A support vector machine approach for truncated fingerprint image detection from sweeping fingerprint sensors.

A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at a non-linear speed. If the truncated fingerprint images were enrolled as reference targets and collected by any automated fingerprint identification system (AFIS), successful prediction rates for fingerprint matching applications would be decreased significantly. In this paper, a novel and effective methodology with low time computational complexity was developed for detecting truncated fingerprints in a real time manner. Several filtering rules were implemented to validate existences of truncated fingerprints. In addition, a machine learning method of supported vector machine (SVM), based on the principle of structural risk minimization, was applied to reject pseudo truncated fingerprints containing similar characteristics of truncated ones. The experimental result has shown that an accuracy rate of 90.7% was achieved by successfully identifying truncated fingerprint images from testing images before AFIS enrollment procedures. The proposed effective and efficient methodology can be extensively applied to all existing fingerprint matching systems as a preliminary quality control prior to construction of fingerprint templates.

A genome-wide association study on amyotrophic lateral sclerosis in the Taiwanese Han population.

Identification of mutations in patients with amyotrophic lateral sclerosis (ALS) in a genome-wide association study can reveal possible biomarkers of such a rapidly progressive and fatal neurodegenerative disease. It was observed that significant single nucleotide polymorphisms vary when the tested population changes from one ethnic group to another. To identify new loci associated with ALS susceptibility in the Taiwanese Han population, we performed a genome-wide association study on 94 patients with sporadic ALS and 376 matched controls. We uncovered two new susceptibility loci at 13q14.3 (rs2785946) and 11q25 (rs11224052). In addition, we analyzed the functions of all the associated genes among 54 significant single nucleotide polymorphisms using Gene Ontology annotations, and the results showed several statistically significant neural- and muscle-related Gene Ontology terms and the associated diseases.