Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Rahaman, Mohammad Saiedur"'
Occupation information can be utilized by digital assistants to provide occupation-specific personalized task support, including interruption management, task planning, and recommendations. Prior research in the digital workplace assistant domain req
Externí odkaz:
http://arxiv.org/abs/2407.18518
Publikováno v:
Neurocomputing Neurocomputing Volume 508, 7 October 2022, Pages 182-207
Accurate and reliable prediction of Photovoltaic (PV) power output is critical to electricity grid stability and power dispatching capabilities. However, Photovoltaic (PV) power generation is highly volatile and unstable due to different reasons. The
Externí odkaz:
http://arxiv.org/abs/2210.00269
Autor:
Khaokaew, Yonchanok, Holcombe-James, Indigo, Rahaman, Mohammad Saiedur, Liono, Jonathan, Trippas, Johanne R., Spina, Damiano, Belkin, Nicholas, Bailey, Peter, Bennett, Paul N., Ren, Yongli, Sanderson, Mark, Scholer, Falk, White, Ryen W., Salim, Flora D.
Digital Assistants (DAs) can support workers in the workplace and beyond. However, target user needs are not fully understood, and the functions that workers would ideally want a DA to support require further study. A richer understanding of worker n
Externí odkaz:
http://arxiv.org/abs/2208.03443
Publikováno v:
IMWUT. 6(3), 1-23 (2022)
Seating location in the classroom can affect student engagement, attention and academic performance by providing better visibility, improved movement, and participation in discussions. Existing studies typically explore how traditional seating arrang
Externí odkaz:
http://arxiv.org/abs/2112.12342
App usage prediction is important for smartphone system optimization to enhance user experience. Existing modeling approaches utilize historical app usage logs along with a wide range of semantic information to predict the app usage; however, they ar
Externí odkaz:
http://arxiv.org/abs/2108.11561
Inferring human mental state (e.g., emotion, depression, engagement) with sensing technology is one of the most valuable challenges in the affective computing area, which has a profound impact in all industries interacting with humans. The self-repor
Externí odkaz:
http://arxiv.org/abs/2107.00389
Autor:
Rahaman, Mohammad Saiedur, Shao, Wei, Salim, Flora D., Turky, Ayad, Song, Andy, Chan, Jeffrey, Jiang, Junliang, Bradbrook, Doug
Existing parking recommendation solutions mainly focus on finding and suggesting parking spaces based on the unoccupied options only. However, there are other factors associated with parking spaces that can influence someone's choice of parking such
Externí odkaz:
http://arxiv.org/abs/2106.07384
Autor:
Shao, Wei, Zhang, Yu, Xiao, Pengfei, Qin, Kyle Kai, Rahaman, Mohammad Saiedur, Chan, Jeffrey, Guo, Bin, Song, Andy, Salim, Flora D.
Publikováno v:
In Pervasive and Mobile Computing January 2024 97
Autor:
Gao, Nan, Xue, Hao, Shao, Wei, Zhao, Sichen, Qin, Kyle Kai, Prabowo, Arian, Rahaman, Mohammad Saiedur, Salim, Flora D.
Generative Adversarial Networks (GANs) have shown remarkable success in producing realistic-looking images in the computer vision area. Recently, GAN-based techniques are shown to be promising for spatio-temporal-based applications such as trajectory
Externí odkaz:
http://arxiv.org/abs/2008.08903
Publikováno v:
NFW '20: Symposium on New Future of Work, August 03--05, 2020
Due to the increasing nature of flexible work and the recent requirements from COVID-19 restrictions, workplaces are becoming more hybrid (i.e. allowing workers to work between traditional office spaces and elsewhere including from home). Since workp
Externí odkaz:
http://arxiv.org/abs/2007.15807