Occupational Thorium Exposure or Self-Poisoning?
Thoriated electrodes are used in TIG (Tungsten Inert Gas) welding [1]. Thorium intake may happen during grinding and welding operations using thoriated electrodes [2]. The use of thoriated tungsten electrodes may be at the origin of a potential hazard [3]. The annual commited effective dose from inhalation of 232Th, 230Th, 228Th and 228Ra is usually below 1mSv for a full-time TIG welder [4]. Electrode consumption during welding was primarily the result of tip sharpening. Indeed, less than 3% of weight loss was attributable to the welding process [5].
Intakes of thorium while using thoriated tungsten electrodes for TIG welding.
Thoriated electrodes are used in TIG welding. TIG welders, along with persons who grind thoriated electrodes and persons located near relevant welding and grinding sites, might be at risk of thorium intake. The isotopes of radiological relevance are 232Th, 230Th, and 228Th. The studies described in the literature do not provide a consistent picture of the actual hazards, and changes in European and German radiological protection laws have now made it necessary to determine the risks. To accomplish this, a field test was conducted under real working conditions in 26 different welding shops. The airborne activity generated through welding, and through grinding of electrodes, was measured using personal air samplers. Stationary samplers were also used. The filters' samples were evaluated by means of direct alpha spectrometry with proportional counting and by means of gamma spectrometry following neutron activation. The results clearly showed that considerable intake can occur during both alternating-current welding and electrode grinding, if no suction systems are used. The range of 232Th intakes to welders were estimated from 0.1 Bq y(-1) to 144 Bq y(-1) during welding and from 0.02 Bq y(-1) to 30.2 Bq y(-1) during grinding. In 6 of the 26 cases the recent annual limit on intake derived from the most recent ICRP publications was exceeded--in the worst case it was exceeded by a factor of 10--if it is assumed that the persons studied were not exposed workers (not routinely monitored for radiation exposure). When the significantly more restrictive German limits are applied, the amounts by which the limits were exceeded were even greater. Because many qualified welders have very long careers, the risks can thus be considerable. The paper also discusses parameters that influence exposure, and it presents a catalogue of recommended measures for dosage reduction.
Multivariate Image Texture by Multivariate Variogram for Multispectral Image Classification
Traditional image texture measure usually allows a texture description of a single band of the spectrum, characterizing the spatial variability of gray-level values within the singleband image. A problem with the approach while applied to multispectral images is that it only uses the texture information from selected bands. In this paper, we propose a new multivariate texture measure based on the multivariate variogram. The multivariate texture is computed from all bands of a multispectral image, which characterizes the multivariate spatial autocorrelation among those bands. In order to evaluate the performance of the proposed texture measure, the derived multivariate texture image is combined with the spectral data in image classification. The result is compared to classifications using spectral data alone and plus traditional texture images. A machine learning classifier based on Support Vector Machines (SVMs) is used for image classification. The experimental results demonstrate that the inclusion of multivariate texture information in multispectral image classification significantly improves the overall accuracy, with 5 to 13.5 percent of improvement, compared to the classification with spectral information alone. The results also show that when incorporated in image classification as an additional band, the multivariate texture results in high overall accuracy, which is comparable with or higher than the best results from the existing single-band and two-band texture measures, such as the variogram, cross variogram and Gray-Level Co-occurrence Matrix (GLCM) based texture. Overall, the multivariate texture provides the useful spatial information for land-cover classification, which is different from the traditional single band texture. Moreover, it avoids the band selection procedure which is prerequisite to traditional texture computation and would help to achieve high accuracy in the most classification tasks.