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Now showing items 21-30 of 94
Predicting carbonate formation permeability using machine learning
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Elsevier B.V.
, 2020 , Article)
It is imperative to characterize the formation permeability to simulate the flow behavior at subsurface conditions. An accurate characterization at the core scale is possible when large samples are available, but often ...
Real-time throughput prediction for cognitive Wi-Fi networks
(
Academic Press
, 2020 , Article)
Wi-Fi as a wireless networking technology has become a widely acceptable commonplace. Over the course of time, the applications landscape of Wi-Fi networks is growing tremendously. The proliferation of new services is ...
Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Electroencephalography (EEG) based biometric systems are gaining attention for their anti-spoofing capability but lack accuracy due to signal variability at different psychological and physiological conditions. On the other ...
Efficient machine-learning model for fast assessment of elastic properties of high-entropy alloys
(
Elsevier
, 2022 , Article)
We combined descriptor-based analytical models for stiffness-matrix and elastic-moduli with mean-field methods to accelerate assessment of technologically useful properties of high-entropy alloys, such as strength and ...
Towards stacking fault energy engineering in FCC high entropy alloys
(
Elsevier
, 2022 , Article)
Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, ...
RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
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Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...
The P-ART framework for placement of virtual network services in a multi-cloud environment
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Elsevier B.V.
, 2019 , Article)
Carriers network services are distributed, dynamic, and investment intensive. Deploying them as virtual network services (VNS) brings the promise of low-cost agile deployments, which reduce time to market new services. If ...
Fault and performance management in multi-cloud virtual network services using AI: A tutorial and a case study
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Elsevier B.V.
, 2019 , Article)
Carriers find Network Function Virtualization (NFV) and multi-cloud computing a potent combination for deploying their network services. The resulting virtual network services (VNS) offer great flexibility and cost advantages ...
Detection and assessment of marine litter in an uninhabited island, Arabian Gulf: A case study with conventional and machine learning approaches
(
Elsevier
, 2022 , Article)
In 2018, the Ministry of Municipality and Environment, Qatar removed 90 t of marine litter (ML) from the Ras Rakan Island (RRI), a remote uninhabited island in the Arabian Gulf (hereinafter referred to as Gulf). To identify ...
MACHINE LEARNING APPLICATION FOR OPTIMIZING ASYMMETRICAL REDUCTION OF ACETOPHENONE EMPLOYING COMPLETE CELL OF LACTOBACILLUS SENMAIZUKE AS AN ENVIRONMENTALLY FRIENDLY APPROACH
(
Prof. Hysen Mankolli, IJEES Electronic Journal Publication
, 2020 , Article)
Recently, optimization of the bioreduction reactions by optimization methodologies has gained special interest as these reactions are affected by several extrinsic factors that should be optimized for higher yields. An ...