The emergence of sixth generation (6G) mobile networks is poised to transform global communication by providing unmatched speed, dependability, and sophisticated network management. This study examines the essential f...
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ISBN:
(数字)9798331518578
ISBN:
(纸本)9798331518585
The emergence of sixth generation (6G) mobile networks is poised to transform global communication by providing unmatched speed, dependability, and sophisticated network management. This study examines the essential function of AI and machine learning (ML) is in unlocking the whole potential within 6G networks, emphasizing current developments, primary difficulties, and future directions. Machine learning methods are essential for tackling intricate challenges like as distributing resources, energy efficiency, & latency reduction in 6G networks, enabling novel applications such autonomous systems including holographic communication. Notwithstanding the encouraging advancements, obstacles such as the development of scalable machine learning models, the assurance of network security, and the integration of AI-driven solutions into current infrastructures remain. The paper classifies machine learning applications in 6G according to various network topologies and emphasizes unresolved research challenges, especially in improving the trade-off between computational complexity and performance. This study establishes a foundation for future research, highlighting the significance of machine learning in influencing the future development of wireless networks.
This study aims to analyze interpreters’ performance in handling numbers, proper nouns, and complex sentences during AI-assisted simultaneous interpreting. By integrating AI speech recognition capabilities, an eye-tr...
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With the rise of Web3.0 and the continuous development of blockchain technology, traditional transmission protocols such as TCP and UDP are gradually unable to meet the growing demand for network applications. Quick U...
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ISBN:
(数字)9798331533113
ISBN:
(纸本)9798331533120
With the rise of Web3.0 and the continuous development of blockchain technology, traditional transmission protocols such as TCP and UDP are gradually unable to meet the growing demand for network applications. Quick UDP Internet Connection (QUIC) stands out with its multiple features such as low latency and support for multiplexing. However, new network attack methods continue to emerge, and how to accurately identify abnormal network traffic has become an extremely important challenge. Because QUIC traffic has the self-similarity, this research proposes an abnormal traffic detection model based on Ensemble Empirical Mode Decomposition (EEMD) and Approximate Entropy (ApEn). By adaptively decomposing traffic, mining abnormal traffic features, and adding ApEn method to reduce component complexit. Finally, it is determined whether the QUIC transmission network is under attack by comparing the changes in Hurst values before and after the attack. This paper uses the NS-3 platform to implement and evaluate this solution. Experiments have verified that the model proposed in this research can better solve the problems of traditional methods in terms of poor adaptability and low efficiency, and has a high accuracy rate in detecting abnormal traffic, making it suitable for network traffic attack detection.
Blockchain technology is increasingly developing breakthroughs in secure and decentralized data storage. More recently, it has also garnered interest as a possible solution for network security. In particular, this pa...
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Using the 3ds Max software, this paper describes the intricate modelling process of implying shadows onto various objects to make it look more realistic. In this article, Various Shadow types and controls are used in ...
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We study the 3D-Euclidean Multidimensional Stable Roommates problem with (strict) popularity. An agent’s preference depends solely on the distance to its roommates. It prefers to be in a room where the sum of the dis...
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With the rapid development of the artificial intelligence field today, sensor-based human activity recognition (HAR) has become mainstream, especially playing a crucial role in medical rehabilitation. However, existin...
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Drug-Target Interaction (DTI) involves the observation and recognition of interactions that occur between chemical molecules and target proteins in the human body. However, lab experimentation for DTI can be time-cons...
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The spread of biased and misleading opinions on social media regarding climate change necessitates robust solutions to counteract misinformation and promote balanced discourse. In this study, we introduce the Semantic...
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In today’s rapidly evolving world of mobile communications, 5G and 6G networks are leveraging millimeter-wave and sub-millimeter-wave frequencies to achieve faster speeds and higher capacities. To address the challen...
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