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A methodology to automatically optimize dynamic memory managers applying grammatical evolution

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arXiv 2024年

作者： Risco-Martín, José L. Colmenar, J. Manuel Hidalgo, J. Ignacio Lanchares, Juan Díaz, Josefa Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain C. E. S. Felipe II Universidad Complutense de Madrid Aranjuez28300 Spain C.U. Mérida Universidad de Extremadura Mérida06800 Spain

Modern consumer devices must execute multimedia applications that exhibit high resource utilization. In order to efficiently execute these applications, the dynamic memory subsystem needs to be optimized. This complex task can be tackled in two complementary ways: optimizing the application source code or designing custom dynamic memory management mechanisms. Currently, the first approach has been well established, and several automatic methodologies have been proposed. Regarding the second approach, software engineers often write custom dynamic memory managers from scratch, which is a difficult and error-prone work. This paper presents a novel way to automatically generate custom dynamic memory managers optimizing both performance and memory usage of the target application. The design space is pruned using grammatical evolution converging to the best dynamic memory manager implementation for the target application. Our methodology achieves important improvements (62.55% and 30.62% better on average in performance and memory usage, respectively) when its results are compared to five different general-purpose dynamic memory managers. © 2024, CC BY-SA.

关键词： Genetic programming

Evaluating the Inertia of the Jordanian Power Grid

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SSRN

SSRN 2023年

作者： Alnawafah, Hamza Sarrias-Mena, Raúl Harb, Ahmad Fernández-Ramírez, Luis M. Llorens-Iborra, Francisco Department of Electrical Engineering Higher Technical School of Engineering of Algeciras University of Cadiz Algeciras11202 Spain Department of Engineering in Automation Electronics and Computer Architecture & Networks University of Cadiz Higher Technical School of Engineering of Algeciras Algeciras11202 Spain Amman Jordan

The increasing penetration of renewable energy sources in power grids has resulted in the need for a comprehensive evaluation of their impact on the dynamic behavior of the power system, including its inertia. This study aims to evaluate the inertia of the current Jordanian power system at different penetration levels of renewable energy sources. The study was conducted using DIgSILENT PowerFactory simulation software, and the results were analyzed to determine the effect of renewable energy penetration on the inertia of the power system. The results of this study provide valuable information for the development of control strategies for integrating renewable energy sources into the Jordanian power system, ensuring stability and reliability in the power system operation. The findings of this study contribute to the understanding of the impact of renewable energy sources on power system inertia, and support the development of renewable energy integration strategies. © 2023, The Authors. All rights reserved.

关键词： computer software

A preliminary study about gender gap perception in informatics studies in Spain 12

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A preliminary study about gender gap perception in informati...

12th International Conference on Virtual Campus, JICV 2022

作者： Garcia-Holgado, Alicia Gonzalez-Gonzalez, Carina S. Fernandez, Inmaculada Garcia Lopez, Lourdes Moreno Barrenechea, Edurne Rueda, Silvia Navarro, Angeles G. Martinez, Paloma Masia, Belen Navarro, Elena Fornes, Alicia Grial Research Group Universidad DeSalamanca Computer Science and Automation Department Salamanca Spain University of la Laguna Computer Engineering Department San Cristobal de La Laguna Spain Universidad de Málaga Computer Architecture Department Málaga Spain Universidad Carlos Iii de Madrid Computer Science and Engineering Department Madrid Spain Universidad Pública de Navarra Departamento de Estadística Informática y Matemáticas Pamplona Spain Universitat de València Departament of Computer Science Valencia Spain Universidad de Zaragoza Computer Science Department Zaragoza Spain Universidad de Castilla la Mancha Departament of Computing Systems Albacete Spain Computer Vision Center Universitat Autónoma de Barcelona Barcelona Spain

ISBN: (数字)9781665451062

ISBN: (纸本)9781665451062

The gender gap in STEM is an issue that affects regions and countries worldwide. Furthermore, the percentage of women in these areas depends on a range of different factors. In particular, the gender gap is critical in technology in general and, more specifically, in informatics. This problem affects not only the business sector but also society. Informatics is part of our lives;however, 50% of the world population is not represented in the teams that are developing solutions for solving society's problems. In Spain, the number of women with informatics degrees is around 15%. This work describes a case study developed by the committee of Women in Informatics at the Scientific Society of Spanish Informatics (SCIE) to analyse the perception of informatics scientists on the gender gap in informatics. © 2022 IEEE.

