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Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
(
Elsevier B.V.
, 2022 , Article Review)
In modern Smart Grids (SGs) ruled by advanced computing and networking technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this connection, a portion of transported data, containing ...
Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach
(
Springer
, 2020 , Article)
© 2020, Springer-Verlag London Ltd., part of Springer Nature. Bitcoin is a decentralized cryptocurrency, which is a type of digital asset that provides the basis for peer-to-peer financial transactions based on blockchain ...
Smart Edge Healthcare Data Sharing System
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Smart health systems improve the efficiency of healthcare infrastructures and biomedical systems by integrating information and technology into health and medical practices. However, reliability, scalabilty and latency are ...
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
(
Elsevier
, 2024 , Article)
Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ...
Artificial intelligence in sickle disease
(
Churchill Livingstone
, 2023 , Article Review)
Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, ...
Exploration and analysis of On-Surface and In-Air handwriting attributes to improve dysgraphia disorder diagnosis in children based on machine learning methods
(
Elsevier
, 2023 , Article)
Dysgraphia is a type of learning disorder that affects children’s writing skills. Poor writing skills can obstruct students’ academic growth if it is undiagnosed and untreated properly in the early stages. The irregularity ...
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
(
Elsevier
, 2023 , Article)
Introduction: Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide in ...
The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar
(
Elsevier Ltd
, 2022 , Article)
The goal of this study is to use machine-learning (ML) techniques and empirical big data to examine the influence of the COVID-19 pandemic on electricity usage and electricity demand forecasting accuracy in buildings in ...
Cryptocurrencies and artificial intelligence: Challenges and opportunities
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Decentralized cryptocurrencies have gained a lot of attention over the last decade. Bitcoin was introduced as the first cryptocurrency to allow direct online payments without relying on centralized financial entities. The ...
A machine learning-based optimization approach for pre-copy live virtual machine migration
(
Springer
, 2023 , Article)
Organizations widely use cloud computing to outsource their computing needs. One crucial issue of cloud computing is that services must be available to clients at all times. However, the cloud services may be temporarily ...