Advanced Hybrid Techniques for Cyberattack Detection and Defense in IoT Networks
ABSTRACT The Internet of Things (IoT) represents a vast network of devices connected to the Internet, making it easier for users to connect to modern technology. However, the complexity of these networks and the large volume of data pose significant challenges in protecting them from persistent cyberattacks, such as distributed denial‐of‐service (DDoS)
Zaed S. Mahdi +2 more
wiley +1 more source
PCA downsampled DNN feature maps of the training/test images coming from the THINGS database, and also of the ILSVRC-2012 validation/test ...
Alessandro Thomas Gifford
core +1 more source
A Large Language Model‐Based Approach for Fault Detection and Its Application
This work proposes an interpretable fault detection framework utilizing pre‐trained large language models to overcome small sample sizes and label scarcity in industrial datasets. A stepwise tuple‐based validation mitigates hallucinations, ensuring reliable detection.
Yihua Ye, Yin Zhu, Liming Che, Hua Zhou
wiley +1 more source
Hybrid machine learning forecasting for resilient and sustainable pharmaceutical supply chains under regulatory and seasonal disruption. [PDF]
Yahya K, Safaei M, Al Dawsari S.
europepmc +1 more source
Reinforcement Learning With Timed Constraints for Robotics Motion Planning
This work presents a unified automata‐based reinforcement learning framework that enforces MITL time‐bounded task specifications in both MDPs and POMDPs. Results from grid‐world and office scenarios show robust policy learning under stochastic dynamics and partial observability.
Zhaoan Wang +3 more
wiley +1 more source
pedQTNet: A Deep Learning Approach to Estimate Corrected QT Intervals from Multi-Lead Conventional ECG Waveforms in Pediatric Patients. [PDF]
Ruiz VM +7 more
europepmc +1 more source
Shear strength of light weight concrete elements model based on deep neural network and COVID-19 optimization. [PDF]
Shamseldin MA +3 more
europepmc +1 more source
Review on enhancing clinical decision support system using machine learning
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood +4 more
wiley +1 more source
Single-Criterion Optimisation with Consideration of Uncertainties of the Composite Multi-Layer Slabs. [PDF]
Smela P, Miller B.
europepmc +1 more source
Abstract Data is the key element that runs the modern society. Large amounts of data are being released day by day as a result of many activities. The digital data is transferred through the Internet which may be vulnerable to attacks while transmitting. Especially, the medical data is observed to be of at most importance.
Rupa Ch +4 more
wiley +1 more source

