RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observation...
This paper pioneers a novel approach in electromagnetic (EM) system analysis by synergistically combining Bayesian Neural Networks (BNNs) informed by Latin Hypercube Sampling (LHS) with advanced thermal–mechanical surrogate modeling within COMS...
Most accidents and serious incidents of commercial air transport helicopters occur during standard flight phases, whereby a main cause is pilots’ situational awareness. Enabling pilots to better assess their situational awareness can make an im...
Installing offshore wind jackets faces increasing risks from dynamic marine conditions and is challenged by trajectory deviations due to coupled hydrodynamic and environmental factors. To address the limitations of software, such as long simulation t...
This paper introduces a novel and flexible class of continuous probability distributions, termed the Alpha Power Survival Ratio-X (APSR-X) family. Unlike many existing transformation-based families, the APSR-X class integrates an alpha power transfor...
Modern impact monitoring systems combine multiple inputs with machine learning (ML) models for impact detection, localization, and event assessment. Their accuracy relies on large, event-representative datasets, used for algorithmic development and M...
This paper investigates the feasibility of using the three-dimensional omnidirectional inductive channel for power transfer and as a power line communication (PLC) for ground-based vehicle, electric air vehicle, or space applications. The simulation...
In recent years, the energy market has seen an increase in small and medium enterprises (SMEs) participating in the sector and providing relevant services to customers. The energy sector SMEs need to acknowledge whether reengineering their marketing...
A product’s lifespan may be ascertained by analyzing the dependability and aging class of its life distribution. Sustainability metrics are also crucial for assessing the impact on the environment and creating resource-saving strategies. Resear...
Frequent flood disasters have caused serious damage to karst areas with insufficient measured rainfall data, and the analysis of the applicability of satellite rainfall data in runoff simulation is helpful to the local water management. Therefore, th...
The Federal Reserve has played an arguably important role in financial crises in the United States since its creation in 1913 through monetary policy tools. Thus, this paper aims to analyze the impact of monetary policy on the United States’ ec...
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...
Hydro-meteorological datasets are key components for understanding physical hydrological processes, but the scarcity of observational data hinders their potential application in poorly gauged regions. Satellite-retrieved and atmospheric reanalysis pr...
Low-enthalpy geothermal installations for heating, air conditioning, and domestic hot water are gaining traction due to efforts towards energy decarbonization. This article is part of a broader research project aimed at employing artificial intellige...
Supervised machine learning algorithms usually require huge labeled data sets to produce sufficiently good results. For many applications, these data sets are still not available today, and the reasons for this can be manifold. As a solution, the mis...
A problem with applying machine learning for analyzing power system dynamics is the lack of specific datasets. In this realm, defining a strong methodology to obtain power system dynamic data is an important task prior to the application of any machi...
During a construction project life cycle, project costs and time estimations contribute greatly to baseline scheduling. Besides, schedule risk analysis and project control are also influenced by the above factors. Although many papers have offered es...
Understanding the soil and hydrologic processes in agricultural watersheds are vital for reliable assessments of water quantity and quality to support integrated river basin management. However, deriving hydrology-relevant information is complicated...
Research on SARS-CoV-2 and its social implications have become a major focus to interdisciplinary teams worldwide. As interest in more direct solutions, such as mass testing and vaccination grows, several studies appear to be dedicated to the operati...
In this paper, we propose a useful method without adding any extra parameters to obtain new probability distributions. The proposed family is a combination of the two existing families of distributions and is called a weighted sine-G family. A two-pa...
The disadvantage of radar measurements is that the obtained rainfall data is imprecise. Therefore, the use of radar data in hydrological applications usually requires correction. The main aim of the study was to verify and optimize various methods of...
The simulator for hydrological unstructured domains (SHUD) is a cutting-edge, distributed hydrological model based on the finite volume method, representing the next generation of coupled surface–subsurface hydrological simulations. Its applica...
In recent years, there was an increasing number of studies focusing on rockfalls due to their impacts on social and sustainable development. This work carries out a three-dimensional (3D) simulation of rockfalls at a cultural heritage site nearby the...
Dichotomous data correspond with various types of commonly encountered data, e.g., positive/negative, case/control, missing/observed, in many fields, including medicine, health, and social sciences. Despite their ubiquity, criteria for determining di...
This research presents a hybrid approach to generate sample data for future machine learning applications for the prediction of mechanical properties in directed energy deposition-arc (DED-Arc) using the GMAW process. DED-Arc is an additive manufactu...
In this study, we compare two novel hybrid data assimilation (DA) methods: Localized Weighted Ensemble Kalman filter (LWEnKF) and Implicit Equal-Weights Variational Particle Smoother (IEWVPS). These methods integrate a particle filter (PF) with tradi...
