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

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

Waveform-Controlled Terahertz Radiation from the Air Filament Produced by Few-Cycle Laser Pulses

Waveform-controlled Terahertz (THz) radiation is of great importance due to its potential application in THz sensing and coherent control of quantum systems. We demonstrated a novel scheme to generate waveform-controlled THz radiation from air plasma produced when carrier-envelope-phase (CEP) stabilized few-cycle laser pulses undergo filamentation in ambient air. We launched CEP-stabilized 10 fs-long (~ 1.7 optical cycles) laser pulses at 1.8 {\mu}m into air and found that the generated THz waveform can be controlled by varying the filament length and the CEP of driving laser pulses. Calculations using the photocurrent model and including the propagation effects well reproduce the experimental results, and the origins of various phase shifts in the filament are elucidated.Comment: 5pages, 5 figure

A novel testing model for opportunistic screening of pre-diabetes and diabetes among U.S. adults.

ObjectiveThe study aim was to evaluate the performance of a novel simultaneous testing model, based on the Finnish Diabetes Risk Score (FINDRISC) and HbA1c, in detecting undiagnosed diabetes and pre-diabetes in Americans.Research design and methodsThis cross-sectional analysis included 3,886 men and women (≥ 20 years) without known diabetes from the U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2010. The FINDRISC was developed based on eight variables (age, BMI, waist circumference, use of antihypertensive drug, history of high blood glucose, family history of diabetes, daily physical activity and fruit & vegetable intake). The sensitivity, specificity, and the receiver operating characteristic (ROC) curve of the testing model were calculated for undiagnosed diabetes and pre-diabetes, determined by oral glucose tolerance test (OGTT).ResultsThe prevalence of undiagnosed diabetes was 7.0% and 43.1% for pre-diabetes (27.7% for isolated impaired fasting glucose (IFG), 5.1% for impaired glucose tolerance (IGT), and 10.3% for having both IFG and IGT). The sensitivity and specificity of using the HbA1c alone was 24.2% and 99.6% for diabetes (cutoff of ≥6.5%), and 35.2% and 86.4% for pre-diabetes (cutoff of ≥5.7%). The sensitivity and specificity of using the FINDRISC alone (cutoff of ≥9) was 79.1% and 48.6% for diabetes and 60.2% and 61.4% for pre-diabetes. Using the simultaneous testing model with a combination of FINDRISC and HbA1c improved the sensitivity to 84.2% for diabetes and 74.2% for pre-diabetes. The specificity for the simultaneous testing model was 48.4% of diabetes and 53.0% for pre-diabetes.ConclusionsThis simultaneous testing model is a practical and valid tool in diabetes screening in the general U.S. population

Racial/Ethnic Disparities in Health-Related Quality of Life among Participants with Self-Reported Diabetes from NHANES 2001-2010.

PurposeThe purpose of this study is to investigate the racial/ethnic disparities in health-related quality of life (HRQOL) among adults with self-reported diabetes and identify the different risk factors related to HRQOL for specific racial/ethnic groups in the United States.MethodsNational Health and Nutrition Examination Survey (NHANES) 2001-2010 participants (ages 20 years and older) who were self-identified as non-Hispanic white, non-Hispanic black, or Hispanic and with self-reported diabetes were included in the analysis (n = 2594). The Centers for Disease Control and Prevention's HRQOL-4 was used to assess factors associated with HRQOL through multivariate logistic regression models with survey weighting. Stepwise model selection was applied to select the most significant factors for HRQOL in each racial/ethnic group.ResultsHispanic participants were less likely to report 14 or more mentally unhealthy days and activity-limited days compared to non-Hispanic white counterparts, adjusting for age, sex, education, marital status, family poverty-income ratio (PIR), body mass index, smoking status, insurance coverage, and diabetes duration. Current smoking status and obesity were significantly associated with worse HRQOL among whites and blacks. Marital status predicted better HRQOL only among Hispanics. Having insurance coverage predicted better HRQOL among both blacks and Hispanics. Increased family PIR had a favorable association with the 4 HRQOL domains consistently among all races/ethnicities.ConclusionMinimal racial/ethnic disparities in HRQOL were observed among US adults with self-reported diabetes. Support is offered for more individualized health care and communication with patients to target care and interventions that improve health and quality-of-life indicators