Baseline solutions for the named entity recognition task in Russian language were published a few years ago. These solutions rely heavily on the addition data, like databases, and different kinds of preprocessing. Here we demonstrate that it is possible to reproduce the quality of existing database-based solution by character-aware neural net trained on corpus itself only.

This contribution proposes text for two Appendices of the API Baseline document 95-0008, covering aspects of the Data Plane layer. The text for the rst Appendix covers pragmatics of data source and destination. The text for the second Appendix describes the optional extension to the messaging receive primitive mentioned in Section 3.3.2.3 of 95-0008. Submitted as contribution 95-0473 to ATM For...

Most baseline errors of analog strong-motion data still exist in highresolution data. In this study, we identify the major baseline errors of digital strong-motion data and propose a three-step algorithm to correct these errors. The major baseline errors found in these digital data consist of constant drift in the acceleration, low-frequency instrument noise, low-frequency background noise, the...

Motivation: Baseline removal, as the first preprocessing step of SELDI data, critically influences subsequent analysis steps. Current baseline removal algorithms of SELDI data, which are based on mathematical morphology, result in biased signal estimates. Due to the parameterization of current algorithms for baseline removal, noise and spectral signal distributions bias the removal results, whi...

A common feature of many modern technologies used in proteomics--including nuclear magnetic resonance imaging and mass spectrometry--is the generation of large amounts of data for each subject in an experiment. Extracting the signal from the background noise, however, poses significant challenges. One important part of signal extraction is the correct identification of the baseline level of the...

The National Institute of Neurological and Communicative Disorders and Stroke initiated the Stroke Data Bank, which is a multicenter project to prospectively collect data on the clinical course and sequelae of stroke. Additional objectives were to provide information that would enable a standard diagnostic clinical evaluation, to identify prognostic factors, and to provide planning data for fut...

Objectives. To collect normative baseline data and identify any significant differences between hand and foot thermographic distribution patterns in a healthy adult population. Design. A single-centre, randomized, prospective study. Methods. Thermographic data was acquired using a FLIR camera for the data acquisition of both plantar and dorsal aspects of the feet, volar aspects of the hands, an...

Background There is no published study evaluating the performance of cumulative sum (CUSUM) algorithm on meningitis data with limited baseline period. This study aimed to evaluate the CUSUM performance in timely detection of 707 semi-synthetic outbreak days. Methods Simulated outbreaks were generated using syndromic data on fever and neurological symptoms from Mar 2010 to Mar 2013 in Hamadan ...

Most epidemiologic studies will encounter missing covariate data. Software packages typically used for analyzing data delete any cases with a missing covariate to perform a complete case analysis. The deletion of cases complicates variable selection when different variables are missing on different cases, reduces power, and creates the potential for bias in the resulting estimates. Recently, so...

BACKGROUND There is wide variation in the phenotypic expression of Parkinson's disease (PD), which is driven by both genetic and epidemiological influences. OBJECTIVES To define and explain variation in the clinical phenotype of PD, in relation to genotypic variation. METHODS Tracking Parkinson's is a multicentre prospective longitudinal epidemiologic and biomarker study of PD. Patients att...