Search

Your search keyword '"Hwang, Seong Oun"' showing total 356 results
Start Over Author "Hwang, Seong Oun" Publication Year Range Last 10 years
356 results on '"Hwang, Seong Oun"'

3. Energy Efficient Cross Layer Time Synchronization in Cognitive Radio Networks

Author

Hashmi, S. M. Usman, Hussain, Muntazir, Arshad, S. M. Nashit, Inayat, Kashif, and Hwang, Seong Oun

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Time synchronization is a vital concern for any Cognitive Radio Network (CRN) to perform dynamic spectrum management. Each Cognitive Radio (CR) node has to be environment aware and self adaptive and must have the ability to switch between multiple modulation schemes and frequencies. Achieving same notion of time within these CR nodes is essential to fulfill the requirements for simultaneous quiet periods for spectrum sensing. Current application layer time synchronization protocols require multiple timestamp exchanges to estimate skew between the clocks of CRN nodes. The proposed symbol timing recovery method already estimates the skew of hardware clock at the physical layer and use it for skew correction of application layer clock of each node. The heart of application layer clock is the hardware clock and hence application layer clock skew will be same as of physical layer and can be corrected from symbol timing recovery process. So one timestamp is enough to synchronize two CRN nodes. This conserves the energy utilized by application layer protocol and makes a CRN energy efficient and can achieve time synchronization in short span., Comment: International Journal of Internet Technology and Secured Transactions, 2020

Published
2020
Full Text
View/download PDF

4. Implementation of Symbol Timing Recovery for Estimation of Clock Skew

Author

Hashmi, S. M. Usman, Hussain, Muntazir, Muslim, Fahad Bin, Inayat, Kashif, and Hwang, Seong Oun

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

Time synchronization in any distributed network can be achieved by using application layer protocols for time correction. Time synchronization method proposed in this article uses symbol timing recovery at the physical layer to correct application layer clock. This cross layer methodology diminishes the quantity of message trades needed by application layer for time synchronization thus resulting in energy saving. Precision of skew estimate can be increased by using multiple message exchanges. Examination of the cross layer strategy including the simulation results, the experimentation outcomes and mathematical analysis demonstrates that clock skew at physical layer is same as of application layer, which is actually the skew of hardware clock within the node.

Published
2020
Full Text
View/download PDF

8. A Data-Centric AI Paradigm for Socio-Industrial and Global Challenges.

Author

Majeed, Abdul and Hwang, Seong Oun

Subjects
CHATBOTS, LANGUAGE models, ARTIFICIAL intelligence, SUPPLY chain disruptions, PUBLIC investments
Abstract

Due to huge investments by both the public and private sectors, artificial intelligence (AI) has made tremendous progress in solving multiple real-world problems such as disease diagnosis, chatbot misbehavior, and crime control. However, the large-scale development and widespread adoption of AI have been hindered by the model-centric mindset that only focuses on improving the code/architecture of AI models (e.g., tweaking the network architecture, shrinking model size, tuning hyper-parameters, etc.). Generally, AI encompasses a model (or code) that solves a given problem by extracting salient features from underlying data. However, when the AI model yields a low performance, developers iteratively improve the code/algorithm without paying due attention to other aspects such as data. This model-centric AI (MC-AI) approach is limited to only those few businesses/applications (language models, text analysis, etc.) where big data readily exists, and it cannot offer a feasible solution when good data are not available. However, in many real-world cases, giant datasets either do not exist or cannot be curated. Therefore, the AI community is searching for appropriate solutions to compensate for the lack of giant datasets without compromising model performance. In this context, we need a data-centric AI (DC-AI) approach in order to solve the problems faced by the conventional MC-AI approach, and to enhance the applicability of AI technology to domains where data are limited. From this perspective, we analyze and compare MC-AI and DC-AI, and highlight their working mechanisms. Then, we describe the crucial problems (social, performance, drift, affordance, etc.) of the conventional MC-AI approach, and identify opportunities to solve those crucial problems with DC-AI. We also provide details concerning the development of the DC-AI approach, and discuss many techniques that are vital in bringing DC-AI from theory to practice. Finally, we highlight enabling technologies that can contribute to realizing DC-AI, and discuss various noteworthy use cases where DC-AI is more suitable than MC-AI. Through this analysis, we intend to open up a new direction in AI technology to solve global problems (e.g., climate change, supply chain disruption) that are threatening human well-being around the globe. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

9. An Efficient Searchable Encryption Scheme in the Multi-user Environment

Author

Kim, In Tae, Quan, Tran Hai, Duc, Ly Vu, Nguyen, Trong Kha, Hwang, Seong Oun, 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
Full Text
View/download PDF

18. Efficient Anonymous Multi-group Broadcast Encryption

Author

Kim, Intae, Hwang, Seong Oun, Susilo, Willy, Baek, Joonsang, Kim, Jongkil, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Conti, Mauro, editor, Zhou, Jianying, editor, Casalicchio, Emiliano, editor, and Spognardi, Angelo, editor

Published
2020
Full Text
View/download PDF

33. Hash Function

Author

Hwang, Seong Oun, primary, Kim, Intae, additional, and Lee, Wai Kong, additional

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results