Recent developments in spoken term detection: a survey

Spoken term detection (STD) provides an efficient means for content based indexing of speech. However, achieving high detection performance, faster speed, detecting ot-of-vocabulary (OOV) words and performing STD on low resource languages are some of the major research challenges. The paper provides a comprehensive survey of the important approaches in the area of STD and their addressing of the challenges mentioned above. The review provides a classification of these approaches, highlights their advantages and limitations and discusses their context of usage. It also performs an analysis of the various approaches in terms of detection accuracy, storage requirements and execution time. The paper summarizes various tools and speech corpora used in the different approaches. Finally it concludes with future research directions in this area.     

A MULTIGRID-ACCELERATED THREE-DIMENSIONAL TRANSIENT-FLOW CODE AND ITS APPLICATION TO A NEW TEST PROBLEM

A multigrid-assisted solver for the three-dimensional time-dependent incompressible Navier-Stokes equations on graded Cartesian meshes is developed. The spatial accuracy is third-order for the convective terms and fourth-order for the viscous terms, and a fractional-step strategy ensures second-order time accuracy. To achieve good time-wise efficiency a multigrid technique is used to solve the highly time-consuming pressure-Poisson equation that requires to be solved at every time step. The speed-up achieved by multigrid is shown in tabular form. The performance and accuracy of the code are first ascertained by computing the flow in a single-sided lid-driven cubic cavity with good grid-economy and comparing the results available in the literature. The code, thus validated, is then applied to a new test problem we propose and various transient and asymptotically obtained steady-state results are presented. Given the care taken to establish the credibility of the code and the good spatio-temporal accuracy of the discretization, these results are accurate and may be used for ascertaining the performance of any computational algorithm applied to this test problem.     

An efficient FE model and Least Square Error method for accurate calculation of transverse shear stresses in composites and sandwich laminates

Accurate evaluation of transverse stresses in laminated composites and sandwich plates using 2D FE models involves cumbersome post-processing techniques. In this paper a simple and efficient method has been proposed for accurate evaluation of through-the-thickness distribution of transverse stresses in composites and sandwich laminates by using a displacement based C⁰ FE model (2D) derived from Refined Higher Order Shear Deformation Theory (RHSDT) and a Least Square Error (LSE) method. The C⁰ FE model satisfies the inter-laminar shear stress continuity conditions at the layer interfaces and zero transverse shear stress conditions at the top and bottom of the plate. In this model the first derivatives of transverse displacement have been treated as independent variables to circumvent the problem of C¹ continuity associated with the above plate theory (RHSDT). The LSE method is applied to the 3D equilibrium equations of the plate problem at the post-processing stage, after in-plane stresses are calculated by using the above FE model based on RHSDT. Thus the proposed method is quite simple and elegant compared to the usual method of integrating the 3D equilibrium equations at the post-processing stage for calculation of transverse stresses in a composite laminate. In the proposed method, the first two equations of equilibrium are utilized to compute the transverse shear stress variation through the thickness of a laminated plate whereas the third equation of equilibrium gives the normal stress variation. Accuracy of the proposed method is demonstrated in the numerical examples through comparison of the present results with those obtained from different models based on higher order shear deformation theory (HSDT) and 3D elasticity solutions.     

Computational Models for Turbulent Thermal Plumes: Recent Advances and Challenges

