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Laima Zalieckaite,Viktorija Kazakeviciute,Vilma Kalinoviene
Pág. 331 - 344
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P. K. Paul, P. S. Aithal, R. Saavedra, K.S. Tiwary, B. Aremu, S. Mewada
Pág. 99 - 105
AbstractInformation is the power and Technology is the driving force for the development of all the facets. Information Science and Technology as a field of study and professional practice is therefore responsible for providing information and technology...
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Narasimha Rao Vajjhala, Ervin Ramollari
Pág. 129 - 137
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Javid Misirli and Emiliano Casalicchio
The Internet of Things (IoT) uptake brought a paradigm shift in application deployment. Indeed, IoT applications are not centralized in cloud data centers, but the computation and storage are moved close to the consumers, creating a computing continuum b...
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Khaled Arbateni and Amir Benzaoui
Electrocardiography (ECG) is a simple and safe tool for detecting heart conditions. Despite the diaspora of existing heartbeat classifiers, improvements such as real-time heartbeat identification and patient-independent classification persist. Reservoir ...
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Xiaonan Wang, Yang Guo and Yuan Gao
Non-terrestrial network (NTN) is a trending topic in the field of communication, as it shows promise for scenarios in which terrestrial infrastructure is unavailable. Unmanned autonomous intelligent systems (UAISs), as a physical form of artificial intel...
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Feng Zhou, Shijing Hu, Xin Du, Xiaoli Wan and Jie Wu
In the current field of disease risk prediction research, there are many methods of using servers for centralized computing to train and infer prediction models. However, this centralized computing method increases storage space, the load on network band...
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Ivan A. Hernandez-Robles, Xiomara Gonzalez-Ramirez, Juan C. Olivares-Galvan, Rafael Escarela-Perez and Rodrigo Ocon-Valdez
Designing and manufacturing transformers often involves variations in heights and thicknesses of windings. However, such geometric asymmetry introduces a significant impact on the magnitude of stray transformer losses. This study examines the effects of ...
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Hoang Hai Nguyen, Dae-Yun Shin, Woo-Sung Jung, Tae-Yeol Kim and Dae-Hyun Lee
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Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
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