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Empowering Sustainability: The Crucial Role of IoT-Enabled Distributed Learning Systems in Reducing Carbon Footprints

Anjana M S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh • IEEE Access (2025)

Electrical energy plays a pivotal role in modern society by powering homes, industries, and transportation systems. However, the production of electricity is associated with significant carbon emissions, primarily from fossil fuel-based pow...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3539333

Understanding fault-tolerant distributed systems

Flaviu Cristian • Communications of the ACM (1991)

We propose a small number of basic concepts that can be used to explain the architecture of fault-tolerant distributed systems and we discuss a list of architectural issues that we find useful to consider when designing or examining such sy...

OPENALEX Open Access DOI: https://doi.org/10.1145/102792.102801

A Systematic Literature Review on Modern Cryptographic and Authentication Schemes for Securing the Internet of Things

Tehseen Hussain, Fraz Ahmad, Dr. Zia Ur Rehman • NUML International Journal of Engineering and Computing (2026)

The rapid integration of the Internet of Things (IoT) into healthcare ecosystems has revolutionized patient monitoring and data accessibility; however, it has simultaneously expanded the cyber-attack surface, leaving sensitive medical data ...

DOAJ Open Access (DOAJ)

A Novel Slow-Growing Gross Error Detection Method for GNSS/Accelerometer Integrated Deformation Monitoring Based on State Domain Consistency Theory

Ao Sun, Qiuzhao Zhang, Zhangjun Yu, Xiaolin Meng et al. • Remote Sensing (2022)

The accuracy and integrity of structural deformation monitoring can be improved by the GNSS/accelerometer integrated system, and gross error detection is the key to further improving the reliability of GNSS/accelerometer monitoring. Traditi...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14194758

Hybrid spatio-temporal transformer and variational autoencoder framework for advanced sports injury prediction and analysis

Fanjie Meng • Kuwait Journal of Science (2026)

Sports injuries significantly affect sports performance and overall health, making using accurate and reliable prognostic models imperative. Conventional algorithms for injury prediction, e.g., random forest and XGBoost, generally cannot un...

DOAJ Open Access (DOAJ) DOI: https://doi.org/10.1016/j.kjs.2026.100589

A Unified Transformer–BDI Architecture for Financial Fraud Detection: Distributed Knowledge Transfer Across Diverse Datasets

Parul Dubey, Pushkar Dubey, Pitshou N. Bokoro • Forecasting (2025)

Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow...

DOAJ Open Access (DOAJ) DOI: 10.3390/forecast7020031

Decentralized intelligence in smart grids: a comprehensive survey of edge computing and federated learning

Pijush Kanti Dutta Pramanik, Bijoy Kumar Upadhyaya, Ajay Kushwaha, Debashish Bhowmik • Energy and AI (2026)

Modern power grids are becoming more distributed and data-intensive, while centralized, cloud-based analytics struggle to keep pace. Routing everything through a central system introduces delays, strains network capacity, complicates compli...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.egyai.2026.100925

Hardware-Anchored ES-SPA: A Dynamic Zero-Trust Architecture for Secure eSIM Provisioning in 6G IoT via Moving Target Defense

Hari N. N., Kurunandan Jain, Prabu P, Prabhakar Krishnan • Future Internet (2026)

The rapid evolution of 6G networks and large-scale Internet of Things (IoT) deployments intensifies security and privacy challenges in embedded SIM (eSIM) Remote SIM Provisioning (RSP), particularly during the bootstrap and profile delivery...

DOAJ Open Access (DOAJ) DOI: 10.3390/fi18040187

Enhanced Intrusion Detection in Drone Networks: A Cross-Layer Convolutional Attention Approach for Drone-to-Drone and Drone-to-Base Station Communications

Mohammad Aldossary, Ibrahim Alzamil, Jaber Almutairi • Drones (2025)

Due to Internet of Drones (IoD) technology, drone networks have proliferated, transforming surveillance, logistics, and disaster management. Distributed Denial of Service (DDoS) attacks, malware infections, and communication abnormalities i...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones9010046

Practical Vulnerability-Information-Sharing Architecture for Automotive Security-Risk Analysis

Yousik Lee, Samuel Woo, Yunkeun Song, Jungho Lee et al. • IEEE Access (2020)

Emerging trends that are shaping the future of the automotive industry include electrification, autonomous driving, sharing, and connectivity, and these trends keep changing annually. Thus, the automotive industry is shifting from mechanica...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3004661

Graph neural networks for materials science and chemistry

Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi et al. • Communications Materials (2022)

Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials...

OPENALEX cc-by DOI: https://doi.org/10.1038/s43246-022-00315-6 PMC: 9702700

Clinical Aspects of Immunology.

• Annals of Internal Medicine (1969)

Volume 1: anatomical basis of the immune system architecture of immunity induction and regulation of immune responses. Volume 2: advances in technology immunological intervention allergy connective tissue disease immunodeficiency. Volume 3:...

OPENALEX DOI: https://doi.org/10.7326/0003-4819-71-1-229_2

Small Object Detection Algorithm Based on Improved YOLOv8 for Remote Sensing

Hao Yi, Bo Liu, Bin Zhao, Enhai Liu • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)

Due to the limitations of small targets in remote sensing images, such as background noise, poor information, and so on, the results of commonly used detection algorithms in small target detection is not satisfactory. To improve the accurac...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2023.3339235

Microstructure-based variational deep material networks for robust uncertainty quantification in materials digital twins

Andreas E. Robertson, Samuel B. Inman, Ashley T. Lenau, Ricardo A. Lebensohn et al. • npj Computational Materials (2026)

Abstract Aleatoric uncertainties – irremovable variability in microstructure morphology, constituent behavior, and processing conditions – pose a major challenge to developing uncertainty-robust digital twins. We introduce the Variational D...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41524-026-02054-5