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International Conference of the TC Electrimacs Committee, ELECTRIMACS 2024

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

ISBN: (纸本)9783031739200

Nowadays, hybrid AC/DC microgrids (HMG) are growing in popularity because of human needs and their benefits. They are composed of the interconnection of a DC microgrid (MG) and an AC MG, and each MG is constituted by generation, energy storage, and consumption technologies. This study develops a new control strategy for an HMG consisting of a DC MG and an AC MG interconnected through a bidirectional power converter. The AC MG is composed of AC loads, a photovoltaic (PV) generator and a battery bank. The DC MG is made up of a hydrogen system, DC loads, wind turbine (WT) and ultracapacitor (UC). The HMG is evaluated under different conditions in an experimental setup constituted by an OPAL-RT 4512 unit and a Raspberry Pi microcontroller. This experimental setup permits to execute the HMG in real time and to validate the results obtained. Finally, the control system developed for this HMG presents a satisfactory behaviour under different working conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Wind turbines

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Reverse-Engineering Optimization Techniques of High-Level Synthesis: Practical Insights into Accelerating Applications with AMD-Xilinx Vitis

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Koronis, Jorge Garnica, Oscar Hidalgo, J. Ignacio Davila, Juan Lanchares Spain Department of Computer Architecture and Automation Faculty of Computer Science Universidad Complutense de Madrid Spain

Modern AI applications contain computationally expensive sections. Accelerator cards and tools like AMD Vitis HLS leverage high-level synthesis and hardware (HW) optimizations to create custom HW designs to accelerate ***, the learning curve is steep, even for those with previous knowledge of HW design, due to the complexity of the optimization techniques and limited information on their interactions and HW effects. This paper quantitatively analyzes the interactions of optimization techniques after reverse engineering Vitis' optimization directives, both in isolation and in *** 150 experiments were conducted to investigate three distinct goals: assessing pragma behavior and the rules governing pragma application and optimizations, modeling Vitis HLS latency estimates, and evaluating the impact of optimizations on design space exploration, specifically area and latency. These experiments involve different combinations and placements of optimizations in the loop and function hierarchy of the test bench. Our findings offer guidance on using Vitis pragmas and identify promising configurations for optimizing latency and area. © 1982-2012 IEEE.

关键词： Reverse engineering

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Graph-based immune checkpoint inhibitor response prediction model for metastatic renal cell carcinoma patients

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IEEE Access 2025年 13卷 76703-76714页

作者： Alonso, Sandra Hernandez-Lorenzo, Laura Duran, Ignacio Rodriguez, Cristina Garcia-Donas, Jesus Ayala, Jose L. Complutense University of Madrid Department of Computer Architecture and Automation Madrid28040 Spain University Hospital "Marqués de Vadecilla" IDIVAL Department of Medical Oncology Santander39011 Spain Madrid28029 Spain Madrid28050 Spain Technical University of Madrid Center for Computational Simulation Madrid28660 Spain

Immune checkpoint inhibitors (ICIs) have become essential in managing metastatic Renal Cell Carcinoma (mRCC), although selecting the most suitable patients for each specific treatment remains an unmet medical need. In this work, we aimed to create and evaluate a treatment response prediction machine learning model based on tumor gene expression data of patients with mRCC. More specifically, we designed and developed a graph-based prediction model, including information about potential protein-protein interactions (PPI) between the considered expressed genes. For thiswork, we extracted the expression data collected in two different ICIs treatments (nivolumab and avelumab+axitinib) and organized them into two different graph datasets (considering two initial PPI networks: BioGrid and kidney-specific PPT-Ohmnet). Then, we compressed these four different graph datasets with a graph embedding technique (Graph2Vec) and evaluated the embeddings as input for a supervised classification model (Random Forest) to predict the binarized progression-free survival (PFS). Results showed that the Nivolumab and PPT-Ohmnet graph dataset obtained the highest classification performance, with an AUC of 74%. These results suggested that our pipeline could accurately model the response to the drugs, especially those modeling a short-term response (in this case, nivolumab), and that this graph-based approach benefits from tissue-specific networks (kidney-specific PPT-Ohmnet PPI). This work is presented as a data-driven solution towards improving drug selection and identifying different responses to immunotherapy treatments, including poor responses that should be offered alternative therapeutic options. © 2013 IEEE.

关键词： Graph embeddings

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Standardized Post-Quantum Cryptography and Recent Developments in Quantum computers 1

Standardized Post-Quantum Cryptography and Recent Developmen...

