Correlation analysis of Trial of Org 10172 in acute stroke treatment classification and National Institutes of Health Stroke Scale score in acute cerebral infarction with risk factors.

Objective: The aim of this study was to investigate the correlation between the Trial of Org 10172 in acute stroke treatment classification and the National Institutes of Health Stroke Scale score of acute cerebral infarction as well as acute cerebral infarction's risk factors.

Methods: The clinical data of 3,996 patients with acute cerebral infarction hospitalized in Hebei Renqiu Kangjixintu Hospital from January 2014 to November 2018 were analyzed retrospectively. According to Trial of Org 10172 in acute stroke treatment, they were divided into five groups: arteriosclerosis, cardio cerebral embolism, arterial occlusion, other causes, and unknown causes.

Impact fault detection of gearbox based on variational mode decomposition and coupled underdamped stochastic resonance.

In the gear fault diagnosis, the emergence of periodic impulse components in vibration signals is an important symptom of gear failure. However, heavy background noise makes it difficult to extract the weak periodic impulse features. Therefore, the paper presents an impact fault detection method of gearbox by combining variational mode decomposition (VMD) with coupled underdamped stochastic resonance (CUSR) to extract the periodic impulse features.

Progressive Line Processing of Kernel RX Anomaly Detection Algorithm for Hyperspectral Imagery.

The Kernel-RX detector (KRXD) has attracted widespread interest in hyperspectral image processing with the utilization of nonlinear information. However, the kernelization of hyperspectral data leads to poor execution efficiency in KRXD. This paper presents an approach to the progressive line processing of KRXD (PLP-KRXD) that can perform KRXD line by line (the main data acquisition pattern).

A Weighted Spatial-Spectral Kernel RX Algorithm and Efficient Implementation on GPUs.

The kernel RX (KRX) detector proposed by Kwon and Nasrabadi exploits a kernel function to obtain a better detection performance. However, it still has two limits that can be improved. On the one hand, reasonable integration of spatial-spectral information can be used to further improve its detection accuracy.

Advanced similarity metric and its application to the band selection issue of multiple spectra identification.

A multiple spectra oriented similarity metric, referred to as n-dimensional solid spectral angle (NSSA), is addressed in this study. NSSA extends the traditional spectral angle metric (SAM)-calculating two spectra's angle-to the calculation of the high-dimensional solid angle jointly constituted by a set of spectra with any number of bands. Some significant inherent properties of NSSA are also discussed.