The role of explainable Artificial Intelligence in high-stakes decision-making systems: a systematic review

B Sahoh, A Choksuriwong - Journal of Ambient Intelligence and …, 2023 - Springer
A high-stakes event is an extreme risk with a low probability of occurring, but severe
consequences (eg, life-threatening conditions or economic collapse). The accompanying …

Augmented reality and virtual reality in education: Public perspectives, sentiments, attitudes, and discourses

G Lampropoulos, E Keramopoulos, K Diamantaras… - Education …, 2022 - mdpi.com
This study aims to understand the public's perspectives, sentiments, attitudes, and
discourses regarding the adoption, integration, and use of augmented reality and virtual …

ContCommRTD: A distributed content-based misinformation-aware community detection system for real-time disaster reporting

ES Apostol, CO Truică… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Real-time social media data can provide useful information on evolving hazards. Alongside
traditional methods of disaster detection, the integration of social media data can …

Incorporating deep learning and news topic modeling for forecasting pork prices: the case of South Korea

T Chuluunsaikhan, GA Ryu, KH Yoo, HC Rah… - Agriculture, 2020 - mdpi.com
Knowing the prices of agricultural commodities in advance can provide governments,
farmers, and consumers with various advantages, including a clearer understanding of the …

Portability of semantic and spatial–temporal machine learning methods to analyse social media for near-real-time disaster monitoring

C Havas, B Resch - Natural Hazards, 2021 - Springer
Up-to-date information about an emergency is crucial for effective disaster management.
However, severe restrictions impede the creation of spatiotemporal information by current …

Deep learning models for road passability detection during flood events using social media data

L Lopez-Fuentes, A Farasin, M Zaffaroni… - Applied Sciences, 2020 - mdpi.com
During natural disasters, situational awareness is needed to understand the situation and
respond accordingly. A key need is assessing open roads for transporting emergency …

A seed-guided latent dirichlet allocation approach to predict the personality of online users using the pen model

S Sagadevan, NHAH Malim, MH Husin - Algorithms, 2022 - mdpi.com
There is a growing interest in topic modeling to decipher the valuable information embedded
in natural texts. However, there are no studies training an unsupervised model to …

Topic prediction and knowledge discovery based on integrated topic modeling and deep neural networks approaches

Z Shahbazi, YC Byun - Journal of Intelligent & Fuzzy Systems, 2021 - content.iospress.com
Understanding the real-world short texts become an essential task in the recent research
area. The document deduction analysis and latent coherent topic named as the important …

Disaster impacts surveillance from social media with topic modeling and feature extraction: case of Hurricane Harvey

VV Mihunov, NH Jafari, K Wang, NSN Lam… - International Journal of …, 2022 - Springer
Twitter can supply useful information on infrastructure impacts to the emergency managers
during major disasters, but it is time consuming to filter through many irrelevant tweets …

Fusion of geospatial information from remote sensing and social media to prioritise rapid response actions in case of floods

M Wieland, S Schmidt, B Resch, A Abecker, S Martinis - Natural Hazards, 2025 - Springer
Efficiently managing complex disasters relies on having a comprehensive understanding of
the situation at hand. Immediately after a disaster strikes, it is crucial to quickly identify the …