scholarly journals On Signal Surveillance Analysis of Vibration Fault of Main Fan

2021 ◽  
Vol 1885 (4) ◽  
pp. 042069
Author(s):  
Yiyong Liang
Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 205
Author(s):  
Nicola Tarantino ◽  
Domenico G. Della Rocca ◽  
Nicole S. De Leon De La Cruz ◽  
Eric D. Manheimer ◽  
Michele Magnocavallo ◽  
...  

A recent surveillance analysis indicates that cardiac arrest/death occurs in ≈1:50,000 professional or semi-professional athletes, and the most common cause is attributable to life-threatening ventricular arrhythmias (VAs). It is critically important to diagnose any inherited/acquired cardiac disease, including coronary artery disease, since it frequently represents the arrhythmogenic substrate in a substantial part of the athletes presenting with major VAs. New insights indicate that athletes develop a specific electro-anatomical remodeling, with peculiar anatomic distribution and VAs patterns. However, because of the scarcity of clinical data concerning the natural history of VAs in sports performers, there are no dedicated recommendations for VA ablation. The treatment remains at the mercy of several individual factors, including the type of VA, the athlete’s age, and the operator’s expertise. With the present review, we aimed to illustrate the prevalence, electrocardiographic (ECG) features, and imaging correlations of the most common VAs in athletes, focusing on etiology, outcomes, and sports eligibility after catheter ablation.


2021 ◽  
Vol 13 (3) ◽  
pp. 72
Author(s):  
Shengbo Chen ◽  
Hongchang Zhang ◽  
Zhou Lei

Person re-identification (ReID) plays a significant role in video surveillance analysis. In the real world, due to illumination, occlusion, and deformation, pedestrian features extraction is the key to person ReID. Considering the shortcomings of existing methods in pedestrian features extraction, a method based on attention mechanism and context information fusion is proposed. A lightweight attention module is introduced into ResNet50 backbone network equipped with a small number of network parameters, which enhance the significant characteristics of person and suppress irrelevant information. Aiming at the problem of person context information loss due to the over depth of the network, a context information fusion module is designed to sample the shallow feature map of pedestrians and cascade with the high-level feature map. In order to improve the robustness, the model is trained by combining the loss of margin sample mining with the loss function of cross entropy. Experiments are carried out on datasets Market1501 and DukeMTMC-reID, our method achieves rank-1 accuracy of 95.9% on the Market1501 dataset, and 90.1% on the DukeMTMC-reID dataset, outperforming the current mainstream method in case of only using global feature.


2014 ◽  
Vol 27 (1) ◽  
pp. 1-8
Author(s):  
Rahime Burcu Nur ◽  
Duygu Ilhan ◽  
Erdoğan Fisekcioglu ◽  
Inci Oktay ◽  
Tülin Arun

2015 ◽  
Vol 193 (4S) ◽  
Author(s):  
Liam C. Macleod ◽  
William J. Ellis ◽  
Lisa F. Newcomb ◽  
Yingye Zheng ◽  
James D. Brooks ◽  
...  

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