Zobrazeno 1 - 10
of 205
pro vyhledávání: '"Md Delowar, Hossain"'
Publikováno v:
Modelling, Vol 5, Iss 1, Pp 292-314 (2024)
Understanding and analyzing the search intent of a user semantically based on their input query has emerged as an intriguing challenge in recent years. It suffers from small-scale human-labeled training data that produce a very poor hypothesis of rar
Externí odkaz:
https://doaj.org/article/f64e40f3a419447e9c3995a92b11d9cb
Publikováno v:
IEEE Access, Vol 12, Pp 62341-62357 (2024)
The identification of suitable feature subsets from High-Dimensional Low-Sample-Size (HDLSS) data is of paramount importance because this dataset often contains numerous redundant and irrelevant features, leading to poor classification performance. H
Externí odkaz:
https://doaj.org/article/06d6923e3a5e4dc0b17690f2c12390e0
Autor:
Nosin Ibna Mahbub, Md. Delowar Hossain, Sharmen Akhter, Md. Imtiaz Hossain, Kimoon Jeong, Eui-Nam Huh
Publikováno v:
IEEE Access, Vol 12, Pp 55248-55263 (2024)
Cloud computing has become the cornerstone of modern technology, propelling industries to unprecedented heights with its remarkable and recent advances. However, the fundamental challenge for cloud service providers is real-time workload prediction a
Externí odkaz:
https://doaj.org/article/cd8b235ef1fa432695f0f37707598146
Autor:
Md. Delowar Hossain, Tangina Sultana, Sharmen Akhter, Md Imtiaz Hossain, Ngo Thien Thu, Luan N.T. Huynh, Ga-Won Lee, Eui-Nam Huh
Publikováno v:
ICT Express, Vol 9, Iss 6, Pp 1162-1182 (2023)
Edge computing has emerged as a promising computing paradigm that enables real-time data processing and analysis closer to the data source and boosts decision-making applications in a safe manner. On the other hand, the microservice is a new type of
Externí odkaz:
https://doaj.org/article/d0ea52b548654ca285f6901dae4f7637
Synergistic effects of mixing and strain in high entropy spinel oxides for oxygen evolution reaction
Autor:
Jihyun Baek, Md Delowar Hossain, Pinaki Mukherjee, Junghwa Lee, Kirsten T. Winther, Juyoung Leem, Yue Jiang, William C. Chueh, Michal Bajdich, Xiaolin Zheng
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract Developing stable and efficient electrocatalysts is vital for boosting oxygen evolution reaction (OER) rates in sustainable hydrogen production. High-entropy oxides (HEOs) consist of five or more metal cations, providing opportunities to tun
Externí odkaz:
https://doaj.org/article/35aed22dfe824249a0966e3040b8a610
Publikováno v:
IEEE Access, Vol 11, Pp 39845-39854 (2023)
The development of salient object detection is crucial in ubiquitous applications. Existing state-of-the-art models tend to have complex designs and a significant number of parameters, prioritizing performance improvement over efficiency. Hence, ther
Externí odkaz:
https://doaj.org/article/63135c9b37084d74b34aa27f75919ef9
Publikováno v:
IEEE Access, Vol 10, Pp 131555-131566 (2022)
In recent years, Knowledge Distillation has obtained a significant interest in mobile, edge, and IoT devices due to its ability to transfer knowledge from the large and complex teacher to the lightweight student network. Intuitively, Knowledge Distil
Externí odkaz:
https://doaj.org/article/b547c0f479854b0bb5f04996b8c8c8ea
Autor:
Luan N. T. Huynh, Quoc-Viet Pham, Tri D. T. Nguyen, Md. Delowar Hossain, Young-Rok Shin, Eui-Nam Huh
Publikováno v:
IEEE Access, Vol 9, Pp 12943-12954 (2021)
Multi-access edge computing (MEC) can improve the users' computational capacity and battery life by moving computing services to the network edge. In addition, data-content caching on a MEC server improves the user quality of experience and decreases
Externí odkaz:
https://doaj.org/article/1474c5f05f104c3d97aa0c933dfa5667
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-14 (2020)
Single atom catalysts (SACs) are promising in electrocatalysis but challenging to characterize. Here, the authors apply a recently developed quantum mechanical grand canonical potential kinetics method to predict reaction mechanisms and rates for CO2
Externí odkaz:
https://doaj.org/article/7f75fefc22db475a9d1426ce9fe0517a
Publikováno v:
IEEE Access, Vol 8, Pp 206427-206444 (2020)
Deep learning-based action recognition in videos has obtained much attention because of achieving remarkable performance in diverse applications. However, due to the heterogeneous background and noisy spatio-temporal cues, extracting highly discrimin
Externí odkaz:
https://doaj.org/article/05f28599217a418a90993811d342e405