A5081330002- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Climate variability and models
- Geotechnical Engineering and Underground Structures
- Seismic Waves and Analysis
- Seismic Performance and Analysis
- Soil Moisture and Remote Sensing
- Structural Health Monitoring Techniques
- Speech Recognition and Synthesis
- Speech and Audio Processing
- Music and Audio Processing
- Remote Sensing and Land Use
- Geotechnical Engineering and Soil Mechanics
- Vaccine Coverage and Hesitancy
- Plant Water Relations and Carbon Dynamics
- Advanced oxidation water treatment
- Climate change impacts on agriculture
- Flood Risk Assessment and Management
- Nanomaterials for catalytic reactions
- Catalysis and Hydrodesulfurization Studies
- Viral gastroenteritis research and epidemiology
- Geotechnical Engineering and Soil Stabilization
- Electrocatalysts for Energy Conversion
- Tropical and Extratropical Cyclones Research
- Infrastructure Maintenance and Monitoring
Chaohu University
2024
Anhui Agricultural University
2022
The University of Texas at Austin
2019
University of California, Irvine
2014-2018
Irvine University
2014-2017
Beijing Normal University
2012-2014
Abstract Despite the advantage of global coverage at high spatiotemporal resolutions, satellite remotely sensed precipitation estimates still suffer from insufficient accuracy that needs to be improved for weather, climate, and hydrologic applications. This paper presents a framework deep neural network (DNN) improves products, focusing on reducing bias false alarms. The state-of-the-art learning techniques developed in area machine specialize extracting structural information massive amount...
Abstract Compared to ground precipitation measurements, satellite-based estimation products have the advantage of global coverage and high spatiotemporal resolutions. However, accuracy is still insufficient serve many weather, climate, hydrologic applications at In this paper, authors develop a state-of-the-art deep learning framework for using bispectral satellite information, infrared (IR), water vapor (WV) channels. Specifically, two-stage from information designed, consisting an initial...
The small-strain damping ratio (Dmin) is a key parameter in site response models and using values from laboratory tests tends to overpredict the because cannot capture wave scattering effects that are present field. In this study, earthquake motions four downhole array sites used investigate increase Dmin, as quantified by Dmin multiplier applied based required match response. Empirical observations data compared with theoretical results linear-viscoelastic, one-dimensional analysis....
Abstract In the development of a satellite-based precipitation product, two important aspects are sufficient information in satellite-input data and proper methodologies, which used to extract such connect it estimates. this study, effectiveness state-of-the-art deep learning (DL) approaches useful features from bispectral satellite information, infrared (IR), water vapor (WV) channels, produce rain/no-rain (R/NR) detection is explored. To verify models designed evaluated: first model,...
This paper evaluates how post-processing can enhance raw precipitation forecasts made by different numerical weather prediction (NWP) models archived in TIGGE (THORPEX Interactive Grand Global Ensemble) database. Ensemble Pre-Processor (EPP), developed at U.S. National Weather Service, is used to post-process forecasts. EPP involves several major steps: (1) deriving the joint distributions of and observations corresponding canonical events; (2) obtaining probability given forecasts; (3)...
This paper investigates the application of deep neural networks to precipitation estimation from remotely sensed information. Specifically, a stacked denoising auto-encoder is used automatically extract features infrared cloud images and estimate amount precipitation, referred as PERSIANN-SDAE. Due challenging imbalance in data, Kullback-Leibler divergence incorporated objective function preserve distribution it. PERSIANN-SDAE compared with shallow network hand designed an operational...
TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research development of technologies by providing well-designed, easy-to-use, performant PyTorch components. Its contributors routinely engage with users understand their needs fulfill them developing impactful features. Here, we survey TorchAudio's principles contents highlight key features include in its latest version (2.1): self-supervised learning pre-trained pipelines training...
Typhoon Haiyan, which struck Southeast Asia in November 2013, might be the strongest storm on record, with a 10‐minute sustained wind speed of 230 kilometers per hour. In Philippines alone, damage was immense—the killed more than 6000 and completely leveled cities towns, particularly island Leyte.
Abstract The National Center for Environmental Predictions (NCEP) has produced an ensemble meteorological reforecast product by using a fixed version of Global Forecast System (GFS) prediction system since 1 January 1979. 15‐member product, with global coverage at 2.5° × spatial resolution and 14‐day lead time, been used successfully the River Centers Weather Service (NWS) to produce basin scale precipitation temperature forecasts in US several years now. This study evaluates predictive...
ABSTRACT The biases in the Global Circulation Models ( GCMs ) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from assumption that model is stationary. This paper provides a non‐stationary model, termed residual‐based bagging tree RBT to reduce simulation and quantify contributions of single models. Specifically, proposed estimates residuals between individual models observations, takes differences observations ensemble mean into...
ABSTRACT This short note examines the downgoing wave effect and appearance of pseudoresonances in downhole array data. It is demonstrated that pseudoresonances, distinct from resonances associated with outcrop conditions, occur for sites a shallow velocity contrast (VC) or little to no VC. An approach outlined distinguish using theoretical 1D transfer functions within boundary as well horizontal-to-vertical spectral ratio. applied hypothetical shear-wave profiles, three sites. We establish...
This paper illustrates two novel methods for computing the small-strain hysteretic material damping ratio, λmin, of soils from cyclic torsional shear (TS) and viscous Dmin, free-vibration decay (FVD) testing. Both λmin Dmin are challenging to measure, due significant level ambient noise at small strains (<10−4%). A two-step method is proposed combining Fourier Transform a phase-based data fitting testing, this can effectively eliminate strains. Hilbert Transform-based testing in order...
TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research development of technologies by providing well-designed, easy-to-use, performant PyTorch components. Its contributors routinely engage with users understand their needs fulfill them developing impactful features. Here, we survey TorchAudio's principles contents highlight key features include in its latest version (2.1): self-supervised learning pre-trained pipelines training...