This work focused on reflecting the substituting ratio of fine aggregate in an aggregate simulation. The existing simulation studies showed superior performance on generating the particles; however, the studies did not and could not reflect the subst...
The aim of this study was to explore the feasibility of quantitatively evaluating a sapphire’s color by analyzing gemstone images. The color characteristics of gemstones through photography and color extraction were accurately captured, and the...
Extended statistical entropy analysis (eSEA) is used to assess the nitrogen (N) removal performance of the wastewater treatment (WWT) simulation software, the Benchmarking Simulation Model No. 2 (BSM No. 2 ). Six simulations with three different type...
In modern processor development, extensive simulation is required before manufacturing to ensure that Central Processing Unit (CPU) designs function correctly and efficiently. This pre-silicon validation process involves running a wide range of softw...
A statistical damage model (SDM) of fully-graded concrete was created using statistical damage theory, based on the mechanical properties of axial tension and axial compression of the material. The SDM considers two damage modes, fracture and yield,...
This study characterises materials that belong to the group of refuse-derived fuels (RDF). This group of materials regarded as an alternative fuel is derived from industrial, municipal solid and commercial wastes. The aim of this study is to evaluate...
This paper shows simulations of high waves over different bathymetries to collect statistical information, particularly kurtosis and crest exceedance, that quantifies the occurrence of exceptionally extreme waves. This knowledge is especially pertine...
The application of multiple-point statistics (MPS) in the mining industry is not yet widespread and there are very few applications so far. In this paper, we focus on the problem of algorithmic input parameter selection, which is required to perform...
To proactively respond to changes in droughts, technologies are needed to properly diagnose and predict the magnitude of droughts. Drought monitoring using satellite data is essential when local hydrogeological information is not available. The chara...
In this Editorial, we are pleased to introduce the Special Issue of the journal Axioms entitled “Advances in Statistical Simulation and Computing” [...]
Building deformation, for example, tilting, settlement, and uplift, threatens structural safety, yet its rapid assessment is challenged by scarce real samples, subtle features, background clutter, and a lack of automated grading criteria. This study...
Animal experiments have long been used as an educational tool in pharmacological education; however, from the perspective of animal welfare, it is necessary to decrease the number of animals used. ingAlthough using of simulators is effective, the dev...
Purpose: As animal welfare becomes increasingly important, there is a corresponding desire to reduce the number of animals used in experiments. Recently, we reported on statistical models for a local anaesthetic simulator and developed a simulator fo...
The modelling and simulation process in the automotive domain is transforming. Increasing system complexity and variant diversity, especially in new electric powertrain systems, lead to complex, modular simulations that depend on virtual vehicle deve...
Statistical physics models of social systems with a large number of members, each interacting with a subset of others, have been used in very diverse domains such as culture dynamics, crowd behavior, information dissemination and social conflicts. We...
Statistical simulation is a necessary step in integrated circuit design since it provides a realistic picture of the circuit’s behavior in the presence of manufacturing process variations. When some of the circuit components lack an accurate an...
This study analyzed the sensitivity of rainfall patterns in South China and the Indochina Peninsula (ICP) using statistical simulations of observational data. Quantitative changes in rainfall patterns over the ICP were examined for both wet and dry s...
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Background: To elucidate the effects of local anesthetic agents (LAs), guinea pigs are used in pharmacological education. Herein, we aimed to develop a simulator for LAs. Previously, we developed a statistical model to simulate the LAs’ effects...
Estimation of the population distribution function is an important problem in survey sampling with a variety of applications in social sciences, medical studies, environmental research and economics and in industrial quality control. When auxiliary i...
The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling protein interactions, which involve disordered pep...
Simulating wind turbine blade icing quickly is important for wind farms to issue early warnings and effectively deal with the adverse effects of cold weather. However, current numerical simulation methods suffer from high computational costs and lack...
Turbulence statistics and spectra in a radiatively heated convective boundary layer (CBL) under aerosol pollution conditions are less investigated than their counterparts in the clear CBL. In this study, a large-eddy simulation (LES) coupled with an...
It is a critical issue to allocate redundancy to critical smart grid infrastructure for disaster recovery planning. In this study, a framework to combine statistical prediction methods and optimization models for the optimal redundancy allocation pro...
In this paper, we study a new family of Gompertz processes, defined by the power of the homogeneous Gompertz diffusion process, which we term the powers of the stochastic Gompertz diffusion process. First, we show that this homogenous Gompertz diffus...
Molecular dynamics simulation is commonly employed to explore protein dynamics. Despite the disparate timescales between functional mechanisms and molecular dynamics (MD) trajectories, functional differences are often inferred from differences in con...
