Instead of a flag valid/non-valid usually proposed in the quality control (QC) processes of air quality (AQ), we proposed a method that predicts the p-value of each observation as a value between 0 and 1. We based our error predictions on three appro...
Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-s...
Power quality measurements in medium- and high-voltage networks are often performed indirectly using current transformers (CTs) and voltage transformers (VTs). Even when the power quality instrument itself complies with relevant standards, frequency-...
Geometric errors in CNC machine tools accumulate along the tool path and directly affect machining accuracy. Traditional serial-chain-based volumetric error models, such as those based on the homogeneous transformation matrix (HTM) or screw theory, o...
In low-speed flow (Ma < 0.3), pressure-sensitive paint (PSP) technology encounters a significant bottleneck in micro-pressure measurements due to the coupled interference of light source instability, camera noise, and paint photodegradation. This...
This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). By integrating error-driven task sequencing and real-time er...
To improve the user’s positioning accuracy of a Wi-Fi fingerprint-based positioning algorithm, this study proposes a graph optimization model based on the framework of
Accurate real-time positioning of Unmanned Aerial Vehicles (UAVs) is critical for navigation and mapping but remains challenging in complex environments due to signal blockages and multipath effects. This study presents a comparative framework for re...
Hourly satellite precipitation products are often evaluated using aggregate statistics that can conceal compensating errors in precipitation occurrence and event duration, accumulation, and intensity. Using all matched observations from 522 meteorolo...
Identifying flexible loads, such as a heat pump, has an essential role in a home energy management system. In this study, an adaptive ensemble filtering framework integrated with long short-term memory (LSTM) is proposed for identifying flexible load...
Complex terrain conditions and dense vegetation cover in a vegetation area present significant challenges for point cloud data processing and the accurate extraction of ground points. This work integrates the physical characteristics between ground a...
Large-scale hydro–wind–solar systems require scenario sets that represent cross-resource dependence without losing station-level and intra-day characteristics. A remaining challenge is to connect cluster-level joint modeling with station...
In this paper, we propose a weighted link-specific (WLS) approach that establishes a unified statistical inference framework for high-dimensional Poisson and Gamma regression. We regress the parameter deviations as well as the initial estimation erro...
Space-borne antenna pointing is affected by uncertain disturbances like satellite attitude, structural flexibility, and manufacturing/installation errors. Understanding the effect of these uncertainties is crucial for antenna performance. The main co...
Water quality monitoring is crucial for ecological protection and water resource management. However, traditional monitoring methods suffer from limitations in temporal, spatial, and spectral resolution, which constrain the effective evaluation of ur...
Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but...
Territorial heritage documentation programmes require coordinated acquisition, processing and information management across assets with different documentation demands. This study presents the Equivalent Documentation Unit (UDE, retaining the project...
In this study, a novel control framework is proposed to improve the tracking performance of uncertain marine vessels which work in enhanced sea states. The proposed control strategy is based on incorporating a fixed-time nonlinear disturbance observe...
Understanding the demographic structure is vital for wildlife research and conservation. For crocodylians, accurately estimating total length and demographic class usually necessitates close observation or capture, often of partially immersed individ...
Accumulating evidence suggests that migrating animals store navigational “maps” in their brains, decoding location information from geomagnetic information based on their perception of the magnetic field. Inspired by this phenomenon, a no...
Permanent magnet synchronous motor (PMSM)-based servo actuators are fundamental to high-performance electromechanical systems. However, in energy-sensitive aerospace applications, the impact of tracking error on system-level efficiency remains insuff...
In recent years, the integration of renewable energy sources and the widespread use of nonlinear loads have increased dynamic uncertainties in modern power systems, making real-time and synchronized monitoring essential. Accurate M-class synchrophaso...
The liquid-only transfer dividing wall column (LDWC) eliminates the difficulty of controlling the vapor-phase distribution ratio; however, it involves numerous structural and operating parameters, resulting in high initialization difficulty and conve...
To address the challenge of low computational efficiency in nonlinear Economic Model Predictive Control (EMPC) for large-scale systems such as wastewater treatment plants (WWTPs), this paper proposes a Trajectory Piecewise Linearization (TPWL)-based...
This research presents an integrated framework for supply chain finance in which digital twin, blockchain, and multi-objective fuzzy optimization are used in synergy to improve financial decision-making in dynamic and uncertain environments. In this...
This paper presents a comprehensive framework for the identification, state estimation, and robust control of a bistable Duffing–Holmes oscillator, validated through an experimental setup. First, to address parametric uncertainty, a Recursive L...
