Preliminary evidence for a lower brain age in children with attention-deficit/hyperactivity disorder
Frontiers in Psychiatry, 2022 Attention-deficit hyperactivity disorder (ADHD) is a debilitating disorder with apparent roots in abnormal brain development. Here, we quantified the level of individual brain maturation in children with ADHD using structural neuroimaging and a recently ...
Florian Kurth +13 more
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Vector machine techniques for modeling of seismic liquefaction data
Ain Shams Engineering Journal, 2014 This article employs three soft computing techniques, Support Vector Machine (SVM); Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM), for prediction of liquefaction susceptibility of soil.
Pijush Samui
doaj +1 more source
RVM-Based Human Action Classification in Crowd through Projection and Star Skeletonization
EURASIP Journal on Image and Video Processing, 2009 Detection of abnormal human actions in the crowd has become a critical problem in video surveillance applications like terrorist attacks. This paper proposes a real-time video surveillance system which is capable of classifying normal and abnormal ...
Yogameena B +4 more
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Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine [PDF]
, 2012 Machine performance degradation assessment and remaining useful life (RUL) prediction are of crucial importance in condition-based maintenance to reduce the maintenance cost and improve the reliability.
Yang, Bo-Suk +3 more
core +1 more source
Detecting expert’s eye using a multiple-kernel Relevance Vector Machine
Journal of Eye Movement Research, 2014 Decoding mental states from the pattern of neural activity or overt behavior is an intensely pursued goal. Here we applied machine learning to detect expertise from the oculomotor behavior of novice and expert billiard players during free viewing of a ...
Giuseppe Boccignone +4 more
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Prediction method of coal spontaneous combustion based on relevance vector machine
Gong-kuang zidonghua, 2020 In terms of coal spontaneous combustion degree prediction, the radial basis function (RBF) neural network method is complex in structure and easy to fall into local optimum, the kernel function based on support vector machine (SVM) is sensitive to ...
LIU Bao +4 more
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Fully Bayesian analysis of the relevance vector machine classification for imbalanced data problem
CAAI Transactions on Intelligence Technology, 2023 Relevance Vector Machine (RVM) is a supervised learning algorithm extended from Support Vector Machine based on the Bayesian sparsity model. Relevance Vector Machine classification suffers from theoretical limitations and computational inefficiency ...
Wenyang Wang +5 more
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Data Selection for Support Vector Machine Classifiers [PDF]
, 2000 The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classi er, is formulated as a concave minimization problem and solved by a nite number of linear programs.
Olvi L. Mangasarian +3 more
core +1 more source
Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Accelerating Relevance Vector Machine for Large-Scale Data on Spark
ITM Web of Conferences, 2017 Relevance vector machine (RVM) is a machine learning algorithm based on a sparse Bayesian framework, which performs well when running classification and regression tasks on small-scale datasets. However, RVM also has certain drawbacks which restricts its
Liu Fang, Zhong Hao, Li Si-Han
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