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1st International Conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Chib, Shiney Devarajan, Harshitha Raghavan Chundru, Swathi Pulivarthy, Padmaja Isaac, R. Augustian Oku, KrishnaMurthy Meghe Institute of Management Studies Department of Management Datta Maharashtra Nagpur India New York University Department of Computer Science United States Motivity labs INC United States Samsung Korea Republic of Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai602105 India AT&T Services Inc Tech Lead Infrastructure/Cloud Architecture Department of Automation platform Development India

ISBN: (纸本)9798331518578

Traditional cryptographic frameworks are seriously threatened by the quick development of quantum computing, especially those that depend on public-key cryptosystems like RSA and ECC. Post-quantum cryptography (PQC) seeks to create cryptographic methods that are impervious to quantum computer assaults in order to overcome this difficulty. The National Institute of Standards and Technology (NIST), which has selected and standardised quantum-resistant techniques like CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital signatures, has sparked recent advancements in PQC. At the same time, the need for reliable PQC solutions has increased due to developments in quantum computing, such as IBM's improvements in qubit stability and Google's 'quantum supremacy' assertion. In order to protect data security in the post-quantum age, PQC regulations must be adopted globally, as highlighted by the intersection of these fields. Current developments in PQC standardisation and the changing state of quantum computing technology are highlighted in this paper. © 2025 IEEE.

关键词： Quantum cryptography

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Standardized Post-Quantum Cryptography and Recent Developments in Quantum computers

Standardized Post-Quantum Cryptography and Recent Developmen...

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Advances in computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： Shiney Chib Harshitha Raghavan Devarajan Swathi Chundru Padmaja Pulivarthy R. Augustian Isaac KrishnaMurthy Oku Department of Management Datta Meghe Institute of Management Studies Nagpur Maharashtra Department of Computer Science New York University Motivity labs INC Samsung Department of Artificial Intelligence and Machine Learning Saveetha Engineering College Chennai Tamil Nadu Department of Automation platform Development Tech Lead Infrastructure/Cloud Architecture AT&T Services Inc

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Traditional cryptographic frameworks are seriously threatened by the quick development of quantum computing, especially those that depend on public-key cryptosystems like RSA and ECC. Post-quantum cryptography (PQC) seeks to create cryptographic methods that are impervious to quantum computer assaults in order to overcome this difficulty. The National Institute of Standards and Technology (NIST), which has selected and standardised quantum-resistant techniques like CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital signatures, has sparked recent advancements in PQC. At the same time, the need for reliable PQC solutions has increased due to developments in quantum computing, such as IBM's improvements in qubit stability and Google's “quantum supremacy” assertion. In order to protect data security in the post-quantum age, PQC regulations must be adopted globally, as highlighted by the intersection of these fields. Current developments in PQC standardisation and the changing state of quantum computing technology are highlighted in this paper.

关键词： Training Technological innovation Quantum computing Qubit Switches NIST Planning Internet Encryption computer security

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Automated engineered-stone silicosis screening and staging using Deep Learning with X-rays

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computers in Biology and Medicine 2025年 191卷 110153-110153页

作者： Priego-Torres, Blanca Sanchez-Morillo, Daniel Khalili, Ebrahim Conde-Sánchez, Miguel Ángel García-Gámez, Andrés León-Jiménez, Antonio Bioengineering Automation and Robotics Research Group Department of Automation Engineering Electronics and Computer Architecture and Networks School of Engineering University of Cadiz Cádiz Puerto Real11519 Spain Puerta del Mar University Hospital Cádiz11009 Spain Pulmonology Department Puerta del Mar University Hospital Cádiz11009 Spain Radiology Department Puerta del Mar University Hospital Cádiz11009 Spain Radiology Department Puerto Real University Hospital Cádiz Puerto Real11510 Spain

Silicosis, a debilitating occupational lung disease caused by inhaling crystalline silica, continues to be a significant global health issue, especially with the increasing use of engineered stone (ES) surfaces containing high silica content. Traditional diagnostic methods, dependent on radiological interpretation, have low sensitivity, especially, in the early stages of the disease, and present variability between evaluators. This study explores the efficacy of deep learning techniques in automating the screening and staging of silicosis using chest X-ray images. Utilizing a comprehensive dataset, obtained from the medical records of a cohort of workers exposed to artificial quartz conglomerates, we implemented a preprocessing stage for rib-cage segmentation, followed by classification using state-of-the-art deep learning models. The segmentation model exhibited high precision, ensuring accurate identification of thoracic structures. In the screening phase, our models achieved near-perfect accuracy, with ROC AUC values reaching 1.0, effectively distinguishing between healthy individuals and those with silicosis. The models demonstrated remarkable precision in the staging of the disease. Nevertheless, differentiating between simple silicosis and progressive massive fibrosis, the evolved and complicated form of the disease, presented certain difficulties, especially during the transitional period, when assessment can be significantly subjective. Notwithstanding these difficulties, the models achieved an accuracy of around 81% and ROC AUC scores nearing 0.93. This study highlights the potential of deep learning to generate clinical decision support tools to increase the accuracy and effectiveness in the diagnosis and staging of silicosis, whose early detection would allow the patient to be moved away from all sources of occupational exposure, therefore constituting a substantial advancement in occupational health diagnostics. © 2025 The Authors

