A5027255709- Privacy-Preserving Technologies in Data
- Network Traffic and Congestion Control
- Cryptography and Data Security
- Catalytic Cross-Coupling Reactions
- Risk and Safety Analysis
- Organic Light-Emitting Diodes Research
- Marine and Coastal Research
- Internet Traffic Analysis and Secure E-voting
- Luminescence and Fluorescent Materials
- Technology and Data Analysis
- Complex Network Analysis Techniques
- Traffic Prediction and Management Techniques
Jiangsu University
2025
University of Science and Technology of China
2024
Jilin University
2003
Abstract Optoelectronic logic gates (OELGs) are considered a promising alternative to traditional electronic gates, thanks their high computational speed and low power consumption. Meanwhile, there enormous challenges including complex structures single‐function. In this study, the optoelectronic gate device is prepared merely through single Cs 3 Bi 2 Br 9 photodetector. The bidirectional photoresponsive behavior of exhibited under bias voltages modulated by change current level. five...
Abstract We demonstrate novel organic light‐emitting diode (LED) materials that contain a green phosphorescent dye (dmbpy)Re(CO) 3 Cl (dmbpy = 4,4′‐dimethyl‐2,2′‐bipyridine), and red fluorescent 4‐dicyanomethylene‐6‐( p ‐dimethylaminostyryl)‐2‐methyl‐4H‐pyran (DCM) as dopants polyvinylcarbazole (PVK) the host. The photoluminescence (PL) electroluminescence (EL) properties of these complex were studied. energy transfer efficiency from PVK host to DCM is increased by co‐dopant, which has an...
Federated Learning (FL) is a learning architecture in which multiple clients use local data to train gradients and submit them server for global aggregation. However, achieving reliable federated untrusted environments challenging. Malicious users servers can perform Byzantine attacks manipulate the model, curious also extract user privacy from update gradients. Privacy-preserving methods usually consume many communication computing resources are difficult combine with robust aggregation...
Network traffic prediction plays an important role in network management and operation maintenance. Traditional models do not take into account the impact of routing paths on performance, nor different flows same link. To solve this challenge, paper original topology as a link hypergraph, taking source-destination pairs vertices graph links hyperedges, which can effectively extract connections between application flows. influence relationship. On basis, proposes model based spatio-temporal...