41,428 Results Found

The article focuses on mortality models with a random effect applied in order to evaluate human mortality more precisely. Such models are called frailty or Cox models. The main assertion of the paper shows that each positive random effect transforms...

We continue the analysis of the influence of the random effect transformation on the regularity of distribution functions. The paper considers three regularity classes: heavy-tailed distributions, distributions with consistently varying tails, and ex...

Mixed models are useful tools for analyzing clustered and longitudinal data. These models assume that random effects are normally distributed. However, this may be unrealistic or restrictive when representing information of the data. Several papers h...

Novel functionalities of disorder-induced scattering effect in random lasers, attributed to low spatial coherence, draw remarkable attention in high-contrast to superior quality speckle-free imaging applications. This paper demonstrates perovskite-po...

Under the condition of non-classical distributed errors, the test for spatial dependence in spatial panel data models is still a problem waiting to be solved. In this paper, we apply the FDB (Fast Double Bootstrap) method to spatial panel data models...

Vulnerable traffic users, such as bikers and pedestrians, account for a significant number of fatalities on the roadways. Extensive research has been conducted in the literature review to identify factors to those crashes. Studying factors to those c...

The current research empirically analyses the determinants of financial inclusion (FI) for BRICS (Brazil, Russia, India, China and South Africa) nations using the no. of depositors and Automated Teller Machines/user as dependent variables, a proxy fo...

Meta-analyses of clinical trials with binary outcomes frequently rely on normal approximations of effect measures. However, these approximations may become unreliable when trials are small or when event probabilities are close to 0 or 1. In this stud...

In this study, we demonstrate the generation and storage of random voltage values using a ring oscillator consisting of feedback field-effect transistors (FBFETs). This innovative approach utilizes the logic-in-memory function of FBFETs to extract co...

Tracking the progress of an infectious disease is critical during a pandemic. However, the incubation period, diagnosis, and treatment most often cause uncertainties in the reporting of both cases and deaths, leading in turn to unreliable death rates...

Drug side-effects have become a major public health concern as they are the underlying cause of over a million serious injuries and deaths each year. Therefore, it is of critical importance to detect side-effects as early as possible. Existing comput...

The purpose of this study was to offer a comprehensive econometrical framework based on a multilevel random effect logistic model that could highlight important contributors to carpool users among different cities with various attributes. The data wa...

A monolithic three-dimensional integrated static random access memory containing a feedback field effect transistor (M3D-FBFET-SRAM) was proposed. The M3D-FBFET-SRAM cell consists of one metal oxide semiconductor field effect transistor (MOSFET) and...

In recent times, in the literature of inventory management there exists a notorious interest in production-inventory models focused on imperfect production processes with a deterministic time horizon. Nevertheless, it is well-known that there is a hi...

We systematically investigate the combined impact of process variation effects (PVEs), metal gate work function fluctuation (WKF), and random dopant fluctuation (RDF) on the key electrical characteristics of sub-1-nm technology node gate-all-around s...

There are usually noise problems when the position sensorless control of a synchronous reluctance motor (SynRM) is carried out by high-frequency (HF) signal injection method. Due to the special structure, the cross-saturation effect of the SynRM is p...

The spatio-temporal random effect (STRE) model, a type of spatio-temporal Kalman filter model, can be used for the fusion of the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) data to generate high spat...

A random network of indium–gallium–zinc oxide (IGZO) nanowires was fabricated by electrospun-polyvinylpyrrolidone (PVP)-nanofiber template transfer. Conventional electrospun nanofibers have been extensively studied owing to their flexibil...

The capability of multiple valued logic (MVL) circuits to achieve higher storage density when compared to that of existing binary circuits is highly impressive. Recently, MVL circuits have attracted significant attention for the design of digital sys...

This paper presents a one-transistor dynamic random-access memory (1T-DRAM) cell based on a gate-all-around junction-less field-effect transistor (GAA-JLFET) with a Si/SiGe heterostructure for high-density memory applications. The proposed 1T-DRAM ac...

Due to the difficulties associated with scaling of silicon transistors, various technologies beyond binary logic processing are actively being investigated. Ternary logic circuit implementation with carbon nanotube field effect transistors (CNTFETs)...

We experimentally explore the relation between spectral linewidth and RIN transfer in half-open cavity random distributed feedback Raman lasers, demonstrating for the first time the possibility of adjusting the pump-to-signal RIN transfer intensity a...

Poisson mixed-effects models are essential for analyzing repeated count data, relying on latent random effects to account for unobserved heterogeneity and longitudinal dependence. However, the validity of likelihood-based inference in these models is...

An investigation of transient second sound phenomena due to moving heat sources on planar random media is conducted. The spatial material randomness of the relaxation time is modeled by Cauchy or Dagum random fields allowing for decoupling of fractal...

Calcium ions (Ca²⁺) are abundantly present in the human body; they perform essential roles in various biological functions. In this study, we propose a highly sensitive and selective biosensor platform for Ca²⁺ detection, which comprises a dual-gate...

