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检索条件"任意字段=International Conference on Computer Modeling and Simulation"

共 35215 条记录，以下是261-270 订阅

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A Dynamical Equation Approach For Quasi-Periodic Gaussian Processes

A Dynamical Equation Approach For Quasi-Periodic Gaussian Pr...

引用

international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Unnati Nigam Radhendushka Srivastava Michael Burke Faezeh Marzbanrad IITB-Monash Research Academy India Department of Mathematics IIT Bombay Mumbai India Department of Electrical and Computer Systems Engineering Monash University Clayton Australia

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Quasi (pseudo/approximate) periodic signals often occur in natural settings, particularly when a periodic signal is recorded with noise. In this work, we develop a new dynamical equation system to construct a family of Quasi-periodic Gaussian Processes (QPGP). We provide a computationally inexpensive algorithm based on a newly derived likelihood function for parameter estimation. Our approach also simplifies the signal forecasting. We illustrate via a simulation study that the proposed QPGP estimation strategy is faster as well and more accurate than existing constructions. Unlike these existing models, the proposed approach extends to multiple families of kernels, which we illustrate by modeling sunspot data with both periodic Matérn and MacKay’s covariance kernel. This shows the exclusive advantage of the new QPGP family proposed in this work.

关键词： Parameter estimation Computational modeling Noise Signal processing algorithms Gaussian processes Mathematical models Data models Kernel Forecasting Speech processing

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Evaluating Cost-Effective Reconfigurable Hardware for Quantum simulation 20th

Evaluating Cost-Effective Reconfigurable Hardware for Quant...

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20th international conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd international conference on Quantum Technologies, ICEQT 2024, and 21st international conference on modeling, simulation and Visualization Methods, MSV 2024, held as part of the World Congress in computer Science, computer Engineering and Applied Computing, CSCE 2024

作者： Islam, Ishraq Jha, Vinayak Nobel, Alvir Levy, David Chaudhary, Manu Kneidel, Dylan Facer, Audrey El-Araby, Esam University of Kansas LawrenceKS66045 United States

ISBN: (纸本)9783031858833

Quantum computing promises to provide significant speedup over classical computing in several important problem domains, which has garnered the attention of many researchers. Yet, developing and executing algorithms on quantum hardware pose economic challenges, especially for individuals and small research groups. Quantum simulators can bridge this gap by enabling researchers to use readily available classical hardware to perform quantum experiments. However, publicly available simulators are often time-shared through cloud-based high performance computing (HPC) environments and are not customizable to the particular needs of the developer. Moreover, local simulators running on consumer-grade CPUs, suffer from prolonged execution times. Therefore, the acceleration and customization of quantum simulations using local and dedicated hardware accelerators such as FPGAs can provide a better developer experience, faster design iteration, and potentially a cost-effective solution for quantum computing research and prototyping. In this paper, we evaluate using cost-effective, commercial-off-the-shelf FPGA boards for quantum application development on standard and full-featured quantum simulation frameworks such as IBM-Qiskit. More specifically, we provide a trade-off study of using FPGAs for such quantum simulation frameworks with respect to performance, resource, and cost requirements. In our experiments, we use commercially available FPGA boards such as the PYNQ-ZU, KV260, and RFSoC 4x2 for simulating resource and compute-intensive multidimensional quantum convolution as a case study. We leverage the performance-cost-ratio (PCR) metric to compare these boards against a server-grade CPU and show that cost-effective reconfigurable hardware can be a practical, accessible, and affordable option for quantum computing research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Quantum computers

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modeling and Lumped-Element Extraction of PCB-Based Laterally Coupled Coplanar Transformers

Modeling and Lumped-Element Extraction of PCB-Based Laterall...

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Thermal, Mechanical and Multiphysics simulation and Experiments in Micro-Electronics and Micro-Systems EuroSimE

作者： Ozberk Ozturk Najeh Zeidi Fares Tounsi Denis Flandre Murat Kaya Yapici Faculty of Engineering and Natural Sciences Sabanci University Istanbul Turkiye ICTEAM Institute UCLouvain Louvain-la-Neuve Belgium Faculty of Engineering and Natural Sciences Sabanci University Istanbul Türkiye Department of Electrical and Computer Engineering University of Washington Seattle USA

ISBN: (数字)9798350393002

ISBN: (纸本)9798350393019

In this paper, we present a comprehensive analysis of concentric and interleaved coplanar transformer models, focusing on key performance parameters such as self-inductance, resistance, mutual inductance, and interwinding capacitance. These parameters are used to develop a lumped-element model that accurately represents the behavior of a coplanar transformer. We propose a universal method based on FEM simulations to extract each parameter value, while the validity of the lumped model is verified by comparisons with measurements obtained from printed circuit board (PCB) transformers and HFSS simulations.