关键词： computers

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

Mercury: a Modeling, Simulation, and Optimization Framework for Data Stream-Oriented IoT Applications

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arXiv 2023年

作者： Cárdenas, Román Arroba, Patricia Blanco, Roberto Malagón, Pedro Risco-Martín, José L. Moya, José M. Laboratorio de Sistemas Integrados Universidad Politécnica de Madrid 28040 Spain Dpt. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain Center for Computational Simulation Universidad Politécnica de Madrid 28660 Spain

The Internet of Things is transforming our society by monitoring users and infrastructures' behavior to enable new services that will improve life quality and resource management. These applications require a vast amount of localized information to be processed in real-time so, the deployment of new fog computing infrastructures that bring computing closer to the data sources is a major concern. In this context, we present Mercury, a Modeling, Simulation, and Optimization (M&S&O) framework to analyze the dimensioning and the dynamic operation of real-time fog computing scenarios. Our research proposes a location-aware solution that supports data stream analytics applications including FaaS-based computation offloading. Mercury implements a detailed structural and behavioral simulation model, providing fine-grained simulation outputs, and is described using the Discrete Event System Specification (DEVS) mathematical formalism, helping to validate the model's implementation. Finally, we present a case study using real traces from a driver assistance scenario, offering a detailed comparison with other state-of-the-art simulators. © 2023, CC BY-SA.

关键词： Fog computing

An interactive prediction system of breast cancer based on ResNet50, chatbot and PyQt 2

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An interactive prediction system of breast cancer based on R...

2nd International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2021

作者： Yang, Xi Yang, Daiming Huang, Chenfeng Architectural Association School of Architecture Housing and Urbanism London United Kingdom Electrical Engineering and Automation Donghua University DHU College of Information Science and Technology Shanghai China Santa Clara University Mathematics and Computer Science Santa Clara United States

ISBN: (纸本)9781665412964

Breast cancer has gradually become an important killer that endangers people's health. How to diagnose breast cancer quickly and accurately has become a popular research direction. However, traditional testing by the doctor is time-consuming and laborious, and there is still the problem of accuracy. Deep learning becomes a tool of evidence-based medicine, which can effectively solve the above problems and realize the function of detecting breast cancer automatically and with high accuracy. In our study, we selected and applied the optimal CNN model named ResNet50 for breast cancer diagnosis. Due to the small size of images in our dataset, the 3*3 convolutional layer performed better than the 7*7 convolutional layer in our breast cancer classification task. Besides, our pre-trained ResNet50 achieved 94.698% accuracy on the WSI dataset, while un-pretrained ResNet50 only achieved 93.777%. The result presented pretraining in the ImageNet dataset can more effectively reduce the loss and improve accuracy. We also developed an application that integrated the CNN model with a chatbot implemented by NLTK and an interface constructed through PyQt. © 2021 IEEE.

关键词： Diagnosis

Multi-objective Optimization of Energy Consumption and Execution Time in a Single Level Cache Memory for Embedded Systems

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arXiv 2023年

作者： Álvarez, Josefa Díaz Risco-Martín, José L. Manuel Colmenar, J. Centro Universitario de Mérida Universidad de Extremadura Mérida06800 Spain Dpt. of Computer Architecture and Automation Complutense University of Madrid C/Prof. José García Santesmases 9 Madrid28040 Spain Dpt. of Computer Science Rey Juan Carlos University Móstoles28933 Spain

Current embedded systems are specifically designed to run multimedia applications. These applications have a big impact on both performance and energy consumption. Both metrics can be optimized selecting the best cache configuration for a target set of applications. Multi-objective optimization may help to minimize both conflicting metrics in an independent manner. In this work, we propose an optimization method that based on Multi-Objective Evolutionary Algorithms, is able to find the best cache configuration for a given set of applications. To evaluate the goodness of candidate solutions, the execution of the optimization algorithm is combined with a static profiling methodology using several well-known simulation tools. Results show that our optimization framework is able to obtain an optimized cache for Mediabench applications. Compared to a baseline cache memory, our design method reaches an average improvement of 64.43% and 91.69% in execution time and energy consumption, respectively. © 2023, CC BY-SA.

关键词： Evolutionary algorithms

Fast Event-based Double Integral for Real-time Robotics

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arXiv 2023年

作者： Lin, Shijie Zhang, Yingqiang Huang, Dongyue Zhou, Bin Luo, Xiaowei Pan, Jia The Department of Computer Science The University of Hong Kong Hong Kong The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong The School of Computer Science and Engineering Beihang University Beijing China The Department of Architecture and Civil Engineering City University of Hong Kong Hong Kong Peng Cheng Laboratory Guangdong Shenzhen China

Motion deblurring is a critical ill-posed problem that is important in many vision-based robotics applications. The recently proposed event-based double integral (EDI) provides a theoretical framework for solving the deblurring problem with the event camera and generating clear images at high frame-rate. However, the original EDI is mainly designed for offline computation and does not support real-time requirement in many robotics applications. In this paper, we propose the fast EDI, an efficient implementation of EDI that can achieve real-time online computation on single-core CPU devices, which is common for physical robotic platforms used in practice. In experiments, our method can handle event rates at as high as 13 million event per second in a wide variety of challenging lighting conditions. We demonstrate the benefit on multiple downstream real-time applications, including localization, visual tag detection, and feature matching. © 2023, CC0.

关键词： Robotics

Standardized Post-Quantum Cryptography and Recent Developments in Quantum computers

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Standardized Post-Quantum Cryptography and Recent Developmen...

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