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integration algorithm » detection algorithm (Expand Search)
data integration » scale integration (Expand Search), data injection (Expand Search)
integration algorithm » detection algorithm (Expand Search)
data integration » scale integration (Expand Search), data injection (Expand Search)
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Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Published 2021“…This ongoing transition undergoes rapid changes, requiring a plethora of advanced methodologies to process the big data generated by various units. In this context, SG stands tied very closely to Deep Learning (DL) as an emerging technology for creating a more decentralized and intelligent energy paradigm while integrating high intelligence in supervisory and operational decision-making. …”
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143
Novel biomarkers for potential risk stratification of drug induced liver injury (DILI)
Published 2019“…In this review, we have explored the potential role of emerging novel markers of DILI and how they could possibly be integrated into clinical care of patients.</p><h3>Methods:</h3><p dir="ltr">We explored PUBMED and all other relevant databases for scientific studies that explored potential utility of novel biomarkers of DILI, and subsequently carried out a narrative synthesis of this data. …”
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144
Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…The developed cluster-based stochastic optimization approaches showed superior performance compared with baseline and sequencing heuristics using data from a real Outpatient Chemotherapy Center (OCC).…”
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145
Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
Published 2023“…., dry and bare soil. SAR data were complemented with very high-resolution Worldview-3 multispectral images (0.31 m panchromatic, 1.24 m VNIR) to obtain a visual assessment of the study area and its land cover features. …”
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146
Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique
Published 2024“…The primary objective of this study is to estimate the CL index through an innovative approach that employs a hybrid, cluster-based, unsupervised learning technique seamlessly integrated with a 1D Convolutional Neural Network (CNN) architecture tailored for automated feature extraction, rather than conventional supervised algorithms, which facilitated in the acquisition of latent complex patterns without the need for manual categorization. …”
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147
Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks
Published 2024“…Based on our thorough analysis, we identify key limitations in current methodologies and propose potential paths for future research, focusing on integrating real-time data analysis, cross-layer security measures, and collaborative IDS frameworks.…”
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148
An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
Published 2020Get full text
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149
A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
Published 2025Get full text
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150
Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications
Published 2025“…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”