The mean-shift method is a convenient mode-seeking method. Using a principle of the sample mean over an analysis window, or kernel, in a data space where samples are distributed with bias toward the densest direction of sample from the kernel center,...
When handling longitudinal data in regression models, we often encounter problems involving two interrelated response variables. These response variables may display an unknown curve shape in their relationship with one predictor variable, referred t...
Mean Shift is a flexible, non-parametric clustering algorithm that identifies dense regions in data through gradient ascent on a kernel density estimate. Its ability to detect arbitrarily shaped clusters without requiring prior knowledge of the numbe...
This paper presents a method for compiling the load spectrum of the transmission assembly of plug-in hybrid electric vehicles (PHEVs). Based on the analysis of the control strategy of the test vehicle, the power flow transmission route in the transmi...
This paper proposes an analytical design procedure for 2D FIR circular filter banks and also a novel, computationally efficient implementation of the designed filter bank based on a polyphase structure and a block filtering approach. The component fi...
Volunteer-contributed geographic data (VGI) is an important source of geospatial big data that support research and applications. A major concern on VGI data quality is that the underlying observation processes are inherently biased. Detecting observ...
We compare the usefulness of nonparametric and parametric methods of diameter distribution modeling. The nonparametric method was represented by the new tool—kernel estimator of cumulative distribution function with bandwidths of 1 cm (KE1), 2...