关键词： Resistance Analytical models Inductance Printed circuits Transformers Capacitance Vectors Finite element analysis Thermal analysis Integrated circuit modeling

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Predicting Workload in Virtual Flight simulations Using EEG Spectral and Connectivity Features

Predicting Workload in Virtual Flight Simulations Using EEG ...

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IEEE international conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Bas Verkennis Evy van Weelden Francesca L. Marogna Maryam Alimardani Travis J. Wiltshire Max M. Louwerse Department of Cognitive Science and Artificial Intelligence Tilburg University Tilburg Netherlands Faculty of Science Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

Effective cognitive workload management has a major impact on the safety and performance of pilots. Integrating brain-computer interfaces (BCIs) presents an opportunity for real-time workload assessment. Leveraging cognitive workload data from high-fidelity virtual reality (VR) flight simulations allows for dynamic adjustments to training scenarios. While prior studies have predominantly concentrated on EEG spectral power for workload prediction, delving into intra-brain connectivity may yield deeper insights. This study assessed the predictive value of EEG spectral and connectivity features in distinguishing high vs. low workload periods during simulated flight in VR and Desktop conditions. Using an ensemble approach, a stacked classifier was trained to predict workload from the EEG signals of 52 participants. Results showed that the mean accuracy of the model incorporating both spectral and connectivity features improved by 28% compared to the model that solely relied on spectral features. Further research on other connectivity metrics and deep learning models in a large sample of pilots is essential to validate the potential of a real-time workload-prediction BCI. This could contribute to the development of an adaptive training system for safety-critical operational environments.

关键词： Training Solid modeling Adaptation models Accuracy Aerospace simulation Virtual reality Brain modeling Electroencephalography Real-time systems Brain-computer interfaces

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Using AutomationML for Advanced simulation in Industrial Automation 19thth

Using AutomationML for Advanced Simulation in Industrial A...

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

作者： Fellner, Robert Pal, Ramandeep Orsolits, Horst University of Applied Scieneces Technikum Höchstädtplatz 6 Vienna1200 Austria

ISBN: (纸本)9783031829598

This paper investigates practical strategies for improving manufacturing processes through computer simulations in the domain of industrial automation. The focus is on employing Model-Based Systems Engineering (MBSE), utilizing AutomationML—an XML-based framework—and Visual Components, a tool for simulating industrial processes at the layout and kinematics levels. The study specifically addresses the optimization of the simulation modeling process by examining the integration of AutomationML data into Visual Components. The research involves adapting an existing Visual Components XML-Importer add-on to interpret AutomationML data. This modification allows for the updating of an XML file with information related to the entry station in Visual Components, serving as a illustrative example within a broader mechatronic production system. The findings contribute to the broader MBSE framework by demonstrating a practical application of AutomationML and showcasing its role in enhancing simulation capabilities within industrial processes. Furthermore, this research underlines its potentially valuable contribution to the educational context by facilitating teaching with simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Office automation

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

19th International Conference on Computer Aided Systems Theo...

