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检索条件"机构=Dept. Computer Architecture and Automation"

共 45 条记录，以下是1-10 订阅

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A Lake Cyanobacteria Colony Dynamics Simulation Supported by Sph 24

A Lake Cyanobacteria Colony Dynamics Simulation Supported by...

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Proceedings of the Winter Simulation Conference

作者： Samuel Ferrero-Losada José L. Risco-Martín José A. López-Orozco Eva Besada-Portas Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain

ISBN: (纸本)9798331534202

Addressing the prediction of Harmful Cyanobacterial Blooms (CyanoHABs) is critical due to the increasing strain on global water resources from climate change and overexploitation. This paper introduces a combined physical and biological modeling approach for simulating the 3D migration, growth, and decay of cyanobacteria colonies in water bodies. Utilizing the Smoothed Particle Hydrodynamics (SPH) method, our model accommodates complex geometries with high accuracy. This adaptable open-source framework significantly enhances the simulation of cyanobacteria migration in three dimensions, a capability often lacking in existing environmental lake simulators. Moreover, it is being integrated into an advanced early warning system, representing a digital twin of the water body. This integration aims to improve the prediction and management of CyanoHABs, contributing to safeguard water quality and ecosystem health.

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Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics 24

Methodology for Online Estimation of Rheological Parameters ...

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Proceedings of the Winter Simulation Conference

作者： Juan Sandubete-López José L. Risco-Martín Alexander H. McMillan Eva Besada-Portas Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid SPAIN and Microfluidics Innovation Center Paris FRANCE Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid SPAIN Microfluidics Innovation Center Paris FRANCE

ISBN: (纸本)9798331534202

Microfluidic devices are increasingly used in biological and chemical experiments due to their cost-effectiveness for rheological estimation in fluids. However, these devices often face challenges in terms of accuracy, size, and cost. This study presents a methodology, integrating deep learning, modeling and simulation to enhance the design of microfluidic systems, used to develop an innovative approach for viscosity measurement of polymer melts. We use synthetic data generated from the simulations to train a deep learning model, which then identifies rheological parameters of polymer melts from pressure drop and flow rate measurements in a microfluidic circuit, enabling online estimation of fluid properties. By improving the accuracy and flexibility of microfluidic rheological estimation, our methodology accelerates the design and testing of microfluidic devices, reducing reliance on physical prototypes, and offering significant contributions to the field.

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A LAKE CYANOBACTERIA COLONY DYNAMICS SIMULATION SUPPORTED BY SPH

A LAKE CYANOBACTERIA COLONY DYNAMICS SIMULATION SUPPORTED BY...

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2024 Winter Simulation Conference, WSC 2024

作者： Ferrero-Losada, Samuel Risco-Martín, José L. López-Orozco, José A. Besada-Portas, Eva Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain

ISBN: (纸本)9798331534202

关键词： Lakes

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A performance/cost model for a CUDA drug discovery application on physical and public cloud infrastructures

A performance/cost model for a CUDA drug discovery applicati...

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作者： Guerrero, Ginés D. Wallace, Richard M. Vázquez-Poletti, José L. Cecilia, José M. García, José M. Mozos, Daniel Pérez-Sánchez, Horacio Dept. of Computer Architecture University of Murcia 30080 Murcia Spain Dept. of Computer Architecture and Automation Complutense University of Madrid 28040 Madrid Spain Dept. of Computer Science Catholic University of Murcia 30107 Murcia Spain

Virtual Screening (VS) methods can considerably aid drug discovery research, predicting how ligands interact with drug targets. BINDSURF is an efficient and fast blind VS methodology for the determination of protein binding sites, depending on the ligand, using the massively parallel architecture of graphics processing units(GPUs) for fast unbiased prescreening of large ligand databases. In this contribution, we provide a performance/cost model for the execution of this application on both local system and public cloud infrastructures. With our model, it is possible to determine which is the best infrastructure to use in terms of execution time and costs for any given problem to be solved by BINDSURF. Conclusions obtained from our study can be extrapolated to other GPU-based VS methodologies. Copyright © 2013 John Wiley & Sons, Ltd.

关键词： Ligands

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METHODOLOGY FOR ONLINE ESTIMATION OF RHEOLOGICAL PARAMETERS IN POLYMER MELTS USING DEEP LEARNING AND MICROFLUIDICS

METHODOLOGY FOR ONLINE ESTIMATION OF RHEOLOGICAL PARAMETERS ...

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2024 Winter Simulation Conference, WSC 2024

作者： Sandubete-López, Juan Risco-Martín, José L. McMillan, Alexander H. Besada-Portas, Eva Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain Microfluidics Innovation Center Paris France

ISBN: (纸本)9798331534202

关键词： Viscosity measurement

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A study on the parallelization of moeas to predict the patient’s response to the onabotulinumtoxina treatment 51

A study on the parallelization of moeas to predict the patie...

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51st Summer computer Simulation Conference, SCSC 2019, Held at the Summer Simulation Conference, SummerSim 2019

作者： Bravo, Franklin Parrales Del Barrio, Alberto A. Ayala, José Luis Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain

This work deals with the decrease of the computational cost in the task of feature weighting for the predictive models of the response to the treatment of migraine with OnabotulinumtoxinA (BoNT-A). More specifically, we consider the multiobjective evolutionary algorithms (MOEAs) that support parallelization. All this with the aim of improving the training times of predictive models of response to the treatment. The results obtained show that accuracies close to 84 % are obtained while training times are decreased from 8 to less than 2 hours when using 8 threads. All in all, this work remarkably reduces the feature weighting execution time in comparison with Simulated Annealing, while getting similar values of accuracy. © 2019 Society for Modeling & Simulation International (SCS).

