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Jung Woo Lee

Publications and source records attributed to Jung Woo Lee.

3 recordsLinked to original sources

Experimental and theoretical studies of hyperfine structures in $^{21}$Na

We measured the hyperfine structure constants, $A(3s^2S_{1/2})$ and $A(3p^2P_{1/2})$, of the neutron-deficient isotope $^{21}\text{Na}$ using CLaSsy, a setup dedicated to collinear laser spectroscopy at RAON. The hyperfine structure constants of $^{21}\text{Na}$ were measured to be $103.6(10)_{\mathrm{stat}}(9)_{\mathrm{syst}}$ MHz for $A(3p^2P_{1/2})$ and $954.9(11)_{\mathrm{stat}}(25)_{\mathrm{syst}}$ MHz for $A(3s^2S_{1/2})$. A systematic comparison with the state-of-the-art ab-initio relativistic coupled cluster calculations shows the role of higher-order correlation effects such as triple excitations in $^{21}$Na. Furthermore, the measurement demonstrates a capability of the CLaSsy setup to conduct collinear laser spectroscopy experiments with a radioactive beam.

physics.atom-ph↗

Improving Diagnostic Accuracy for Oral Cancer with inpainting Synthesis Lesions Generated Using Diffusion Models

In oral cancer diagnostics, the limited availability of annotated datasets frequently constrains the performance of diagnostic models, particularly due to the variability and insufficiency of training data. To address these challenges, this study proposed a novel approach to enhance diagnostic accuracy by synthesizing realistic oral cancer lesions using an inpainting technique with a fine-tuned diffusion model. We compiled a comprehensive dataset from multiple sources, featuring a variety of oral cancer images. Our method generated synthetic lesions that exhibit a high degree of visual fidelity to actual lesions, thereby significantly enhancing the performance of diagnostic algorithms. The results show that our classification model achieved a diagnostic accuracy of 0.97 in differentiating between cancerous and non-cancerous tissues, while our detection model accurately identified lesion locations with 0.85 accuracy. This method validates the potential for synthetic image generation in medical diagnostics and paves the way for further research into extending these methods to other types of cancer diagnostics.

cs.LG↗

A High-Resolution Human Contact Network for Infectious Disease Transmission

The most frequent infectious diseases in humans - and those with the highest potential for rapid pandemic spread - are usually transmitted via droplets during close proximity interactions (CPIs). Despite the importance of this transmission route, very little is known about the dynamic patterns of CPIs. Using wireless sensor network technology, we obtained high-resolution data of CPIs during a typical day at an American high school, permitting the reconstruction of the social network relevant for infectious disease transmission. At a 94% coverage, we collected 762,868 CPIs at a maximal distance of 3 meters among 788 individuals. The data revealed a high density network with typical small world properties and a relatively homogenous distribution of both interaction time and interaction partners among subjects. Computer simulations of the spread of an influenza-like disease on the weighted contact graph are in good agreement with absentee data during the most recent influenza season. Analysis of targeted immunization strategies suggested that contact network data are required to design strategies that are significantly more effective than random immunization. Immunization strategies based on contact network data were most effective at high vaccination coverage.

physics.med-ph↗