关键词： Occupational diseases

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The Importance of Being Earnest: Multiple Heterogeneous Container Loading with a Simple Genetic Algorithm

The Importance of Being Earnest: Multiple Heterogeneous Con...

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28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025

作者： Rusin, Francesco Fiala, Jan Sanker, Julian Bhattarai, Suyesh Ekárt, Anikó Department of Engineering and Architecture University of Trieste Trieste Italy Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic Yale College Yale University New Haven United States Mechatherm International Limited Cradley Heath United Kingdom Aston Centre for Artificial Intelligence Research and Application Aston University Birmingham United Kingdom

ISBN: (纸本)9783031900617

In this study we address the complex practical problem of multiple heterogeneous container loading with a simple genetic algorithm. We demonstrate that with a well-chosen representation including a heuristic and a suitable fitness function the other aspects of the genetic algorithm do not need extensive work for good results. Following systematic study of our method on synthetically generated data, we visually showcase the solution for a company-based problem instance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Genetic algorithms

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HGRID: A Self-configuring Grid Resource Discovery

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Journal of Computing and Information Technology 2008年第4期16卷 333-338页

作者： Gallardo, Antonia de Cerio, Luis Diaz Sanjeevan, Kana Department of Computer Architecture Polytechnic University of Catalonia Barcelona Spain Department of Automation and Computer Science Public University of Navarre Pamplona Spain

Grid Resource Discovery Service is a fundamental problem that has been the focus of research in the recent past. We propose a scheme that presents essential characteristics for efficient, self-configuring and fault-tolerant resource discovery able to handle dynamic attributes such as memory capacity. Our approach consists of an overlay network with a hypercube topology connecting the grid nodes and a scalable, fault-tolerant, self-configuring search algorithm. By design, the algorithm improves the probability of reaching all working nodes in the system, even in the presence of non-alive nodes (inaccessible, crashed or nodes loaded by heavy traffic). We analyze the static resilience of the approach presented, which is the measure of how well the algorithm can discover resources without having to update the routing tables. The results show that the presented approach has significantly high static resilience. © 2008, University of Zagreb Faculty of Electrical Engineering and Computing. All rights reserved.

关键词： Fault tolerance

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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： Fredy Barrientos-Espillco Gonzalo Pajares José A. López-Orozco Eva Besada-Portas Department of Computer Architecture and Automation University Complutense of Madrid 28040 Madrid Spain Institute for Knowledge Technology University Complutense of Madrid 28040 Madrid 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.

关键词： Artificial intelligence Machine vision systems Text-to-image generation Fine-tuning Large language model Convolutional neural networks Autonomous surface vehicles Cyanobacterial blooms

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A framework for reconfigurable computing: Task scheduling and context management - A summary

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IEEE Circuits and Systems Magazine 2002年第4期2卷 48-51页

作者： Maestre, Rafael Kurdahi, Fadi J. Fernández, Milagros Hermida, Román Bagherzadeh, Nader Singh, Hartej DSP Firmware Group Morpho Technologies Department of Electrical and Computer Engineering University of California Irvine Department of Computer Architecture and Automation Facultad de Informatica Complutense University Department of Computer Architecture and Automation Complutense University Madrid Department of Electrical and Computer Engineering Henry Samueli School of Engineering University of California Irvine IEEE

Dynamically reconfigurable architectures are emerging as a viable design alternative to implement a wide range of computationally intensive applications. At the same time, an urgent necessity has arisen for support tool development to automate the design process and achieve optimal exploitation of the architectural features of the system. Task scheduling and context (configuration) management become very critical issues in achieving the high performance that digital signal processing (DSP) and multimedia applications demand. This article proposes a strategy to automate the design process which considers all possible optimizations that can be carried out at compilation time, regarding context and data transfers. This strategy is general in nature and could be applied to different reconfigurable systems. We also discuss the key aspects of the scheduling problem in a reconfigurable architecture such as MorphoSys. In particular, we focus on a task scheduling methodology for DSP and multimedia applications, as well as the context management and scheduling optimizations.

关键词： Computation theory

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