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Lina Zhou, Leijinyu Zhou, Hongbo Wu, Tingting Jing, Tianhao Li, Jinsheng Li, Lijuan Kong and Limei Chen
In order to monitor cadmium contamination in lettuce quickly, non-invasively, and accurately, and to understand the growth status of lettuce under cadmium pollution, lettuce was used as the test material to detect and analyze the visible?near-infrared re...
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Torrey Wagner, Dennis Guhl and Brent Langhals
Given the emergence of China as a political and economic power in the 21st century, there is increased interest in analyzing Chinese news articles to better understand developing trends in China. Because of the volume of the material, automating the cate...
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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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Zihao Zhu and Yonghua Xie
Black soil plays an important role in maintaining a healthy ecosystem, promoting high-yield and efficient agricultural production, and conserving soil resources. In this paper, a typical black soil area of Keshan Farm in Qiqihar City, Heilongjiang Provin...
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Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap...
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Firas Alghanim, Ibrahim Al-Hurani, Hazem Qattous, Abdullah Al-Refai, Osamah Batiha, Abedalrhman Alkhateeb and Salama Ikki
Identifying menopause-related breast cancer biomarkers is crucial for enhancing diagnosis, prognosis, and personalized treatment at that stage of the patient?s life. In this paper, we present a comprehensive framework for extracting multiomics biomarkers...
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Lei Sun, Chongchong Yang, Jun Wang, Xiwen Cui, Xuesong Suo, Xiaofei Fan, Pengtao Ji, Liang Gao and Yuechen Zhang
Existing maize production is grappling with the hurdles of not applying nitrogen fertilizer accurately due to subpar detection accuracy and responsiveness. This situation presents a significant challenge, as it has the potential to impact the optimal yie...
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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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Carlos Alejandro Perez Garcia, Marco Bovo, Daniele Torreggiani, Patrizia Tassinari and Stefano Benni
The escalating global population and climate change necessitate sustainable livestock production methods to meet rising food demand. Precision Livestock Farming (PLF) integrates information and communication technologies (ICT) to improve farming efficien...
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Károly Héberger
Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread wi...
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