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This study proposes a two-level stacking machine learning approach for predicting rainfall erosivity (Rm) in Taiwan, providing a flexible alternative to traditional empirical methods. Conventional models rely on limited ...

Graphical models allow modeling of complex dependencies among components of a random vector. In many applicationsof graphical models, however, for example microbiome data, the data have an excess number of zero values. W...

Traditional poppy vinegar is a functional fermented food matrix enriched with diverse biomolecules that may contribute to metabolic health. In this study, the effects of thermosonication on the biomolecular profile, anti...

Abstract Alkaline water electrolysis represents a promising pathway for green hydrogen production, yet comprehensive multi-physics simulation remains computationally prohibitive for practical design optimization. This st...

Abstract Background Metabolic syndrome (MetS) obviously increases the risk of major adverse cardiac and cerebrovascular events (MACCE) in patients with acute myocardial infarction (AMI). However, the metabolic mechanisms...

The relevance of the study is driven by the need to identify ways to replenish the state budget and to establish an effective tax rate for virtual assets in Ukraine in the context of the digital transformation of the eco...

Prior validation against well-documented benchmark experiments is essential for establishing a reliable computational foundation for liquefied natural gas (LNG) vapor dispersion simulations in safety assessments and haza...

Short-term wind speed forecasting remains challenging due to the inherent nonstationarity and multiscale variability of atmospheric processes. This study proposes a hybrid multiscale forecasting framework combining four-...

In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that empl...

The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training...

Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an int...

En la presente tesis se plantea el modelado del equilibrio entre fases de mezclas de importancia en biorrefinerías, y el desarrollo de módulos de simulación de procesos y productos. El modelo termodinámico empleado...

La actividad agrícola actual enfrenta diversos desafíos: existencia de una limitada área de cultivo, demanda creciente de producción debido al aumento de la población mundial, necesidad de adecuación a climas adv...

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide ...

Materias / palabras clave: decision analytics, data-driven decision making, predictive modeling, prescriptive analytics, decision science, optimization; Social Sciences: Commerce: Business: Business mathematics. Commercial arithmetic. Including ta...

Materias / palabras clave: data science, artificial intelligence, data analytics, predictive modeling, cybersecurity, algorithms; Science: Mathematics: Instruments and machines: Electronic computers. Computer science