Search Results (58)

We propose a novel Bayesian wavelet regression approach using a three-component spike-and-slab prior for wavelet coefficients, combining a point mass at zero, a moment (MOM) prior, and an inverse moment (IMOM) prior. This flexible prior supports small and large coefficients differently, offering advantages for highly dispersed data where wavelet coefficients span multiple scales. The IMOM prior’s heavy tails capture large coefficients, while the MOM prior is better suited for smaller non-zero coefficients. Further, our method introduces innovative hyperparameter specifications for mixture probabilities and scale parameters, including generalized logit, hyperbolic secant, and generalized normal decay for probabilities, and double exponential decay for scaling. Hyperparameters are estimated via an empirical Bayes approach, enabling posterior inference tailored to the data. Extensive simulations demonstrate significant performance gains over two-component wavelet methods. Applications to electroencephalography and noisy audio data illustrate the method’s utility in capturing complex signal characteristics. We implement our method in an R package, NLPwavelet (≥1.1). Full article

Reliable estimation of extreme waves is essential for offshore wind turbine system design; however, site-specific conditions limit the application of one-size-fits-all statistical methods. We analyzed extreme wave conditions at potential offshore wind farm sites in South Korea using high-resolution hindcast data (1979–2022) based on the Weather Research and Forecasting (WRF) model. While previous studies have typically relied on a limited combination of distribution types and parameter estimation methods, this study systematically applied various Weibull distribution models and parameter estimation techniques to the environmental contour (EC) method. The results show that the optimal statistical approach varied by site according to the tail characteristics of the wave height distribution. The inverse second-order reliability method (I-SORM) provided the highest accuracy in regions with rapidly decaying tails, achieving root mean square error (RMSE) values of 0.21 in Shinan (using the three-parameter Weibull distribution with maximum likelihood estimation, MLE) and 0.34 in Chujado (with the method of moments, MOM). In contrast, the inverse first-order reliability method (I-FORM) yielded superior performance in areas where the tail decays more gradually, such as Yokjido (RMSE = 0.47 with MLE using the exponentiated Weibull distribution) and Ulsan (RMSE = 0.29, with MLE using the exponentiated Weibull distribution). These findings underscore the importance of selecting site-specific combinations of statistical models and estimation techniques based on wave distribution characteristics, thereby improving the accuracy and reliability of extreme design wave predictions. The proposed framework can significantly contribute to the establishment of reliable design criteria for offshore wind turbine systems by reflecting region-specific marine environmental conditions. Full article

This manuscript investigates the applicability and behavior of the Generalized Extreme Value (GEV) distribution in flood frequency analysis, comparing it with the Pearson III and Wakeby distributions. Traditional approaches often rely on a limited set of statistical distributions and estimation techniques, which may not adequately capture the behavior of extreme events. The study focuses on four hydrometric stations in Romania, analyzing maximum discharges associated with rare and very rare events. The research employs seven parameter estimation methods: the method of ordinary moments (MOM), the maximum likelihood estimation (MLE), the L-moments, the LH-moments, the probability-weighted moments (PWMs), the least squares method (LSM), and the weighted least squares method (WLSM). Results indicate that the GEV distribution, particularly when using L-moments, consistently provides more reliable predictions for extreme events, reducing biases compared to MOM. Compared to the Wakeby distribution for an extreme event (T = 10,000 years), the GEV distribution produced smaller deviations than the Pearson III distribution, namely +7.7% (for the Danube River, Giurgiu station), +4.9% (for the Danube River, Drobeta station), and +35.3% (for the Ialomita River). In the case of the Siret River, the Pearson III distribution generated values closer to those obtained by the Wakeby distribution, being 36.7% lower than those produced by the GEV distribution. These results support the use of L-moments in national hydrological guidelines for critical infrastructure design and highlight the need for further investigation into non-stationary models and regionalization techniques. Full article

