Automation in the service industry is emerging as a new wave of industrial revolution. Standardization and consistency of service quality is an important part of the automation process. The quality control methods widely used in the manufacturing ind...
The paper discusses an extension of the variance-gamma process with stochastic linear drift coefficient. It is assumed that the linear drift coefficient may switch to a different value at the exponentially distributed time. The size of the drift jump...
The paper builds a Variance-Gamma (VG) model with five parameters: location (
Within statistical process control (SPC), normality is often assumed as the underlying probabilistic generator where the process variance is assumed equal for all rational subgroups. The parameters of the underlying process are usually assumed to be...
Recently, maintaining a complex mechanical system at the appropriate times is considered a significant task for reliability engineers and researchers. Moreover, the development of advanced mechanical systems and the dynamics of the operating environm...
The stochastic differential equation (SDE) has been used to model various phenomena and investigate their properties. Conditional moments of stochastic processes can be used to price financial derivatives whose payoffs depend on conditional moments o...
With the rapid development of advanced sensor technologies, it has become popular to monitor multiple quality variables for a manufacturing process. Consequently, multivariate statistical process control (MSPC) charts have been commonly used for moni...
In this paper, the parameter optimization of the hybrid-tandem gas metal arc welding (GMAW) process was studied. The hybrid-tandem GMAW process uses an additional filler-wire with opposite polarity in contrast to the conventional tandem process. In t...
Simulations of landslide generated waves (LGWs) are prone to high levels of uncertainty. Here we present a probabilistic sensitivity analysis of an LGW model. The LGW model was realised through a smooth particle hydrodynamics (SPH) simulator, which i...
Determining process variances in biopharmaceutical manufacturing is challenging due to limited data availability. To address this, we introduce a Bayesian hierarchical model designed for meta-analysis of process variance. This approach can improve pr...
In this paper, under some suitable assumptions, using the Taylor expansion, Borel–Cantelli lemma and the almost sure central limit theorem for independent random variables, the almost sure central limit theorem for error variance estimator in t...
With increasing demands for SAR image applications, spaceborne SAR systems are evolving towards higher resolution and wider swath capabilities. However, these advancements lead to more pronounced range-dependent variance effects. Previous research ha...
The aim of the present paper is that of conducting a study on the basis of which the optimal parameters for the manufacturing of polymer parts by means of the single point incremental forming process can be chosen in such a way that the process force...
Wastewater treatment plants (WWTPs) are high-energy-consuming units. Reasonable operation strategies can enable WWTPs to meet discharge standards while reducing the operating cost. In this study, the activated sludge model 2d (ASM2d), Pareto analysis...
In the information-based pricing framework of Brody, Hughston & Macrina, the market filtration
Shewhart charts are the most commonly utilised control charts for process monitoring in industries with the assumption that the underlying distribution of the quality characteristic is normal. However, this assumption may not always hold true in prac...
This work demonstrates for the first time the application of network topology of variance decompositions in analyzing the connectedness of chemical plant process variable oscillations arising from disturbances and faults. Specifically, the time-based...
Stochastic models play a crucial role in global navigation satellite systems (GNSS) data processing. Many studies contribute to the stochastic modeling of GNSS observation noise, whereas few studies focus on the stochastic modeling of process noise....
We use the representation of a continuous time Hattendorff differential equation and Matlab to compute
In this paper, we propose a generalized multiperiod mean-variance portfolio optimization based on consideration of benchmark orientation and intertemporal restrictions, in which the investors not only focus on their own performance but also tend to c...
We present and prove a triple sum series formula for the European call option price in a market model where the underlying asset price is driven by a Variance Gamma process. In order to obtain this formula, we present some concepts and properties of...
Time-frequency analysis (TFA) technology is an important tool for analyzing non-Gaussian mechanical fault vibration signals. In the complex background of infinite variance process noise and Gaussian colored noise, it is difficult for traditional meth...
The Susceptible–Infected–Susceptible (SIS) model in complex networks is one of the critical models employed in the modeling of virus spread. The study of the heterogeneous SIS model with a non-homogeneous nodal infection rate in finite-si...
Wind-power generators around the world face two risks, one due to changes in wind intensity impacting energy production, and the second due to changes in electricity retail prices. To hedge these risks simultaneously, the quanto option is an ideal fi...
This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading u...
This paper overviews our recent results of energy market modeling, including The option pricing formula for a mean-reversion asset, variance and volatility swaps on energy markets, applications of weather derivatives on energy markets, pricing crude...
