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arXiv 2023年

作者： Carrascal, Gines Roman, Beatriz Botella, Guillermo del Barrio, Alberto Department of Informatic Systems and Computation Faculty of Informatics Complutense University of Madrid Madrid28040 Spain IBM Quantum IBM Consulting España Madrid28830 Spain Data Science PwC España Madrid28830 Spain Department of Computer Architecture and Automation Faculty of Informatics Complutense University of Madrid Madrid28040 Spain

Crypto-currency markets are known to exhibit inefficiencies, which presents opportunities for profitable cyclic transactions or arbitrage, where one currency is traded for another in a way that results in a net gain without incurring any risk. Quantum computing has shown promise in financial applications, particularly in resolving optimization problems like arbitrage. In this paper, we introduce a differential evolution (DE) optimization algorithm for Variational Quantum Eigensolver (VQE) using Qiskit framework. We elucidate the application of crypto-currency arbitrage using different VQE optimizers. Our findings indicate that the proposed DE-based method effectively converges to the optimal solution in scenarios where other commonly used optimizers, such as COBYLA, struggle to find the global minimum. We further test this procedure’s feasibility on IBM’s real quantum machines up to 127 qubits. With a three-currency scenario, the algorithm converged in 417 steps over a 12-hour period on the "ibm_geneva" machine. These results suggest the potential for achieving a quantum advantage in solving increasingly complex *** Codes 49 © 2023, CC BY.

关键词： Global optimization

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Pathways for Efficient Transition into Net Zero Energy Buildings (Nzeb) in Sub-Saharan Africa. Case Study: Cameroon, Senegal, and Côte D’Ivoire

SSRN

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SSRN 2023年

作者： Umaru Mohammed, Bongwirnso Wiysahnyuy, Yufenyuy Severine Ashraf, Noman Mempouo, Blaise Mengata, Ghislain Mengounou Department of Building Engineering College of Architecture and Planning Imam Abdulrahman Bin Faisal University Dammam31451 Saudi Arabia Laboratory of Computer Science Engineering and Automation University of Douala Cameroon Smart Green Shift Ltd Rotherham United Kingdom Laboratory of Technology and Applied Sciences University of Douala Cameroon

The combustion of fossil fuels to generate electricity to meet up with high energy demands of buildings, increases pollution;deteriorating the environment and accelerating climate change. The idea of net zero energy buildings (nZEB) was developed to reduce building energy use and pollution. However, there are still many obstacles to implementing the nZEB idea, notably in sub-Saharan Africa, where energy consumption and pollutant emissions from buildings are particularly high. This article focuses on Cameroon, Senegal, and Côte d'Ivoire and proposes guidelines for making a smooth transition to nZEB in sub-Saharan Africa, as are examples of strategies that might be used to minimize energy consumption in buildings and pollution. The path has been shown to consist of the following steps: conducting a baseline assessment;creating building energy codes and standards;conducting a stakeholder analysis;carrying out capacity building and awareness-raising;setting up financing mechanisms and incentives;creating a strong supply chain;setting up a monitoring and evaluation framework;piloting nZEB projects;disseminating best practices;and scaling up adoption. With this plan in place, sub-Saharan Africa can make the most of its resources while preserving the environment as it makes the move to nZEB © 2023, The Authors. All rights reserved.

关键词： Energy utilization

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Lock-Free Simulation Algorithm to Enhance the Performance of Sequential and Parallel Devs Simulators in Shared-Memory architectures

SSRN

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SSRN 2024年

作者： Cárdenas, Román Arroba García, Patricia Risco-Martín, José Luis Department of Electronics Engineering Universidad Politécnica de Madrid Avenida Complutense 30 Madrid Madrid28040 Spain Center for Computational Simulation Universidad Politécnica de Madrid Campus de Montegancedo Boadilla del Monte Madrid28660 Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Calle Profesor José García Santesmases 9 Madrid Madrid28040 Spain

This paper presents a new algorithm for the Discrete EVent System Specification (DEVS) formalism that improves the performance of simulating complex systems by reducing the number of iterations through the model components in each simulation step. It also minimizes unnecessary visits to model components by propagating simulation routines only when necessary. Additionally, we provide two parallel versions of this new simulation algorithm that use work-stealing scheduling and avoid locking mechanisms without compromising the validity of the execution in shared-memory architectures. We implemented the proposed algorithms in the xDEVS simulator and evaluated their performance using the DEVStone synthetic benchmark. The results show that the proposed algorithms outperform state-of-the-art alternatives. For computationally intensive models, parallel implementations achieve high parallelism efficiency. Furthermore, they are more resilient to model complexity than the sequential algorithm, showing better performance for complex models even without computational overhead in state transition functions. © 2024, The Authors. All rights reserved.

