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127 results on '"Jung, Jinman"'

1. The 2022 FASEB Virtual Catalyst Conference on the Cardiac Interatrial Septum and Stroke Risk, December 7, 2022

Author

Schilling, Jonathan, Lin, Jeannette P, Mankad, Sunil V, Krishnam, Mayil S, Ning, MingMing, Patel, Pranav M, Kim, Chi Kyung, Kapoor, Ruchi, Di Tullio, Marco R, Jung, Jinman, Kim, Jin Kyung, and Fisher, Mark J

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Heart Disease, Cardiovascular, Biomedical Imaging, Stroke, Brain Disorders, Good Health and Well Being, Humans, Heart Septal Defects, Atrial, Cardiology, Catalysis, Echocardiography, Embryonic Development, interatrial septum, left atrial septal pouch, patent foramen ovale, stroke, transesophageal echocardiography, transthoracic echocardiography, Biochemistry and Cell Biology, Physiology, Medical Physiology, Biochemistry & Molecular Biology, Biochemistry and cell biology, Medical physiology
Abstract

There is emerging evidence that the cardiac interatrial septum has an important role as a thromboembolic source for ischemic strokes. There is little consensus on treatment of patients with different cardiac interatrial morphologies or pathologies who have had stroke. In this paper, we summarize the important background, diagnostic, and treatment considerations for this patient population as presented during the Federation of American Societies for Experimental Biology (FASEB) Virtual Catalytic Conference on the Cardiac Interatrial Septum and Stroke Risk, held on December 7, 2022. During this conference, many aspects of the cardiac interatrial septum were discussed. Among these were the embryogenesis of the interatrial septum and development of anatomic variants such as patent foramen ovale and left atrial septal pouch. Also addressed were various mechanisms of injury such as shunting physiologies and the consequences that can result from anatomic variants, as well as imaging considerations in echocardiography, computed tomography, and magnetic resonance imaging. Treatment options including anticoagulation and closure were addressed, as well as an in-depth discussion on whether the left atrial septal pouch is a stroke risk factor. These issues were discussed and debated by multiple experts from neurology, cardiology, and radiology.

Published
2023

5. Detection of GUI Elements on Sketch Images Using Object Detector Based on Deep Neural Networks

Author

Yun, Young-Sun, Jung, Jinman, Eun, Seongbae, So, Sun-Sup, Heo, Junyoung, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Hwang, Seong Oun, editor, Tan, Syh Yuan, editor, and Bien, Franklin, editor

Published
2019
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49. Key node selection based on a genetic algorithm for fast patching in social networks.

Author

Kim, Bongjae, Jung, Jinman, Heo, Junyoung, and Min, Hong

Subjects
SOCIAL networks, ONLINE social networks, POWER (Social sciences), POINT processes, INFORMATION sharing
Abstract

Summary: Online social network users provide considerable amounts of personal information and share this information with friends without space‐time limitations. The tight connectivity among users of social networks causes the rapid spreading of information. Given the popularity of social networking sites, there is a high probability of attacks. Worms target popular users with interesting information to infect them, as their higher reputations have more power in social networks. Therefore, timely patch propagation schemes must be able to inhibit the activity of worms. To improve the patch propagation speed, it is important to select key nodes that are the starting points of the patch process. In this paper, we proposed a key node selection scheme based on a genetic algorithm to find the most significant contribution nodes of patch propagation. We modeled the usage patterns of an online social network user and simulated the proposed scheme with data from this user. Simulation results show that the proposed scheme propagates patches more rapidly than existing schemes. [ABSTRACT FROM AUTHOR]

Published
2021
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