The identification of Aspergillus flavus (A. flavus), a fungus known for producing aflatoxins, poses a taxonomic challenge due to its morphological plasticity and similarity to closely related species. This article proposes a computational approach f...
We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other r...
To improve machining efficiency and product precision in scroll manufacturing, we studied three adaptive milling processes: adaptive feed rate planning, chatter suppression measures, and optimization of milling parameters during the rough, semi-fine,...
We discuss the dynamic mean-variance (MV) problem for pairs trading with the assumptions that one of the security prices satisfies a stochastic volatility model (SVM) and the corresponding price spread follows an Ornstein–Uhlenbeck (OU) process...
Micro drilled holes are utilized in many of today’s fabrication processes.Precision production processes in industries are trending toward the use of smaller holeswith higher aspect ratios, and higher speed operation for micro deep hole drilling. How...
The compositions and transfer processes affecting coastal sea sediments from the Seto Inland Sea and the Pacific Ocean are examined through the construction of comprehensive terrestrial and marine geochemical maps for western Japan. Two-way analysis...
This article proposes a Radial Basis Function Artificial Neural Network (RBF-ANN) to classify tempered steel cams as correctly or incorrectly treated pieces by using multi-frequency nondestructive eddy current testing. Impedances at five frequencies...
Complex composite structures manufactured using a low-pressure vacuum bag-only (VBO) method are more susceptible to defects than flat laminates because of the presence of complex compaction conditions at corners. This study investigates the contribut...
High-dimensional surrogate modeling with limited high-fidelity data poses a major challenge in uncertainty quantification. Classical supervised dimension reduction methods often fail in this setting due to insufficient accurate observations, while lo...
The FGH95 superalloy used for turbine disk manufacturing was strengthened by the oblique laser shock processing (OLSP). The laser energy, beam diameter, and number of impacts were selected as the test factors, and the three-factor three-level oblique...
The gas turbine engine is a widely used thermodynamic system for aircraft. The demand for quantifying the uncertainty of engine performance is increasing due to the expectation of reliable engine performance design. In this paper, a fast, accurate, a...
The global navigation satellite system (GNSS) has been applied to many areas, e.g., the autonomous ground vehicle, unmanned aerial vehicle (UAV), precision agriculture, smart city, and the GNSS-reflectometry (GNSS-R), being of considerable significan...
A new energy transition policy in Korea has increased the importance of liquefied natural gas (LNG) in the energy mix. The Asia-Pacific LNG market is inflexible because long-term contracts are dominant. This market characteristic means that the devel...
Variance, as a measurement of dispersion, is a basic component of decision-making processes. Recent advances in intelligent systems have included the concept of variance in information fusion techniques for decision-making under uncertainty. These di...
This research investigates the heat treatment parameters of 6061-aluminum alloy to enhance its mechanical properties. The Taguchi design-of-experiments (DOE) method was employed to systematically examine the effects of solutionizing temperature, solu...
Control charts are considered as powerful tools in detecting any shift in a process. Usually, the Shewhart control chart is used when data follows the symmetrical property of a normal distribution. In practice, the data from the industry may follow a...
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...
A new approach to the multi-criteria optimization of L-PBF process parameters in the face of high variability is proposed, based on the application of the reward function (RF), which is essentially the inverse of the Taguchi quality loss function (QL...
The reliability information for novel products and specimens available for various tests is limited during the development stage. In many real cases, the results of general tests under use and the maximum stress levels for checking performance and de...
The recently developed rough Bergomi (rBergomi) model is a rough fractional stochastic volatility (RFSV) model which can generate a more realistic term structure of at-the-money volatility skews compared with other RFSV models. However, its non-Marko...
The presence of calcium sulfate in the process water during the coal flotation greatly influences the recovery and selectivity of the separation. The concentrations of calcium and sulfate ions modify mineral hydrophobicity by altering surface propert...
This paper presents a comparative analysis of the laser operating power (P1 and P2) and synthetic leather thickness to achieve the optimal quality of components in the airbag area, produced through micro-perforation laser processing. Within the study...
Two multi-parameter distributions, namely the Pearson type IV and metalog distributions, are discussed and suggested as alternatives to the normal distribution for modelling path delay data that determines the maximum clock frequency (FMAX) of a micr...
Terahertz (THz) time of flight (TOF) tomography systems offer a new measurement modality for non-destructive evaluation (NDE) of the subsurface layers of protective coatings and/or laminated composite materials for industrial, security and biomedical...
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