Towards Locally Differentially Private Generic Graph Metric Estimation

2020 ◽  
Author(s):  
Qingqing Ye ◽  
Haibo Hu ◽  
Man Ho Au ◽  
Xiaofeng Meng ◽  
Xiaokui Xiao
Keyword(s):  
Graph Metric

scholarly journals Near-Optimal Compression for the Planar Graph Metric

2018 ◽  
pp. 530-549 ◽  
Author(s):  
Amir Abboud ◽  
Pawel Gawrychowski ◽  
Shay Mozes ◽  
Oren Weimann
Keyword(s):  
Planar Graph ◽  
Graph Metric

scholarly journals A Graph Metric for Model Predictive Control of Petri Nets

2018 ◽  
Vol 51 (2) ◽  
pp. 254-259
Author(s):  
M. Appel ◽  
U. Konigorski ◽  
M. Walther
Keyword(s):  
Model Predictive Control ◽  
Petri Nets ◽  
Predictive Control ◽  
Graph Metric

scholarly journals DIVISIBLE SANDPILE ON SIERPINSKI GASKET GRAPHS

Fractals ◽  
2019 ◽  
Vol 27 (03) ◽  
pp. 1950032
Author(s):  
WILFRIED HUSS ◽  
ECATERINA SAVA-HUSS
Keyword(s):  
Growth Model ◽  
Sierpinski Gasket ◽  
Internal Diffusion ◽  
Exact Representation ◽  
Sierpiński Gasket ◽  
Diffusion Limited Aggregation ◽  
Sandpile Model ◽  
Diffusion Limited ◽  
Graph Metric ◽  
Divisible Sandpile

The divisible sandpile model is a growth model on graphs that was introduced by Levine and Peres [Strong spherical asymptotics for rotor-router aggregation and the divisible sandpile, Potential Anal. 30(1) (2009) 1–27] as a tool to study internal diffusion limited aggregation. In this work, we investigate the shape of the divisible sandpile model on the graphical Sierpinski gasket [Formula: see text]. We show that the shape is a ball in the graph metric of [Formula: see text]. Moreover, we give an exact representation of the odometer function of the divisible sandpile.

scholarly journals Application of Graph Analytics for Simulations of Electronic Money Turnover: Solutions, Evaluations, Forecasts

2019 ◽  
Vol 224 ◽  
pp. 06006
Author(s):  
Olga E. Pyrkina ◽  
Sergey A. Zadadaev
Keyword(s):  
System Analysis ◽  
Real Life ◽  
Graph Model ◽  
Economic Security ◽  
Centrality Measures ◽  
Electronic Money ◽  
Graph Models ◽  
Graph Analytics ◽  
Network Nodes ◽  
Graph Metric

The graph model for electronic money turnover developed in this paper considers the system of electronic money turnover as a technological complex network. This network includes systems of electronic money payments, communications between bank and its clients, and interbank communications. The application of the graph models is based on its essential advantages such as an opportunity to expand this system to arbitrary size and visualization of the system links. While graph plotting provides us with the opportunity of carrying out qualitative (visual) system analysis, e computations of the graph metric allows performing a more quantitative analysis. The composite metric, created on the base of graph centrality measures and giving us possibilities of estimating and ranking potential risks, is considered as a foundation for methods of stability, quality and economic security control for systems of the electronic money turnover. A validity of this classification has been investigated and supported by the so-called crash tests, which simulate the random consecutive deleting of graph nodes represented in the real life by communication network nodes, for example, banks or other members of electronic money turnover system, and also by the analysis of the overall performance of the system.

Task-linked Diurnal Brain Network Reorganization in Older Adults: A Graph Theoretical Approach

2017 ◽  
Vol 29 (3) ◽  
pp. 560-572 ◽  
Author(s):  
John A. E. Anderson ◽  
Saman Sarraf ◽  
Tarek Amer ◽  
Buddhika Bellana ◽  
Vincent Man ◽  
...  
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Brain Activity ◽  
Brain Network ◽  
Time Of Day ◽  
Network Organization ◽  
Graph Metrics ◽  
Graph Metric ◽  
Graph Theoretical Approach ◽  
Brain Network Reorganization

Testing older adults in the morning generally improves behavioral performance relative to afternoon testing. Morning testing is also associated with brain activity similar to that of young adults. Here, we used graph theory to explore how time of day (TOD) affects the organization of brain networks in older adults across rest and task states. We used nodes from the automated anatomical labeling atlas to construct participant-specific correlation matrices of fMRI data obtained during 1-back tasks with interference and rest. We computed pairwise group differences for key graph metrics, including small-worldness and modularity. We found that older adults tested in the morning and young adults did not differ on any graph metric. Both of these groups differed from older adults tested in the afternoon during the tasks—but not rest. Specifically, the latter group had lower modularity and small-worldness (indices of more efficient network organization). Across all groups, higher modularity and small-worldness strongly correlated with reduced distractibility on an implicit priming task. Increasingly, TOD is seen as important for interpreting and reproducing neuroimaging results. Our study emphasizes how TOD affects brain network organization and executive control in older adults.

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