spatial intensity
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2021 ◽  
Author(s):  
Michael McDonnell ◽  
James Grant-Jacob ◽  
Matthew Praeger ◽  
Robert Eason ◽  
Benjamin Mills


2021 ◽  
Author(s):  
Yezid Torres Moreno ◽  
Aristide Dogariu ◽  
Cristian Hernando Acevedo Cáceres


Author(s):  
Navaneethakrishna Makaram ◽  
Sridhar P. Arjunan ◽  
Dinesh Kumar ◽  
Ramakrishnan Swaminathan

In this, study, we have investigated to identify the muscle fatigue using spatial maps of High-Density Electromyography (HDEMG). The experiment involves subjects performing plantar flexion at 40% maximum voluntary contraction until fatigue. During the experiment, HDEMG signal was recorded from the tibialis anterior muscle. The monopolar and bipolar spatial intensity maps were extracted from the HDEMG signal. The random forest classifier with different tree configurations was tested to distinguish nonfatigue and fatigue condition. The results indicate that selected electrodes from the differential intensity map results in an accuracy of 83.3% with the number of trees set at 17. This method of spatial analysis of HDEMG signals may be extended to assess fatigue in real life scenarios.



2021 ◽  
Vol 68 (2) ◽  
pp. 116-123
Author(s):  
Yuhu Ren ◽  
Jimo Jian ◽  
Jing Wang ◽  
Cunguang Zhu ◽  
Wei Xia


Author(s):  
Nicoletta D’Angelo ◽  
Mauro Ferrante ◽  
Antonino Abbruzzo ◽  
Giada Adelfio

This paper aims at analyzing the spatial intensity in the distribution of stop locations of cruise passengers during their visit at the destination through a stochastic point process modelling approach on a linear network. Data collected through the integration of GPS tracking technology and questionnaire-based survey on cruise passengers visiting the city of Palermo are used, to identify the main determinants which characterize their stop locations pattern. The spatial intensity of stop locations is estimated through a Gibbs point process model, taking into account for both individual-related variables, contextual-level information, and for spatial interaction among stop points. The Berman-Turner device for maximum pseudolikelihood is considered, by using a quadrature scheme generated on the network. The approach used allows taking into account the linear network determined by the street configuration of the destination under analysis. The results show an influence of both socio-demographic and trip-related characteristics on the stop location patterns, as well as the relevance of distance from the main attractions, and potential interactions among cruise passengers in stop configuration. The proposed approach represents both improvements from the methodological perspective, related to the modelling of spatial point process on a linear network, and from the applied perspective, given that better knowledge of the determinants of spatial intensity of visitors’ stop locations in urban contexts may orient destination management policy.



2020 ◽  
Vol 15 (10) ◽  
pp. 105008
Author(s):  
Qingmei Wang ◽  
Xia Liang ◽  
Yingchun Wang ◽  
Ligang Wang ◽  
Arvin R Mosier ◽  
...  


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