1,238 research outputs found
Content-Aware Quantization Index Modulation:Leveraging Data Statistics for Enhanced Image Watermarking
Image watermarking techniques have continuously evolved to address new
challenges and incorporate advanced features. The advent of data-driven
approaches has enabled the processing and analysis of large volumes of data,
extracting valuable insights and patterns. In this paper, we propose two
content-aware quantization index modulation (QIM) algorithms: Content-Aware QIM
(CA-QIM) and Content-Aware Minimum Distortion QIM (CAMD-QIM). These algorithms
aim to improve the embedding distortion of QIM-based watermarking schemes by
considering the statistics of the cover signal vectors and messages. CA-QIM
introduces a canonical labeling approach, where the closest coset to each cover
vector is determined during the embedding process. An adjacency matrix is
constructed to capture the relationships between the cover vectors and
messages. CAMD-QIM extends the concept of minimum distortion (MD) principle to
content-aware QIM. Instead of quantizing the carriers to lattice points,
CAMD-QIM quantizes them to close points in the correct decoding region.
Canonical labeling is also employed in CAMD-QIM to enhance its performance.
Simulation results demonstrate the effectiveness of CA-QIM and CAMD-QIM in
reducing embedding distortion compared to traditional QIM. The combination of
canonical labeling and the minimum distortion principle proves to be powerful,
minimizing the need for changes to most cover vectors/carriers. These
content-aware QIM algorithms provide improved performance and robustness for
watermarking applications.Comment: 12 pages, 10 figure
Urban-Rural Differences in the Associations of Risk Factors With Epilepsy Based on the California Health Interview Survey: A Multiple Logistic Regression Analysis
Background: Previous studies provided inconsistent associations of smoking, stroke, and serious psychological distress (SPD) with epilepsy while urban-rural differences in the associations of risk factors with epilepsy are not well documented.
Objectives: This study aimed to evaluate the associations of lifestyle, health conditions, and SPD with epilepsy and to examine whether the associations differ between urban and rural areas.
Patients and Methods: A total of 604 adults with epilepsy and 42416 controls were selected from the 2005 California Health Interview Survey. Weighted univariate and multiple logistic regression analyses were used to estimate the associations of potential factors (behavioral factors, SPD, social factors and health conditions) with epilepsy. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated.
Results: The overall prevalence of epilepsy was 1.3% and the prevalence was higher in urban area than rural area (1.4 vs. 1.1%). The prevalence of SPD was 11% in cases and 4% in controls, respectively. The percentage of stroke was higher in cases than in controls (9% vs. 2%). After adjusting for other factors using multiple logistic regression, current smoking, stroke, cancer, SPD and living in urban were positively significantly associated with epilepsy (OR = 1.74, 95% CI = 1.28 - 2.38; OR = 4.81, 95% CI = 3.13 - 7.41; OR = 1.52, 95% CI = 1.12 - 2.06; OR = 2.02, 95% CI = 1.39 - 2.92, and OR = 1.4, 95% CI = 1.08 - 1.81, respectively); while binge drinking was negatively associated with epilepsy (OR = 0.65, 95% CI = 0.43 - 0.99). Stratified by residence, in the urban area, current smoking and race were only associated with epilepsy. Stroke and SPD showed stronger association with epilepsy in the rural area (OR = 7.63, 95% CI = 3.68 - 15.8, and OR = 3.14, 95% CI = 1.52 - 6.47, respectively) comparing with urban region (OR = 4.51, 95% CI = 2.79 - 7.28 and OR = 1.9, 95% CI = 1.27 - 2.86, respectively)
Urban-Rural Differences in the Associations of Risk Factors With Epilepsy Based on the California Health Interview Survey: A Multiple Logistic Regression Analysis