Continuous data associated with many real-world events often exhibit non-normal characteristics, which contribute to the difficulty of accurately modeling such data with statistical procedures that rely on normality assumptions. Traditional statistical procedures often fail to accurately model non-normal distributions that are often observed in real-world data. This paper introduces a novel modeling approach using mixed third-order polynomials, which significantly enhances accuracy and flexibility in statistical modeling. The main objective of this study is divided into three parts: The first part is to introduce two new non-normal probability distributions by mixing standard normal and logistic variables using a piecewise function of third-order polynomials. The second part is to demonstrate a methodology that can characterize these two distributions through the method of L-moments (MoLMs) and method of moments (MoMs). The third part is to compare the MoLMs- and MoMs-based characterizations of these two distributions in the context of parameter estimation and modeling non-normal real-world data. The simulation results indicate that the MoLMs-based estimates of L-skewness and L-kurtosis are superior to their MoMs-based counterparts of skewness and kurtosis, especially for distributions with large departures from normality. The modeling (or data fitting) results also indicate that the MoLMs-based fits of these distributions to real-world data are superior to their corresponding MoMs-based counterparts. Full article

Nanocomposites composed of Cu and Mo were investigated by means of molecular dynamics (MD) simulations to study the incoherent interface between Cu and Mo. In order to select an appropriate potential capable of accurately describing the Cu-Mo system, five many-body potentials were compared: three Embedded Atom Method (EAM) potentials, a Tight Binding Second Moment Approximation (TB-SMA) potential, and a Modified Embedded Atom Method (MEAM) potential. Among these, the EAM potential proposed by Zhou in 2001 was determined to provide the best compromise for the current study. The simulated system was constructed with two layers of Cu and Mo forming an incoherent fcc-Cu(111)/bcc-Mo(110) interface, based on the Nishiyama–Wassermann (NW) and Kurdjumov–Sachs (KS) orientation relationships (OR). The interfacial energies were calculated for each orientation relationship. The NW configuration emerged as the most stable, with an interfacial energy of 1.83 J/m², compared to 1.97 J/m² for the KS orientation. Subsequent simulations were dedicated to modeling Cu atomic deposition onto a Mo(110) substrate at 300 K. These simulations resulted in the formation of a dense layer with only a few defects in the two Cu planes closest to the interface. The interfacial structures were characterized by computing selected area electron diffraction (SAED) patterns. A direct comparison of theoretical and numerical SAED patterns confirmed the presence of the NW orientation relationship in the nanocomposites formed during deposition, corroborating the results obtained with the model fcc-Cu(111)/bcc-Mo(110) interfaces. Full article

An innovative and efficient hybrid technique, which combines the Method of Moments (MoM) with Volume Meshed Shooting and Bouncing Ray (VSBR), is presented to analyze the scattering of metallic–dielectric mixed multi-scale structures in urban scenes. Additionally, the technique can rapidly generate radar images at different angles, which is useful for the video remote sensing community. By dividing the mixed multi-scale targets into sub-regions, different solvers are employed to compute the scattering contributions based on their varying electrical sizes. For large-scale sub-regions, the VSBR method is employed on both the medium and metal parts, leading to a multilevel electromagnetic field including both the direct induced field and the multi-reflection field. This field contributes to the integral equation in the MoM sub-regions. Additionally, interactions from the MoM region are considered within the VSBR region, followed by a surface current integration to compute the scattered field. When addressing mixed multi-scale electromagnetic problems, this technique proves to be more efficient and easier to implement in general-purpose computer codes. Furthermore, this method is accelerated using the local coupling (LC) theory and fast multipole method (FMM). Using this fast computational method, efficient simulation results of radar images at different angles for the scenes can be obtained and the numerical results demonstrate the efficiency and accuracy of the proposed method. Full article

