A literature review of textual hate speech detection methods and datasets

F Alkomah, X Ma - Information, 2022 - mdpi.com
Online toxic discourses could result in conflicts between groups or harm to online
communities. Hate speech is complex and multifaceted harmful or offensive content …

[PDF][PDF] Design of accurate classification of COVID-19 disease in X-ray images using deep learning approach

JIZ Chen - Journal of ISMAC, 2021 - scholar.archive.org
COVID-19 appears to be having a devastating influence on world health and wellbeing.
Moreover, the COVID-19 confirmed cases have recently increased to over 10 million …

[HTML][HTML] A comprehensive survey of fingerprint presentation attack detection

K Karampidis, M Rousouliotis, E Linardos… - … , Security and Safety, 2021 - oaepublish.com
Nowadays, the number of people that utilize either digital applications or machines is
increasing exponentially. Therefore, trustworthy verification schemes are required to ensure …

Solar radiation prediction using different machine learning algorithms and implications for extreme climate events

L Huang, J Kang, M Wan, L Fang, C Zhang… - Frontiers in Earth …, 2021 - frontiersin.org
Solar radiation is the Earth's primary source of energy and has an important role in the
surface radiation balance, hydrological cycles, vegetation photosynthesis, and weather and …

[HTML][HTML] Estimating the heavy metal contents in farmland soil from hyperspectral images based on Stacked AdaBoost ensemble learning

N Lin, R Jiang, G Li, Q Yang, D Li, X Yang - Ecological Indicators, 2022 - Elsevier
Heavy metal pollution poses a huge challenge to the soil environment. With the increasing
pollution level, the traditional monitoring methods cannot quickly obtain information on large …

Uncertainty management in electricity demand forecasting with machine learning and ensemble learning: case studies of COVID-19 in the US metropolitans

MR Baker, KH Jihad, H Al-Bayaty, A Ghareeb… - … Applications of Artificial …, 2023 - Elsevier
Improving load forecasting is becoming increasingly crucial for power system management
and operational research. Disruptive influences can seriously impact both the supply and …

Combating hate speech using an adaptive ensemble learning model with a case study on COVID-19

S Agarwal, CR Chowdary - Expert Systems with Applications, 2021 - Elsevier
Social media platforms generate an enormous amount of data every day. Millions of users
engage themselves with the posts circulated on these platforms. Despite the social …

Forensic-based investigation-optimized extreme gradient boosting system for predicting compressive strength of ready-mixed concrete

JS Chou, LY Chen, CY Liu - Journal of Computational Design …, 2023 - academic.oup.com
Regulations mandate testing concrete's compressive strength after the concrete has cured
for 28 days. In the ideal situation, cured strength equals the target strength. Advanced …

Towards asymmetric uncertainty modeling in designing General Type-2 Fuzzy classifiers for medical diagnosis

E Ontiveros-Robles, O Castillo, P Melin - Expert Systems with Applications, 2021 - Elsevier
One of the most studied application areas of intelligent systems is the classification area,
and this is because classification covers a wide range of real-world problems. Some …

Driver lane-changing intention recognition based on stacking ensemble learning in the connected environment: A driving simulator study

H Zhang, S Gao, Y Guo - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
The connected environment provides information on surrounding traffic and areas beyond
the visual range traffic to improve driving behavior and avoid dangerous incidents. However …