[HTML][HTML] Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education

R Sajja, Y Sermet, M Cikmaz, D Cwiertny, I Demir - Information, 2024 - mdpi.com
This paper presents a novel framework, artificial intelligence-enabled intelligent assistant
(AIIA), for personalized and adaptive learning in higher education. The AIIA system …

Enhancing FAIR data services in agricultural disaster: A review

L Hu, C Zhang, M Zhang, Y Shi, J Lu, Z Fang - Remote Sensing, 2023 - mdpi.com
The agriculture sector is highly vulnerable to natural disasters and climate change, leading
to severe impacts on food security, economic stability, and rural livelihoods. The use of …

[HTML][HTML] Performance of ChatGPT on the US fundamentals of engineering exam: Comprehensive assessment of proficiency and potential implications for professional …

V Pursnani, Y Sermet, M Kurt, I Demir - Computers and Education: Artificial …, 2023 - Elsevier
In recent years, advancements in artificial intelligence (AI) have led to the development of
large language models like GPT-4, demonstrating potential applications in various fields …

Flood detection with SAR: A review of techniques and datasets

D Amitrano, G Di Martino, A Di Simone, P Imperatore - Remote Sensing, 2024 - mdpi.com
Floods are among the most severe and impacting natural disasters. Their occurrence rate
and intensity have been significantly increasing worldwide in the last years due to climate …

Platform-independent and curriculum-oriented intelligent assistant for higher education

R Sajja, Y Sermet, D Cwiertny, I Demir - International Journal of …, 2023 - Springer
Miscommunication between instructors and students is a significant obstacle to post-
secondary learning. Students may skip office hours due to insecurities or scheduling …

A novel multi-strategy hydrological feature extraction (MHFE) method to improve urban waterlogging risk prediction, a case study of Fuzhou City in China

H Huang, X Lei, W Liao, X Zuo, H Wang - Science of The Total Environment, 2023 - Elsevier
Reliable hydrological data ensure the precision of the urban waterlogging simulation. To
reduce the simulation error caused by insufficient basic data, a multi-strategy method …

[HTML][HTML] A novel urban heat vulnerability analysis: Integrating machine learning and remote sensing for enhanced insights

F Li, T Yigitcanlar, M Nepal, KN Thanh, F Dur - Remote Sensing, 2024 - mdpi.com
Rapid urbanization and climate change exacerbate the urban heat island effect, increasing
the vulnerability of urban residents to extreme heat. Although many studies have assessed …

A new multi-source remote sensing image sample dataset with high resolution for flood area extraction: GF-FloodNet

Y Zhang, P Liu, L Chen, M Xu, X Guo… - International Journal of …, 2023 - Taylor & Francis
Deep learning algorithms show good prospects for remote sensing flood monitoring. They
mostly rely on huge amounts of labeled data. However, there is a lack of available labeled …

Pemanfaat Geographic Artificial Intelligence (Geo-AI) Untuk Identifikasi Daerah Rawan Banjir Di Kota Ambon

A Muin, H Rakuasa - Gudang Jurnal Multidisiplin Ilmu, 2023 - gudangjurnal.com
Penelitian ini bertujuan untuk menerapkan Geographic Artificial Intelligence (Geo-AI) dalam
identifikasi daerah rawan banjir di Kota Ambon. Geo-AI merupakan kombinasi teknologi …

MA-SARNet: A one-shot nowcasting framework for SAR image prediction with physical driving forces

Z Li, Z **ang, BZ Demiray, M Sit, I Demir - ISPRS journal of photogrammetry …, 2023 - Elsevier
Remote sensing imagery is one of the most widely used data sources for large-scale Earth
observations with consistent spatial and temporal quality. However, the current usage …