Deep neural networks for driver identification using accelerometer signals from smartphones

With the evolution of the onboard communications services and the applications of ride-sharing, there is a growing need to identify the driver. This identification, within a given driver set, helps in tasks of antitheft, autonomous driving,fleet management systems or automobile insurance. The object of this paper is to identify a driver in the least invasive way possible, using the smartphone that the driver carries inside the vehicle in a free position, and using the minimum number of sensors, only with the tri-axial accelerometer signals from the smartphone. For this purpose, different Deep Neural Networks have been tested, such as the ResNet-50 model and Recurrent Neural Networks. For the training, temporal signals of the accelerometers have been transformed asimages. The accuracies obtained have been 69.92% and 90.31% at top-1 andtop-5 driver level respectively, for a group of 25 drivers. These results outper-form works in the state of the art, which can even utilize more signals (likeGPS- Global Positioning System- measurement data) or extra-equipment (like the Controller Area-Network of the vehicle)

Survey of type 6 group variants of hepatitis C virus in Southeast Asia by using a core-based genotyping assay

Previous surveys of the prevalences of genotypes of hepatitis C virus (HCV) in different populations have often used genotyping assays based upon analysis of amplified sequences from the 5' noncoding region (5'NCR), such as restriction fragment length polymorphism (RFLP) or hybridization with type- specific probes (e.g., InnoLipa). Although highly conserved, this region contains several type-specific nucleotide polymorphisms that allow major genotypes 1 to 6 to be reliably identified. Recently, however, novel HCV variants found in Vietnam and Thailand that are distantly related to the type 6a genotype (type 6 group) by phylogenetic analysis of coding regions of the genome often have sequences in the 5'NCR that are similar or identical to those of type 1 and could therefore not be identified by any assay of sequences in this region. We developed a new genotyping assay based upon RFLP of sequences amplified from the more variable core region to investigate their distribution elsewhere in southeast (SE) Asia. Among 108 samples from blood donors in seven areas that were identified as type 1 by RFLP in the 5'NCR, type 6 group variants were found in Thailand (7 from 28 samples originally identified as type 1) and Burma (Myanmar) (1 of 3) but were not found in Hong Kong (n = 43), Macau (n = 8), Taiwan (n = 6), Singapore (n = 2), or Malaysia (n = 18). Although this small survey suggests a relatively limited distribution for type 6 group variants in SE Asia, larger studies will be required to explore their distribution in other geographical regions and the extent to which their presence would limit the practical usefulness of 5'NCR-based genotyping assays for clinical or epidemiological purposes.link_to_subscribed_fulltex