Zobrazeno 1 - 10
of 9 871
pro vyhledávání: '"Nguyen, A. N."'
We investigate an internet-of-things system where energy-harvesting devices send status updates to a common receiver using the irregular repetition slotted ALOHA (IRSA) protocol. Energy shortages in these devices can cause transmission failures that
Externí odkaz:
http://arxiv.org/abs/2411.01446
Autor:
Le, Cuong Chi, Truong-Vinh, Hoang-Chau, Phan, Huy Nhat, Le, Dung Duy, Nguyen, Tien N., Bui, Nghi D. Q.
Predicting program behavior and reasoning about code execution remain significant challenges in software engineering, particularly for large language models (LLMs) designed for code analysis. While these models excel at understanding static syntax, t
Externí odkaz:
http://arxiv.org/abs/2410.23402
Autor:
Van Huynh, Nguyen, Zhang, Bolun, Tran, Dinh-Hieu, Hoang, Dinh Thai, Nguyen, Diep N., Zheng, Gan, Niyato, Dusit, Pham, Quoc-Viet
Spectrum access is an essential problem in device-to-device (D2D) communications. However, with the recent growth in the number of mobile devices, the wireless spectrum is becoming scarce, resulting in low spectral efficiency for D2D communications.
Externí odkaz:
http://arxiv.org/abs/2410.17971
This paper introduces a novel lossless compression method for compressing geometric attributes of point cloud data with bits-back coding. Our method specializes in using a deep learning-based probabilistic model to estimate the Shannon's entropy of t
Externí odkaz:
http://arxiv.org/abs/2410.18115
Large Language Models (LLMs) have revolutionized software engineering (SE), showcasing remarkable proficiency in various coding tasks. Despite recent advancements that have enabled the creation of autonomous software agents utilizing LLMs for end-to-
Externí odkaz:
http://arxiv.org/abs/2409.16299
The ability to estimate 3D movements of users over edge computing-enabled networks, such as 5G/6G networks, is a key enabler for the new era of extended reality (XR) and Metaverse applications. Recent advancements in deep learning have shown advantag
Externí odkaz:
http://arxiv.org/abs/2409.00087
Predicting program behavior without execution is a crucial and challenging task in software engineering. Traditional models often struggle to capture the dynamic dependencies and interactions within code. This paper introduces a novel machine learnin
Externí odkaz:
http://arxiv.org/abs/2408.02816
Autor:
Pandya, A., Migkas, K., Reiprich, T. H., Stanford, A., Pacaud, F., Schellenberger, G., Lovisari, L., Ramos-Ceja, M. E., Nguyen-Dang, N. T., Park, S.
In standard cosmology, the late Universe is assumed to be statistically homogeneous and isotropic. However, a recent study based on galaxy clusters by Migkas et al. (2021, arXiv:2103.13904) found an apparent spatial variation of approximately $9\%$ i
Externí odkaz:
http://arxiv.org/abs/2408.00726
Regression testing of software is a crucial but time-consuming task, especially in the context of user interface (UI) testing where multiple microservices must be validated simultaneously. Test case prioritization (TCP) is a cost-efficient solution t
Externí odkaz:
http://arxiv.org/abs/2408.00705
This paper aims to propose a novel framework to address the data privacy issue for Federated Learning (FL)-based Intrusion Detection Systems (IDSs) in Internet-of-Vehicles(IoVs) with limited computational resources. In particular, in conventional FL
Externí odkaz:
http://arxiv.org/abs/2407.18503