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Mathematical models, usually implemented in computer programs known as computer models, are widely used in all areas of science and technology to represent complex systems in the real world. However, computer models are ...

This paper presents an innovative methodology for modeling and predicting high-frequency harmonic losses in the rotating field of an electrical machine powered by a frequency converter. Conventional approaches are often ...

Kriging models are used in many scientific disciplines to investigate the behavior of physical systems. In the Kriging model (KM), the response of the computer simulation code (CSC) is considered to have a Gaussian proce...

Gaussian process regression models are used as statistical representations of computational models, due to their flexibility in capturing the shape of smooth functions. The Gaussian process regression model has a number ...

Stimulated parametric down-conversion is a nonlinear optical process that can be used for phase conjugation and frequency conversion of an optical field. A precise description of the outgoing stimulated field has been de...

Accurate geomagnetic field mapping plays a critical role in the navigation and localization of autonomous underwater vehicles (AUVs), especially in environments where traditional satellite navigation is unavailable. This...

The article is devoted to modelling the growth of thin films on the surfaces of crystals having a similar crystal structure with a small parameter of mismatch of the lattice of substances from which the film and the crys...

Abstract The peak identification scheme based method (three-point definition) and the spectral moments based method (spectral moment approach) are both widely used for asperity peak modeling in tribology. To discover the...

Abstract The stability of surrounding rock is a critical challenge in underground engineering. Accurate prediction of Excavation Damaged Zone Thickness (EDZT) in surrounding rock is vital for designing safe underground s...

Barndorff‑Nielsen and Shephard (2001) proposed a class of stochastic volatility models in which the volatility process is the Ornstein‑Uhlenbeck process driven by a Levy process without gaussian component. Parameter ...

Conventional meta-atom designs rely heavily on researchers’ prior knowledge and trial-and-error searches using full-wave simulations, resulting in time-consuming and inefficient processes. Inverse design methods based ...

In the power plants operation, the combustion process will produce particulate emissions. Particulate emissions themselves are known have a negative impact on health, such as causing respiratory problems. The pattern of ...

Abstract The accurate prediction of the deterioration of Continuously Reinforced Concrete Pavement (CRCP) is essential for the effective management of pavements and the maintenance of infrastructure. In this study, a co...

Precipitation generators are statistical models used to produce synthetic sequences of (multisite) precipitation for hydrological applications such as flood risk assessment and water resource management. Among these, app...

The configuration of the Northern Hemisphere ice sheets during the Last and Penultimate Glacial Maxima (LGM; PGM) influenced millennial-scale climate changes, as well as solid Earth and sea level changes that occurred du...

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...

This paper considers the problem of supply-demand imbalances in Mobility-on-Demand (MoD) services. These imbalances occur due to uneven stochastic travel demand and can be mitigated by proactively rebalancing empty vehic...

"This paper presents a statistical signal processing method for the characterization of EEG of patients suffering from epilepsy. A statistical model is proposed for the signals and the Kullback-Leibler divergence is used...

The data-driven Intelligent Transportation System (ITS) provides great support to travel decisions and system management but inevitably encounters the issue of data missing in monitoring systems. Hence, network-wide traf...

Abstract The remaining useful life (RUL) estimation of bearings is critical for ensuring the reliability of mechanical systems. Owing to the rapid development of deep learning methods, a multitude of data-driven RUL esti...

Abstract Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region. This paper proposes a novel cell to pack health and lifetime prognostics method based on the comb...

Abstract Accurate estimation of the shear capacity of steel fiber reinforced concrete (SFRC) beams without stirrups remains challenging because the response is governed by strongly coupled geometric, material, and reinfo...

Waste material, including glass, presents significant environmental challenges due to its non-biodegradable nature and low global recycling rates. Incorporating waste glass into concrete offers a sustainable solution, bu...