Embedding Feature Selection for Large-scale Hierarchical Classification

Large-scale Hierarchical Classification (HC) involves datasets consisting of thousands of classes and millions of training instances with high-dimensional features posing several big data challenges. Feature selection that aims to select the subset of discriminant features is an effective strategy to deal with large-scale HC problem. It speeds up the training process, reduces the prediction time and minimizes the memory requirements by compressing the total size of learned model weight vectors. Majority of the studies have also shown feature selection to be competent and successful in improving the classification accuracy by removing irrelevant features. In this work, we investigate various filter-based feature selection methods for dimensionality reduction to solve the large-scale HC problem. Our experimental evaluation on text and image datasets with varying distribution of features, classes and instances shows upto 3x order of speed-up on massive datasets and upto 45% less memory requirements for storing the weight vectors of learned model without any significant loss (improvement for some datasets) in the classification accuracy. Source Code: https://cs.gmu.edu/~mlbio/featureselection.Comment: IEEE International Conference on Big Data (IEEE BigData 2016

Stress and failure analysis of 3D angle interlock woven composites

A three-dimensional woven composite strength model is presented for predicting the failure behavior of three-dimensional angle interlock woven composites under on-axis uniaxial static tensile loading and shear loading. The model is based on two-level discretization of the repeating unit cell. The repeating unit cell is discretized into sections, elements, subsections and subelements. The model predicts the stress levels at which the secondary Failures take place at subelement level. The effect of secondary failure is considered for further analysis and the ultimate tensile strength and shear strength and the corresponding strains are predicted. A parametric study has been carried out For different 3D angle interlock woven composite configurations

Stress and failure analysis of 3D orthogonal interlock woven composites

A three-dimensional woven composite strength model is presented for predicting the failure behavior of three-dimensional orthogonal interlock woven composites under on-axis uniaxial static tensile loading and shear loading. The model is based on two-level discretization of the repeating unit cell. The repeating unit cell is discretized into sections, elements, subsections and subelements. The model predicts the stress levels at which the secondary failures take place at subelement level. The effect of secondary failure is considered for further analysis and the ultimate tensile strength and shear strength and the corresponding strains are predicted. A parametric study has been carried out for different 3D orthogonal interlock woven composite configurations. In general, it is seen that there is no significant reduction in the inplane elastic and strength properties for 3D orthogonal woven composites, compared to the corresponding cross-ply laminates made of unidirectional layers, but there is a significant increase in the through-the-thickness properties

Interlaminar fracture characterization for plain weave fabric composites

For the analysis of laminated composite plates under transverse loading and drilling of composites, all the elastic, strength and fracture properties of the composite plates are essential. Interlaminar critical strain energy release rate properties in mode I, mode II, mixed mode I/II and mode III have been evaluated for two types of plain weave fabric E-glass/epoxy laminates. The double cantilever beam test and the end notch flexure test have been used for mode I and mode II loading. The mixed mode bending test and split cantilever beam test have been used for mixed mode I/II and mode III loading. It is observed that the plain weave fabric composite with lesser strand width has higher interlaminar fracture properties compared to the plain weave fabric composite with more strand width. Further, crack length versus crack growth resistance plots have been presented for mode III loading. In general, it is observed that total fracture resistance is significantly higher than the critical strain energy release rate. (C) 2002 Kluwer Academic Publishers

Prospects and technological advancement of cellulosic bioethanol ecofuel production

Energy security, rapid depletion of fossil fuels and the huge greenhouse gas emission from the utilization of fossil fuels are the growing concerns in today's world. Bioethanol is considered as one of the attractive ecofuel due to its environmental sustainability and renewability over fossil fuels. So far cellulosic ethanol (second generation) production has gained attention at commercial scale over the other feedstocks such as first, third and fourth generation as it has no impact on food security. Third and fourth generation bioethanol technologies are in the immature stage and need further research. In this study, an outline of the systematic development of bioethanol production has been presented. The advancements in bioethanol technology and the status of installed commercial/pilot/demonstration scale plants based on lignocellulosic feedstocks all over the world have been highlighted. Finally, we have tried to underline the issues and challenges associated with the commercial scale production of cellulosic ethanol