H

Hao Sun

Weifang University

ORCID: 0009-0001-5612-7276

Publishes on Recommender Systems and Techniques, Neural Networks and Applications, Traffic and Road Safety. 9 papers and 9 citations.

9Publications
9Total Citations

Is this you? Claim your profile.

Add your photo, update your bio, and get notified when your ranking changes.

Top publicationsby citations

Relieving photobleaching impacts on fluorescence thermometry via neural network predictions
jiahao wang, B. H. Wu, Chunrui Wang et al.|Applied Optics|2024
Cited by 2

The thermal sensitivity of luminescence intensities enables fluorescence thermometry for remote temperature probing with high spatial and temporal resolutions. However, its accuracy suffers from factors such as nonlinear thermal response and the photochemical stability of fluorescence sensors. In this work, we realized thermometric measurements with high spatial resolution at micrometer scale using thin films with europium (Eu) complexes and microscopic measurements. We identified tris(dibenzoylmethane)phenanthroline europium(III)/polystyrene (Eu(DBM) 3 Phen/PS) thin film as an optimal choice for not only its linear dependence on fluorescence intensity for temperatures of biological interest but also its stronger resistance to the photobleaching effect. More importantly, we show that the latter effect can be effectively compensated via neural network methods. This approach has been validated for surface temperature mapping at the thermal equilibrium, where better uniformity as compared with results without correcting the photobleaching effect was achieved. The temperature elevation of resistive wires due to Joule heating can be clearly identified. This work shows that neural network models are powerful tools in improving the accuracy of fluorescence thermometry and beneficial for applications ranging from biology to nanotechnologies.

Mashup FOAF for Video Recommendation LightWeight Prototype
Cited by 2

There are more and more xml document, web services, feeds and so on and so forth cheap, network accessible resources to use. As one of the most widely used semantic web project, FOAF (Friend of a Friend) pays more and more attention to FOAF semantic features to analyze users' interest and to recommend to FOAF users recent years. This essay focuses on applying FOAF to a latest online television programs recommendation system for a particular user. In this paper television programs come from various online video web sites that a user has registered in are watched at different time. The article describes the approach to such services based on HMM (Hidden Markov Model) and FOAF project. In order to protect the user's privacy when providing services, this system is designed as a local-service desktop model. We conduct experiments to illustrate users' high degree of satisfaction to our techniques.

Overview: Research on the Consistency of Multi-Agent Systems
Heli Xing, Dazhi Liu, Liang Yu et al.|Unknown|2025
Cited by 0

Firstly, this article briefly introduces the basic concepts and development history related to multi-agent systems, and lists important time points in the development history. Subsequently, from the perspectives of unified consensus in multi-agent systems, consistency under switching topologies, distributed parameter multi-agent consensus, theory and application of Pulse Width Modulation (PWM) and multi-agent pulse width modulation, the main content of current research on multi-agent consensus is summarized, laying out the direction for multi-agent consensus research. Finally, we provide direction and ideas for future research on multi-agent consensus.