Artificial neural network (ANN) is a commonly used approach to estimate or forecast air pollution levels, which are usually assessed by the concentrations of air contaminants such as nitrogen dioxide, sulfur dioxide, carbon monoxide, ozone, and suspended particulate matters (PMs) in the atmosphere of the concerned areas. Even through ANN can accurately estimate air pollution levels they are num...

Non-volatile write-back caches enable storage controllers to provide quick write response times by hiding the latency of the disks. Managing a write cache well is critical to the performance of storage controllers. Over two decades, various algorithms have been proposed, including the most popular, LRW, CSCAN, and WOW. While LRW leverages temporal locality in the workload, and CSCAN creates spa...

Objectives Environmental pollution is a significant global issue. Both objective (scientifically measured) environmental pollution and perceived levels of pollution are important predictors of self-reported health. The purpose of this study was to compare the associations between perceived environmental pollution and health in China, Japan, and South Korea. Methods Data were obtained from the...

While ambient air pollution levels in excess of prescribed health standards are generally unacceptable, the exceedance is even more serious in areas where people reside. Vulnerability caused by poverty, disease, lack of education, and poor living conditions exacerbates the problem. Air quality management plans identify prioritized strategies for improved air quality independent of consideration...

Boundary environmental pollution and pollution spillovers are important issues for improving the water quality of trans-boundary rivers. This paper explores the empirical effects of the evolution of the pollution reduction mandates on boundary pollution by studying the change of water pollution levels (as proxied by pH, BOD, COD and NH3-N) of key state monitoring stations from 2004 to 2014. The...