Air pollution emerges as an imminent issue in metropolitan cities like Hong Kong, and attracts much attention in recent years. Prediction of pollutant levels and their tendency is an important topic in environmental science today. To achieve such prediction tasks, the use of neural network (NN), in particular, the multi-layer perceptron, is regarded as a cost-e7ective technique superior to trad...

Yorbik et al. reported novel findings regarding a hypothesized relationship between childhood attention-deficit hyperactivity disorder (ADHD) and later risk for coronary heart disease in adulthood. The authors found that mean platelet volume (MPV), a marker of platelet reactivity and a presumable biomarker in patients with cardiovascular disease, was significantly elevated in children with ADHD...

Spatial data contain information about both the attribute of interest as well as its location. Examples can be found in a large number of disciplines including ecology, geology, epidemiology, geography, image analysis, meteorology, forestry, and geosciences. The location may be a set of coordinates, such as the latitude and longitude associated with an observed pollutant level, or it may be a s...

Relationships between indoor carbon dioxide (CO2) levels and mucous membrane and lower respiratory sick building syndrome (SBS) symptoms are explored in 41 office buildings from the US EPA BASE study. Elevated indoor CO2 concentrations may indicate inadequate ventilation per occupant and elevated indoor pollutant concentrations, leading to SBS symptoms. Two CO2 metrics were constructed: average...

For time-series forecasting problems, there have been several prediction models to data, but the development of a more accurate model is very difficult because of high non-linear and non-stable relations between input and output data. Almost all the models at hand are not applicable online, although online prediction, especially for air quality parameters forecasting, has very important signifi...

Pollutant forecasting is an important problem in the environmental sciences. Data mining is an approach to discover knowledge from large data. This paper tries to use data mining methods to forecast concentration level, which is an important air pollutant. There are several tree-based classification algorithms available in data mining, such as CART, C4.5, Random Forest (RF) and C5.0. RF and C5....

We observed a panel of 133 children (5-13 years of age) with asthma residing in the greater Seattle, Washington, area for an average of 58 days (range 28-112 days) during screening for enrollment in the Childhood Asthma Management Program (CAMP) study. Daily self-reports of asthma symptoms were obtained from study diaries and compared with ambient air pollution levels in marginal repeated measu...