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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

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. © 2024 IEEE.

关键词： Lakes

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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

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. © 2024 IEEE.

关键词： Viscosity measurement

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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

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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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Simulation Winter 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: (数字)9798331534202

ISBN: (纸本)9798331534219

关键词： Geometry Adaptation models Solid modeling Three-dimensional displays Cyanobacteria Water quality Lakes Hydrodynamics Water resources Strain

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Acceleration and energy consumption optimization in cascading classifiers for face detection on low-cost ARM *** asymmetric architectures

arXiv

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arXiv 2024年

作者： Corpas, Alberto Costero, Luis Botella, Guillermo Igual, Francisco D. García, Carlos Rodríguez, Manuel Dept. of Architecture and Computer Technology ETSIIT University of Granada Granada18071 Spain Dept. Computer Architecture and Automation Complutense University of Madrid Madrid28040 Spain

This paper proposes a mechanism to accelerate and optimize the energy consumption of a face detection software based on Haar-like cascading classifiers, taking advantage of the features of low-cost Asymmetric Multicore Processors (AMPs) with limited power budget. A modelling and task scheduling/allocation is proposed in order to efficiently make use of the existing features on *** ARM processors, including: (I) source-code adaptation for parallel computing, which enables code acceleration by applying the OmpSs programming model, a task-based programming model that handles data-dependencies between tasks in a transparent fashion;(II) different OmpSs task allocation policies which take into account the processor asymmetry and can dynamically set processing resources in a more efficient way based on their particular features. The proposed mechanism can be efficiently applied to take advantage of the processing elements existing on low-cost and low-energy multi-core embedded devices executing object detection algorithms based on cascading classifiers. Although these classifiers yield the best results for detection algorithms in the field of computer vision, their high computational requirements prevent them from being used on these devices under real-time requirements. Finally, we compare the energy efficiency of a heterogeneous architecture based on asymmetric multicore processors with a suitable task scheduling, with that of a homogeneous symmetric architecture. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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Control of Microgrid Cluster Using Raspberry Pi

Control of Microgrid Cluster Using Raspberry Pi

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Carrasco-González, David Sarrias-Mena, Raúl Horrillo-Quintero, Pablo Llorens-Iborra, Francisco Fernández-Ramírez, Luis M. Suret Research Group Department of Electrical Engineering Algeciras Spain Uca Suret Reseach Group Dept. of Engineering in Automation Electronics and Computer Architecture and Networks Algeciras Spain

ISBN: (纸本)9781665471640

Currently, microgrid clusters (MGC) are being increasingly used owing to their benefits and human needs. MGs can be composed of power generation, consumption, and storage elements. They permit the combination of DC and AC technologies, even for a single microgrid (MG). In this paper, a new control system of a MGC consisting of two MGs connected to the main grid is developed. One of them is a DC MG that is composed of a wind turbine (WT), electrolyzer (EZ), ultracapacitor (UC), fuel cell (FC) and DC loads. The other MG is an AC MG, which is made up of a PV generator, a battery bank and AC loads. The MGC is tested under different working conditions in an experimental setup composed of a Raspberry Pi microcontroller, an OPAL-RT 4510 unit and a PC host. The experimental setup allows the system to run in real time and validate the results obtained. Finally, the control system implemented in the MGC exhibits a correct behaviour under different conditions, according to the results obtained. © 2023 IEEE.

关键词： energy management system Microgrid cluster Raspberry Pi real-time simulation

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A Suite of Division Algorithms for Posit Arithmetic

A Suite of Division Algorithms for Posit Arithmetic

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International Conference on Application Specific Systems (ASAP), architectures and Processors

作者： Raul Murillo Alberto A. Del Barrio Guillermo Botella Dept. of Computer Architecture and Automation Faculty of Physics University of Madrid Madrid Spain Dept. of Computer Architecture and Automation Faculty of Computer Science Complutense University of Madrid Madrid Spain

Posit ™ arithmetic is a promising alternative to IEEE 754 floating-point arithmetic due to its higher accuracy, larger dynamic range, and bitwise compatibility. While posit arithmetic has been well studied for basic arithmetic operations, division has received little attention. This paper proposes multiple divider designs for posit arithmetic based on digit recurrence and iterative approximation, and evaluates their performance. ASIC synthesis results show that the proposed designs significantly reduce hardware requirements for 32-bit division units compared to previous works by 1.14 × in area, 1.11× in power, and 1.04×in datapath delay. Moreover, the paper introduces an approximate logarithmic posit division that achieves an 8.8×reduction in area and 29×reduction in energy consumption with negligible degradation of the final results, making it suitable for error-tolerant applications.

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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 ...

引用

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

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

arXiv

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arXiv 2024年

关键词： Viscosity measurement

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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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Simulation Winter Conference

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

关键词： Deep learning Viscosity Accuracy Prototypes Life estimation Pressure measurement Polymers Microfluidics Testing Synthetic data

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