关键词： Simulated annealing

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Advanced migraine prediction hardware system 50

Advanced migraine prediction hardware system

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50th Summer computer Simulation Conference, SCSC 2018, Part of the 2018 Summer Simulation Multi-Conference, SummerSim 2018

作者： Henares, Kevin Pagán, Josué Ayala, José L. Risco-Martín, José L. Dept. of Computer Architecture and Automation Complutense University of Madrid Madrid Spain Electronic Engineering Department Universidad Politécnica de Madrid Spain CCS-Center for Computational Simulation Madrid Spain Dept. of Computer Architecture and Automation Complutense University of Madrid CCS-Center for Computational Simulation Madrid Spain

ISBN: (纸本)9781510860209

Migraine is one of the most disabling neurological diseases. Its prevalence reaches 15% of the population in developed countries and lead to high economic costs for private and national health systems. There is no cure for the migraine yet. Objective and accurate migraine prediction turns necessary in order to increase the effectiveness of the current treatments. To tackle this problem authors demonstrated in previous works the feasibility of the migraine modeling and presented a DEVS-based model for migraine prediction in a real time framework. This work presents the first step to bring migraine predictive models and simulations to real devices for the first time in the literature. To do this, the DEVS-based model has been ported to a robust hardware description language (VHDL) to be implemented into a FPGA. This paper leads to the final stage: the physical implementation of a predictive migraine monitoring device. © 2018 Society for Modeling & Simulation International (SCS).

关键词： Field programmable gate arrays (FPGA)

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Unit testing platform to verify devs models

Unit testing platform to verify devs models

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2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： Henares, Kevin Risco-Martín, José L. Ayala, José L. Hermida, Román Dept. of Computer Architecture and Automation Complutense University of Madrid Calle Prof. José García Santesmases 9 Madrid28040 Spain

ISBN: (纸本)9781713819462

The natural progression from classic Model-Based Systems Engineering (MBSE) methodologies to Modeling and Simulation-Based Systems Engineering (M&SBSE) brings the need for more flexible and powerful validation tools. Completing the structure and descriptions of static models with self-diagnosis greatly facilitates the development, implementation, and validation of complex models. However, current simulation development environments and libraries often lack providing complete tools to validate these complex models straightforwardly and with the proper level of detail. In this article, we tackle this issue transferring one of the traditional software testing methods, unit testing, to the modeling and simulation field. To this end, we integrate a unit-testing method to the DEVS methodology, allowing the specification of expected states, outcomes, and behaviors of the simulation modules in an XML-based syntax, in all the levels of the hierarchical design. As a result, this methodology enables the generation of powerful and easy-readable verification files. ©2020 Society for Modeling & Simulation International (SCS)

关键词： Systems engineering

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A combination of evolutionary algorithm and mathematical programming for the 3D thermal-aware floorplanning problem 11

A combination of evolutionary algorithm and mathematical pro...

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13th Annual Genetic and Evolutionary Computation Conference, GECCO 2011

作者： Cuesta, David Risco-Martín, José L. Ayala, José L. Hidalgo, J. Ignacio Dept. of Computer Architecture and Automation Universidad Complutense de Madrid C/ Prof. José García Santesmases s/n 28040 Madrid Spain

ISBN: (纸本)9781450305570

1Heat removal and power density distribution delivery have become two major reliability concerns in 3D stacked technology. Additionally, the placement of Through-Silicon-Vias (TSVs) for connecting different layers is one of the key issues in 3D technology. Although a few recent works have considered thermal-aware placement of cores in chip multiprocessor architectures, the concepts of 3D and TSVs have not been conveniently incorporated. Therefore, new suitable exploration methods for the 3D thermal-aware floorplaning problem need to be developed. In this paper we analyze the benefits of two different exploration techniques for the floorplanning problem: Multi-Objective Genetic Algorithm (MOGA) and a Mixed Integer Linear Program (MILP). We present a novel algorithm that uses MILP to minimize average temperature in the 3D chip, whereas uses MOGA to insert TSVs, connecting the layers while the total wire length is minimized. Our experiments with two different 3D chips show that our algorithm achieves 10% reduction in the maximum temperature and thermal gradient. Copyright 2011 ACM.

关键词： Multiobjective optimization

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Emotion detection in infants using an ensemble classifier with a novel member selection technique

Emotion detection in infants using an ensemble classifier wi...

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2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： Fahmy, Hesham Ahmed Fahmy, Sherif Fadel Del Barrio García, Alberto A. Juan, Guillermo Botella Dept. of Electronics and Communications Dept. of Computer Engineering Arab Academy for Science Technology and Maritime Transport 2401 Smart Village Campus Giza12577 Egypt Dept. of Computer Architecture and Automation Complutense University of Madrid Ciudad Universitaria C/ Jose Santesmases 9 Madrid28040 Spain

ISBN: (纸本)9781713819462

In this paper, we develop a method for detecting infant emotion from images using machine learning techniques. It is important to develop automatic infant emotion detection algorithms as they can become part of an integrated system that monitors the well-being of infants at home and in institutional settings. In particular, we develop an ensemble classifier that combines the results from diverse individual classifiers to produce better classification results. We present a novel method for selecting members of the ensemble that is based on the Pearson correlation coefficient of the location of the errors in the classifiers. The results show that the ensemble classifier outperforms individual classifiers by at least 1.4 times, and outperforms a state-of-the-art open-source algorithm for adult emotion detection by a larger margin. The results also indicate that Pearson Correlation among classifiers at a certain number of classifier count is a good criterion for selecting ensemble members. ©2020 Society for Modeling & Simulation (SCS) International

关键词： Machine learning

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