The general framework of the bottom-up approach for modeling mobile emissions and energy use involves the following major components: (1) quantifying traffic flow and (2) calculating emission and energy consumption factors. In most cases, researchers...
This paper presents an analytical and numerical benchmark verification framework for explicit time integration procedures applied to the one-dimensional wave equation. The study combines an exact analytical solution, a closed-form discrete central-di...
In high-speed machining, linear toolpaths constructed from a series of short line segments are widely used but inevitably introduce tangent and curvature discontinuities at segment junctions, which may cause feedrate fluctuation and contouring error....
Downward shortwave radiation (DSR) to the Earth’s surface is an essential renewable energy component. Accurate knowledge of solar radiation, i.e., solar energy resource assessment, is a prior requirement for the development of the solar energy...
The Internet of Vehicles (IoV), a burgeoning technology, merges advancements in the internet, vehicle electronics, and wireless communications to foster intelligent vehicle interactions, thereby enhancing the efficiency and safety of transportation s...
Contemporary business process modeling lacks a systematic framework for converting unstructured requirements into structured models. Traditional manual approaches fail to support integrated lifecycle management from requirements elicitation to iterat...
This paper presents a mathematics-focused AI iterative prediction framework that combines Extreme Gradient Boosting (XGBoost) for nonlinear function approximation with nonlinear autoregressive model with exogenous inputs (NARXs) for time-series model...
Predicting algal proliferation in freshwater systems is crucial for effective water quality management and ecological sustainability. This study proposes a novel data-driven framework that integrates correlation-based feature ranking with a concatena...
A meticulous image processing workflow is oftentimes required to derive quality image data from high-resolution, unmanned aerial systems. There are many subjective decisions to be made during image processing, but the effects of those decisions on pr...
This study investigates the predictive modeling of total Polycyclic Aromatic Hydrocarbon (PAH) concentrations in smoked fish products based on various smoking parameters using machine learning techniques in the Waikato Environment for Knowledge Analy...
Physical access to robotic manipulators remains constrained by cost, safety requirements, and limited laboratory availability, creating barriers to both research and education. This paper presents a computational framework that combines stochastic er...
Reliable counting of horticultural seeds is important for seed grading, batch consistency assessment, packaging, sowing-rate control, and post-harvest quality evaluation. Manual counting is labor-intensive, whereas conventional image-processing metho...
The accuracy of the rain distribution could be enhanced by assimilating the remotely sensed and gauge-based precipitation data. In this study, a new nonparametric general regression (NGR) framework was proposed to assimilate satellite- and gauge-base...
We present a methodology for analyzing data that contain both statistical and systematic uncertainties when the correlations among systematic errors are unknown. The approach employs Monte Carlo sampling over the full range of admissible correlation...
Water quality monitoring plays a vital role in the water environment management, while efficient monitoring provides direction and verification of the effectiveness of water management. Traditional water quality monitoring for a variety of water para...
The success of kinematic analysis that relies on inertial measurement units (IMUs) heavily depends on the performance of the underlying algorithms. Quantifying the level of uncertainty associated with the models and approximations implemented within...
This paper addresses the tracking control problem of robotic manipulators under a universal symmetry constraint framework in the presence of lumped uncertainties and external disturbances. Unlike conventional constrained control schemes that treat tr...
Matching of multi-run magnetic flux leakage (MFL) in-line inspection data for oil and gas pipelines provides an essential basis for defect evolution analysis, corrosion growth assessment, and integrity management. However, in practical engineering ap...
Three-dimensional human pose estimation from monocular video remains challenging for clinical gait analysis due to high computational cost and the need for temporal consistency. We present Pose3DM, a bidirectional Mamba-based state-space framework th...
In surface energy tests of asphalt materials, the inaccuracy of the calculation method (e.g., least squares (LS)) and the arbitrary selection of chemical reagent combinations lead to unstable results, threatening the quantitative evaluation of asphal...
Laser beam welding (LBW) involves complex and rapid interactions between the laser and material, often resulting in defects such as pore formation. Emissions collected during the process offer valuable insight but are difficult to interpret directly...
Systematic inconsistencies between evaluated nuclear data libraries and experimental measurements may reflect structured, non-stochastic deviations rather than random error. This study develops a residual-learning framework for the neutron total cros...
Accurate plant counting supports stand assessment and crop management, but canopy overlap, camera motion, and temporary occlusion complicate video-based monitoring. This study developed an RGB image- and video-based framework for detecting, tracking,...
The environmental issues we are currently facing require long-term prospective efforts for sustainable growth. Renewable energy sources seem to be one of the most practical and efficient alternatives in this regard. Understanding a nation’s pat...
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