Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization

H Du, R Zhang, Y Liu, J Wang, Y Lin, Z Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …

Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

H Du, R Zhang, Y Liu, J Wang, Y Lin… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …

Mobile crowdsourcing in smart cities: Technologies, applications, and future challenges

X Kong, X Liu, B Jedari, M Li, L Wan… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Local administrations and governments aim at leveraging wireless communications and
Internet of Things (IoT) technologies to manage the city infrastructures and enhance the …

Public participation in the Geoweb era: Defining a typology for geo-participation in local governments

S Zhang - Cities, 2019 - Elsevier
Advancements in citizen sensing and geospatial big data have enabled new opportunities
for government-citizen interactions and have played important roles in developing smart (er) …

Mobile crowdsensing as a service: a platform for applications on top of sensing clouds

G Merlino, S Arkoulis, S Distefano, C Papagianni… - Future Generation …, 2016 - Elsevier
Consumer-centric mobile devices, such as smartphones, are an emerging category of
devices at the edge of the Internet. Leveraging volunteers and their mobiles as a (sensing) …

Public acceptance of a crowdsourcing platform for traffic enforcement

M Khojastehpour, S Sahebi, A Samimi - Case studies on transport policy, 2022 - Elsevier
Iran is a country with numerous traffic accidents, offenses, and disruptions. According to the
deterrence theory, increased detection of traffic offenses would decrease violations …

A fair incentive mechanism for crowdsourcing in crowd sensing

X Zhu, J An, M Yang, L Xiang… - IEEE Internet of Things …, 2016 - ieeexplore.ieee.org
Crowd sensing (CS) is a new paradigm of collecting large amounts of sensing information
from a crowd. Unfortunately, not everyone is willing to participate in sensing tasks or provide …

SimRa: Using crowdsourcing to identify near miss hotspots in bicycle traffic

AS Karakaya, J Hasenburg, D Bermbach - Pervasive and Mobile …, 2020 - Elsevier
An increased modal share of bicycle traffic is a key mechanism to reduce emissions and
solve traffic-related problems. However, a lack of (perceived) safety keeps people from using …

Cloud, edge, and mobile computing for smart cities

Q Liu, J Gu, J Yang, Y Li, D Sha, M Xu, I Shams, M Yu… - Urban Informatics, 2021 - Springer
Smart cities evolve rapidly along with the technical advances in wireless and sensor
networks, information science, and human–computer interactions. Urban computing …

QuaCentive: a quality-aware incentive mechanism in mobile crowdsourced sensing (MCS)

Y Wang, X Jia, Q Jin, J Ma - The Journal of Supercomputing, 2016 - Springer
Today's smartphones with a rich set of cheap powerful embedded sensors can offer a variety
of novel and efficient ways to opportunistically collect data, and enable numerous mobile …