[HTML][HTML] A systematic literature review on windows malware detection: Techniques, research issues, and future directions
The aim of this systematic literature review (SLR) is to provide a comprehensive overview of
the current state of Windows malware detection techniques, research issues, and future …
the current state of Windows malware detection techniques, research issues, and future …
IP2FL: interpretation-based privacy-preserving federated learning for industrial cyber-physical systems
D Namakshenas, A Yazdinejad… - … on Industrial Cyber …, 2024 - ieeexplore.ieee.org
The expansion of Industrial Cyber-Physical Systems (ICPS) has introduced new challenges
in security and privacy, highlighting a research gap in effective anomaly detection while …
in security and privacy, highlighting a research gap in effective anomaly detection while …
[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …
the threat of malware to computer system, android-based smart phones, Internet of Things …
An ensemble-based parallel deep learning classifier with PSO-BP optimization for malware detection
Digital networks and systems are susceptible to malicious software (malware) attacks. Deep
learning (DL) models have recently emerged as effective methods to classify and detect …
learning (DL) models have recently emerged as effective methods to classify and detect …
An improved binary owl feature selection in the context of Android malware detection
Recently, the proliferation of smartphones, tablets, and smartwatches has raised security
concerns from researchers. Android-based mobile devices are considered a dominant …
concerns from researchers. Android-based mobile devices are considered a dominant …
Thermal-hydraulic performance and multi-objective optimization using ANN and GA in microchannels with double delta-winglet vortex generators
Z Li, Z Feng, Q Zhang, J Zhou, J Zhang… - International Journal of …, 2023 - Elsevier
This study presents a multi-objective optimization approach to design microchannels with
double delta-winglet vortex generators for obtaining the best hydrothermal performance …
double delta-winglet vortex generators for obtaining the best hydrothermal performance …
A depth graph attention-based multi-channel transfer learning network for fluid classification from logging data
H Li, S Qiao, Y Sun - Physics of Fluids, 2024 - pubs.aip.org
Fluid classification is a fundamental task in the field of geological sciences to achieve
effective reservoir characterization and hydrocarbon exploration. Traditional fluid …
effective reservoir characterization and hydrocarbon exploration. Traditional fluid …
[HTML][HTML] Explainable AI for Alzheimer detection: A review of current methods and applications
Alzheimer's disease (AD) is the most common cause of dementia, marked by cognitive
decline and memory loss. Recently, machine learning and deep learning techniques have …
decline and memory loss. Recently, machine learning and deep learning techniques have …
A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Accurate fault detection and diagnosis (FDD) is critical to ensure the safe and reliable
operation of industrial machines. Deep learning has recently emerged as effective methods …
operation of industrial machines. Deep learning has recently emerged as effective methods …
A short-term PV power forecasting method based on weather type credibility prediction and multi-model dynamic combination
Accurate short-term photovoltaic (PV) power forecasting results can provide solid supports
for power gird management. The PV power generation exhibits different daily output patterns …
for power gird management. The PV power generation exhibits different daily output patterns …