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Soil is a huge carbon (C) reservoir, but where and how much extra C can be stored is unknown. Current methods to estimate the maximum amount of mineral‐associated organic carbon (MAOC) stabilized in the fine fraction (clay + silt, ) fit through the MAOC versus clay + silt relationship, not their maxima, making their estimates more uncertain and unreliable. We...
Summary The parameters extracted from quantitative computed tomography (QCT) images were used to predict vertebral strength through machine learning models, and the highly accurate prediction indicated that it may be a promising approach to assess fracture risk in clinics. Introduction Vertebral fracture is common in elderly populations. The main factor contributing to vertebral fracture is the...
The goal of this Special Issue was to attract the latest and best research articles in the field of Artificial Immune Systems, providing readers with a snapshot of the field today. We particularly encouraged papers that developed novel immune-based models or algorithms for cyber-security and data privacy, fault tolerance and self-organization.
A Deep Neural Network (DNN) using the same activation function for all hidden neurons has an optimization limitation due to its single mathematical functionality. To solve it, a new DNN with different activation functions is designed to globally optimize both parameters (weights and biases) and function selections. In addition, a novel Genetic Deep Neural Network (GDNN) with different activation functions...
This paper describes a new approach to the use of particle swarm optimisation (PSO) for object classification problems. Instead of using PSO to evolve only a set of good parameter values for another machine learning method for object classification, the new approach developed in this paper can be used as a stand alone method for classification. Two new methods are developed in the new approach. The...
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