Accurate wind speed prediction is of importance for long-span cross-sea bridges. To this end, data decomposition techniques are usually employed to promote accuracy of the prediction model. Since wind speed data come sequentially, real-time decomposi...
Long-term multivariate time series forecasting serves as a fundamental analytical tool across diverse domains, such as energy management, transportation analysis, and meteorology. However, conventional modeling paradigms often yield suboptimal result...
Fault diagnosis plays a crucial role in maintaining the operational safety of mechanical systems. As intelligent data-driven approaches evolve, deep learning (DL) has emerged as a pivotal technique in fault diagnosis research. However, the collected...
In time series analysis, the ability to effectively handle data with varying sampling rates is crucial for accurate modeling and analysis. This paper presents the MR-BoF (Multi-Resolution Bag of Functions) framework, which leverages sampling-rate-ind...
With the rapid development of China’s economy and industry, characterizing the spatial and temporal changes of aerosols in China has attracted widespread attention from researchers. The national-level urban agglomerations are the most concentra...
This paper presents a novel framework to determine the number of resolution levels in the application of a wavelet transformation to a rainfall time series. The rainfall time series are decomposed using the à trous wavelet transform. Then, multi-scal...
Wavelet transform is a well-known multi-resolution tool to analyze the time series in the time-frequency domain. Wavelet basis is diverse but predefined by manual without taking the data into the consideration. Hence, it is a great challenge to selec...
Attaining a high-resolution and accurate location for a radiated passive intermodulation source (R-PIMS) has been an increasingly interesting problem in modern multi-carrier wireless communication systems. For precisely positioning multiple closely s...
The spectral decomposition is a valuable tool for improving the resolution of seismic interpretation, and thus can improve the accuracy of the subtle geo-features (thin and narrow channels, thin reservoirs, etc.). Variational mode decomposition (VMD)...
Land cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spa...
Stereo matching is an open problem in Computer Vision, for which local features are extracted to identify corresponding points in pairs of images. The results are heavily dependent on the initial steps. We apply image decomposition in multiresolution...
With the continuous development of power systems, WAMS have become increasingly important for real-time system monitoring. As the core devices of WAMS, PMUs can provide synchronized, high-precision, and high-resolution measurements of power system st...
Total phosphorus (TP) dynamics between reservoirs and inflowing rivers critically affect eutrophication risks, but their multi-scale interactions remain insufficiently quantified. This study applied wavelet transform analysis to 8-year TP time series...
Fast-response pressure sensitive paint (PSP) is used in this work to measure and analyze the acoustic pressure field in a rectangular cavity. The high spatial resolution and fast frequency response of PSP effectively captures the spatial and temporal...
This study proposes a hybrid analytical framework for detecting chondromalacia using vibroacoustic (VAG) signals from patients with knee osteoarthritis (OA) and healthy controls (HCs). The methodology combines nonlinear signal decomposition, feature...
Existing infrared (IR)-visible (VIS) image fusion algorithms demand source images with the same resolution levels. However, IR images are always available with poor resolution due to hardware limitations and environmental conditions. In this correspo...
Conventional decomposition models (empirical and numerical decomposition models) estimate direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) from global horizontal irradiance (GHI) based on empirical correlations or physical equat...
Electroencephalography (EEG) provides excellent temporal resolution for brain activity analysis but limited spatial resolution at the sensors, making source unmixing essential. Our objective is to enable accurate brain activity analysis from EEG by p...
Interferometric Synthetic Aperture Radar (InSAR) is an advanced imaging geodesy technique for detecting and characterizing surface deformation with high spatial resolution and broad spatial coverage. However, as an inherently post-event observation m...
Accurate ultra-short-term wind power forecasting is vital for the secure and economic operation of power systems with high renewable penetration. Conventional models, however, struggle with multi-scale frequency feature extraction, dynamic cross-vari...
Transitioning predictive maintenance from expensive, high-frequency piezoelectric sensors to affordable, edge-deployed MEMS sensors poses a significant challenge in industrial tool condition monitoring (TCM). Both technologies differ in signal qualit...
Pipeline systems are prone to defects due to the harsh service conditions, which may induce catastrophic failure if found not in time. Ultrasonic guided wave (UGW) testing provides a convenient option for pipeline detection, showing high-efficiency,...
The 3D reconstruction of vessel hulls is crucial for enhancing safety, efficiency, and knowledge in the maritime industry. Neural Radiance Fields (NeRFs) are an alternative to 3D reconstruction and rendering from multi-view images; particularly, tens...
Structural health monitoring of buried pipelines is essential due to their exposure to corrosion, impact loads, and geotechnical disturbances, which may induce abnormal vibration responses. Acceleration signals provide direct and sensitive measuremen...
