Image classification by visual bag-of-words refinement and reduction

This paper presents a new framework for visual bag-of-words (BOW) refinement and reduction to overcome the drawbacks associated with the visual BOW model which has been widely used for image classification. Although very influential in the literature, the traditional visual BOW model has two distinct drawbacks. Firstly, for efficiency purposes, the visual vocabulary is commonly constructed by directly clustering the low-level visual feature vectors extracted from local keypoints, without considering the high-level semantics of images. That is, the visual BOW model still suffers from the semantic gap, and thus may lead to significant performance degradation in more challenging tasks (e.g. social image classification). Secondly, typically thousands of visual words are generated to obtain better performance on a relatively large image dataset. Due to such large vocabulary size, the subsequent image classification may take sheer amount of time. To overcome the first drawback, we develop a graph-based method for visual BOW refinement by exploiting the tags (easy to access although noisy) of social images. More notably, for efficient image classification, we further reduce the refined visual BOW model to a much smaller size through semantic spectral clustering. Extensive experimental results show the promising performance of the proposed framework for visual BOW refinement and reduction

AN ASSESSMENT OF THE EFFICACY AND COST OF ALTERNATIVE CARBON MITIGATION POLICIES FOR THE STATE OF INDIANA

A nation-wide climate policy targeting the power sector might lead to dramatic changes to Indiana\u27s electricity generation system. This is because Indiana relies heavily on coal as its primary source for electricity generation and coal is much more carbon-intensive than other fossil fuels. In the possible event that Indiana will have to take action on carbon mitigation, for example because of a national climate policy in the future, it is important for state policymakers to understand the costs and efficacy of alternative strategies. In addition, assessing the impacts of the policy alternatives on Indiana serves as guidance for the national policy design process regarding the subnational impacts

Sub-Ohmic spin-boson model with off-diagonal coupling: Ground state properties

We have carried out analytical and numerical studies of the spin-boson model in the sub-ohmic regime with the influence of both the diagonal and off-diagonal coupling accounted for via the Davydov D1 variational ansatz. While a second-order phase transition is known to be exhibited by this model in the presence of diagonal coupling only, we demonstrate the emergence of a discontinuous first order phase transition upon incorporation of the off-diagonal coupling. A plot of the ground state energy versus magnetization highlights the discontinuous nature of the transition between the isotropic (zero magnetization) state and nematic (finite magnetization) phases. We have also calculated the entanglement entropy and a discontinuity found at a critical coupling strength further supports the discontinuous crossover in the spin-boson model in the presence of off-diagonal coupling. It is further revealed via a canonical transformation approach that for the special case of identical exponents for the spectral densities of the diagonal and the off-diagonal coupling, there exists a continuous crossover from a single localized phase to doubly degenerate localized phase with differing magnetizations.Comment: 11 pages, 7 figure

A highly accurate perfectly-matched-layer boundary integral equation solver for acoustic layered-medium problems

Based on the perfectly matched layer (PML) technique, this paper develops a high-accuracy boundary integral equation (BIE) solver for acoustic scattering problems in locally defected layered media in both two and three dimensions. The original scattering problem is truncated onto a bounded domain by the PML. Assuming the vanishing of the scattered field on the PML boundary, we derive BIEs on local defects only in terms of using PML-transformed free-space Green's function, and the four standard integral operators: single-layer, double-layer, transpose of double-layer, and hyper-singular boundary integral operators. The hyper-singular integral operator is transformed into a combination of weakly-singular integral operators and tangential derivatives. We develop a high-order Chebyshev-based rectangular-polar singular-integration solver to discretize all weakly-singular integrals. Numerical experiments for both two- and three-dimensional problems are carried out to demonstrate the accuracy and efficiency of the proposed solver.Comment: 19 pages, 16 figure

An Experimental Study on the Burning Behavior of Fabric used Indoor

AbstractFabrics used indoor has a major impact on the development and spread of indoor fires and fire hazards because of its easy ignition, fast burning speed and the rapid spread rate. In this paper, the burning behavior of five kinds of fabrics used indoor such as cotton woven, jeans, woollen sweater, linen rope and sponge, were studied by means of the cone calorimeter. The ignition time, the heat release rate, the mass loss rate, the yield of CO and the smoke production rate of the five kinds of fabrics used indoor were analyzed and compared at different external heat flux conditions with the specific experimental data and image. Our results indicated that: with the increase of the heat flux, five kinds of fabrics were more and more to be ignited; in higher heat flux condition, average heat release rate and the peak mass loss rate were higher; In lower heat flux condition, due to the incomplete combustion, smoke production rate and the yield of CO were higher; and the effect of the density of the structure and moisture content to burning behavior of fabrics can’t be ignored. Fire risk order of five kinds of fabrics is: woollen fabrics> sponge fabrics> cotton fabrics> linen fabrics