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Structured feature ranking for genomic marker identification accommodating multiple types of networks.
Biometrics
October 2024
Department of Urology, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai 200092, China.
Numerous statistical methods have been developed to search for genomic markers associated with the development, progression, and response to treatment of complex diseases. Among them, feature ranking plays a vital role due to its intuitive formulation and computational efficiency. However, most of the existing methods are based on the marginal importance of molecular predictors and share the limitation that the dependence (network) structures among predictors are not well accommodated, where a disease phenotype usually reflects various biological processes that interact in a complex network.
View Article and Find Full Text PDFPrediction of time-dependent bearing capacity of concrete pile in cohesive soil using optimized relevance vector machine and long short-term memory models.
Sci Rep
December 2024
Department of Geosciences, Geotechnology, and Materials Engineering for Resources, Graduate School of International Resource Sciences, Akita University, Akita, Japan.
The present investigation employs relevance vector machine (RVM) and long short-term memory (LSTM) models to predict the time-dependent bearing capacity of concrete piles. Each RVM model (SRVM) is configured by each linear, polynomial, gaussian, sigmoid, laplacian, and exponential kernel function. Each SRVM model has been optimized by each genetic (GA_SRVM) and particle swarm optimization (PSO_RVM) algorithm.
View Article and Find Full Text PDFEvent-triggered affine formation of second-order multi-agent systems via complex-valued Laplacian.
ISA Trans
December 2024
Key Laboratory of Intelligent Analysis and Decision on Complex Systems, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China. Electronic address:
This paper investigates event-triggered affine formation control of second-order multi-agent systems with directed communication graph. An approach based on complex-valued Laplacian is used as a means of avoiding the use of global information. Two event-triggered strategies are proposed, both of which are capable of achieving global convergence and forming the desired formation without Zeno-behavior, while also optimizing the utilization of resources.
View Article and Find Full Text PDFLMI approach of H consensus for multi-agent systems under Markov switching topology by dynamic output-feedback controller.
ISA Trans
December 2024
Department of Electrical Engineering, POSTECH, Gyungbuk Pohang 37673, Republic of Korea. Electronic address:
This study investigates the H consensus problem for multi-agent systems under Markov switching topology by designing a dynamic output-feedback (DOF) controller. First, an invariant property is presented to address the Markov switching topology utilizing the eigenvalues and eigenvectors of the Laplacian matrix. Second, the eigenvalues of each Laplacian matrix are regarded as bounded uncertainties, representing the variations between the second smallest eigenvalue and the largest eigenvalue, removing the effect of variable eigenvalues.
View Article and Find Full Text PDFSoft x-ray tomography using L1 regularization for MHD modes with limited sight lines in JT-60SA.
Rev Sci Instrum
December 2024
National Institute for Fusion Science, National Institutes of Natural Sciences, 322-6 Oroshi-cho, Toki 509-5292, Japan.
Soft x-ray (SX) tomography is a useful diagnostic in fusion research, and a multi-channel SX diagnostic will be installed in JT-60SA, the largest elongated tokamak in the world. However, in the SX diagnostic of JT-60SA, plasmas will be only viewed from the low field side and the upper side of plasmas; the sight lines are limited, which would be common in future devices as well as JT-60SA. This kind of limited sight lines is not preferred for SX tomography to investigate the spatial structure of magnetohydrodynamics (MHD) modes because inadequate information of plasmas makes artifacts in the reconstructed SX profiles.
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