Multilevel semicontinuous data occur frequently in medical, environmental, insurance and financial studies. Such data are often measured with covariates at different levels; however, these data have traditionally been modelled with covariate-independ...

The electrical switching behavior of the GeTe phase-changing material grown by atomic layer deposition is characterized for the phase change random access memory (PCRAM) application. Planar-type PCRAM devices are fabricated with a TiN or W bottom ele...

A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effect...

This paper continues the analysis from Parts I and II, which addressed two-dimensional dispersed random composites. This part extends previous analytical studies by incorporating machine learning (ML) methods to quantitatively classify microstructure...

We report dependence of random lasing performance of directly spin-coated multicrystalline thin films of an organic–inorganic hybrid, halide perovskite CH₃NH₃PbBr₃ (MAPbBr₃), on different substrates. It was discovered that random lasing perform...

We propose a random effects panel data model with both spatially correlated error components and spatially lagged dependent variables. We focus on diagnostic testing procedures and derive Lagrange multiplier (LM) test statistics for a variety of hypo...

Physiological health effects (vibration perception thresholds and infrared skin temperature) of single-impact exposures and vibration exposures have been evaluated. In this experiment, a total of 52 healthy male participants were randomly exposed to...

Our meta-epidemiological study aimed to describe the prevalence of reporting effect modification only on relative scale outcomes and inappropriate interpretations of the coefficient of interaction terms in nonlinear models on categorical outcomes. Ou...

The step-stress accelerated degradation test (ADT) provides a feasible method for assessing the storage life of high-reliability, long-life products. However, this method results in a slower rate of performance degradation at the beginning of the tes...

Clustered proportion responses often exhibit bounded support, skewness, heterogeneous dispersion, and within-cluster dependence. We propose a correlated mean–precision random-effects beta regression model that jointly represents cluster-level h...

Vaccine hesitancy remains a major public health concern in the effort towards addressing the COVID-19 pandemic. This study analyzed the effects of indicators of compliance with preventive practices on the willingness to take COVID-19 vaccines in Keny...

Objective: The purpose of this article was to use the Random Forest method and nonlinear mixed-effects method to develop a model for determining tree height–diameter at breast height (DBH) for a natural coniferous and broad-leaved mixed forest...

Random effect panel data hurdle models are established to research the daily crash frequency on a mountainous section of highway I-70 in Colorado. Road Weather Information System (RWIS) real-time traffic and weather and road surface conditions are me...

Meta-analysis aggregates information across related studies to provide more reliable statistical inference and has been a vital tool for assessing the safety and efficacy of many high-profile pharmaceutical products. A key challenge in conducting a m...

Background: The treatment of functional speech sound disorders (SSDs) in children is often lengthy, ill-defined, and without satisfactory evidence of success; effectiveness studies on SSDs are rare. This randomized controlled trial evaluates the effe...

In the field of reliability analysis, the constant-stress accelerated degradation test is one of the most commonly used methods to evaluate a product’s reliability as degradation data are provided. In this paper, a constant-stress accelerated d...

This paper investigates degradation modeling and failure time prediction for constant-stress accelerated degradation tests (CSADT) using a generalized Wiener process. Owing to differences in manufacturing processes and operating environments, the deg...

This paper presents a comparative empirical analysis of three modeling approaches applied to the forecasting of Morocco’s Real Effective Exchange Rate (REER): the ARIMA model, the Random Forest algorithm, and the Dynamic Factor Model (DFM). Uti...

This study estimates transient and persistent technical efficiencies (TEs) using a generalized true random-effects (GTRE) model. We estimate the GTRE model using maximum likelihood and Bayesian estimation methods, then compare it to three simpler mod...

Environmental pollution and health problems caused by the excessive use of motor vehicles have received widespread attention from all over the world. Currently, research lacks attention to the nonlinear effects of the built environment on short-dista...

Eliciting different attitudes with survey questionnaires may impact on intention to donate organs. Previous research used varying numbers of questionnaire items, or different modes of intervention delivery, when comparing groups. We aimed to determin...

The exposure of spaceborne devices to high-energy charged particles in space results in the occurrence of both a total ionizing dose (TID) and the single-event effect (SEE). These phenomena present significant challenges for the reliable operation of...

Background: Ensemble tree-based models such as Xgboost are highly prognostic in cardiovascular medicine, as measured by the Clinical Effectiveness Metric (CEM). However, their ability to handle correlated data, such as hospital-level effects, is limi...

Among various data-driven approaches for remaining useful life (RUL) prediction, Wiener process-based degradation models are interpretable and quantify uncertainty. However, existing methods that combine artificial neural networks (ANNs) with the Wie...

Background: Although recent research suggests that alterations in gut microbiota and metabolites play a critical role in the pathophysiology of immunoglobulin A nephropathy (IgAN), the causal relationship between specific intestinal flora and metabol...