Gradient boosting machines are a family of powerful machine-learning techniques that have
shown considerable success in a wide range of practical applications. They are highly …

Sewer overflow (SO), which has attracted global attention, poses serious threat to public
health and ecosystem. SO impacts public health via consumption of contaminated drinking …

Ensemble methods that train multiple learners and then combine them to use, with Boosting
and Bagging as representatives, are well-known machine learning approaches. It has …

Citizen-science projects engage volunteers to gather or process data to address scientific
questions. But citizen-science projects vary in their ability to contribute usefully for science …

Species distribution models (SDMs) are widely used to explain and predict species ranges
and environmental niches. They are most commonly constructed by inferring species' …

Building useful models of species distributions requires attention to several important issues,
one being imperfect detection of species. Data sets of species detections are likely to suffer …

Identifying ecological patterns across broad spatial and temporal extents requires novel
approaches and methods for acquiring, integrating and modeling massive quantities of …

Knowledge about the spatial distribution of seabirds at sea is important for conservation.
During marine conservation planning, logistical constraints preclude seabird surveys …

Ensuring that conservation decisions are informed by the best available data is a
fundamental challenge in the face of rapid global environmental change. Too often, new …

In recent years reactive powder concrete (RPC), also known as ultrahigh-performance
concrete, emerged as one of the most efficient building materials due to its ultrahigh …