In this paper, two ultra-wideband monopoles in a colinear structure are presented for application in remote terrestrial communication systems. The antennas consist of a loaded monopole with a hat and an elevated loaded monopole located in the upper position. All lumped loads are modeled as linear frequency-dependent components to approximate the practical component property for achieving ultra-wideband characteristics, since the constant value property of a component is only present in a relatively narrow band. The antennas are simulated by the method of moments (MoM) with asymptotic waveform evaluation (AWE) to speed up frequency sweep across a wide bandwidth. For proper simulation with the AWE process, the parallel RLC load with linear frequency-dependent components is modeled in a corresponding impedance function. With the optimized load parameters, one antenna covers 30–750 MHz with a VSWR < 3.5 and the other one covers 800 MHz–3000 MHz with a VSWR < 2.5, which are promising results for terrestrial omnidirectional applications. Full article

This paper describes an efficient approach to the broadband analysis of lightning protection systems (LPSs) using the method of moments (MoM) implemented in the frequency domain. The adaptive frequency sampling (AFS) algorithm, based on a rational interpolation of the relevant observable (e.g., voltage, current, electric or magnetic field) which describes the properties of the LPS, is employed to reduce the number of samples computed by the full-wave MoM. This improvement is achieved by the quick comparison of two interpolants with the use of the Stöer–Bulirsch algorithm, which provides the frequency location of the next MoM samples for computations. This algorithm allows for the efficient localization of resonant frequencies while reducing the number of samples computed over the entire frequency range. In the instances when the induced noise is determined in low-voltage installations protected by various types of LPSs, reductions in computational overhead equal to 47.9× and 72.1× in broadband LPS simulations are obtained. Hence, the proposed approach allows for a significant reduction in computational overhead in comparison to standard, uniformly sampled simulations. Full article

Background: Forensic investigative genetic genealogy (FIGG) has developed rapidly in recent years and is considered a novel tool for crime investigation. However, crime scene samples are often of low quality and quantity and are challenging to analyze. Deciding which approach should be used for kinship inference in forensic practice remains a troubling problem for investigators. Methods: In this study, we selected four popular approaches—KING, IBS, TRUFFLE, and GERMLINE—comprising one method of moment (MoM) estimator and three identical by descent (IBD) segment-based tools and compared their performance at varying numbers of SNPs and levels of genotyping errors using both simulated and real family data. We also explored the possibility of making robust kinship inferences for samples with ultra-high genotyping errors by integrating MoM and the IBD segment-based methods. Results: The results showed that decreasing the number of SNPs had little effect on kinship inference when no fewer than 164 K SNPs were used for all four approaches. However, as the number decreased further, decreased efficiency was observed for the three IBD segment-based methods. Genotyping errors also had a significant effect on kinship inference, especially when they exceeded 1%. In contrast, MoM was much more robust to genotyping errors. Furthermore, the combination of the MoM and the IBD segment-based methods showed a higher overall accuracy, indicating its potential to improve the tolerance to genotyping errors. Conclusions: In conclusion, this study shows that different approaches have unique characteristics and should be selected for different scenarios. More importantly, the integration of the MoM and the IBD segment-based methods can improve the robustness of kinship inference and has great potential for applications in forensic practice. Full article

We present theoretical investigations examining the electronic and magnetic properties of the SmFe_12−xMo_x (x = 1, 2) and SmFe₁₀Mo₂H compounds, including magneto-crystalline anisotropy, magnetic moments, exchange-coupling parameters, and Curie temperatures. The spin-polarized fully relativistic Korringa–Kohn–Rostoker (SPR-KKR) band structure method has been employed, using the coherent potential approximation (CPA) to deal with substitutional disorder. Hubbard-U correction was applied to the local spin density approximation (LSDA+U) in order to account for the significant correlation effects arising from the 4f electronic states of Sm. According to our calculations, the total magnetic moments increases with H addition, in agreement with experimental data. Adding one H atom in the near-neighbor environment of the Fe 8j site reduces the magnetic moments of Fe 8j and enhances the magnetic moment of Fe 8f. For every investigated alloy, the site-resolved spin magnetic moments of Fe on the 8i, 8j, and 8f sites exhibit the same magnitude sequence, with $m_s^{Fe}$ (8i) > $m_s^{Fe}$ (8j) > $m_s^{Fe}$ (8f). While the addition of H has a positive impact on magneto-crystalline anisotropy energy (MAE), the increase in Mo concentration is detrimental to MAE. The computed exchange-coupling parameters reveal the highest values between the closest Fe 8i spins, followed by Fe 8i and Fe 8j spins, for all investigated alloys. The Curie temperature of the alloys under investigation is increased by decreasing the Mo concentration or by H addition, which is qualitatively consistent with experimental findings. Full article

