scholarly journals Revisited Carmichael’s Reduced Totient Function

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1800
Author(s):  
Samir Brahim Belhaouari ◽  
Yassine Hamdi ◽  
Abdelouahed Hamdi
Keyword(s):  
Iterative Scheme

The modified Totient function of Carmichael λ(.) is revisited, where important properties have been highlighted. Particularly, an iterative scheme is given for calculating the λ(.) function. A comparison between the Euler φ and the reduced totient λ(.) functions aiming to quantify the reduction between is given.

A two-scale iterative scheme for a phase-field model for precipitation and dissolution in porous media

2021 ◽  
Vol 396 ◽  
pp. 125933
Author(s):  
Manuela Bastidas Olivares ◽  
Carina Bringedal ◽  
Iuliu Sorin Pop
Keyword(s):  
Porous Media ◽  
Phase Field ◽  
Field Model ◽  
Iterative Scheme ◽  
Phase Field Model

scholarly journals ClusterSLAM: A SLAM backend for simultaneous rigid body clustering and motion estimation

2021 ◽  
Author(s):  
Jiahui Huang ◽  
Sheng Yang ◽  
Zishuo Zhao ◽  
Yu-Kun Lai ◽  
Shi-Min Hu
Keyword(s):  
Motion Estimation ◽  
Rigid Body ◽  
Iterative Scheme ◽  
Dynamic Environments ◽  
Rigid Bodies ◽  
Factor Graph ◽  
Agglomerative Clustering ◽  
Multiple Objects ◽  
Graph Optimization ◽  
Dynamic Objects

AbstractWe present a practical backend for stereo visual SLAM which can simultaneously discover individual rigid bodies and compute their motions in dynamic environments. While recent factor graph based state optimization algorithms have shown their ability to robustly solve SLAM problems by treating dynamic objects as outliers, their dynamic motions are rarely considered. In this paper, we exploit the consensus of 3D motions for landmarks extracted from the same rigid body for clustering, and to identify static and dynamic objects in a unified manner. Specifically, our algorithm builds a noise-aware motion affinity matrix from landmarks, and uses agglomerative clustering to distinguish rigid bodies. Using decoupled factor graph optimization to revise their shapes and trajectories, we obtain an iterative scheme to update both cluster assignments and motion estimation reciprocally. Evaluations on both synthetic scenes and KITTI demonstrate the capability of our approach, and further experiments considering online efficiency also show the effectiveness of our method for simultaneously tracking ego-motion and multiple objects.

scholarly journals Entropic measure unveils country competitiveness and product specialization in the World trade web

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gianluca Teza ◽  
Michele Caraglio ◽  
Attilio L. Stella
Keyword(s):  
Iterative Scheme ◽  
Entropy Function ◽  
Bipartite Networks ◽  
Complexity Measures ◽  
Wide Range ◽  
Self Consistent ◽  
Set Up ◽  
Technical Features ◽  
Country Competitiveness ◽  
Entropic Measure

AbstractWe show how the Shannon entropy function can be used as a basis to set up complexity measures weighting the economic efficiency of countries and the specialization of products beyond bare diversification. This entropy function guarantees the existence of a fixed point which is rapidly reached by an iterative scheme converging to our self-consistent measures. Our approach naturally allows to decompose into inter-sectorial and intra-sectorial contributions the country competitivity measure if products are partitioned into larger categories. Besides outlining the technical features and advantages of the method, we describe a wide range of results arising from the analysis of the obtained rankings and we benchmark these observations against those established with other economical parameters. These comparisons allow to partition countries and products into various main typologies, with well-revealed characterizing features. Our methods have wide applicability to general problems of ranking in bipartite networks.

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