The data collected by floating cars is an important source for lane-level map production. Compared with other data sources, this method is a low-cost but challenging way to generate high-accuracy maps. In this paper, we propose a data correction algo...
The first airborne hyperspectral campaign in the Antarctic Peninsula region was carried out by the British Antarctic Survey and partners in February 2011. This paper presents an insight into the applicability of currently available radiative transfer...
The mode bias is present and time-dependent due to imperfect configurations. Data assimilation is the process by which observations are used to correct the model forecast, and is affected by the bias. How to reduce the bias is an important issue. Thi...
Many models assumed to be able to predict the response of structural systems fail to efficiently accomplish that purpose because of two main reasons. First, some structures in operation undergo localized damage that degrades their mechanical performa...
This paper describes and implements a time-spatial correction of the regional prediction wave system, compared with altimeter data, by using an ensemble Kalman filter. The technique is successful in areas with substantial wave height around the Azore...
In recent years, data hiding techniques have emerged as a prominent area of research due to the increasing demand for information security. Existing data hiding techniques typically do not prioritize the verification of the correctness of the extract...
Reliable climate data are essential for sustainable water management systems, especially under the challenges posed by climate change. In data-scarce regions, reanalysis products such as ERA5 can support flood and drought risk assessment and water se...
Accurate geospatial data are essential for intelligent transportation systems and automated reporting applications, as location precision directly impacts safety analysis and decision-making. GPS devices are now routinely employed by law enforcement...
In recent years, outliers caused by manual operation errors and equipment acquisition failures often occur, bringing challenges to big data analysis. In view of the difficulties in identifying and correcting outliers of multi-source data, an intellig...
The accuracy of shallow-water multibeam bathymetry is critically dependent on precise heave correction. However, sensor limitations often lead to incomplete correction, leaving periodic along-track stripe noises (heave residuals) that distort seabed...
Background/Objectives: This study applies the previously introduced structure-preserving hybrid framework for compartmental pharmacokinetic models and extends its clinical evaluation using published clinical datasets. The framework combines a mechani...
This paper proposes a data anomaly detection and correction algorithm for the tea plantation IoT system based on deep learning, aiming at the multi-cause and multi-feature characteristics of abnormal data. The algorithm is based on the Z-score standa...
Shallow-water depth information is essential for ship navigation and fishery farming. However, the accurate acquisition of shallow-water depth has been a challenge for marine mapping. Combining Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) ba...
Recent advancements in precision agriculture have been significantly bolstered by the Uncrewed Aerial Vehicles (UAVs) equipped with multispectral sensors. These systems are pivotal in transforming sensor-recorded Digital Number (DN) values into unive...
A distinction is made between data rescue (i.e., copying, digitizing, and archiving) and data recovery that implies deciphering, interpreting, and transforming early instrumental readings and their metadata to obtain high-quality datasets in modern u...
The geometric accuracy of a workpiece represents one of the key parameters defining its quality, and it is affected by the appropriate selection of the machine tool, control system, NC program and cutting conditions. Up-to-date control systems contai...
The past decade has witnessed the rapid development of the SRTM (Shuttle Radar Topography Mission) DEM (digital elevation model) in engineering applications and scientific research. The near-global SRTM DEM was generated based on radar interference t...
Reliable tabular data correction is a prerequisite for trustworthy analytics in enterprise information systems. Tabular data in such environments frequently contain formatting errors, semantic conflicts, missing values, and cross-field inconsistencie...
To improve the prediction accuracy of compressor performance for marine gas turbine applications, a data-driven adaptive correction method is proposed. A one-dimensional meanline model is first developed; however, noticeable discrepancies are observe...
In ocean color remote sensing, most of the radiative energy received by sensors comes from the atmosphere, requiring highly accurate atmospheric correction. Although atmospheric correction models based on ground measurements—especially the Grou...
China’s marine satellite infrared radiometer SST remote sensing observations began relatively late. Thus, it is essential to evaluate and correct the SST observation data of the Ocean Color and Temperature Scanner (COCTS) onboard the China HY-1...
Operational applications for Synthetic Aperture Radar (SAR) are under development around the world, driven by the free-and-open access of SAR C-band observations that Sentinel-1 of Copernicus has provided since 2014. Radiometric Terrain Correction (R...
Big data has emerged as a fundamental component in various domains, enabling organizations to extract valuable insights and make informed decisions. However, ensuring data quality is crucial for effectively using big data. Thus, big data quality has...
The most realistic information about a transparent sample such as a live cell can be obtained using bright-field light microscopy. Under high-intensity pulsing LED illumination, we captured a primary 12-bit-per-channel (bpc) response from an observed...
Morocco’s meteorological observation network is quite old, but the spatial coverage is insufficient to conduct studies over large areas, especially in mountainous regions, such as the Fez-Meknes region, where spatio-temporal variability in prec...
