In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
Abstract: This paper investigates the application of low altitude platform station (LAPS) and device-to-device (D2D) techniques in maritime emergency communications. The hovering LAPS acts as an ...
School of Pharmaceutical Sciences, University of Geneva, Rue Michel Servet 1, 1206 Genève, Switzerland Institute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University of Geneva, 1206 ...
Computer simulations of time–activity curve data were developed to evaluate the bias and SD of delay estimation approaches. A high-temporal-resolution IF (0.1-s sampling) representing a bolus of 18 ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. A five-step method is proposed for determining the design space of mesenchymal stem ...
Choosing a statistical model and accounting for uncertainty about this choice are important parts of the scientific process and are required for common statistical tasks such as parameter estimation, ...
Abstract: A new class of six-degree-of-freedom (DOFs) spatial parallel platform mechanism is considered in this paper. The architecture consists of a mobile platform connected to the base by three ...
A k-submodular function is a generalization of a submodular function, where the input consists of k disjoint subsets, instead of a single subset, of the domain. Many machine learning problems, ...
Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is ...
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