1,159 Results Found

During the vascular surgical reconstruction of aorto-iliac occlusive/aneurysmal disease, bifurcated grafts are used where vascular surgeons intra-operatively select the size and the relative lengths of the parent and daughter portions of the graft. C...

Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well...

Validation of groundwater models is relatively challenging due to the need to reserve scarce water level data for calibration targets. In addition, traditional statistical validation metrics are unintuitive for non-technical audiences and do not dire...

The present paper deals with nonlinear, non-monotonic data regression. This paper introduces an efficient algorithm to perform data transformation from non-monotonic to monotonic to be paired with a statistical bivariate regression method. The propos...

In this study, a novel symbolic regression-based empirical equation has been developed to compute the joint roughness coefficient (JRC) value based on the statistical parameters of rock joints. The symbolic regression was adopted to map the nonlinear...

Although linear regression models are fundamental tools in statistical science, the estimation results can be sensitive to outliers. While several robust methods have been proposed in frequentist frameworks, statistical inference is not necessarily s...

Wire Arc Additive Manufacturing (WAAM) represents a disruptive technology in the field of metal additive manufacturing. Understanding the relationship between input factors and layer geometry is crucial for studying the process comprehensively and de...

Modeling the interrelationships between the input parameters and outputs (responses) in any machining processes is essential to understand the process behavior and material removal mechanism. The developed models can also act as effective prediction...

Uncertain regression analysis is a powerful tool for analyzing and interpreting the complex relationships between explanatory and response variables under uncertain environments, and a crucial step in analyzing datasets containing complex uncertainti...

In predictive microbiology, both primary and secondary models are widely used to estimate microbial growth, often applied through two-step or one-step modelling approaches. This study focused on developing a tool to predict the growth of Pseudomonas...

Large multiple datasets were simulated through sampling, and regression modeling results were compared with known parameters—an analysis undertaken here for the first time on such a scale. The study demonstrates that the impact of multicollinea...

Carefully selecting variables in problems with large volumes of data are extremely important, as it reduces the complexity of the model, improves the interpretation of the results, and increases computational efficiency, ensuring more accurate and re...

Beta regression models are a class of supervised learning tools for regression problems with univariate and limited response. Current fitting procedures for beta regression require variable selection based on (potentially problematic) information cri...

Regression models are a form of supervised learning methods that are important for machine learning, statistics, and general data science. Despite the fact that classical ordinary least squares (OLS) regression models have been known for a long time,...

Machining of medium-carbon steels, such as AISI 1050, poses a significant challenge in terms of achieving stable cutting conditions, controlled chip evacuation and high surface integrity, in particular when full-face milling is performed under elevat...

Recently, the Unesp-Botucatu sheep acute pain scale (USAPS) was created, refined, and psychometrically validated as a tool that offers fast, robust, and simple application. Evidence points to an improvement in pain diagnosis when the importance of th...

The GNSS LABoratory tool (gLAB) is an interactive educational suite of applications for processing data from the Global Navigation Satellite System (GNSS). gLAB is composed of several data analysis modules that compute the solution of the problem of...

Income modeling is crucial in determining workers’ earnings and is an important research topic in labor economics. Traditional regressions based on normal distributions are statistical models widely applied. However, income data have an asymmet...

Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work...

Metabolic flux analysis (MFA) is an indispensable tool in metabolic engineering. The simplest variant of MFA relies on an overdetermined stoichiometric model of the cell’s metabolism under the pseudo-steady state assumption to evaluate the intracellu...

The acceptance sampling plans are one of the most important tools for the inspection of a lot of products. Sometimes, it is difficult to study the variable of interest, and some additional or auxiliary information which is correlated to that variable...

Taking account of sex and gender in occupational health studies poses statistical challenges. Other sociodemographic variables, such as racialization, class, and age, also affect the relations between workplace exposures and health and interact with...

The use of advanced chemometrics tools in food authenticity research is crucial for managing the huge amount of data that is generated by applying state-of-the-art analytical methods such as chromatographic, spectroscopic, and non-targeted fingerprin...

Machinability analyses of metal matrix composites are essential for manufacturing industries. The current study is focused on the mathematical modeling of the machinability of an in-situ synthesized RZ5-8 wt.% TiB₂ composite using the Taguchi design...

This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities’ prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventio...

The implementation of smart technologies as well as artificial intelligence resulted in an increase in productivity and efficiency in production, optimization of costs, and automation of time-consuming processes. The situation is similar in the field...

