A5100763522- Hydrology and Watershed Management Studies
- Fish Ecology and Management Studies
- Soil and Water Nutrient Dynamics
- Adsorption and biosorption for pollutant removal
- Advanced oxidation water treatment
- EEG and Brain-Computer Interfaces
- Microbial bioremediation and biosurfactants
- Oil Spill Detection and Mitigation
- Membrane Separation Technologies
- Marine and coastal ecosystems
- Geological and Geochemical Analysis
- Aquatic Ecosystems and Phytoplankton Dynamics
- Water resources management and optimization
- Wastewater Treatment and Nitrogen Removal
- Water Treatment and Disinfection
- earthquake and tectonic studies
- Stock Market Forecasting Methods
- Water Quality and Pollution Assessment
- Arsenic contamination and mitigation
- Nanomaterials for catalytic reactions
- Hydrological Forecasting Using AI
- Chemical Synthesis and Characterization
- Coagulation and Flocculation Studies
- Environmental Chemistry and Analysis
- Environmental Changes in China
Nanjing University of Science and Technology
2025
Jinzhou Medical University
2021-2025
Qingdao University of Technology
2007-2024
International Institute for Applied Systems Analysis
2024
Peking University
2022-2024
Jilin Jianzhu University
2024
Hunan University
2023-2024
Sichuan University
2024
Fudan University
2024
Ministry of Ecology and Environment
2024
The motor imagery brain–computer interface (MI-BCI) system is currently one of the most advanced rehabilitation technologies, and it can be used to restore function stroke patients. deep learning algorithms in MI-BCI require lots training samples, but electroencephalogram (EEG) data patients quite scarce. Therefore, expansion EEG has become an important part clinical research. In this paper, a convolution generative adversarial network (DCGAN) model proposed generate artificial further...
The beneficial effect of probiotics on host health is impaired due to the substantial loss survivability during gastric transit caused by small intestinal enzymes and bile acids. Encapsulation helps preserve species from severe environmental factors.
Water diversion is a common strategy to enhance water quality in eutrophic lakes by increasing available resources and accelerating nutrient circulation. Its effectiveness depends on changes the source lake conditions. However, challenge of optimizing remains because it difficult simultaneously improve minimize amount diverted water. Here, we propose new approach called dynamic optimization (DWDO), which combines comprehensive model with deep reinforcement learning algorithm. We applied DWDO...
Abstract Deep learning networks have been successfully applied to transfer functions so that the models can be adapted from source domain different target domains. This study uses multiple convolutional neural decode electroencephalogram (EEG) of stroke patients design effective motor imagery (MI) brain-computer interface (BCI) system. has introduced ‘fine-tune’ model parameters and reduced training time. The performance proposed framework is evaluated by abilities for two-class MI...
To develop an efficient brain-computer interface (BCI) system, electroencephalography (EEG) measures neuronal activities in different brain regions through electrodes. Many EEG-based motor imagery (MI) studies do not make full use of network topology. In this paper, a deep learning framework based on modified graph convolution neural (M-GCN) is proposed, which temporal-frequency processing performed the data S-transform (MST) to improve decoding performance original EEG signals types MI...
Riverine nitrogen (N) loading is increasing rapidly due to both climate change and human activities, posing severe threats global water quality. However, the contributions of precipitation, temperature their interactions in driving these increases remain insufficiently understood at scale. Here, we establish a Global River Nitrogen Discharge (GRIND) observations database develop machine learning model generate high-resolution (5-arcminute) spatially explicit estimates riverine N loading,...
ABSTRACT In this study, four thermal damage assessment methods were used to investigate the caused by femtosecond lasers on skin tissues. Collagen volume and texture characteristic parameters of microstructure calculated analyzed Masson staining samples grayscale covariance matrix. The degree protein denaturation Arrhenius equation Raman spectroscopy. results show that as laser power increases or scanning speed decreases, collagen tissue angular second‐order moments correlations increase,...
Summary This article reports a brand‐new methodology based on active learning Kriging model for hybrid reliability analysis (HRA) with both random and interval variables. Unlike probabilistic analysis, the limit state surface (LSS) of HRA is projected into banded region in domain Only approximating bounds able to meet accuracy requirement HRA. In proposed methodology, problem innovatively transformed traditional system (SRA) numerous failure modes. And then basic idea from field SRA borrowed...