https://elib.vku.udn.vn/handle/123456789/3368 2026-04-09T23:39:47Z 2026-04-09T23:39:47Z Dang, Dai Tho Hwang, Dosam https://elib.vku.udn.vn/handle/123456789/5914 2025-11-18T09:37:14Z 2024-10-01T00:00:00Z

Title: Consensus-based methods for distributed systems, blockchain, and voting: a survey Authors: Dang, Dai Tho; Hwang, Dosam Abstract: Condorcet and Borda first introduced the consensus theory in the eighteenth century when they studied voting systems. Consensus problems have been investigated for a long time in many fields such as economics, sociology, computer science, bioinformatics, collective intelligence, and automation. They are fundamental to developing distributed systems. In recent years, with blockchain’s great applications and potential, consensus problems have received significant attention from many researchers. The consensus method allows a blockchain network to function in a distributed system, especially IoT (Internet of Things). Voting consensus has been applied in distributed systems and blockchain, and consensus in distributed systems is also used in blockchain systems. This study reviews the consensus methods in voting, distributed systems, and blockchain. Description: Journal of Information and Telecommunication; Vol. 9, No. 2; pp: 237-260

2024-10-01T00:00:00Z Dang, Dai Tho https://elib.vku.udn.vn/handle/123456789/5911 2025-11-18T09:08:49Z 2024-11-01T00:00:00Z

Title: Evolutionary Algorithms to Find Consensus for Incomplete Ordered Partitions Authors: Dang, Dai Tho Abstract: An incomplete ordered partition (IOP) is a helpful structure for representing people's opinions. For a set of elements representing the opinions of a group of people for one problem, one should determine an element called consensus that best describes these elements. Finding consensus for an IOP collective is crucial in making decisions. However, finding one 2-optimality consensus for IOP collectives is an NP-hard problem that has yet to be widely considered for resolution. This study proposes evolutionary algorithms to solve this problem: one genetic algorithm (GA) and one hybrid algorithm (HA). The GA algorithm is based on the traditional genetic algorithm. The HA algorithm focuses on growing the balance of exploitation and exploration. The simulation shows that the two proposed algorithms find high-quality consensus, and the HA generates a higher-quality consensus. Description: 2024 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)

2024-11-01T00:00:00Z Phan, Thi Yen Dang, Vinh https://elib.vku.udn.vn/handle/123456789/5910 2025-11-18T08:47:03Z 2024-10-01T00:00:00Z

Title: The application of Total Quality Management (TQM) model in University governance and development Authors: Phan, Thi Yen; Dang, Vinh Abstract: Research shows that there are three levels of university quality management: quality control, quality assurance, and Total Quality Management (TQM). Currently, all three levels of quality management coexist in university management across different countries, as each of these methods aims to ensure that higher education products meet certain standards. There are various university quality management models, such as the university quality assurance model, the European EFQM Quality Award model, the ISO 9001 model, the organizational factors model, the C.I.P.O. model, and the TQM model. At present, higher education institutions are gradually improving their quality management systems. Total Quality Management is a comprehensive approach to quality improvement, emphasizing continuous enhancement across all aspects of an organization. In the context of universities in the region, which often face specific challenges and limitations, the implementation of TQM principles can offer significant benefits in terms of efficiency, performance, and stakeholder satisfaction. The research highlights the potential challenges and opportunities related to TQM deployment in regional university settings, including issues such as resource limitations, organizational culture, and stakeholder expectations. Description: International Journal of Advances in Engineering and Management (IJAEM); Volume 6, Issue 10; pp: 51-58

2024-10-01T00:00:00Z Tran, T. M. Hanh Nguyen, V. Hieu Bui, Van Phuc Ha, Tien Ngoc Nguyen, Van Tho Nguyen, Duc Hien Le, T. P. Mai https://elib.vku.udn.vn/handle/123456789/5909 2025-11-18T08:44:25Z 2024-12-01T00:00:00Z

Title: Encoding reality with semantic interpretation in metaverse interactions Authors: Tran, T. M. Hanh; Nguyen, V. Hieu; Bui, Van Phuc; Ha, Tien Ngoc; Nguyen, Van Tho; Nguyen, Duc Hien; Le, T. P. Mai Abstract: In the rapidly evolving landscape of the metaverse, efficiently managing and processing vast amounts of data is a critical challenge. This paper introduces a novel data management framework designed specifically for the metaverse, addressing the complexities of handling extensive data in its increasingly intricate and expansive digital environments. Leveraging advancements in wireless communication technologies, our framework optimizes resource allocation while managing massive data loads. We propose an innovative approach that integrates change grading and semantic encoding techniques, utilizing edge computing to process data locally and reduce server load. By processing data locally and minimizing server load, our approach stores static scenes on local devices and detects significant changes by comparing them with newly captured data. This selective transmission of only new or altered information based on change grades dramatically reduces bandwidth requirements and boosts network efficiency. This paper details the technical aspects of our methodology, showcases experimental results that demonstrate its effectiveness, and discusses its implications for the future scalability and sustainability of metaverse architectures. Our framework aims to refine the real-time digital representation of the metaverse, ensuring its operational efficiency and continuous accessibility as it evolves. Description: AEU - International Journal of Electronics and Communications; Volume 187, 155512

2024-12-01T00:00:00Z