Understanding the determinants of housing price movements is an ongoing subject of debate. Estimating these determinants becomes a valuable tool for predicting price trends and mitigating the risks of market volatility. This article presents a system...

The “Timed-Up-and-Go” test (TUG) is a standard assessment tool for functional mobility as it assesses several functional components, including balance, gait, and lower-extremity strength. It has good reliability and validity and is cost-e...

Bioretention cells are an urban stormwater management technology used to address both water quality and quantity concerns. A lack of region-specific design guidelines has limited the widespread implementation of bioretention cells, particularly in co...

Routine least squares regression analyses may sometimes miss important aspects of data. To exemplify this point we analyse a set of 1171 observations from a questionnaire intended to illuminate the relationship between customer loyalty and perception...

Timely and accurate detection of cardiovascular diseases (CVDs) is critically important to minimize the risk of a myocardial infarction. Relations between factors of CVDs are complex, ill-defined and nonlinear, justifying the use of artificial intell...

Hearing loss is one of the more common occupation health hazards across the globe yet is preventable. Extensive research has been done across a number of industries measuring the magnitude and frequency of hearing impairment. This study uses the Nati...

This paper presents a study on optimising self-brazing powder mixtures for powder metallurgy diamond tools, specifically focusing on wire saws used in cutting natural stone. The research aimed to understand the relationship between the chemical compo...

Annual river discharge is a critical variable for water resources planning and management. Tree rings are widely used to reconstruct annual discharge, but errors can be large when tree growth fails to respond commensurately to hydrologically importan...

The aim of the current study was to determine the scale and underlying causes for the waste of raw and processed fruits and vegetables in Polish households. A survey was conducted on a representative sample of 1100 respondents. The collected empirica...

Predictions of microbial crude protein (MCP) synthesis for beef cattle generally rely on empirical regression equations, with intakes of energy and protein as key variables. Using a database from published literature, we developed new equations based...

Voice pathology diagnosis is essential for the timely detection and management of voice disorders, which can significantly impact an individual’s quality of life. This study employed logistic regression to evaluate the predictive power of varia...

The conservation of heritage buildings requires non-invasive tools that can predict material performance while maintaining historical integrity and structural safety. This study introduces a multivariate statistical framework that integrates regressi...

Forests play a crucial role as the primary sink for greenhouse gases, and forest mortality significantly impacts the carbon sequestration capacity of forest ecosystems. A single type of forest mortality model has been developed, and its model variabl...

The titanium alloy Ti-6Al-4V is widely used in the aerospace, medical, and automotive industries; however, its machining remains challenging due to its low thermal conductivity and high chemical reactivity. This study investigates the influence of th...

Background: Up to 60% of the antibiotics prescribed to patients hospitalized with seasonal influenza are unnecessary. Procalcitonin (PCT) has the potential as an antimicrobial stewardship program (ASP) tool because it can differentiate between viral...

This article is focused mainly on verifying the suitability of data from the experimental milling of heat-treated beech wood and on investigating the effects of the technical and technological parameters of milling on the energy consumption of this p...

In this study, a revision of the previously published data on hydrogen (²H/¹H) and oxygen (¹⁸O/¹⁶O) stable isotope ratio of precipitation in northern Chile is presented. Using the amount-weighted mean data and the combined standard deviation (related...

Although there is an increasing awareness of the suitability of using compositional data methodology in public health research, classical methods of statistical analysis have been primarily used so far. The present study aims to illustrate the potent...

Accurately capturing children’s word learning abilities is critical for advancing our understanding of language development. Researchers have demonstrated that utilizing more complex statistical methods, such as mixed-effects regression and hie...

Due to the teacher shortage in the U.S., an automatic toolbox with secondary development based on the ArcPy package was created to explore the spatial imbalance of the pupil–teacher ratio. It consists of four tools (or toolsets) for multi-scale...

This article analyses the adverse impact of Chopin Airport in Warsaw on the prices of single-family houses located within the aircraft noise impact zone. The specific feature of the largest airport in Poland is its location within the city limits and...

Background: Delirium is a common complication in patients receiving extracorporeal membrane oxygenation (ECMO), but its prevalence and determinants remain uncertain due to variable clinical practices. We conducted a systematic review and meta-analysi...

This research work dealt with the development of an operational methodology with appropriate technical components for monitoring and forecasting of rice crop (Boro) production in Bangladesh. Designed system explores integrated application of remote s...

In epidemiology, a risk factor is a variable associated with increased disease risk. Understanding the role of risk factors is significant for developing a strategy to improve global health. There is strong evidence that risk factors like smoking, al...