Zobrazeno 1 - 10
of 2 548
pro vyhledávání: '"M. Hadi"'
Publikováno v:
Journal of Applied Fluid Mechanics, Vol 17, Iss 11, Pp 2411-2423 (2024)
When a flying vehicle approaches a water or land surface, it induces changes in the fluid flow field pattern known as the "ground effect." This research analyzes the ground effect phenomenon, exploring its impact on aerodynamic coefficients and flow
Externí odkaz:
https://doaj.org/article/d458ab99369a4ae487d907f9306d4c5b
Autor:
Ivida Dewi Amrih Suci, M. Hadi Shubhan, Herowati Poesoko, R. Murjiyanto, Mohd Zamre Mohd Zahir, Sudiyana
Publikováno v:
Media Iuris, Vol 7, Iss 2, Pp 299-322 (2024)
Systemic principles serve as the basic basis for thought and action processes, representing interconnected elements that contribute to the formation of a comprehensive whole. Bankruptcy law is a special and special law, regulated in Articles 222 to 2
Externí odkaz:
https://doaj.org/article/1ea8f0a7cffe4e0c9703ab05d2c6de41
Autor:
Jueal Mia, M. Hadi Amini
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 5, Pp 495-508 (2024)
Federated Learning is a decentralized machine learning technique that creates a global model by aggregating local models from multiple edge devices without a need to access the local data. However, due to the distributed nature of federated learning,
Externí odkaz:
https://doaj.org/article/2231ae17b10f4a4cb3e1752cbe85b312
Publikováno v:
Journal of Hydroinformatics, Vol 26, Iss 1, Pp 319-336 (2024)
Flooding is one of the most frequent natural hazards and causes more economic loss than all the other natural hazards. Fast and accurate flood prediction has significance in preserving lives, minimizing economic damage, and reducing public health ris
Externí odkaz:
https://doaj.org/article/c79c5ee877b44818b01eebadadd1cfb5
Publikováno v:
Iranian Journal of Applied Ecology, Vol 12, Iss 3, Pp 81-95 (2023)
This research was conducted to investigate the energy balance and global warming potential of almond production through by traditional and mechanized cultivation in Lenjan county, Isfahan province. Information related to the consumption of inputs and
Externí odkaz:
https://doaj.org/article/9e8da6a6ff4a4bf092561db1ad849031
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-16 (2023)
Abstract Extensive prior work has provided methods for the optimization of routing based on weights assigned to travel duration, and/or travel cost, and/or the distance traveled. Routing can be in various modalities, such as by car, on foot, by bicyc
Externí odkaz:
https://doaj.org/article/7c5eb12a75f549d8aacfef5ed9928414
Autor:
Rr. Herini Siti Aisyah, M. Hadi Shubhan, Nur Basuki Minarno, Siswanto Siswanto, Sudarsono Sudarsono, Siswandi Hendarta, Raissa Virgy Rianda, Rama Azalix Rianda, Ahmad Munir, Heru Irianto
Publikováno v:
Sriwijaya Law Review, Vol 7, Iss 1, Pp 173-188 (2023)
Clean and Healthy Living Behavior (CHLB) is influenced by some factors such as knowledge, attitudes, economic status, and supports from health and social officers. Increasing the knowledge of CHLB in the household structure is very important. The reg
Externí odkaz:
https://doaj.org/article/8d800dce5c38489aae1f4b43708bef52
Publikováno v:
مجلة الأنبار للعلوم الزراعية, Vol 20, Iss 1, Pp 156-172 (2022)
The government sector contributes to providing the basic development requirements of the agricultural sector. A number of national programs have been established to improve and multiply the seeds of strategic grain crops. The most important of which
Externí odkaz:
https://doaj.org/article/0699fe0969f54c4b9508eac87f6d4875
Autor:
Saadati, Yasaman, Amini, M. Hadi
Federated Learning (FL) is a decentralized learning approach that protects sensitive information by utilizing local model parameters rather than sharing clients' raw datasets. While this privacy-preserving method is widely employed across various app
Externí odkaz:
http://arxiv.org/abs/2411.12244
Autor:
Mia, Md Jueal, Amini, M. Hadi
Federated Learning has emerged as a leading approach for decentralized machine learning, enabling multiple clients to collaboratively train a shared model without exchanging private data. While FL enhances data privacy, it remains vulnerable to infer
Externí odkaz:
http://arxiv.org/abs/2411.05260