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Omar Serghini, Hayat Semlali, Asmaa Maali, Abdelilah Ghammaz and Salvatore Serrano
Spectrum sensing is an essential function of cognitive radio technology that can enable the reuse of available radio resources by so-called secondary users without creating harmful interference with licensed users. The application of machine learning tec...
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Tomasz Gajewski and Pawel Skiba
The main goal of this work is to combine the usage of the numerical homogenization technique for determining the effective properties of representative volume elements with artificial neural networks. The effective properties are defined according to the...
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Juan Botero-Valencia, Erick Reyes-Vera, Elizabeth Ospina-Rojas and Flavio Prieto-Ortiz
In this study, a novel system was designed to enhance the efficiency of data acquisition in a portable and compact instrument dedicated to the spectral analysis of various surfaces, including plant leaves, and materials requiring characterization within ...
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Qiuyue Li, Hao Sheng, Mingxue Sheng and Honglin Wan
Efficient document recognition and sharing remain challenges in the healthcare, insurance, and finance sectors. One solution to this problem has been the use of deep learning techniques to automatically extract structured information from paper documents...
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May Alsaidi, Nadim Obeid, Nailah Al-Madi, Hazem Hiary and Ibrahim Aljarah
Autism spectrum disorder (ASD) is a developmental disorder that encompasses difficulties in communication (both verbal and non-verbal), social skills, and repetitive behaviors. The diagnosis of autism spectrum disorder typically involves specialized proc...
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Fidel Lozano, Seyyedbehrad Emadi, Seyedmilad Komarizadehasl, Jesús González Arteaga and Ye Xia
The development of low-cost structural and environmental sensors has sparked a transformation across numerous fields, offering cost-effective solutions for monitoring infrastructures and buildings. However, the affordability of these solutions often come...
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Shuyan Liu, Xuegeng Chen, Dongyan Huang, Jingli Wang, Xinming Jiang, Xianzhang Meng and Xiaomei Gao
Soil classification stands as a pivotal aspect in the domain of agricultural practices and environmental research, wielding substantial influence over decisions related to real-time soil management and precision agriculture. Nevertheless, traditional met...
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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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Sunny Kumar Poguluri and Yoon Hyeok Bae
The incorporation of machine learning (ML) has yielded substantial benefits in detecting nonlinear patterns across a wide range of applications, including offshore engineering. Existing ML works, specifically supervised regression models, have not underg...
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Chen Xia, Christian Eduardo Verdonk Gallego, Adrián Fabio Bracero, Víctor Fernando Gómez Comendador and Rosa María Arnaldo Valdés
This paper investigates the impact of trajectory predictor performance on the encounter probability generated by an adaptive conflict detection tool and examines the flexibility of the tool dependent on its adjustable thresholds, using historical radar t...
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