Random Node Pair Sampling-Based Estimation of Average Path Lengths in Networks

2018 ◽  
Author(s):  
Luis E. Castro ◽  
Nazrul I. Shaikh
Keyword(s):  
Node Pair ◽  
Random Node ◽  
Path Lengths

Random Node Pair Sampling-Based Estimation of Average Path Lengths in Networks

2018 ◽  
Vol 9 (3) ◽  
pp. 27-51
Author(s):  
Luis E. Castro ◽  
Nazrul I. Shaikh
Keyword(s):  
Path Length ◽  
Network Size ◽  
Computational Time ◽  
Computationally Efficient ◽  
Node Pair ◽  
Random Node ◽  
Speed Up ◽  
Sampling Algorithms ◽  
Path Lengths ◽  
Time Required

This article describes how the average path length (APL) of a network is an important metric that provides insights on the interconnectivity in a network and how much time and effort would be required for search and navigation on that network. However, the estimation of APL is time-consuming as its computational complexity scales nonlinearly with the network size. In this article, the authors develop a computationally efficient random node pair sampling algorithm that enables the estimation of APL with a specified precision and confidence. The proposed sampling algorithms provide a speed-up factor ranging from 240-750 for networks with more than 100,000 nodes. The authors also find that the computational time required for estimation APL does not necessarily increase with the network size; it shows an inverted U shape instead.

An improved magnetic prism design for a transmission electron microscope energy filter

1978 ◽  
Vol 36 (1) ◽  
pp. 40-41 ◽  
Author(s):  
John W. Andrew ◽  
F.P. Ottensmeyer ◽  
E. Martell
Keyword(s):  
Energy Resolution ◽  
Symmetry Plane ◽  
Fringe Field ◽  
Focal Distance ◽  
Electron Trajectories ◽  
Focusing Effect ◽  
Transmission Electron ◽  
Path Lengths ◽  
Electron Microscopes ◽  
Focusing Properties

Energy selecting electron microscopes of the Castaing-Henry prism-mirror-prism design suffer from a loss of image and energy resolution with increasing field of view. These effects can be qualitatively understood by examining the focusing properties of the prism shown in Fig. 1. A cone of electrons emerges from the entrance lens crossover A and impinges on the planar face of the prism. The task of the prism is to focus these electrons to a point B at a focal distance f2 from the side of the prism. Electrons traveling in the plane of the diagram (i.e., the symmetry plane of the prism) are focused toward point B due to the different path lengths of different electron trajectories in the triangularly shaped magnetic field. This is referred to as horizontal focusing; the better this focusing effect the better the energy resolution of the spectrometer. Electrons in a plane perpendicular to the diagram and containing the central ray of the incident cone are focused toward B by the curved fringe field of the prism.

Problems in Thin-Film X-ray Quantification

1990 ◽  
Vol 48 (2) ◽  
pp. 458-459
Author(s):  
J N Chapman ◽  
W A P Nicholson
Keyword(s):  
Thin Film ◽  
Specimen Thickness ◽  
X Rays ◽  
Characteristic Peak ◽  
Local Composition ◽  
X Ray ◽  
Measured Ratio ◽  
Path Lengths ◽  
Composition Changes

Energy dispersive x-ray microanalysis (EDX) is widely used for the quantitative determination of local composition in thin film specimens. Extraction of quantitative data is usually accomplished by relating the ratio of the number of atoms of two species A and B in the volume excited by the electron beam (nA/nB) to the corresponding ratio of detected characteristic photons (NA/NB) through the use of a k-factor. This leads to an expression of the form nA/nB = kAB NA/NB where kAB is a measure of the relative efficiency with which x-rays are generated and detected from the two species.Errors in thin film x-ray quantification can arise from uncertainties in both NA/NB and kAB. In addition to the inevitable statistical errors, particularly severe problems arise in accurately determining the former if (i) mass loss occurs during spectrum acquisition so that the composition changes as irradiation proceeds, (ii) the characteristic peak from one of the minority components of interest is overlapped by the much larger peak from a majority component, (iii) the measured ratio varies significantly with specimen thickness as a result of electron channeling, or (iv) varying absorption corrections are required due to photons generated at different points having to traverse different path lengths through specimens of irregular and unknown topography on their way to the detector.

scholarly journals Modeling and evaluating beat gestures for social robots

2021 ◽  
Author(s):  
Unai Zabala ◽  
Igor Rodriguez ◽  
José María Martínez-Otzeta ◽  
Elena Lazkano
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Desirable Feature ◽  
Quantitative Results ◽  
Path Lengths ◽  
End Effectors ◽  
The One ◽  
Made In

