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Showing 20 of 1,156 academic articles
Yitu Fu, Ju Xu • IEEE Access
(2019)
In this paper, we model the malware detection problem as a graph inference problem, and develop a novel belief propagation approach within a semi-supervised learning scheme that fully makes use of files' and hosts' connections to detect mal...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2948374
Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO)
(2014)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...
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DOI: https://doi.org/10.1109/micro.2014.58
Sergio Muñoz, Carlos Á. Iglesias • Big Data and Cognitive Computing
(2024)
The proliferation of fake news threatens the integrity of information ecosystems, creating a pressing need for effective and interpretable detection mechanisms. Recent advances in machine learning, particularly with transformer-based models...
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Open Access (DOAJ)
DOI: 10.3390/bdcc8100129
Oishi Jyoti, Md. Samiul Habib, Nguyen Hoang Hai, S. M. Abdur Razzak • IEEE Access
(2025)
We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) w...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3631711
Upendra Kumar Pradhan, Nitesh Kumar Sharma, Prakash Kumar, Ashwani Kumar et al. • PLoS ONE
(2021)
Formation of mature miRNAs and their expression is a highly controlled process. It is very much dependent upon the post-transcriptional regulatory events. Recent findings suggest that several RNA binding proteins beyond Drosha/Dicer are inv...
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Open Access (DOAJ)
DOI: 10.1371/journal.pone.0258550
Felix Brockherde, Leslie Vogt-Maranto, Li Li, Mark E. Tuckerman et al. • Nature Communications
(2017)
Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields. Machine learning holds the promise of learning the energy fun...
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DOI: https://doi.org/10.1038/s41467-017-00839-3
PMC: 5636838
Kostiantyn Fuks • Green, Blue and Digital Economy Journal
(2024)
The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysi...
DOAJ
Open Access (DOAJ)
DOI: 10.30525/2661-5169/2024-1-4
Simon Willcock, Javier Martínez‐López, Danny A. P. Hooftman, Kenneth J. Bagstad et al. • Ecosystem Services
(2018)
Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...
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DOI: https://doi.org/10.1016/j.ecoser.2018.04.004
Min-Hwa Choi, Woongchang Yoon • IEEE Access
(2025)
Port congestion and prolonged ship waiting times pose challenges for global trade and increase operational costs and inefficiencies. In this study, a novel machine learning-based predictive approach was proposed to improve port operations b...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3566429
Ziad F. Doughan, Sari S. Itani • IEEE Access
(2025)
This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RD...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3641537
Xiuhua April Si, Jinxiang Xi • Journal of Nanotheranostics
(2021)
Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...
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Open Access (DOAJ)
DOI: 10.3390/jnt2030007
Jorge Buzzio-Garcia, Jaime Vergara, Santiago Rios-Guiral, Christian Garzon et al. • IEEE Access
(2024)
In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3378271
Quoc Hoan Tran, Sanjib Ghosh, Kohei Nakajima • Physical Review Research
(2023)
Current quantum technologies bring a new integration of quantum data with classical data for hybrid processing. However, the frameworks of these technologies are restricted to a single classical or quantum task, which limits their flexibili...
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Open Access (DOAJ)
DOI: 10.1103/PhysRevResearch.5.043127
Zhiqiang Gong, Ping Zhong, Weidong Hu • IEEE Access
(2019)
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine...
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Open Access
DOI: https://doi.org/10.1109/access.2019.2917620
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
J. W. Njoroge, M. Koeva, M. Farnaghi, D. Petrova-Antonova et al. • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2026)
Digital twins are increasingly used in smart buildings to monitor energy use. This requires reliable sensor data, geospatial information, and semantically rich 3D building geometry. However, building sensor data often has inconsistent sampl...
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Open Access (DOAJ)
DOI: 10.5194/isprs-annals-XII-4-W1-2026-251-2026
Maria Schuld, Ilya Sinayskiy, Francesco Petruccione • Contemporary Physics
(2014)
Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT...
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Open Access
DOI: https://doi.org/10.1080/00107514.2014.964942
Lianlin Li, Hengxin Ruan, Che Liu, Ying Li et al. • Nature Communications
(2019)
Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...
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DOI: https://doi.org/10.1038/s41467-019-09103-2
PMC: 6403242
Nazish Shahid • Discover Education
(2022)
Abstract A synthesized investigation, employing graphical and analytical approach, has been conducted to examine inadequacy of electronic education and limitations posed by transformative mode of learning from students’ perspective. Moreove...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44217-022-00020-z
Simon Rogers, Mark Girolami • Chapman & Hall/CRC eBooks
(2016)
"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations ...
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DOI: https://doi.org/10.1201/9781315382159