191,643 research outputs found

    Homogenous Ensemble Phonotactic Language Recognition Based on SVM Supervector Reconstruction

    Get PDF
    Currently, acoustic spoken language recognition (SLR) and phonotactic SLR systems are widely used language recognition systems. To achieve better performance, researchers combine multiple subsystems with the results often much better than a single SLR system. Phonotactic SLR subsystems may vary in the acoustic features vectors or include multiple language-specific phone recognizers and different acoustic models. These methods achieve good performance but usually compute at high computational cost. In this paper, a new diversification for phonotactic language recognition systems is proposed using vector space models by support vector machine (SVM) supervector reconstruction (SSR). In this architecture, the subsystems share the same feature extraction, decoding, and N-gram counting preprocessing steps, but model in a different vector space by using the SSR algorithm without significant additional computation. We term this a homogeneous ensemble phonotactic language recognition (HEPLR) system. The system integrates three different SVM supervector reconstruction algorithms, including relative SVM supervector reconstruction, functional SVM supervector reconstruction, and perturbing SVM supervector reconstruction. All of the algorithms are incorporated using a linear discriminant analysis-maximum mutual information (LDA-MMI) backend for improving language recognition evaluation (LRE) accuracy. Evaluated on the National Institute of Standards and Technology (NIST) LRE 2009 task, the proposed HEPLR system achieves better performance than a baseline phone recognition-vector space modeling (PR-VSM) system with minimal extra computational cost. The performance of the HEPLR system yields 1.39%, 3.63%, and 14.79% equal error rate (EER), representing 6.06%, 10.15%, and 10.53% relative improvements over the baseline system, respectively, for the 30-, 10-, and 3-s test conditions

    Numerical Study of the Magnetorotational Instability in Princeton MRI Experiment

    Full text link
    In preparation for an experimental study of magnetorotational instability (MRI) in liquid metal, we present non-ideal axisymmetric magnetohydrodynamic simulations of the nonlinear evolution of MRI in the experimental geometry. The simulations adopt fully insulating boundary conditions. No-slip conditions are imposed at the cylinders. A clear linear phase is observed with reduced linear growth rate. MRI results in an inflowing "jet" near the midplane and enhances the angular momentum transport at saturation.Comment: 22 pages, 12 figures, ApJ 684, 515 (2008). Minor changes according to referee's repor

    Ultra-directional super-scattering of homogenous spherical particles with radial anisotropy

    Full text link
    We study the light scattering of homogenous radially-anisotropic spherical particles. It is shown that radial anisotropy can be employed to tune effectively the electric resonances, and thus enable flexible overlapping of electric and magnetic dipoles of various numbers, which leads to unidirectional forward super-scattering at different spectral positions. We further reveal that through adjusting the radial anisotropy parameters, electric and magnetic resonances of higher orders can be also made overlapped, thus further collimating the forward scattering lobes. The ultra-directional super-scattering we have obtained with individual homogenous radially anisotropic spherical particles may shed new light to the design of compact and efficient nanoantennas, which may find various applications in solar cells, bio-sensing and many other antenna based researches.Comment: 10 pages, 3 figures, comments welcome

    Cloud Storage Performance and Security Analysis with Hadoop and GridFTP

    Get PDF
    Even though cloud server has been around for a few years, most of the web hosts today have not converted to cloud yet. If the purpose of the cloud server is distributing and storing files on the internet, FTP servers were much earlier than the cloud. FTP server is sufficient to distribute content on the internet. Therefore, is it worth to shift from FTP server to cloud server? The cloud storage provider declares high durability and availability for their users, and the ability to scale up for more storage space easily could save users tons of money. However, does it provide higher performance and better security features? Hadoop is a very popular platform for cloud computing. It is free software under Apache License. It is written in Java and supports large data processing in a distributed environment. Characteristics of Hadoop include partitioning of data, computing across thousands of hosts, and executing application computations in parallel. Hadoop Distributed File System allows rapid data transfer up to thousands of terabytes, and is capable of operating even in the case of node failure. GridFTP supports high-speed data transfer for wide-area networks. It is based on the FTP and features multiple data channels for parallel transfers. This report describes the technology behind HDFS and enhancement to the Hadoop security features with Kerberos. Based on data transfer performance and security features of HDFS and GridFTP server, we can decide if we should replace GridFTP server with HDFS. According to our experiment result, we conclude that GridFTP server provides better throughput than HDFS, and Kerberos has minimal impact to HDFS performance. We proposed a solution which users authenticate with HDFS first, and get the file from HDFS server to the client using GridFTP
    • …