Sample selection is one of the most important factors in estimating the unknown parameters of distributions, as it saves time, saves effort, and gives the best results. One of the challenges is deciding on a suitable distribution estimate technique and adequate sample selection to provide the best results in comparison with earlier research. The method of moments (MOM) was decided on to estimate the unknown parameters of the Gumbel distribution, but with four changes in the sample selection, which were simple random sample (SRS), ranked set sampling (RSS), maximum ranked set sampling (MRSS), and ordered maximum ranked set sampling (OMRSS) techniques, due to small sample sizes. The MOM is a traditional method for estimation, but it is difficult to use when dealing with RSS modification. RSS modification techniques were used to improve the efficiency of the estimators based on a small sample size compared with the usual SRS estimator. A Monte Carlo simulation study was carried out to compare the estimates based on different sampling. Finally, two datasets were used to demonstrate the adaptability of the Gumbel distribution based on the different sampling techniques. Full article

Introduction: Breastfeeding is one of the strategies that has been shown to be effective in preventing severe forms of bronchopulmonary dysplasia (BPD). When mother’s own milk (MOM) is not available, pasteurized donor milk (DM) is the best alternative. However, the evidence is inconclusive on the difference in the incidence of bronchopulmonary dysplasia (BPD) between patients fed MOM and those fed with DM. As standard DM is usually mature pooled milk donated by mothers who have delivered their babies at term, the potential benefits of preterm milk may be lost. Materials and Methods: An observational, retrospective, single-center study was conducted in the neonatology department of a high-complexity hospital. The study included newborns <32 weeks of gestational age born between January 2020 and December 2022. When supplemental milk was needed, non-pooled preterm pasteurized donor milk (PDM) matched for gestational age and moment of lactation was used in this study, classifying preterm infants in two groups: mainly MOM (>50% of the milk) or mainly PDM (>50% of the milk). Two groups were established: those who received >50% MOM and those who received >50% PDM. They were also classified according to the diagnosis of DBP: one group included no BPD or grade 1 BPD (noBPD/1), while the other included grade 2 or 3 BPD (BPD 2–3). The objectives of this study were, firstly, to evaluate the incidence of BPD 2–3 among patients who predominantly received PDM versus MOM. Secondly, to analyze differences in the type of human milk received and its nutritional components, as well as to study the growth in patients with or without BPD. Results: One hundred ninety-nine patients were included in the study. A comparison of noBPD/1 versus BPD 2–3 groups between those receiving mainly MOM versus PDM showed no significant differences (19% vs. 20%, p 0.95). PDM colostrum in BPD 2–3 compared to noBPD/1 was higher in protein content (2.24 g/100 mL (SD 0.37) vs. 2.02 g/100 mL (SD 0.29) p < 0.01), although the statistical significance decreased after adjustment for gestational age and birth weight z-score (OR 3.53 (0.86–14.51)). No differences were found in the macronutrients in the mature milk of patients feeding more than 50% PDM in both study groups. Growth of BPD 2–3 showed a greater decrease in the difference in z-scores for height at birth and at discharge compared to noBPD/1 (−1.64 vs. −0.43, p 0.03). Conclusions: The use of mainly MOM or PDM demonstrates a similar incidence of noBPD/1 or BPD 2–3. Non-pooled and matched by gestational age and time of lactation preterm donor milk can probably be an alternative when mother’s own milk is not available, with a similar protective effect in the prevention of severe BPD. Full article

