Modeling data flow in socio-information networks

2011 ◽  
Author(s):  
Ting Wang ◽  
Mudhakar Srivatsa ◽  
Dakshi Agrawal ◽  
Ling Liu
Keyword(s):  
Data Flow ◽  
Information Networks ◽  
Modeling Data

scholarly journals Modeling Data Flow Constraints for Design-Time Confidentiality Analyses

2021 ◽  
Author(s):  
Sebastian Hahner ◽  
Stephan Seifermann ◽  
Robert Heinrich ◽  
Maximilian Walter ◽  
Tomas Bures ◽  
...  
Keyword(s):  
Data Flow ◽  
Design Time ◽  
Modeling Data ◽  
Flow Constraints

Modeling Data Flow and Control Flow for DSP System Synthesis

1994 ◽  
pp. 219-259 ◽  
Author(s):  
Michaël F. X. B. Swaaij ◽  
Frank H. M. Franssen ◽  
Francky V. M. Catthoor ◽  
Hugo J. Man
Keyword(s):  
Data Flow ◽  
Control Flow ◽  
System Synthesis ◽  
Dsp System ◽  
Modeling Data ◽  
And Control

Data flow modeling, data mining and QSAR in high-throughput discovery of functional nanomaterials

2011 ◽  
Vol 35 (4) ◽  
pp. 671-678 ◽  
Author(s):  
Yang Yang ◽  
Tian Lin ◽  
Xiao L. Weng ◽  
Jawwad A. Darr ◽  
Xue Z. Wang
Keyword(s):  
Data Mining ◽  
High Throughput ◽  
Data Flow ◽  
Flow Modeling ◽  
Functional Nanomaterials ◽  
Modeling Data

Positional Estimation Within a Latent Space Model for Networks

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Susan Shortreed ◽  
Mark S. Handcock ◽  
Peter Hoff
Keyword(s):  
Random Effects ◽  
Network Data ◽  
Random Effects Models ◽  
Space Model ◽  
Network Analyses ◽  
Recent Advances ◽  
Latent Space ◽  
Latent Space Model ◽  
Modeling Data

Recent advances in latent space and related random effects models hold much promise for representing network data. The inherent dependency between ties in a network makes modeling data of this type difficult. In this article we consider a recently developed latent space model that is particularly appropriate for the visualization of networks. We suggest a new estimator of the latent positions and perform two network analyses, comparing four alternative estimators. We demonstrate a method of checking the validity of the positional estimates. These estimators are implemented via a package in the freeware statistical language R. The package allows researchers to efficiently fit the latent space model to data and to visualize the results.

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