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computational increases » computational sciences (Expand Search)
impaired » impacted (Expand Search)
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A multi-targeted approach to identify potential flavonoids against three targets in the SARS-CoV-2 life cycle
Published 2022“…By examining the effects of glycosylation and other structural-activity relationships, the presence of sugar moiety in flavonoids significantly reduces its binding energy. It increases the solubility of flavonoids leading to reduced toxicity and higher bioavailability. …”
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Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities
Published 2023“…A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. …”
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Strain response of hot-mix asphalt overlays for bottom-up reflective cracking
Published 2017Get full text
Get full text
Get full text
Get full text
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…Processing similar features that provide redundant information increases the computational time, which is a critical problem especially for users with constrained resources (battery, energy). …”
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Mixed precision iterative refinement with adaptive precision sparse approximate inverse preconditioning
Published 2025“…Our numerical experiments show that this approach can potentially lead to a reduction in the cost of storing and applying sparse approximate inverse preconditioners, although a significant reduction in cost may comes at the expense of increasing the number of GMRES iterations required for convergence.…”
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SRP: An Efficient Runtime Protection Framework for Blockchain-based Smart Contracts
Published 2023“…Our empirical and experimental results indicate the feasibility and efficiency of our approach, where SRP outperforms the onchain-only mechanism in terms of service time and throughput, for increasing workloads.</p><h2>Other Information</h2> <p> Published in: Journal of Network and Computer Applications<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jnca.2023.103658" target="_blank">https://dx.doi.org/10.1016/j.jnca.2023.103658</a></p>…”
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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…Deep learning approaches have made significant progress in digital image processing, particularly in object recognition and classification, and are among the most popular computer vision tools. …”
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Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
Published 2022“…Specifically, our numerical results highlight the effectiveness of our approach and its ability to provide 4–6% increase in the classification accuracy, with respect to hierarchical FL schemes that consider distance-based user assignment. …”
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VisioDECT: a novel approach to drone detection using CBAM-integrated YOLO and GELAN-E models
Published 2025“…This improvement in spatial and channel attention significantly boosts detection performance, particularly for small and occluded drones. …”
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Noise2Weight: On detecting payload weight from drones acoustic emissions
Published 2022“…<p>The increasing popularity of autonomous and remotely-piloted drones has paved the way for several use-cases and application scenarios, including merchandise delivery, surveillance, and warfare, to cite a few. …”
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A Multi-Channel Convolutional Neural Network approach to automate the citation screening process
Published 2021“…<p dir="ltr">The systematic literature review (SLR) process is separated into several steps to increase rigor and reproducibility. The selection of primary studies (i.e., citation screening) is an important step in the SLR process. …”