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Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation
Published 2022“…Our experimental results show a possible decrease in data perturbation error by 51.7% and 61.2% for smart meters and fog-computing data aggregators perturbed data, respectively, compared to the commonly used Gaussian mechanism.…”
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Reversal of memory and neuropsychiatric symptoms and reduced tau pathology by selenium in 3xTg-AD mice
Published 2018“…Selenium significantly decreased the number of aggregated tau-positive neurons and astrogliosis, without globally affecting amyloid plaques, in the hippocampus of 3xTg-AD mice. …”
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Influence of temperature on tire-pavement noise in hot climates: Qatar case
Published 2021“…There is an apparent trend of decreasing temperature coefficient with increasing mean texture depth of dense graded asphalt pavements. …”
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The Effect of Number of Corrugation on Crashworthiness of Aluminum Corrugated Tube under Lateral Loading
Published 2017“…The results show that tubes with corrugations have a higher mean crushing force which is directly proportional to the number of corrugations. …”
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Influence of temperature on tire-pavement noise in hot climates: Qatar case
Published 2021“…There is an apparent trend of decreasing temperature coefficient with increasing mean texture depth of dense graded asphalt pavements. …”
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Chiropractic manipulations gone wrong
Published 2016“…CeAD is a common cause of ‘ischaemic’ stroke, a stroke caused by an inadequate blood supply, in people under 45. …”
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Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA
Published 2022“…Driven by the rising deployment of deep reinforcement learning (DRL) techniques that are capable of coping with solving non-convex optimization problems, we employ DRL to predict and optimally tune the IRS phase shift matrices. …”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
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Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation
Published 2023“…Deep RL is utilized to model the EV chargers and the EV users. …”
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Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation
Published 2023“…Deep RL is utilized to model the EV chargers and the EV users. …”
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FLACON: A Deep Federated Transfer Learning-Enabled Transient Stability Assessment During Symmetrical and Asymmetrical Grid Faults
Published 2024“…In practice, TSA based on deep learning is preferable for its high accuracy but often overlooks challenges in maintaining data privacy while coping with network topology changes. …”
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From metabolic dysregulation to neurodegenerative pathology: the role of hyperglycemia, oxidative stress, and blood-brain barrier breakdown in T2D-driven Alzheimer’s disease
Published 2025“…<p dir="ltr">Type 2 Diabetes (T2D) and Alzheimer’s Disease (AD) share common risk factors that can be seen through T2D nearly doubling an individual’s likelihood of developing AD. …”
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Data-Efficient Wheat Disease Detection Using Shifted Window Transformer: Enhancing Accuracy, Sustainability, and Global Food Security
Published 2025“…This research presents a deep learning technique based on the Shifted Window (Swin) Transformer, a powerful attention-based model that effectively captures both local and global information for enhanced classification output. …”
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Improving pediatric trauma care: an automated system for wrist trauma detection using GELAN
Published 2025“…The results of our study highlight the capacity of deep learning to improve the diagnosis of pediatric trauma, decrease the burden on radiologists, and boost patient outcomes.…”
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YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm
Published 2025“…First, the standard backbone network of the YOLOv11 algorithm is replaced with the Swin Transformer to extract more robust features of defects, and the Convolutional Block Attention Module (CBAM) is added in the Patch Merging modules to alleviate feature leakage during the downsampling operation. …”
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Energy-Efficient Cell Association and Load Balancing for Low Battery Users in Heterogeneous Cellular Networks
Published 2025“…This paper proposes improved cell association schemes based on the battery levels of UE and Deep Q-learning (DQL) to achieve load balancing and to decrease the power consumption of Low Battery Users (LBUs). …”