Economic considerations make the conventional chest radiograph (X-ray) film an important ingredient in the diagnostic process. An initial clinical investigation for patients with suspected lung ailments is the study of the chest X-rays. The problem of detection for diseases in their early stages are well known using X-ray. A technique involving wavelets coefficient as the feature vector and Andrew's Curve has been proposed for detection of Mycobacterium Tuberculosis (MTB). This paper presents new and important results whereby lung cancer (LC) may be detected and differentiated from MTB. A method to calculate misclassification probabilities is given.
This study determined the source contribution of PM2.5 (particulate matter <2.5 μm) in air at three locations on the Malaysian Peninsula. PM2.5 samples were collected using a high volume sampler equipped with quartz filters. Ion chromatography was used to determine the ionic composition of the samples and inductively coupled plasma mass spectrometry was used to determine the concentrations of heavy metals. Principal component analysis with multilinear regressions were used to identify the possible sources of PM2.5. The range of PM2.5 was between 10 ± 3 and 30 ± 7 µg m(-3). Sulfate (SO4 (2-)) was the major ionic compound detected and zinc was found to dominate the heavy metals. Source apportionment analysis revealed that motor vehicle and soil dust dominated the composition of PM2.5 in the urban area. Domestic waste combustion dominated in the suburban area, while biomass burning dominated in the rural area.