Thermal plumes have been the subject of research due to their technological and environmental importance in many physical processes, such as spread of smoke and toxic gases from fires, and release of gases from volcanic eruptions and industrial stacks. In this paper, history and current trends in the computation of turbulent buoyant plume have been reviewed. First an introduction to the turbulent buoyant plume is presented, which includes its importance, the flow physics, and heat transfer characteristics. Subsequently, a brief review of the experimental works reported in the literature is presented, followed by a review of the computational methods. Several subgrid-scale models used in large eddy simulation performed in the literature to simulate buoyant plume are discussed. Further, the boundary conditions, computational schemes, and computational grid sizes are discussed. The efficacy of various Reynolds-averaged Navier–Stokes (RANS)-based modeling techniques to simulate turbulent buoyant plumes has been reviewed. It has been concluded that the dynamic subgrid-scale models perform fairly well in predicting the statistics of turbulent buoyant plume. However, no subgrid-scale model has been able to capture the inverse energy cascade, called backscatter, which is an important phenomenon in the evolution of a plume. In case of RANS modeling of plumes, models based on the generalized gradient diffusion hypothesis capture the flow accurately as compared with the models based on the simple gradient diffusion hypothesis.     

Recent Trends in Computation of Turbulent Jet Impingement Heat Transfer

A review of the current status of computation of turbulent impinging jet heat transfer is presented. It starts with a brief introduction to flow and heat transfer characteristics of jet impinging flows considering the simplest jet impinging geometry: normal impingement of a single jet into a flat surface. Subsequently, a review of recent computational studies related to the same geometry is presented. The effects of different subgrid scale models, boundary conditions, numerical schemes, grid distribution, and size of the computational domain adopted in various large eddy simulations of this flow configuration are reviewed in detail. A review of direct numerical simulation of the same geometry is also presented. Further, some recent attempts in Reynolds-averaged Navier–Stokes modeling of impinging flows are also reviewed. A review of computation of other complex impinging flows is also presented. The review concludes with a listing of some important findings and future directions in the computation of impinging flows.     

Genotype and growing environment influence chickpea (Cicer arietinum L.) seed composition

BACKGROUND: As a first step towards genetic improvement of seed quality in chickpea (Cicer arietinum L.), seven desi and nine kabuli varieties were grown at multiple sites to assess the affect of environment on seed yield, weight and selected seed constituents. The sites were chosen to represent a range of environments in chickpea production areas of the Canadian prairies. RESULTS: Genotype × environment interaction effects on starch, amylose and protein (desi only) concentrations and seed yield were significant, suggesting that the varieties did not perform consistently relative to each other in the different environments. Starch concentration was negatively correlated (r_kabuli = ?0.25, P < 0.05; r_desi = ?0.16, P < 0.05) with protein concentration in both chickpea market classes. However, repeatability estimates of starch, amylose and protein concentrations were low and inconsistent across chickpea market classes, possibly owing to complex biosynthetic pathways for these constituents. CONCLUSION: The results suggest that testing for seed constituent traits over a range of environments will be required to improve seed quality in individual chickpea varieties. The best selection strategies for seed constituent improvement in chickpea will be influenced by genotype and genotype × environment interaction for these traits. The negative relationship between seed constituents and yield indicates that selection for chickpea cultivars with desired seed composition may require compromise and indirect selection. Copyright © 2009 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.     

Role of graphene-based materials (GO) in improving physicochemical properties of cementitious nano-composites: a review

Journal of Materials Science - This work deals with the review of graphene-based cementitious composites, which is primarily focused on the effect on microstructure, hydration mechanism, and...     

A novel automated magnetic resonance image segmentation approach based on elliptical gamma mixture model for breast lumps detection

This article introduces a novel semisupervised automated segmentation approach for breast magnetic resonance (MR) image on multicore CPU-GPU systems. The basic idea of the proposed method is clustering-based semisupervised classifier devised by elliptical gamma mixture model (EGMM). Parameters of EGMM are identified by the iterative log-expectation maximization (EM) algorithm. The suggested classifier labels the groups of voxels in an input image first and then classifies the image slices using the EGMM. Two different implementations of the proposed algorithm have been developed based on two different types of high-performance computing architectures such as graphics processing units (GPUs) and multicore processors. To realize the real-time segmentation performance of our algorithm with two distinctive architecture, we have tested a set of breast MR images collected from MedPix. Comparison between two architectures in terms of segmentation performance and computational cost is assessed by the analysis of simulation and experimental results.