Background: Previous studies provided inconsistent associations of smoking, stroke, and serious psychological distress (SPD) with epilepsy while urban-rural differences in the associations of risk factors with epilepsy are not well documented. Objectives: This study aimed to evaluate the associations of lifestyle, health conditions, and SPD with epilepsy and to examine whether the associations differ between urban and rural areas. Patients and Methods: A total of 604 adults with epilepsy and 42416 controls were selected from the 2005 California Health Interview Survey. Weighted univariate and multiple logistic regression analyses were used to estimate the associations of potential factors (behavioral factors, SPD, social factors and health conditions) with epilepsy. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. Results: The overall prevalence of epilepsy was 1.3% and the prevalence was higher in urban area than rural area (1.4 vs. 1.1%). The prevalence of SPD was 11% in cases and 4% in controls, respectively. The percentage of stroke was higher in cases than in controls (9% vs. 2%). After adjusting for other factors using multiple logistic regression, current smoking, stroke, cancer, SPD and living in urban were positively significantly associated with epilepsy (OR = 1.74, 95% CI = 1.28 - 2.38; OR = 4.81, 95% CI = 3.13 - 7.41; OR = 1.52, 95% CI = 1.12 - 2.06; OR = 2.02, 95% CI = 1.39 - 2.92, and OR = 1.4, 95% CI = 1.08 - 1.81, respectively); while binge drinking was negatively associated with epilepsy (OR = 0.65, 95% CI = 0.43 - 0.99). Stratified by residence, in the urban area, current smoking and race were only associated with epilepsy. Stroke and SPD showed stronger association with epilepsy in the rural area (OR = 7.63, 95% CI = 3.68 - 15.8, and OR = 3.14, 95% CI = 1.52 - 6.47, respectively) comparing with urban region (OR = 4.51, 95% CI = 2.79 - 7.28 and OR = 1.9, 95% CI = 1.27 - 2.86, respectively). Conclusions: Smoking, stroke, and SPD were associated with epilepsy; while the associations differed between urban and rural areas
Galactic Disk Bulk Motions as Revealed by the LSS-GAC DR2
We report a detailed investigation of the bulk motions of the nearby Galactic
stellar disk, based on three samples selected from the LSS-GAC DR2: a global
sample containing 0.57 million FGK dwarfs out to 2 kpc, a local subset
of the global sample consisting 5,400 stars within 150 pc, and an
anti-center sample containing 4,400 AFGK dwarfs and red clump stars
within windows of a few degree wide centered on the Galactic anti-center. The
global sample is used to construct a three-dimensional map of bulk motions of
the Galactic disk from the solar vicinity out to 2 kpc with a spatial
resolution of 250 pc. Typical values of the radial and vertical
components of bulk motion range from 15 km s to 15 km s, while
the lag behind the circular speed dominates the azimuthal component by up to
15 km s. The map reveals spatially coherent, kpc-scale stellar
flows in the disk, with typical velocities of a few tens km s. Bending-
and breathing-mode perturbations are clearly visible, and vary smoothly across
the disk plane. Our data also reveal higher-order perturbations, such as breaks
and ripples, in the profiles of vertical motion versus height. From the local
sample, we find that stars of different populations exhibit very different
patterns of bulk motion. Finally, the anti-center sample reveals a number of
peaks in stellar number density in the line-of-sight velocity versus distance
distribution, with the nearer ones apparently related to the known moving
groups. The "velocity bifurcation" reported by Liu et al. (2012) at
Galactocentric radii 10--11 kpc is confirmed. However, just beyond this
distance, our data also reveal a new triple-peaked structure.Comment: 27 pages, 17 figures, Accepted for publication in a special issue of
Research in Astronomy and Astrophysics on LAMOST science
A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III
We established a method on measuring the \dzdzb mixing parameter for
BESIII experiment at the BEPCII collider. In this method, the doubly
tagged events, with one decays to
CP-eigenstates and the other decays semileptonically, are used to
reconstruct the signals. Since this analysis requires good separation,
a likelihood approach, which combines the , time of flight and the
electromagnetic shower detectors information, is used for particle
identification. We estimate the sensitivity of the measurement of to be
0.007 based on a fully simulated MC sample.Comment: 6 pages, 7 figure
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