Bias correction is a key prerequisite for radiance data assimilation. Directly assimilating the radiance observations generally involves large systematic biases affecting the numerical prediction accuracy. In this study, a nonlinear bias correction s...
Land surface reflectance (LSR) data form the basis of quantitatively remotely sensed applications. For accurate LSR retrieval, atmospheric correction has been investigated by many researchers and implemented in typical processing systems, including c...
The development of electricity spot markets necessitates more refined and accurate load forecasting capabilities to enable precise dispatch control and the creation of new trading products. Accurate load forecasting relies on high-quality historical...
Satellite-derived soil moisture (SM) observations are widely assimilated in global land data assimilation systems. These systems typically assume zero-mean errors in the land surface model and observations. In practice, systematic differences (biases...
Functional near-infrared spectroscopy (fNIRS) is an optical non-invasive neuroimaging technique that allows participants to move relatively freely. However, head movements frequently cause optode movements relative to the head, leading to motion arti...
Background: Motion is a long-standing problem in cardiac PET/CT. An automated data-driven motion correction (DDMC) algorithm for within-reconstruction motion correction (MC) has been developed and validated in static images from [13N]NH3 and 82Rb PET...
In the field of ocean observation, we often face the challenge of the contradiction between the vast ocean environment and limited ocean sensor observations, resulting in significant sparsity in the acquired ocean sensor data. This sparse ocean senso...
Soil organic carbon (SOC) is a critical indicator of soil health, directly influencing crop productivity, soil structure, and environmental sustainability. Existing SOC estimation techniques using satellite reflectance data are effective for large-sc...
Concerning power systems, real-time monitoring of cyber–physical security, false data injection attacks on wide-area measurements are of major concern. However, the database of the network parameters is just as crucial to the state estimation process...
A two-channel, time–wavelength interleaved photonic analog-to-digital converter (PADC) system with a sampling rate of 10.4 GSa/s was established, and a concise method for measuring and data correcting the channel sampling timing walk-off of PAD...
Track quality instruments use low-cost accelerometers placed on or attached to the floors of operating trains, and these instruments collect substantial amounts of data over short inspection periods. The measurements collected by the instruments are...
Deformation of a phased array antenna surface can degrade its electrical performance. Conventional modal reconstruction depends on the accuracy of the structural model, while purely data-driven methods require extensive experimental data. We propose...
Optical focal plane assemblies are increasingly being used in high-resolution optical satellite systems to enhance the width of the image using linear push-broom imaging. With this system, vignetting occurs in the area of overlap, affecting image qua...
Gridded precipitation datasets are increasingly used as operational tools, with growing emphasis on cloud-native processing to handle multi-decadal archives through reproducible and auditable workflows. This paper presents an end-to-end pipeline that...
In order to improve the accuracy and reliability of an existing rutting performance prediction model, based on the long-term observation data of the RIOHTrack’s full-scale pavement structure, the rutting performance prediction model in China&rs...
Meteorological satellite remote sensing is important for numerical weather forecasts, but its accuracy is affected by many things during observation and retrieval, showing that it can be improved. As a standard way to measure wind from space, atmosph...
More and more spaceborne infrared hyperspectral atmospheric observations are assimilated into data assimilation systems. The key to bias correction (BC) of these instruments depends on selecting predictors. However, it is difficult to find a set of p...
High-spatiotemporal-resolution land surface temperature (LST) data are crucial for analyzing surface energy balance, modeling temperature-related processes, and monitoring thermal environments. However, despite advancements in multi-source fusion and...
Alzheimer’s disease (AD) is the most common form of dementia. An increasing number of studies have confirmed epigenetic changes in AD. Consequently, a robust phenotyping mechanism must take into consideration the environmental effects on the pa...
Accurate velocity estimation in GPS-denied environments remains a core challenge for autonomous unmanned aerial vehicle (UAV) navigation. Our previous work demonstrated that fusing optical flow (OF) with dead reckoning (DR) substantially reduces posi...
In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image fro...
Traditional methods of counting bicyclists are resource-intensive and generate data with sparse spatial and temporal detail. Previous research suggests big data from crowdsourced fitness apps offer a new source of bicycling data with high spatial and...
High-quality geomagnetic measurements are widely used in both fundamental research of the magnetic field and numerous industrial applications. However, vector data measured by fluxgate sensors show a dependency on temperature due to sensitive coil co...
We provide corrections to the data in Sholin’s tables from his paper in Optics and Spectroscopy 26 (1969) 27. Since his data was used numerous times by various authors to calculate the asymmetry of hydrogenic spectral lines in plasmas, our correction...
This paper studies quantile regression for spatial panel data models with varying coefficients, taking the time and location effects of the impacts of the covariates into account, i.e., the implications of covariates may change over time and location...
of 335