Trace element speciation of an integrated soil amendment matrix was studied with a modified BCR sequential extraction procedure. The analysis included pseudo-total concentration determinations according to USEPA 3051A and relevant physicochemical properties by standardized methods. Based on the results, the soil amendment matrix possessed neutralization capacity comparable to commercial fertili...

Information extraction (IE) is an important problem for information integration with broad applications. It is an attractive application for machine learning. The core of this problem is to learn extraction rules from given input. This paper extends a pattern discovery approach called IEPAD to the rapid generation of information extractors that can extract structured data from semi-structuredWe...

the mobility and bioavailability of trace elements in the agricultural soils are extremely important in assessing the risk of toxicity to the growing plants. a five step sequential extraction procedure (sep) has been employed to study the speciation of as, sb, cr, cu, cd, pb, zn, ni, fe and mn in 18 soil samples neighboring an industrial complex in isfahan, central iran. enrichment factor (ef) ...

Knowledge of the probable origin and behaviour of arsenic certainly gives valuable insights into the potential for transfer in the environment and of the risks involved in mining sites. Sequential extraction analyses are common experiments often used to study the origin and behaviour of potentially toxic elements. The method, however, presents some deficiencies, including labor-intensive proced...

The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a sequential combination of both. We show that applying ML methods with the support of a trivial grammar gives results better than a relatively complicated partial grammar, and much better than pure ML approach.

This paper introduces a novel technique for sequential blind extraction of singularly mixed sources. First, a neural-network model and an adaptive algorithm for single-source blind extraction are introduced. Next, extractability analysis is presented for singular mixing matrix, and two sets of necessary and sufficient extractability conditions are derived. The adaptive algorithm and neural-netw...