Zobrazeno 1 - 10
of 18 694
pro vyhledávání: '"Nauman AT"'
Software analytics (SA) is frequently proposed as a tool to support practitioners in software engineering (SE) tasks. We have observed that several secondary studies on SA have been published. Some of these studies have overlapping aims and some have
Externí odkaz:
http://arxiv.org/abs/2410.05796
Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared to real-wo
Externí odkaz:
http://arxiv.org/abs/2409.16968
Visual perspective-taking (VPT), the ability to understand the viewpoint of another person, enables individuals to anticipate the actions of other people. For instance, a driver can avoid accidents by assessing what pedestrians see. Humans typically
Externí odkaz:
http://arxiv.org/abs/2409.12969
Autor:
van Dreven, Jonne, Cheddad, Abbas, Alawadi, Sadi, Ghazi, Ahmad Nauman, Koussa, Jad Al, Vanhoudt, Dirk
District Heating (DH) systems are essential for energy-efficient urban heating. However, despite the advancements in automated fault detection and diagnosis (FDD), DH still faces challenges in operational faults that impact efficiency. This study int
Externí odkaz:
http://arxiv.org/abs/2408.14499
Optimizing QoS in HD Map Updates: Cross-Layer Multi-Agent with Hierarchical and Independent Learning
The data collected by autonomous vehicle (AV) sensors such as LiDAR and cameras is crucial for creating high-definition (HD) maps to provide higher accuracy and enable a higher level of automation. Nevertheless, offloading this large volume of raw da
Externí odkaz:
http://arxiv.org/abs/2408.11605
Reinforcement Learning (RL) algorithms have been used to address the challenging problems in the offloading process of vehicular ad hoc networks (VANET). More recently, they have been utilized to improve the dissemination of high-definition (HD) Maps
Externí odkaz:
http://arxiv.org/abs/2407.21460
In this study, we introduce StylusAI, a novel architecture leveraging diffusion models in the domain of handwriting style generation. StylusAI is specifically designed to adapt and integrate the stylistic nuances of one language's handwriting into an
Externí odkaz:
http://arxiv.org/abs/2407.15608
Publikováno v:
2024 11th International Conference on Wireless Networks and Mobile Communications (WINCOM)
One effective way to optimize the offloading process is by minimizing the transmission time. This is particularly true in a Vehicular Adhoc Network (VANET) where vehicles frequently download and upload High-definition (HD) map data which requires con
Externí odkaz:
http://arxiv.org/abs/2408.03329
Autor:
Wang, Liming, Gong, Yuan, Dawalatabad, Nauman, Vilela, Marco, Placek, Katerina, Tracey, Brian, Gong, Yishu, Premasiri, Alan, Vieira, Fernando, Glass, James
Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a more efficient and objective alternative than manual approaches. We propose ALS longitudinal speech transformer (ALST), a neural network-based automatic predic
Externí odkaz:
http://arxiv.org/abs/2406.18625
Sample efficiency in Reinforcement Learning (RL) has traditionally been driven by algorithmic enhancements. In this work, we demonstrate that scaling can also lead to substantial improvements. We conduct a thorough investigation into the interplay of
Externí odkaz:
http://arxiv.org/abs/2405.16158