A5101710174- Privacy-Preserving Technologies in Data
- Stochastic Gradient Optimization Techniques
- Traffic Prediction and Management Techniques
- Perovskite Materials and Applications
- Recycling and Waste Management Techniques
- Blockchain Technology Applications and Security
- Atmospheric and Environmental Gas Dynamics
- Advanced Graph Neural Networks
- Traffic control and management
- Municipal Solid Waste Management
- Privacy, Security, and Data Protection
- Anomaly Detection Techniques and Applications
- Human Mobility and Location-Based Analysis
- Gait Recognition and Analysis
- Electrohydrodynamics and Fluid Dynamics
- Solar Radiation and Photovoltaics
- Cryptography and Data Security
- Vehicular Ad Hoc Networks (VANETs)
- Quantum Dots Synthesis And Properties
- Electrokinetic Soil Remediation Techniques
- Ionic liquids properties and applications
- Conducting polymers and applications
- Groundwater flow and contamination studies
- Atmospheric aerosols and clouds
- Job Satisfaction and Organizational Behavior
East China Normal University
2023-2024
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)
2023
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)
2023
Sun Yat-sen University
2023
Northwestern Polytechnical University
2023
Northeast Electric Power University
2021
Guiyang Medical University
2021
Xi'an Jiaotong University
2021
Tsinghua University
2018
Hunan University of Humanities, Science and Technology
2014
A multifunctional molecule at interface was explored to inhibit phase separation and passivate defects, producing perovskite solar cells with efficiencies of 21.82% (0.05 cm 2 ) 18.05% (1.92 1.67 eV bandgap excellent stability.
Federated Learning (FL) is a promising paradigm for massive data mining service while protecting users' privacy. In wireless federated learning networks (WFLNs), limited communication resources and heterogeneity of user devices have essential impacts on training efficiency FL, hence it critical to select clients allocate network bandwidths among them in each round improve the efficiency. this article, we formulate joint client selection bandwidth allocation optimization problem as MDP...
Federated Learning (FL) is a promising paradigm for mining massive data while respecting users' privacy. However, the deployment of FL on resource-constrained edge devices remains elusive due to its high resource demand. In this paper, unlike existing works that use expensive dense models, we propose utilize dynamic sparse training in and design novel sparse-to-sparse framework, named as POP-FL. The framework can reduce both computation communication overheads maintaining performance global...
Hexachlorobenzene (HCB) contamination of soils remains a significant environmental challenge all over the world. Reductive stabilization is developing technology that can decompose HCB with dechlorination process. A nanometallic Al/CaO (n-Al/CaO) dispersion mixture was developed utilizing ball-milling in this study. The efficiency contaminated by n-Al/CaO grinding treatment evaluated. Response surface methodology (RSM) employed to investigate effects three variables (soil moisture content,...
Clouds are important modulators of the solar radiation reaching earth’s surface. However, impacts cloud properties other than cover seldom mentioned. By combining satellite-retrieved properties, latest radiative transfer model, and an advanced PVLIB-python software for photovoltaic (PV) estimation, different types clouds on maximum available PV potential (measured with plane-of-array-irradiance, POAI) quantified. The ice liquid water found to be highest Tibetan Plateau over western China in...
One of the primary challenges in cloud-edge environments is efficiently utilizing significant amounts data on edge devices for machine learning tasks, enabling adaptation to increasingly complex computing and service scenarios. Federated Learning (FL) a paradigm that enables collaborative training models involving multiple warehouses privacy-preserving manner. However, classical federated has poor convergence highly heterogeneous data, which limits its performance global model each device....
Abstract Rock climbing is a sports activity that integrates competition, entertainment, and culture. With the development of economy improvement in living standards, rock has embarked on path self-development entered lives urban youth at an increasingly rapid rate. This paper studies probabilistic model recognition based time series multi-information fusion sensors so climbers can climb more standardized. Based practice, this conducted research design hardware platform actually applied it to...
In the big data era, Federated Learning (FL), which allows multiple participants to collaboratively train a global model without sharing their raw data, emerges as promising solution address challenges of isolated silos and privacy protection. learning has two main communication strategies: synchronous asynchronous. Synchronous FL ensures stable convergence but may encounter quality degradation server crash risks. Asynchronous avoids straggler effect supports more participants, unstable...
Family supportive supervisor behaviors (FSSB) aim to influence employees positively, yet scholars know little about how it affects actors themselves. We draw on conservation of resources theory and self-determination develop hypotheses the effects FSSB supervisors. suggest that although can cause supervisor’s emotional exhaustion consequent laissez-faire behaviors, is also positively associated with perception prosocial impact, motivation sequent servant leadership behaviors. Furthermore,...