Zobrazeno 1 - 10
of 339
pro vyhledávání: '"Javad Mohammadpour"'
Publikováno v:
Thermo, Vol 2, Iss 4, Pp 383-393 (2022)
Attention to photovoltaic (PV) cells to convert solar irradiation into electricity is significantly growing for domestic usage and large-scale projects such as solar farms. However, PV efficiency decreases on hot days. This paper proposes an effectiv
Externí odkaz:
https://doaj.org/article/b14d2d92644a400b92054a26da80390a
Publikováno v:
Sensors, Vol 24, Iss 3, p 970 (2024)
In this paper, we present the development of a low-cost distributed computing pipeline for cotton plant phenotyping using Raspberry Pi, Hadoop, and deep learning. Specifically, we use a cluster of several Raspberry Pis in a primary-replica distribute
Externí odkaz:
https://doaj.org/article/c172eb3ba56b4dab98c97ee941e8e797
Publikováno v:
IET Generation, Transmission & Distribution, Vol 15, Iss 16, Pp 2298-2308 (2021)
Abstract The negative impacts of data integrity attacks against multi‐settlement electricity markets have been recently studied. It has been shown that adversaries could launch profitable cyber attacks by casting an incorrect image of transmission
Externí odkaz:
https://doaj.org/article/45f76e5a136e44b4aaa503c7ea2b3c78
Autor:
Bao, Yajie, Velni, Javad Mohammadpour
Scenario-based optimization and control has proven to be an efficient approach to account for system uncertainty. In particular, the performance of scenario-based model predictive control (MPC) schemes depends on the accuracy of uncertainty quantific
Externí odkaz:
http://arxiv.org/abs/2407.14492
Publikováno v:
Fire, Vol 6, Iss 1, p 29 (2023)
Hydrogen fuel cell vehicle (HFCV) technology poses great promise as an alternative to significantly reduce the environmental impact of the transport sector’s emissions. However, hydrogen fuel cell technology is relatively new, therefore, confirmati
Externí odkaz:
https://doaj.org/article/dbabdab8f4514270b1cf260eba74d78a
Publikováno v:
Sensors, Vol 23, Iss 1, p 309 (2022)
This paper develops an approach to perform binary semantic segmentation on Arabidopsis thaliana root images for plant root phenotyping using a conditional generative adversarial network (cGAN) to address pixel-wise class imbalance. Specifically, we u
Externí odkaz:
https://doaj.org/article/7996f0fe2cb94485a88e8dd482fc24db
Publikováno v:
Energies, Vol 15, Iss 9, p 3426 (2022)
The high latent heat thermal energy storage (LHTES) potential of phase change materials (PCMs) has long promised a step-change in the energy density for thermal storage applications. However, the uptake of PCM systems has been limited due to their re
Externí odkaz:
https://doaj.org/article/5f3fa40d278447289ecd4a61d6283d9c
Publikováno v:
Plants, Vol 10, Iss 12, p 2652 (2021)
Global population growth has increased food production challenges and pushed agricultural systems to deploy the Internet of Things (IoT) instead of using conventional approaches. Controlling the environmental parameters, including light, in greenhous
Externí odkaz:
https://doaj.org/article/6effde54729849a78ce2e3a06d9c7cea
Publikováno v:
IEEE/ASME Transactions on Mechatronics, vol. 29, no. 4, pp. 2785-2793, 2024
Simulation to reality (sim2real) transfer from a dynamics and controls perspective usually involves re-tuning or adapting the designed algorithms to suit real-world operating conditions, which often violates the performance guarantees established ori
Externí odkaz:
http://arxiv.org/abs/2401.11542
Publikováno v:
Sensors, Vol 20, Iss 23, p 6896 (2020)
The use of deep neural networks (DNNs) in plant phenotyping has recently received considerable attention. By using DNNs, valuable insights into plant traits can be readily achieved. While these networks have made considerable advances in plant phenot
Externí odkaz:
https://doaj.org/article/01e8ca5d92f644eebc43b940259498ff