13 November 2019
Hierarchical Bayesian log-linear models for Poisson-distributed response data, especially Besag, York and Mollié (BYM) model, are widely used for disease mapping. In some cases, due to the high proportion of zero, Bayesian zero-inflated Poisso...
Competing risks are frequently overlooked, and the event of interest is analyzed with conventional statistical techniques. In this article, we consider the analysis of bi-causes of failure in the context of competing risk models using the extension o...
To mitigate the power shortage problem in the South Pacific island nations and the equatorial area, we studied the development characteristics of ocean thermal energy conversion (OTEC) using abundant clean ocean energy. Through the simulation of open...
In this paper, we introduce a new three-parameter inverse Rayleigh distribution that extends the inverse Rayleigh distribution, constructed based on the generalized transmuted family of distributions proposed by Alizadeh, Merovci, and Hamedani. We ex...
In this work, an open-source computational–statistical platform to obtain synthetic homogeneous isotropic turbulent flow and passive scalar transport is presented. A parallel implementation of the well-known pseudo-spectral method in addition t...
Microwave-driven plasma gasification technology has the potential to produce clean energy from municipal and industrial solid wastes. It can generate temperatures above 2000 K (as high as 30,000 K) in a reactor, leading to complete combustion and red...
In this article, a progressive-stress accelerated life test (ALT) that is based on progressive type-II censoring is studied. The cumulative exposure model is used when the lifetime of test units follows Pareto-IV distribution. Different estimates as...
In this research, we present a new approach to define the distribution of block volumes during rockfall simulations. Unmanned aerial vehicles (UAVs) are utilized to generate high-accuracy 3D models of the inaccessible SW flank of the Mount Rava (Ital...
The worldwide commitment to the electrification of road transport will require a broad overhaul of equipment and infrastructure. Heavy-duty trucks account for over one-third of on-road energy use. Electrified roadways (e-Hwys) are an emerging technol...
This article assesses the predictive accuracy of factor models utilizing Partial·Least·Squares (PLS) and Principal·Component·Analysis (PCA) in comparison to autometrics and penalization techniques. The simulation exercise...
This study aims to propose a flexible, fully parametric hazard-based regression model for censored time-to-event data with crossing survival curves. We call it the accelerated hazard (AH) model. The AH model can be written with or without a baseline...
Most current land surface models (LSMs) coupled to regional climate models (RCMs) have been implemented at the several tens of kilometer spatial scales. Modeling land surface processes in LSMs at a finer resolution is necessary for improvements in te...
Access to safe and reliable water is a fundamental requirement for sustainable urban development. However, water distribution systems (WDSs), particularly in small and aging municipalities, face persistent challenges, including infrastructure degrada...
The possibilities of applying the pure Lagrangian vortex methods of computational fluid dynamics to viscous incompressible flow simulations are considered in relation to various problem formulations. The modification of vortex methods—the Visco...
Predictive regression models often face a common challenge known as multicollinearity. This phenomenon can distort the results, causing models to overfit and produce unreliable coefficient estimates. Ridge regression is a widely used approach that in...
Many engineering systems can be described by using differential models whose solutions, generally obtained after discretization, can exhibit a noticeable deviation with respect to the response of the physical systems that those models are expected to...
In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with the parallel factor analysis model. Traditional methods, such as scaling, orthogonality constraints, non-negativity constraints, and sparse techniques...
In this paper, we propose a multi-group SIR to simulate the spread of COVID-19 in an island context. The multi-group aspect enables us to modelize transmissions of the virus between non-vaccinated individuals within an age group as well as between di...
The family of logistic type distributions has been widely studied and applied in the literature. However, certain estimation problems exist in some members of this family. Particularly, the three-parameter type I generalized logistic distribution pre...
9 September 2019
Accurate spatiotemporal air quality data are critical for use in assessment of regulatory effectiveness and for exposure assessment in health studies. A number of data fusion methods have been developed to combine observational data and chemical tran...
Numerical weather prediction (NWP) has become an important method of predicting extreme weather events, but orography is one of the key factors affecting the performance of NWPs. In this paper, based on Advanced Spaceborne Thermal Emission and Reflec...
Training of neural networks requires large amounts of data. Simulated data sets can be helpful if the data required for the training is not available. However, the applicability of simulated data sets for training neuronal networks depends on the qua...
Data simulation is widely used in remote sensing to produce imagery for a new sensor in the design stage, for scale issues of some special applications, or for testing of novel algorithms. Hyperspectral data could provide more abundant information th...
Originating from the Luria–Delbrück experiment in 1943, fluctuation analysis (FA) has been well developed to demonstrate random mutagenesis in microbial cell populations and infer mutation rates. Despite the remarkable progress in its theo...
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