Resistive random access memory (RRAM) has two distinct processes, the SET and RESET processes, that control the formation and dissolution of conductive filament, respectively. The laws of thermodynamics state that these processes correspond to the lo...
In large eddy simulation (LES) of turbulent flows, dynamic subgrid models would account for an average cascade of kinetic energy from the largest to the smallest scales of the flow. Yet, it is unclear which of the most critical dynamical processes ca...
This study presents a comprehensive analysis of zoonotic disease transmission dynamics between baboon and human populations using both deterministic and stochastic modeling approaches. The model is constructed with a symmetric compartmental structure...
The reservoir operation is a notable source of uncertainty in the natural streamflow and it should be represented in hydrological modelling to quantify the reservoir impact for more effective hydrological forecasting. While many researches focused on...
A statistical downscaling method based on Self-Organizing Maps (SOM), of which the SOM Precipitation Statistical Downscaling Method (SOM-SD) is named, has received increasing attention. Herein, its applicability of downscaling daily precipitation ove...
This study investigates the influence of façade-design parameters on daylighting performance in hot arid climates, with a particular focus on Egypt. A total of nine façade configurations of a residential building were modeled and simula...
The full pinion engagement planetary gear trains are comparatively little known especially when it comes to the load sharing between the planets. In this paper, an attempt has been made to compensate for the lack of statistical data by extending the...
Anaerobic digestion (AD) is a promising way to produce renewable energy. The solid-state anaerobic digestion (SSAD) with a dry matter content more than 15% in the reactors is seeing its increasing potential in biogas plant deployment. The relevant pr...
The spread of infectious diseases is a complex system in which pathogens, humans, the environment, and sometimes vectors interact. Mathematical and simulation modelling is a suitable approach to investigate the dynamics of such complex systems. The 2...
Accurate modeling of photovoltaic (PV) cell behavior under varying operational conditions is essential for optimizing energy yield and system reliability. This study presents an extended simulation-based methodology for analyzing monocrystalline sili...
GROMACS MD simulations of food proteins and processes are often run over relatively short simulation lengths due to their high computational power demand. As long-timescale simulations are not always feasible, the purpose of this study was to determi...
Pandemic curves, such as COVID-19, often show multiple and unpredictable contamination peaks, often called second, third and fourth waves, which are separated by wide plateaus. Here, by considering the statistical inhomogeneity of age groups, we show...
Roadway accidents significantly contribute to intermittent congestion and increased CO2 emissions on freeways. This research introduces a statistical approach designed to predict the rise in CO2 emissions resulting from traffic disturbances or jams t...
We have developed a method for estimating protein-ligand binding free energy (DG) based on the direct protein-ligand interaction obtained by a molecular dynamics simulation. Using this method, we estimated the DG value statistically by the average va...
This paper applies established saddlepoint approximation techniques to nonlinear statistics arising from inverse Gaussian models. In particular, we consider the product of independent inverse Gaussian random variables and the ratio of weighted linear...
α-Amylase inhibitory peptides are used to treat diabetes, but few studies have statistically characterized their interaction with α-amylase. This study performed the molecular docking of α-amylase with inhibitory peptides from publi...
Statistical tolerance analysis based on Monte Carlo simulation can be applied to obtain a cost-optimized tolerance specification that satisfies both the cost and quality requirements associated with manufacturing. However, this process requires time-...
In this study, we aimed to assess the capacity of a physics-based earthquake simulator to improve our understanding of the seismogenic process. In this respect, we applied a previously tested earthquake simulator to two well-known and completely diff...
Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API–carrier mixture and the prin...
Wind tunnel tests and numerical simulations are the mainstream methods to study the wind-induced vibration of structures. However, few articles use statistical parameters to point out the differences and errors of these two research methods in explor...
Researchers have always been concerned about collision risks between ships and structures on busy waterways, as the consequences can be catastrophic. The models for determining the probabilities of these accidents, however, vary widely, with discrepa...
This paper introduces and studies a new discrete distribution with one parameter that expands the Poisson model, discrete weighted Poisson Lerch transcendental (DWPLT) distribution. Its mathematical and statistical structure showed that some of the b...
Due to the complexity of the data being generated day in and day out in many practical domains, as a result of the development of scales for rating the success or failure of reliability, a new domain of reliability called the classes of life and dete...
Modeling bounded data presents a fundamental challenge in reliability and risk analysis, particularly when the underlying observations exhibit heterogeneous distributional shapes and complex failure-rate patterns. To address this challenge, we introd...
COVID-19 has become the largest pandemic in recent history to sweep the world. This study is devoted to developing and investigating three models of the COVID-19 epidemic process based on statistical machine learning and the evaluation of the results...
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