Stochastic finite automata are useful for identifying substrings (chunks) within larger units of text. Relevant applications include tokenization, base-NP chunking, named entity recognition, and other information extraction tasks. For a given input string, a stochastic automaton represents a probability distribution over strings of labels encoding the location of chunks. For chunking and extrac...

background: the best management for an ovarian mass is provided by appropriate prediction of malignancy. the aim of our study is to construct and validate a new malignancy probability score based on four simple sonographic findings and age. methods: in a cross sectional study; histopathological files of 3303 ovarian mass patients and tertiary hospitals, have reviewed within 6 years (2000-2006)....

empirical studies show that there is stronger dependency between large losses than large profit in financial market, which undermine the performance of using symmetric distribution for modeling these asymmetric. that is why the assuming normal joint distribution of returns is not suitable because of considering the linier dependence, and can be lead to inappropriate estimate of var. copula theo...

the present study aim is to offer a systematic method of assessing the credit risk of banks and also to identify key indicators using decision making trial and evaluation laboratory (dematel) technique as well as using logit regression in order to predict the credit risk of listed banks. the population of the study consists of the legal clients of the bank (ansar bank, bank saderat iran, bank m...

background & objectives:airq software proved to be a valid and reliable tool to estimate the potential short term effects of air pollution. in this study the airq2.2.3 model was used to evaluate adverse health effects caused by nitrogen dioxide(no2) exposure in ahvaz during 2009. materials & methods:the airq,developed by the world health organization (who) to predict health endpoints a...

We present minimum Bayes-risk system combination, a method that integrates consensus decoding and system combination into a unified multi-system minimum Bayes-risk (MBR) technique. Unlike other MBR methods that re-rank translations of a single SMT system, MBR system combination uses the MBR decision rule and a linear combination of the component systems’ probability distributions to search for ...

shear modulus and damping ratio are important input parameters in dynamic analysis. a series of resonant column tests was carried out on pure clays and sand-clay mixtures prepared at different densities to investigate the effects of aggregate content, confining stress, void ratio and clay plasticity on the maximum shear modulus and minimum damping ratio. test results revealed an increase in the...