that dynamically move and interact within them is a non-trivial task. The workflow for extracting meaningful information from the raw trajectory data is…
Advancements in high-computing devices increase the necessity for improved and new understanding and development of smart manufacturing factories. Discrete-event models with simulators have been shown to be critical to architect, designing,…
The Discrete Event System Specification formalism (DEVS), which supports hierarchical and modular model composition, has been widely used to understand, analyze and develop a variety of systems. DEVS has been implemented in various…
Active inference is an account of cognition and behavior in complex systems which brings together action, perception, and learning under the theoretical mantle of Bayesian inference. Active inference has seen growing applications in…
SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides…
This paper discusses our proposal and implementation of Distill, a domain-specific compilation tool based on LLVM to accelerate cognitive models. Cognitive models explain the process of cognitive function and offer a path to human-like…
Modern power systems face growing risks from cyber-physical attacks, necessitating enhanced resilience due to their societal function as critical infrastructures. The challenge is that defense of large-scale systems-of-systems requires…