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19,879 results on '"Choi, In-Jin"'

221. Case Report and Literature Review of Occupational Transmission of Monkeypox Virus to Healthcare Workers, South Korea

Author

Choi, Yunsang, Jeon, Eun-bi, Kim, Taeyoung, Choi, Seong Jin, Moon, Song Mi, Song, Kyoung-Ho, Kim, Hong Bin, and Kim, Eu Suk

Subjects
Human monkeypox -- Diagnosis -- Care and treatment, Disease transmission -- Prevention, Medical personnel -- Health aspects, Smallpox vaccine -- Dosage and administration, Health
Abstract

In July 2022, the World Health Organization (WHO) declared the international mpox outbreak a global public health emergency (1). Mpox, caused by monkeypox virus, is transmitted through person-to-person contact, contaminated [...]

Published
2023
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229. FOLFIRINOX or Gemcitabine-based Chemotherapy for Borderline Resectable and Locally Advanced Pancreatic Cancer: A Multi-institutional, Patient-Level, Meta-analysis and Systematic Review

Author

Eshmuminov, Dilmurodjon, Aminjonov, Botirjon, Palm, Russell F., Malleo, Giuseppe, Schmocker, Ryan K., Abdallah, Raëf, Yoo, Changhoon, Shaib, Walid L., Schneider, Marcel André, Rangelova, Elena, Choi, Yoo Jin, Kim, Hongbeom, Rose, J. Bart, Patel, Sameer, Wilson, Gregory C., Maloney, Sarah, Timmermann, Lea, Sahora, Klaus, Rössler, Fabian, Lopez-Lopez, Víctor, Boyer, Emanuel, Maggino, Laura, Malinka, Thomas, Park, Jeong Youp, Katz, Matthew H. G., Prakash, Laura, Ahmad, Syed A., Helton, Scott, Jang, Jin-Young, Hoffe, Sarah E., Salvia, Roberto, Taieb, Julien, He, Jin, Clavien, Pierre-Alain, Held, Ulrike, and Lehmann, Kuno

Published
2023
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235. An isogeometric finite element formulation for geometrically exact Timoshenko beams with extensible directors

Author

Choi, Myung-Jin, Sauer, Roger A., and Klinkel, Sven

Subjects
Physics - Applied Physics, Computer Science - Computational Engineering, Finance, and Science
Abstract

An isogeometric finite element formulation for geometrically and materially nonlinear Timoshenko beams is presented, which incorporates in-plane deformation of the cross-section described by two extensible director vectors. Since those directors belong to the space ${\Bbb R}^3$, a configuration can be additively updated. The developed formulation allows direct application of nonlinear three-dimensional constitutive equations without zero stress conditions. Especially, the significance of considering correct surface loads rather than applying an equivalent load directly on the central axis is investigated. Incompatible linear in-plane strain components for the cross-section have been added to alleviate Poisson locking by using an enhanced assumed strain (EAS) method. In various numerical examples exhibiting large deformations, the accuracy and efficiency of the presented beam formulation is assessed in comparison to brick elements. We particularly use hyperelastic materials of the St. Venant-Kirchhoff and compressible Neo-Hookean types., Comment: 67 pages, 29 figures

Published
2020
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236. WaveNODE: A Continuous Normalizing Flow for Speech Synthesis

Author

Kim, Hyeongju, Lee, Hyeonseung, Kang, Woo Hyun, Cheon, Sung Jun, Choi, Byoung Jin, and Kim, Nam Soo

Subjects
Computer Science - Sound, Computer Science - Computation and Language, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In recent years, various flow-based generative models have been proposed to generate high-fidelity waveforms in real-time. However, these models require either a well-trained teacher network or a number of flow steps making them memory-inefficient. In this paper, we propose a novel generative model called WaveNODE which exploits a continuous normalizing flow for speech synthesis. Unlike the conventional models, WaveNODE places no constraint on the function used for flow operation, thus allowing the usage of more flexible and complex functions. Moreover, WaveNODE can be optimized to maximize the likelihood without requiring any teacher network or auxiliary loss terms. We experimentally show that WaveNODE achieves comparable performance with fewer parameters compared to the conventional flow-based vocoders., Comment: 8 pages, 4 figures, Second workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (ICML 2020)

Published
2020

237. Probabilistic Neural Network: Frequency and Moment Learnings

Author

Rim, Kyung Soo and Choi, U Jin

Subjects
Mathematics - Probability, Electrical Engineering and Systems Science - Signal Processing, 94A17
Abstract

We introduce probabilistic neural networks that describe unsupervised synchronous learning on an atomic Hardy space and space of bounded real analytic functions, respectively. For a stationary ergodic vector process, we prove that the probabilistic neural network yields a unique collection of neurons in global optimization without initialization and back-propagation. During learning, we show that all neurons communicate with each other, in the sense of linear combinations, until the learning is finished. Also, we give convergence results for the stability of neurons, estimation methods, and topological statistics to appreciate unsupervised estimation of a probabilistic neural network. As application, we attach numerical experiments on samples drawn by a standing wave., Comment: 18 pages, 30 figures

Published
2020

238. Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization

Author

Nguyen, Giang, Chen, Shuan, Do, Thao, Jun, Tae Joon, Choi, Ho-Jin, and Kim, Daeyoung

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Interpreting the behaviors of Deep Neural Networks (usually considered as a black box) is critical especially when they are now being widely adopted over diverse aspects of human life. Taking the advancements from Explainable Artificial Intelligent, this paper proposes a novel technique called Auto DeepVis to dissect catastrophic forgetting in continual learning. A new method to deal with catastrophic forgetting named critical freezing is also introduced upon investigating the dilemma by Auto DeepVis. Experiments on a captioning model meticulously present how catastrophic forgetting happens, particularly showing which components are forgetting or changing. The effectiveness of our technique is then assessed; and more precisely, critical freezing claims the best performance on both previous and coming tasks over baselines, proving the capability of the investigation. Our techniques could not only be supplementary to existing solutions for completely eradicating catastrophic forgetting for life-long learning but also explainable., Comment: 8 pages, 6 figures, 3 tables

Published
2020

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