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Yiping Peng, Ting Wang, Shujuan Xie, Zhenhua Liu, Chenjie Lin, Yueming Hu, Jianfang Wang and Xiaoyun Mao
Soil exchange cations are a basic indicator of soil quality and environmental clean-up potential. The accurate and efficient acquisition of information on soil cation content is of great importance for the monitoring of soil quality and pollution prevent...
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Dexi Zhan, Yongqi Mu, Wenxu Duan, Mingzhu Ye, Yingqiang Song, Zhenqi Song, Kaizhong Yao, Dengkuo Sun and Ziqi Ding
Soil water content is an important indicator used to maintain the ecological balance of farmland. The efficient spatial prediction of soil water content is crucial for ensuring crop growth and food production. To this end, 104 farmland soil samples were ...
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Hua Zhang, Muwei Wang, Lingjun Zhang, Yifan Wu and Yizhang Luo
Global photographic aesthetic image generation aims to ensure that images generated by generative adversarial networks (GANs) contain semantic information and have global aesthetic feelings. Existing image aesthetic generation algorithms are still in the...
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Olurotimi Oguntola and Steven Simske
This study proposes a framework for a systems engineering-based approach to context-aware personalization, which is applied to e-commerce through the understanding and modeling of user behavior from their interactions with sales channels and media. The f...
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Jian Yang and Jinhan Guan
In today?s world, heart disease is the leading cause of death globally. Researchers have proposed various methods aimed at improving the accuracy and efficiency of the clinical diagnosis of heart disease. Auxiliary diagnostic systems based on machine lea...
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Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez and Susan A. Murphy
Online reinforcement learning (RL) algorithms are increasingly used to personalize digital interventions in the fields of mobile health and online education. Common challenges in designing and testing an RL algorithm in these settings include ensuring th...
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Hugo Silva and Jorge Bernardino
Decision support systems with machine learning can help organizations improve operations and lower costs with more precision and efficiency. This work presents a review of state-of-the-art machine learning algorithms for binary classification and makes a...
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Youngki Park and Youhyun Shin
The existing block-based machine learning educational environments have a drawback in that they do not support model training based on large-scale data. This makes it difficult for young students to learn the importance of large amounts of data when crea...
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Onder Tutsoy and Ceyda Tanrikulu
The most important underlying reasons for marketing failures are incomplete understanding of customer wants and needs and the inability to accurately predict their future behaviors. This study develops a machine learning model to estimate the number of d...
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Zhihao Guo, Shengyuan Chen, Xiao Huang, Zhiqiang Qian, Chunsing Yu, Yan Xu and Fang Ding
Most machine-learning algorithms assume that instances are independent of each other. This does not hold for networked data. Node representation learning (NRL) aims to learn low-dimensional vectors to represent nodes in a network, such that all actionabl...
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