AbstractNatural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemented by the Fréchet Gesture Distance (FGD) that aims to measure the fidelity of the generated gestures with respect to the provided ones. Results show that the described system is able to learn natural gestures just by observation and improves the one developed with a simpler motion capture system. The quantitative results are sustained by questionnaire based human evaluation.

scholarly journals An Algorithm Based on Loop Cutting Contribution Function for Loop Cutset Problem in Bayesian Network

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 462
Author(s):  
Jie Wei ◽  
Yufeng Nie ◽  
Wenxian Xie
Keyword(s):  
Bayesian Inference ◽  
Bayesian Network ◽  
Network Structure ◽  
Computational Efficiency ◽  
Numerical Experiments ◽  
Global Perspective ◽  
Node Pair ◽  
Bayesian Network Structure ◽  
Network Structure Analysis ◽  
Contribution Index

The loop cutset solving algorithm in the Bayesian network is particularly important for Bayesian inference. This paper proposes an algorithm for solving the approximate minimum loop cutset based on the loop cutting contribution index. Compared with the existing algorithms, the algorithm uses the loop cutting contribution index of nodes and node-pairs to analyze nodes from a global perspective, and select loop cutset candidates with node-pair as the unit. The algorithm uses the parameter μ to control the range of node pairs, and the parameter ω to control the selection conditions of the node pairs, so that the algorithm can adjust the parameters according to the size of the Bayesian networks, which ensures computational efficiency. The numerical experiments show that the calculation efficiency of the algorithm is significantly improved when it is consistent with the accuracy of the existing algorithm; the experiments also studied the influence of parameter settings on calculation efficiency using trend analysis and two-way analysis of variance. The loop cutset solving algorithm based on the loop cutting contribution index uses the node-pair as the unit to solve the loop cutset, which helps to improve the efficiency of Bayesian inference and Bayesian network structure analysis.

scholarly journals Subgraphs of Interest Social Networks for Diffusion Dynamics Prediction

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 492
Author(s):  
Valentina Y. Guleva ◽  
Polina O. Andreeva ◽  
Danila A. Vaganov
Keyword(s):  
Social Networks ◽  
Sampling Method ◽  
Building Blocks ◽  
Global Dynamics ◽  
Diffusion Dynamics ◽  
Different Types ◽  
Prediction And Control ◽  
Path Lengths ◽  
And Control ◽  
Diffusion Prediction

Finding the building blocks of real-world networks contributes to the understanding of their formation process and related dynamical processes, which is related to prediction and control tasks. We explore different types of social networks, demonstrating high structural variability, and aim to extract and see their minimal building blocks, which are able to reproduce supergraph structural and dynamical properties, so as to be appropriate for diffusion prediction for the whole graph on the base of its small subgraph. For this purpose, we determine topological and functional formal criteria and explore sampling techniques. Using the method that provides the best correspondence to both criteria, we explore the building blocks of interest networks. The best sampling method allows one to extract subgraphs of optimal 30 nodes, which reproduce path lengths, clustering, and degree particularities of an initial graph. The extracted subgraphs are different for the considered interest networks, and provide interesting material for the global dynamics exploration on the mesoscale base.

Pillar Cuvettes: Capillary-Filled, Microliter Quartz Cuvettes with Microscale Path Lengths for Optical Spectroscopy

2015 ◽  
Vol 87 (9) ◽  
pp. 4757-4764 ◽  
Author(s):  
Gregor Holzner ◽  
Frederik Hermanus Kriel ◽  
Craig Priest
Keyword(s):  
Optical Spectroscopy ◽  
Path Lengths

The ν1 Band of Carbon Dioxide in Pressure-Induced Absorption. II. Density and Temperature Dependence of the Intensity; Critical Phenomena

1972 ◽  
Vol 50 (12) ◽  
pp. 1355-1362 ◽  
Author(s):  
L. Mannik ◽  
J. C. Stryland
Keyword(s):  
Carbon Dioxide ◽  
Absorption Coefficient ◽  
Density Range ◽  
Induced Absorption ◽  
Lennard Jones ◽  
Molecular Potential ◽  
Band Profile ◽  
Gaseous Carbon Dioxide ◽  
Interaction Term ◽  
Path Lengths

The ν1 band of gaseous carbon dioxide has been studied in pressure-induced absorption at temperatures of ~ 190, ~ 300, and ~ 470 K, over a density range from 0.5 to 300 amagat, and with path lengths from 0.007 to 56 m. The observed temperature variation of the binary absorption coefficient can be satisfactorily accounted for only by adding a quadrupole–quadrupole interaction term to the usual Lennard–Jones model for the inter-molecular potential. The band profile is in agreement with the theory of quadrupole-induced absorption. There is some increase in the intensity of the band near the critical point due to the divergence of the correlation length. A very marked increase in the intensity is possibly prevented by the "cancellation effect".

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