To address the challenges posed by composite targets composed of an anisotropic medium and metal in electromagnetic (EM) scattering calculations, this paper introduces an innovative hybrid algorithm tailored for simulating the EM scattering characteristics of such complex targets. Utilizing impedance boundary condition (IBC), the method employs surface impedance vectors to precisely depict the EM properties of the medium. By harnessing the distinct advantages of the Method of Moments (MoMs) at low frequency and Physical Optics (POs) at high frequency, the algorithm ensures both accuracy and efficiency in the EM simulation of composite targets. By transforming the EM scattering problem of targets coated with a thin-layered medium into an equivalent radiation problem of EM currents on impedance surfaces, this research has achieved rapid and high-precision calculations of the Radar Cross Section (RCS) for complex targets with anisotropic medium coatings. To assess the performance of the algorithm, three target models—square plates, simplified aircraft, and complex satellites—are selected as test cases. The dual metrics of RCS and surface current distribution are utilized as evaluation benchmarks, and comparisons are made against the Method of Moments–Finite Element Method (MoM-FEM) hybrid numerical method. The comparative results demonstrate that the proposed method meets the engineering standards in terms of both the root mean square error (RMSE) of RCS and the relative error in surface current distribution, while also achieving a significant improvement of over 50% in computational efficiency, thereby validating its superior accuracy and practical utility. Full article

In this paper, a compound-Gaussian model (CGM) with the Nakagami-distributed textures (CGNG) is proposed to model sea clutter at medium/high grazing angles. The corresponding amplitude distributions are referred to as the CGNG distributions. The analysis of measured data shows that the CGNG distributions can provide better goodness-of-the-fit to sea clutter at medium/high grazing angles than the four types of commonly used biparametric distributions. As a new type of amplitude distribution, its parameter estimation is important for modelling sea clutter. The estimators from the method of moments (MoM) and the [zlog(z)] estimator from the method of generalized moments are first given for the CGNG distributions. However, these estimators are sensitive to sporadic outliers of large amplitude in the data. As the second contribution of the paper, outlier-robust tri-percentile estimators of the CGNG distributions are proposed. Moreover, experimental results using simulated and measured sea clutter data are reported to show the suitability of the CGNG amplitude distributions and outlier-robustness of the proposed tri-percentile estimators. Full article

South Africa is currently grappling with a national energy crisis and the high infrastructure costs associated with expanding the national grid to remote areas. Simultaneously, the government has made substantial efforts to harness renewable energy technologies, particularly wind energy. The average wind speed in a specific region significantly influences the energy yield from wind turbines. The vast open inland terrains, mountainous regions, and coastal areas in the Northern Cape, Eastern Cape, and Western Cape provinces of South Africa possess the most substantial wind potential. It is imperative to initiate wind energy projects in these provinces to cater to a significant portion of the local electricity demand, especially in remote areas disconnected from the national grid. Wind energy generation is inherently stochastic, subject to variations in both time and space. Consequently, it is essential to gain a comprehensive understanding of the local wind patterns to assess the feasibility of utilizing wind resources. In the Eastern Cape Province, the Mthatha area still lags in household electrification, presenting an opportunity to electrify some households using wind energy. This study aimed to evaluate the wind resource potential for Mthatha area, utilizing data spanning from 2018 to 2023, provided by the South African Weather Services. Two distribution models, the two-parameter Weibull and three-parameter Weibull, were employed to characterize the provided wind data. To determine the parameters associated with each distribution model, two estimation methods, the Maximum Likelihood Method (MLM) and the Method of Moments (MOM), were utilized. The performance of these distribution models was assessed using the Root Mean Square Error (RMSE) statistical indicator. The results showed that Mthatha area predominantly experiences low wind speeds, with an annual average wind speed of 3.30 m/s and an overall wind power density of approximately 48.48 W/m². The prevailing winds predominantly originate from the south and east–southeast directions. Consequently, Mthatha is recommended for stand-alone applications, with the added suggestion of augmented wind turbines for the area. Full article