The relation between degree-2160 spectral models of Earth’s gravitational and topographic potential: a guide on global correlation measures and their dependency on approximation effects

2017 ◽  
Vol 91 (10) ◽  
pp. 1179-1205 ◽  
Author(s):  
Christian Hirt ◽  
Moritz Rexer ◽  
Sten Claessens ◽  
Reiner Rummel
Keyword(s):  
Global Correlation ◽  
Spectral Models ◽  
Topographic Potential ◽  
Correlation Measures

Efficient global correlation measures for a collaborative filtering dataset

2018 ◽  
Vol 147 ◽  
pp. 36-42 ◽  
Author(s):  
Adrian Satja Kurdija ◽  
Marin Silic ◽  
Klemo Vladimir ◽  
Goran Delac
Keyword(s):  
Collaborative Filtering ◽  
Global Correlation ◽  
Correlation Measures

scholarly journals Are Mobility and COVID-19 Related? A Dynamic Analysis for Portuguese Districts

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 786
Author(s):  
António Casa Nova ◽  
Paulo Ferreira ◽  
Dora Almeida ◽  
Andreia Dionísio ◽  
Derick Quintino
Keyword(s):  
Time Series ◽  
Population Density ◽  
Research Work ◽  
Daily Basis ◽  
Dynamic Correlation ◽  
Global Correlation ◽  
Linear Relationships ◽  
Correlation Measures ◽  
Lower Population ◽  
Lower Population Density

In this research work, we propose to assess the dynamic correlation between different mobility indices, measured on a daily basis, and the new cases of COVID-19 in the different Portuguese districts. The analysis is based on global correlation measures, which capture linear and non-linear relationships in time series, in a robust and dynamic way, in a period without significant changes of non-pharmacological measures. The results show that mobility in retail and recreation, grocery and pharmacy, and public transport shows a higher correlation with new COVID-19 cases than mobility in parks, workplaces or residences. It should also be noted that this relationship is lower in districts with lower population density, which leads to the need for differentiated confinement policies in order to minimize the impacts of a terrible economic and social crisis.

scholarly journals Compressed pseudo-SLAM: pseudorange-integrated compressed simultaneous localisation and mapping for unmanned aerial vehicle navigation

2021 ◽  
pp. 1-13
Author(s):  
Jonghyuk Kim ◽  
Jose Guivant ◽  
Martin L. Sollie ◽  
Torleiv H. Bryne ◽  
Tor Arne Johansen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computational Cost ◽  
Satellite System ◽  
Measurement Unit ◽  
Electronic Systems ◽  
Computationally Efficient ◽  
Global Correlation ◽  
Aerial Vehicle ◽  
Correlation Information ◽  
Global Navigation Satellite

Abstract This paper addresses the fusion of the pseudorange/pseudorange rate observations from the global navigation satellite system and the inertial–visual simultaneous localisation and mapping (SLAM) to achieve reliable navigation of unmanned aerial vehicles. This work extends the previous work on a simulation-based study [Kim et al. (2017). Compressed fusion of GNSS and inertial navigation with simultaneous localisation and mapping. IEEE Aerospace and Electronic Systems Magazine, 32(8), 22–36] to a real-flight dataset collected from a fixed-wing unmanned aerial vehicle platform. The dataset consists of measurements from visual landmarks, an inertial measurement unit, and pseudorange and pseudorange rates. We propose a novel all-source navigation filter, termed a compressed pseudo-SLAM, which can seamlessly integrate all available information in a computationally efficient way. In this framework, a local map is dynamically defined around the vehicle, updating the vehicle and local landmark states within the region. A global map includes the rest of the landmarks and is updated at a much lower rate by accumulating (or compressing) the local-to-global correlation information within the filter. It will show that the horizontal navigation error is effectively constrained with one satellite vehicle and one landmark observation. The computational cost will be analysed, demonstrating the efficiency of the method.

NIR spectral models for early detection of bitter pit in asymptomatic ‘Fuji’ apples

2021 ◽  
Vol 280 ◽  
pp. 109945
Author(s):  
Miguel Rene Mogollón ◽  
Carolina Contreras ◽  
Sergio Tonetto de Freitas ◽  
Juan Pablo Zoffoli
Keyword(s):  
Early Detection ◽  
Spectral Models ◽  
Bitter Pit
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