Converting nanotoxicity data to information using artificial intelligence and simulation
Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …
However, data is not equal to information. The question is how to extract critical information …
Machine learning methods in smart lighting toward achieving user comfort: a survey
Smart lighting has become a universal smart product solution, with global revenues of up to
US 5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) …
US 5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) …
[HTML][HTML] Adapting feature selection algorithms for the classification of Chinese texts
Text classification has been highlighted as the key process to organize online texts for better
communication in the Digital Media Age. Text classification establishes classification rules …
communication in the Digital Media Age. Text classification establishes classification rules …
[HTML][HTML] Ensuring network security with a robust intrusion detection system using ensemble-based machine learning
MA Hossain, MS Islam - Array, 2023 - Elsevier
Intrusion detection is a critical aspect of network security to protect computer systems from
unauthorized access and attacks. The capacity of traditional intrusion detection systems …
unauthorized access and attacks. The capacity of traditional intrusion detection systems …
[HTML][HTML] Hardening machine learning denial of service (DoS) defences against adversarial attacks in IoT smart home networks
Abstract Machine learning based Intrusion Detection Systems (IDS) allow flexible and
efficient automated detection of cyberattacks in Internet of Things (IoT) networks. However …
efficient automated detection of cyberattacks in Internet of Things (IoT) networks. However …
Selecting features by utilizing intuitionistic fuzzy Entropy method
Feature selection is the most significant pre-processing activity, which intends to reduce the
data dimensionality for enhancing the machine learning process. The evaluation of feature …
data dimensionality for enhancing the machine learning process. The evaluation of feature …
A survey on sentiment analysis and its applications
TA Al-Qablan, MH Mohd Noor, MA Al-Betar… - Neural Computing and …, 2023 - Springer
Analyzing and understanding the sentiments of social media documents on Twitter,
Facebook, and Instagram has become a very important task at present. Analyzing the …
Facebook, and Instagram has become a very important task at present. Analyzing the …
[HTML][HTML] A heart disease prediction model based on feature optimization and smote-Xgboost algorithm
J Yang, J Guan - Information, 2022 - mdpi.com
In today's world, heart disease is the leading cause of death globally. Researchers have
proposed various methods aimed at improving the accuracy and efficiency of the clinical …
proposed various methods aimed at improving the accuracy and efficiency of the clinical …
[HTML][HTML] Exploring the dominant features and data-driven detection of polycystic ovary syndrome through modified stacking ensemble machine learning technique
Polycystic ovary syndrome (PCOS) is the most frequent endocrinological anomaly in
reproductive women that causes persistent hormonal secretion disruption, leading to the …
reproductive women that causes persistent hormonal secretion disruption, leading to the …
Distributionally robust chance-constrained planning for regional integrated electricity–heat systems with data centers considering wind power uncertainty
W Li, T Qian, Y Zhang, Y Shen, C Wu, W Tang - Applied Energy, 2023 - Elsevier
This paper proposed an optimal planning method for regional integrated electricity–heat
systems with data centers (DC-RIEHS) considering wind power uncertainty to reduce …
systems with data centers (DC-RIEHS) considering wind power uncertainty to reduce …