Synthetic radar image recognition is an area of interest for military applications including automatic target recognition, air traffic control, and remote sensing. Here a dynamic range compression two-beam-coupling joint transform correlator for detecting synthetic aperture radar targets is utilized. The joint input image consists of a prepower-law, enhanced scattering center of the input image and a linearly synthesized power-law-enhanced scattering center template. Enhancing the scattering center of both the synthetic template and the input image furnishes the conditions for achieving dynamic range compression correlation in two-beam coupling. Dynamic range compression (a) enhances the signal-to-noise ratio, (b) enhances the high frequencies relative to low frequencies, and (c) converts the noise to high frequency components. This improves the correlation-peak intensity to the mean of the surrounding noise significantly. Dynamic range compression correlation has already been demonstrated to outperform many optimal correlation filters in detecting signals in severe noise environments. The performance is evaluated via established metrics such as peak-to-correlation energy, Horner efficiency, and correlation-peak intensity. The results showed significant improvement as the power increased.
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http://dx.doi.org/10.1364/ao.47.003072 | DOI Listing |
Langmuir
January 2025
Department of Chemistry, Indian Institute of Technology Patna, Patna 801103, Bihar, India.
Polyoxometalates (POMs) are composed of nanometric metal-oxide anions and have rich solution chemistry. In this class, Keggin POMs have been identified as the most influential inorganic additives for aqueous nonionic soft matter systems. POMs being at the borderline of classical ions and charged colloids possess fascinating solution properties; the present work aims to delve deeper into the interactions between nanoions and nonionic soft matters from a spectroscopic point of view.
View Article and Find Full Text PDFClin Orthop Relat Res
January 2025
Department of Orthopaedic Surgery, Mayo Clinic, Phoenix, AZ, USA.
Background: Resilience refers to the ability to adapt or recover from stress. There is increasing appreciation that it plays an important role in wholistic patient-centered care and may affect patient outcomes, including those of orthopaedic surgery. Despite being a focus of the current orthopaedic evidence, there is no strong understanding yet of whether resilience is a stable patient quality or a dynamic one that may be modified perioperatively to improve patient-reported outcome scores.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Department of Materials Science & Engineering, City University of Hong Kong, Kowloon, Hong Kong.
Despite numerous studies of water structures at the two-dimensional water-solid interfaces, much less is known about the phase behaviors of water at the one-dimensional (1D) liquid-solid interface. In this work, the 1D interfacial water phase behavior on the outer surface of carbon nanotube-like (CNT-like) models is studied by tuning the Lennard-Jones potential parameter ε of the surface atoms at various temperatures. Extensive molecular dynamics simulations show that ice nanotubes (INTs) can be spontaneously formed on CNT-like model surfaces without nanoconfinement.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States.
Colloidal crystals of micrometer-sized colloids create prismatic structural colors through the grating diffraction of visible light. Here, we develop design rules to engineer such structural color by specifically accounting for the effect of crystal defects. The local quality and grain size of the colloidal structure are varied by performing self-assembly in the presence of a direct current (DC) electric field.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States of America.
Determining COVID-19 vaccination strategies presents many challenges in light of limited vaccination capacity and the heterogeneity of affected communities. Who should be prioritized for early vaccination when different groups manifest different levels of risks and contact rates? Answering such questions often becomes computationally intractable given that network size can exceed millions. We obtain a framework to compute the optimal vaccination strategy within seconds to minutes from among all strategies, including highly dynamic ones that adjust vaccine allocation as often as required, and even with modest computation resources.
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