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Exploring the impact of AI on the EFL context: A case study of Saudi universities
This research aims to determine whether or not it is possible to use artificial intelligence (AI)
in English for speakers of other languages (ESOL) courses. The purpose of the research is …
in English for speakers of other languages (ESOL) courses. The purpose of the research is …
[HTML][HTML] A stacking ANN ensemble model of ML models for stream water quality prediction of Godavari River Basin, India
The importance of water quality models has increased as their inputs are critical to the
development of risk assessment framework for environmental management and monitoring …
development of risk assessment framework for environmental management and monitoring …
[HTML][HTML] Information extraction of seasonal dissolved oxygen in urban water bodies based on machine learning using sentinel-2 imagery: An open access application …
L Shi, C Gao, T Wang, L Liu, Y Wu, X You - Ecological Informatics, 2024 - Elsevier
Water bodies are crucial components of urban ecology. The development of rapid and timely
water-quality assessment tools using easily measured variables is essential for the health …
water-quality assessment tools using easily measured variables is essential for the health …
Artificial Intelligence in IoT Security: Review of Advancements, Challenges, and Future Directions
N Srinivasan - Challenges, and Future Directions (May 29, 2024), 2024 - papers.ssrn.com
Abstract The Internet of Things (IoT) has revolutionized various industries, but its rapid
expansion has also exposed a vast attack surface, making it vulnerable to cyber threats …
expansion has also exposed a vast attack surface, making it vulnerable to cyber threats …
Secure and Energy Efficient Routing in Wireless Sensor Network using Machine Learning
Security and energy efficiency are significant issues in Wireless Sensor Network (WSN). It is
a critical task to provide reliability during data transmission in routing. Due to the presence of …
a critical task to provide reliability during data transmission in routing. Due to the presence of …
Deep reinforcement learning-based dynamic scheduling
R Liu - 2022 - dr.ntu.edu.sg
Attempts to address the production scheduling problem thus far rely on simplifying
assumptions, such as static environment and inflexible size of the problem, which …
assumptions, such as static environment and inflexible size of the problem, which …
Prediction of Water Quality Through Machine Learning: A Review
Due to the fast expansion of data required for the aquatic environment, machine learning
has become a necessary tool for analysis, grou**, and prediction. Methods that have been …
has become a necessary tool for analysis, grou**, and prediction. Methods that have been …