Zobrazeno 1 - 10
of 981
pro vyhledávání: '"Hybrid architecture"'
Autor:
Lina Wang
Publikováno v:
Systems and Soft Computing, Vol 6, Iss , Pp 200162- (2024)
With the development of Internet technology, network English teaching system came into being and developed rapidly. Based on optimized J2EE, this paper presents the implementation of sentence feature recognition in the English teaching system. Optimi
Externí odkaz:
https://doaj.org/article/0f87b4b580fe45be827cd6ec09255664
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract In the field of engineering systems—particularly in underground drilling and green stormwater management—real-time predictions are vital for enhancing operational performance, ensuring safety, and increasing efficiency. Addressing this n
Externí odkaz:
https://doaj.org/article/2050cec9c81b444cb849a0f5c7038bb6
Publikováno v:
IEEE Access, Vol 12, Pp 126624-126639 (2024)
In the realm of positive building design, local energy production systems are gaining prominence. Strategies aimed at advancing this concept often involve optimizing hybrid renewable systems through various means, including sizing, maximizing power e
Externí odkaz:
https://doaj.org/article/450432bdf33b487ba4ad500cc4b2a5ac
Autor:
XiaoXiao Liu, Colin Flanagan, Gang Li, Yiming Lei, Liaoyuan Zeng, Jingchao Fang, Xiangyang Guo, Sean McGrath, Yongzheng Han
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Background Identification of difficult laryngoscopy is a frequent demand in cervical spondylosis clinical surgery. This work aims to develop a hybrid architecture for identifying difficult laryngoscopy based on new indexes. Methods Initially
Externí odkaz:
https://doaj.org/article/cd63cf3dfcc246f4811f7def6d48445e
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract As the first point of contact for patients, General Practitioners (GPs) play a crucial role in the National Health Service (NHS). An accurate primary diagnosis from the GP can alleviate the burden on specialists and reduce the time needed to
Externí odkaz:
https://doaj.org/article/a6daae12b9e64d8ca2659b5ea8a48567
Publikováno v:
Mathematics, Vol 12, Iss 23, p 3689 (2024)
Knowledge graph embedding has been identified as an effective method for node-level classification tasks in directed graphs, the objective of which is to ensure that nodes of different categories are embedded as far apart as possible in the feature s
Externí odkaz:
https://doaj.org/article/98a01b4c5fa54caeb1f9c95f54adb71b
Publikováno v:
Sensors, Vol 24, Iss 20, p 6545 (2024)
The motion of an object or camera platform makes the acquired image blurred. This degradation is a major reason to obtain a poor-quality image from an imaging sensor. Therefore, developing an efficient deep-learning-based image processing method to r
Externí odkaz:
https://doaj.org/article/5fe450badd444188b6950d3914100913
Publikováno v:
Measurement: Sensors, Vol 33, Iss , Pp 101201- (2024)
In order to improve the efficiency of the educational administration system in colleges and universities, a technology based on the hybrid architecture of C/S and B/S is proposed. Based on the development experience of previous information management
Externí odkaz:
https://doaj.org/article/88600402bee94fefbe14a2a0a4088449
Publikováno v:
Remote Sensing, Vol 16, Iss 17, p 3278 (2024)
Advances in deep learning and computer vision techniques have made impacts in the field of remote sensing, enabling efficient data analysis for applications such as land cover classification and change detection. Convolutional neural networks (CNNs)
Externí odkaz:
https://doaj.org/article/8c34864bef9948169a4e61c1fcc79c4e
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Plants are widely grown around the world and have high economic benefits. plant leaf diseases not only negatively affect the healthy growth and development of plants, but also have a negative impact on the environment. While traditional manual method
Externí odkaz:
https://doaj.org/article/83aee69e8c654ee4815440e8f124a506