A5068077636- Advanced Data Storage Technologies
- Distributed and Parallel Computing Systems
- Parallel Computing and Optimization Techniques
- Cloud Computing and Resource Management
- Caching and Content Delivery
- Scientific Computing and Data Management
- IoT and Edge/Fog Computing
- Peer-to-Peer Network Technologies
- Distributed systems and fault tolerance
- Energy Efficient Wireless Sensor Networks
- Cloud Data Security Solutions
- COVID-19 epidemiological studies
- Interconnection Networks and Systems
- Medical Imaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Data-Driven Disease Surveillance
- Engineering and Information Technology
- Advanced X-ray and CT Imaging
- Energy Harvesting in Wireless Networks
- Algorithms and Data Compression
- Blockchain Technology Applications and Security
- Simulation Techniques and Applications
- Real-Time Systems Scheduling
- Influenza Virus Research Studies
- Advanced Software Engineering Methodologies
Universidad Carlos III de Madrid
2016-2025
Sociedad Española de Medicina Interna
2025
Center for Research and Advanced Studies of the National Polytechnic Institute
2023
University of Iowa Hospitals and Clinics
2023
Washington University in St. Louis
2023
University of Nebraska Medical Center
2022-2023
University of Cambridge
2022
Universidad de Cádiz
2021
Hospital General Universitario Gregorio Marañón
2017-2020
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
2019-2020
Abstract The main purpose of this work is to investigate and compare several deep learning enhanced techniques applied X-ray CT-scan medical images for the detection COVID-19. In paper, we used four powerful pre-trained CNN models, VGG16, DenseNet121, ResNet50,and ResNet152, COVID-19 binary classification task. proposed Fast.AI ResNet framework was designed find out best architecture, pre-processing, training parameters models largely automatically. accuracy F1-score were both above 96% in...
The driving force behind the smart city initiative is to offer better, more specialized services which can improve quality of life citizens while promoting sustainability. To achieve both these apparently competing goals, must be increasingly autonomous and continuously adaptive changes in their environment information coming from other services. In this paper we focus on lighting, a relevant application domain for propose an intelligent street light control system based behavior rules. We...
Abstract Background Nowadays doctors and radiologists are overwhelmed with a huge amount of work. This led to the effort design different Computer-Aided Diagnosis systems (CAD system), aim accomplishing faster more accurate diagnosis. The current development deep learning is big opportunity for new CADs. In this paper, we propose novel architecture convolutional neural network (CNN) ensemble classifying chest X-ray (CRX) images into four classes: viral Pneumonia, Tuberculosis, COVID-19,...
The edge, the fog, cloud, and even end-user's devices play a key role in management of health sensitive content/data lifecycle. However, creation solutions including multiple applications executed by users environments (edge, cloud) to process repositories that, at same time, fulfilling non-functional requirements (NFRs) represents complex challenge for care organizations. This paper presents design, development, implementation an architectural model create, on-demand, edge-fog-cloud...
This survey reviews the scientific literature on techniques for reducing interference in real-time multicore systems, focusing approaches proposed between 2015 and 2020. It also presents proposals that use reduction without considering predictability issue. The highlights sources categorizes from perspective of shared resource. covers contentions main memory, cache a memory bus, integration effects into schedulability analysis. Every section contains an overview each proposal assessment its...
Virtualization has become one of the main tools for making efficient use resources offered by multicore embedded platforms. In recent years, even sectors such as space, aviation, and automotive, traditionally wary adopting this type technology due to impact it could have on safety their systems, been forced introduce into day-to-day work, applications are becoming increasingly complex demanding. This article provides a comprehensive review research work that uses or considers hypervisor...
Collaborative comparisons and combinations of epidemic models are used as policy-relevant evidence during outbreaks. In the process collecting multiple model projections, such collaborations may gain or lose relevant information. Typically, modellers contribute a probabilistic summary at each time-step. We compared this to directly simulated trajectories. aimed explore information on key quantities; ensemble uncertainty; performance against data, investigating potential continuously from...
This paper presents a continuous delivery/continuous verifiability (CD/CV) method for IoT dataflows in edge–fog–cloud. A CD model based on extraction, transformation, and load (ETL) mechanism as well directed acyclic graph (DAG) construction, enable end-users to create efficient schemes the verification validation of execution applications edge–fog–cloud infrastructures. scheme also verifies validates established sequences integrity digital assets. CV converts ETL DAG into business model,...
Cloud computing has become a popular solution for organizations implementing Earth Observation Systems (EOS). However, this produces dependency on provider resources. Moreover, managing and executing tasks data in these environments are challenges that commonly arise when building an EOS. This paper presents GeoNimbus, serverless framework composing deploying spatio-temporal EOS multiple infrastructures, e.g., on-premise resources public or private clouds. organizes as functions...