关键词： Discrete event simulation

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Ultracolor Multiplexing in QR Codes for Data Encryption and Transmission

Ultracolor Multiplexing in QR Codes for Data Encryption and ...

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2024 Frontiers in Optics, FiO 2024

作者： Ignacio-Cerrato, Sara Pacios, David Rodríguez, José Miguel Ezquerro Vázquez-Poletti, José Luis Mariño, María Estefanía Avilés Stravakakis, Konstantinos Di Iorio, Alessio Cesarano, Clemente Schetakis, Nikolaos Optics Department Faculty of Optics and Optometry Universidad Complutense de Madrid Calle Arcos de Jalón 118 Madrid28037 Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain Alma Sistemi Srl Guidonia Rome00012 Italy Section of Mathematics International Telematic University Uninettuno Corso Vittorio Emanuele II 39 Rome Italy Departamento de Lingüística Aplicada a la Ciencia y a la Tecnología Universidad Politécnica de Madrid Calle de José Gutiérrez Abascal 2 Madrid28006 Spain Computational Mechanics and Optimization Laboratory School of Production Engineering and Management Technical University of Crete Chania73100 Greece Quantum Innovation Pc Chania73100 Greece

This paper introduces an innovative encryption method using ultracolor codification via the Prism Algorithm, which effectively encodes large data volumes into images with base64 encoding, demonstrating practical reliability and potential for secure data transmission. © Optica Publishing Group 2024, © 2024 The Author(s)

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Toward Ultra-Low-Power Remote Health Monitoring: An Optimal and Adaptive Compressed Sensing Framework for Activity Recognition

arXiv

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arXiv 2023年

作者： Pagán, Josué Fallahzadeh, Ramin Pedram, Mahdi Risco-Martín, José L. Moya, José M. Ayala, José L. Ghasemzadeh, Hassan Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain School of Electrical Engineering and Computer Science Washington State University PullmanWA99164 United States Universidad Politécnica de Madrid Madrid28040 Spain Center for Computational Simulation Universidad Politécnica de Madrid Campus de Montegancedo Boadilla del Monte Madrid28660 Spain

Activity recognition, as an important component of behavioral monitoring and intervention, has attracted enormous attention, especially in Mobile Cloud Computing (MCC) and Remote Health Monitoring (RHM) paradigms. While recently resource constrained wearable devices have been gaining popularity, their battery life is limited and constrained by the frequent wireless transmission of data to more computationally powerful back-ends. This paper proposes an ultra-low power activity recognition system using a novel adaptive compressed sensing technique that aims to minimize transmission costs. Coarse-grained on-body sensor localization and unsupervised clustering modules are devised to autonomously reconfigure the compressed sensing module for further power saving. We perform a thorough heuristic optimization using Grammatical Evolution (GE) to ensure minimal computation overhead of the proposed methodology. Our evaluation on a real-world dataset and a low power wearable sensing node demonstrates that our approach can reduce the energy consumption of the wireless data transmission up to 81.2% and 61.5%, with up to 60.6% and 35.0% overall power savings in comparison with baseline and a naive state-of-the-art approaches, respectively. These solutions lead to an average activity recognition accuracy of 89.0%—only 4.8% less than the baseline accuracy—while having a negligible energy overhead of on-node computation. © 2023, CC BY-SA.

关键词： Optimization

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Customization of the text-to-image diffusion model by fine-tuning for the generation of synthetic images of cyanobacterial blooms in lentic water bodies

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Expert Systems with Applications 2025年 287卷

作者： Barrientos-Espillco, Fredy Pajares, Gonzalo López-Orozco, José A. Besada-Portas, Eva Department of Computer Architecture and Automation University Complutense of Madrid Madrid28040 Spain Institute for Knowledge Technology University Complutense of Madrid Madrid28040 Spain