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

ISBN: (纸本)9783031829598

The proceedings contain 104 papers. The special focus in this conference is on computer Aided Systems Theory. The topics include: Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance;adaptive Combination in Frequency Domain: An Approach for Robust Nonlinear Acoustic Echo Cancellation;using of a Robotic Platform to Detect Acoustic Events for Indoor Environments;modeling Wildlife Accident Risk with Gaussian Mixture Models;towards a Unified Incident Detection and Response System for Autonomous Transportation;edge-Processing of Myoelectric Signals for the Control of Hand and Arm-Prostheses;AI-Driven Gesture and Action Recognition for Learning Medicine Through Virtual Reality;Medical Protocols and AI-Driven Algorithms for Enhanced Monitoring of Cardiac Implantable Electronic Devices;a Survey of Machine Learning Methods for Analyzing Synovitis Arthritis in Human Joints;motion Tracking in Augmented and Mixed Realities for Healthcare and Medicine Applications;advancements and Applications of Medical Human Digital Twin Technology in Cerebral Palsy Diagnosis, Therapy, and Rehabilitation;Transformation of IEC 61131-3 onto an Embedded Platform Using LLVM;machine Learning Based Parameter Estimation of Energy Models in Digital Production Environments;efficient Classification of Live Sensor Data on Low-Energy IoT Devices with Simple Machine Learning Methods;machine Learning Using a Hybrid Quantum Classical Algorithm with Amplitude Data Encoding;quantitative Trend Analysis of Reinforcement Learning Algorithms in Production Systems;Using AutomationML for Advanced simulation in Industrial Automation;AR Digital Twin Demonstrator for Industrial Robotics Education;Accelerating Manual Pick-and-Place Operations with AR-Projected CAD Plans and AI-Assisted Object Recognition;variety Engineering – A Cybernetic Concept with Practical Implications;using a System Archetype to Explore a Business Model for Digital Textile Microfactories;interacting with the Water Cycle -

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

19th International Conference on Computer Aided Systems Theo...

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

ISBN: (纸本)9783031829512

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

19th International Conference on Computer Aided Systems Theo...

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19th international conference on computer Aided Systems Theory, EUROCAST 2024

ISBN: (纸本)9783031838873

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A Multi-Agent Reinforcement Learning Scheme for SFC Placement in Edge Computing Networks

A Multi-Agent Reinforcement Learning Scheme for SFC Placemen...

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international conference on Computing, Networking and Communications (ICNC)

作者： Congzhou Li Zhouxiang Wu Divya Khanure Jason P. Jue Department of Computer Science The University of Texas at Dallas Richardson Texas USA

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

In the 5G era and beyond, it is favorable to deploy latency-sensitive and reliability-aware services on edge computing networks in which the computing and network resources are more limited compared to cloud and core networks but can respond more promptly. These services can be composed as Service Function Chains (SFCs) which consist of a sequence of ordered Virtual Network Functions (VNFs). To achieve efficient edge resources allocation for SFC requests and optimal profit for edge service providers, we formulate the SFC placement problem in an edge environment and propose a multi-agent Reinforcement Learning (RL) scheme to address the problem. The proposed scheme employs a set of RL agents to collaboratively make SFC placement decisions, such as path selection, VNF configuration, and VNF deployment. simulation results show our model can improve the profit of edge service providers by 12% compared with a heuristic solution.

关键词： Cloud computing Service function chaining 5G mobile communication simulation Computational modeling Reinforcement learning Resource management Reliability Edge computing

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AR/VR Digital Twin for simulation and Data Collection of Robotic Environments

AR/VR Digital Twin for Simulation and Data Collection of Rob...

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IEEE international conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： João G. Martins Karle Nutonen Paulo Costa Vladimir Kuts Tauno Otto Armando Sousa Marcelo R. Petry CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal ViruTech - Virumaa innovation center of digitalization and green technologies Taltech Virumaa College Kohtla-Jarve Estonia Department of Mechanical and Indusrial Taltech Tallinn Estonia

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Digital twins enable real-time modeling, simulation, and monitoring of complex systems, driving advancements in automation, robotics, and industrial applications. This study presents a large-scale digital twin-testing facility for evaluating mobile robots and pilot robotic systems in a research laboratory environment. The platform integrates high-fidelity physical and environmental models, providing a controlled yet dynamic setting for analyzing robotic behavior. A key feature of the system is its comprehensive data collection framework, capturing critical parameters such as position, orientation, and velocity, which can be leveraged for machine learning, performance optimization, and decision-making. The facility also supports the simulation of discrete operational systems, using predictive modeling to bridge informational gaps when real-time data updates are unavailable. The digital twin was validated through a matrix manufacturing system simulation, with an Augmented Reality (AR) interface on the HoloLens 2 to overlay digital information onto mobile platform controllers, enhancing situational awareness. The main contributions include a digital twin framework for deploying data-driven robotic systems and three key AR/VR integration optimization methods. Demonstrated in a laboratory setting, the system is a versatile tool for research and industrial applications, fostering insights into robotic automation and digital twin scalability while reducing costs and risks associated with real-world testing.

关键词： Service robots Navigation Metaverse Databases Scalability Digital representation Real-time systems Digital twins Mobile robots Robots

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