High accuracy and a high spatiotemporal resolution of precipitation are essential for the hydrological, ecological, and environmental fields. However, the existing daily gridded precipitation datasets, such as remote sensing products, are limited bot...
Gesture recognition is important for rehabilitation assistance and intelligent prosthetic control. However, surface electromyography (sEMG) signals exhibit strong non-stationarity, and conventional deep-learning models require long training time and...
Monitoring power quality (PQ) and classifying disturbances are essential for guaranteeing the reliable operation of contemporary electrical systems. Nonetheless, deriving discriminative features from PQ signals poses difficulties due to the complexit...
Due to the small number of baselines (2–3), the traditional L1 norm compressive sensing method for layover solution in InSAR has poor separation ability and height estimation stability and a long operation time. This paper, based on the idea of...
With high performances of image capturing tools, image information can be easily obtained by screenshots that make image copyright protection a challenging task. The existing screen-shooting watermarking algorithms suffer from a huge running time, in...
Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is...
Data interpretation is the crucial scientific component that influences the inspection accuracy of ground penetrating radar (GPR). Developing algorithms for interpreting GPR data is a research focus of increasing interest. The problem of algorithms f...
As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and...
This work targets a knowledge gap in the high-pressure decomposition of methanol, complementing prior moderate-pressure diamond anvil studies below 4 GPa and hyperbaric-pressure laser chemical vapour deposition (HP-LCVD) experiments below 0.01 GPa. L...
Carbon efficiency, measuring effective output per unit of carbon emissions, is vital for managing low-carbon workshops and advancing sustainable manufacturing. However, production processes often face concurrent discrete events (e.g., equipment failu...
Non-contact heart rate estimation technology based on frequency-modulated continuous wave (FMCW) radar has garnered extensive attention in single-target scenarios, yet it remains underexplored in multi-target environments. Accurate discrimination of...
Azimuth multi-channel techniques show great promise in high-resolution, wide-swath synthetic aperture radar systems. However, in practical engineering applications, errors between channels can significantly affect the reconstruction of multi-channel...
High-accuracy calibration of resolver signals is the key to improve its angular measurement accuracy. However, inductive harmonics, residual excitation components, and random noise in signals dramatically restrict the further improvement of calibrati...
Azimuth multi-channel synthetic aperture radar (SAR) has always been an important technical means to achieve high-resolution wide-swath (HRWS) SAR imaging. However, in the space-borne azimuth multi-channel SAR system, random phase noise will be produ...
Sea level monitoring is particularly important in coastal areas that are vulnerable to marine disasters. It was recently demonstrated that the global navigation satellite system multipath reflectometry (GNSS-MR) technique, which uses multipath signal...
Real-time seismic reservoir monitoring of geologic reservoirs requires both large-scale data management and efficient computational workflows. Addressing these challenges is facilitated by developing techniques capable of selectively capturing critic...
The severe effects of attention deficit hyperactivity disorder (ADHD) among adolescents can be prevented by timely identification and prompt therapeutic intervention. Traditional diagnostic techniques are complicated and time-consuming because they a...
The internal flow of a semi-open axial flow fan is highly three-dimensional and unsteady due to the absence of a confined passage. The evolution of complex vortical structures, such as the tip leakage vortex (TLV) and corner separation vortex (CSV),...
As the global energy system accelerates its transition toward a low-carbon economy, renewable energy sources (RESs), such as wind and photovoltaic power, are rapidly replacing traditional fossil fuels. These RESs are becoming a critical element of de...
Partial discharge (PD) is a critical indicator of insulation degradation in high-voltage DC systems, necessitating accurate diagnosis to ensure long-term reliability. Conventional AC-based diagnostic methods, such as phase-resolved partial discharge...
While occurrences of wavelike motion in the stable boundary layer due to the presence of a significant restoring buoyancy force are rarely disputed, their modalities and interaction with turbulence remain a subject of active research. In this work, t...
This work revisits a class of biomimetically inspired waveforms introduced by R.A. Altes in the 1970s for use in sonar detection. Similar to the chirps used for echolocation by bats and dolphins, these waveforms are log-periodic oscillations, windowe...
Typhoon-induced extreme weather poses a severe threat to power systems with high offshore wind penetration. Source-side wind turbine tripping and grid-side transmission line failures are likely to occur simultaneously, which may trigger cascading out...
Accurate crack severity classification in rotating shafts remains a challenging task due to the strong spectral overlap between adjacent damage levels and the absence of distinct fault-specific frequency components. In such conditions, conventional v...
For multi-temporal high resolution remote sensing images, the image registration is important but difficult due to the high resolution and low-stability land-cover. Especially, the changing of land-cover, solar altitude angle, radiation intensity, an...
Surface deformation is characterized by long-term accumulation and significant spatial differences, commonly inducing ground fissures and structural damage to roads and buildings, and in severe cases, causing collapses and other accidents that direct...
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