Cyanobacterial blooms emerge unpredictably on the surface of lentic water bodies, posing both ecological threats and public health risks. To effectively monitor these events, this study introduces the use of Machine Vision Systems (MVS) integrated into Autonomous Surface Vehicles (ASVs). These ASVs are capable of autonomous and safe navigation, enabling them to detect cyanobacterial blooms while avoiding obstacles. Convolutional Neural Networks (CNNs) are employed for early detection and continuous monitoring, but their effectiveness hinges on access to large, high-quality training datasets. Due to the sporadic and uncontrollable nature of bloom occurrences, acquiring sufficient real-world images for training and validating CNN models is a significant challenge. To overcome this, the Stable Diffusion XL (SDXL) text-to-image generative model is utilized to produce realistic synthetic images, ensuring a sufficient dataset for training. However, SDXL alone struggles to accurately depict cyanobacterial blooms. To address this limitation, DreamBooth is used to fine-tune SDXL with a small set of real bloom-specific image patches. To ensure the diversity of the synthetic dataset, detailed prompts for SDXL are generated using a Large Language Model (LLM). The combination of SDXL fine-tuning with LLM-driven prompts design applied to environmental monitoring and autonomous navigation in lentic environments represents the core innovation of this work. A dual-task CNN model is then trained on the synthetic dataset to simultaneously detect blooms and obstacles. Experimental results demonstrate the effectiveness and novelty of the proposed approach, showing improvements of up to 15.74% in object detection and 6.48% in semantic segmentation compared to the baseline dataset. © 2025 The Author(s)

关键词： Convolutional neural networks

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A cluster of FPAAs to recognize images using neural networks

TechRxiv

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TechRxiv 2021年

作者： Daniel, García Moreno Alberto, Del Barrio A. Guillermo, Botella Jennifer, Hasler The Department of Computer Architecture and Automation Complutense University of Madrid Madrid28040 Spain Georgia Institute of Technology GA Atlanta30332-0250 United States

Analog computing has been recovering its relevance in the recent years. FPAAs are the equivalent to FPGAs but in the analog domain. The main drawback of FPAAs is their reduced integration capacity. In order to increase the amount of analog resources, in this paper a cluster of 40 FPAAs is proposed. As a use case, a 19-8-6-4 feedforward Neural Network has been implemented on such cluster. With the help of a DCT-based software framework, this NN is able to classify 28x28 MNIST images. Results show that the analog network is able to obtain almost the same results as the software baseline network. I © 2021, CC BY-NC-SA.

关键词： computer programming

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Customized Posit Adders and Multipliers using the FloPoCo Core Generator

Customized Posit Adders and Multipliers using the FloPoCo Co...

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IEEE International Symposium on Circuits and Systems (ISCAS)

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

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

The posit number system, which is proposed as a replacement of IEEE floating-point numbers, is in the spotlight of Arithmetic research due to the recent breakthroughs. This format claims to provide more accurate results with the same bitwidth than standard floating point, but the run-time variability during the detection of the posit fields involves a hardware design challenge. In this work, we propose parameterized designs for multiple posit functional units, including addition and multiplication, and integrate them as templates of the FloPoCo framework. The integration of the proposed algorithms within FloPoCo can provide synthesizable VHDL code for posit arithmetic of any possible configuration 〈n, es〉. Experiments show an improvement in terms of area and energy with respect to state-of-the-art works up to 35.9% and 30.8%, respectively.

关键词： Decoding Encoding Standards Hardware Detectors Data mining Open area test sites

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Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior

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Psychoradiology 2021年第1期1卷 23-41页

作者： Xi Jiang Tuo Zhang Shu Zhang Keith MKendrick Tianming Liu School of Life Science and Technology MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Automation Northwestern Polytechnical UniversityXi’an 710129China Center for Brain and Brain-Inspired Computing Research School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710129China Cortical Architecture Imaging and Discovery Laboratory Department of Computer Science and Bioimaging Research CenterThe University of GeorgiaAthensGA 30605USA

Folding of the cerebral cortex is a prominent characteristic of mammalian *** or deficits in cortical folding are strongly correlated with abnormal brain function,cognition,and ***,a precise mapping between the anatomy and function of the brain is critical to our understanding of the mechanisms of brain structural architecture in both health and *** and sulci,the standard nomenclature for cortical anatomy,serve as building blocks to make up complex folding patterns,providing a window to decipher cortical anatomy and its relation with brain *** efforts have been devoted to this research topic from a variety of disciplines including genetics,cell biology,anatomy,neuroimaging,and neurology,as well as involving computational approaches based on machine learning and artificial intelligence ***,despite increasing progress,our understanding of the functional anatomy of gyro-sulcal patterns is still in its *** this review,we present the current state of this field and provide our perspectives of the methodologies and conclusions concerning functional differentiation between gyri and sulci,as well as the supporting information from genetic,cell biology,and brain structure *** particular,we will further present a proposed framework for attempting to interpret the dynamic mechanisms of the functional interplay between gyri and ***,this review will provide a comprehensive summary of anatomo-functional relationships in the cortical gyro-sulcal system together with a consideration of how these contribute to brain function,cognition,and behavior,as well as to mental disorders.

关键词： cortical folding gyro-sulcal pattern brain anatomo-function

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