Swarm Measures of Performance: Social Network Parameters

2021 ◽  
Author(s):  
Elizabeth Mezzacappa ◽  
Ross Arnold ◽  
Melissa Jablonski ◽  
Jonathan Jablonski ◽  
Benjamin Abruzzo
Keyword(s):  
Social Network ◽  
Network Parameters ◽  
Measures Of Performance

scholarly journals Octodon degus kin and social structure

2015 ◽  
Vol 97 (2) ◽  
pp. 361-372 ◽  
Author(s):  
Garrett T. Davis ◽  
Rodrigo A. Vásquez ◽  
Elie Poulin ◽  
Esteban Oda ◽  
Enrique A. Bazán-León ◽  
...  
Keyword(s):  
Social Network ◽  
Genetic Relatedness ◽  
Social Groups ◽  
Clustering Coefficient ◽  
Habitat Characteristics ◽  
Redes Sociales ◽  
Octodon Degus ◽  
Local Conditions ◽  
Network Parameters ◽  
Los Grupos

Abstract A growing body of evidence showing that individuals of some social species live in non-kin groups suggests kin selection is not required in all species for sociality to evolve. Here, we investigate 2 populations of Octodon degus , a widespread South American rodent that has been shown to form kin and non-kin groups. We quantified genetic relatedness among individuals in 23 social groups across 2 populations as well as social network parameters (association, strength, and clustering coefficient) in order to determine if these aspects of sociality were driven by kinship. Additionally, we analyzed social network parameters relative to ecological conditions at burrow systems used by groups, to determine if ecological characteristics within each population could explain variation in sociality. We found that genetic relatedness among individuals within social groups was not significantly higher than genetic relatedness among randomly selected individuals in both populations, suggesting that non-kin structure of groups is common in degus. In both populations, we found significant relationships between the habitat characteristics of burrow systems and the social network characteristics of individuals inhabiting those burrow systems. Our results suggest that degu sociality is non-kin based and that degu social networks are influenced by local conditions. Es creciente la evidencia que apoya la ocurrencia de especies sociales donde los individuos no están emparentados genéticamente, lo que sugiere que la selección de parentesco no es indispensable para la evolución de la sociabilidad. En este estudio se examinaron dos poblaciones de Octodon degus , un roedor sudamericano donde los grupos sociales pueden o no incluir individuos cercanamente emparentados. Se cuantificó el parentesco genético entre individuos en 23 grupos sociales y en redes sociales de dos poblaciones para determinar si estos aspectos de la sociabilidad dependen del grado de parentesco. Además, se examinaron asociaciones entre los parámetros cuantificados de las redes sociales (asociación, fuerza, coeficiente de anidamiento) y las condiciones ecológicas a nivel de los sistemas de madriguera usados por cada grupo. El grado de parentesco genético dentro de los grupos no fue distinto del grado de parentesco entre individuos de la población tomados al azar, lo que apoya que una estructura de grupos no emparentada es la regla en Octodon degus . En ambas poblaciones se registró una asociación entre características ecológicas de los sistemas de madriguera y atributos de las redes sociales de los individuos que usan estas estructuras. Nuestros resultados indican que la sociabilidad en Octodon degus no está basada en relaciones de parentesco y que las redes sociales de estos animales dependen de las condiciones ecológicas.

Social Network Analysis of Different Parameters Derived From Real-Time Facebook Profiles

2018 ◽  
pp. 95-108
Author(s):  
Paramita Dey ◽  
Krishnendu Dutta
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Real Time ◽  
Social Structures ◽  
Graph Topology ◽  
Global Perspectives ◽  
Meaningful Information ◽  
Network Parameters ◽  
Online Social Media

With the advent of online social media, it is possible to collect large information and extract information. One of the powerful roles that networks play is to bridge gap between the local and the global perspectives. For example, social network analysis could be used to offer explanations for how simple processes at the level of individual nodes and links can have a global effect. Social networks like Twitter, Facebook, LinkedIn are very large in size with millions of vertices and billions of edges. To collect meaningful information from these densely connected graphs and huge volume of data, it is important to find proper topology of the network as well as conduct analysis based on different network parameters. The main objective of this work is to study the network parameters commonly used to explain social structures. We extract data from the three real-time Facebook accounts using the Netvizz application, analyze and evaluate their network parameters on some widely recognized graph topology using Gephi, a free and open source software.

scholarly journals Development of prediction models for upper and lower respiratory and gastrointestinal tract infections using social network parameters in middle-aged and older persons -The Maastricht Study-

2017 ◽  
Vol 146 (5) ◽  
pp. 533-543 ◽  
Author(s):  
S. Brinkhues ◽  
S. M. J. van Kuijk ◽  
C. J. P. A. Hoebe ◽  
P. H. M. Savelkoul ◽  
M. E. E. Kretzschmar ◽  
...  
Keyword(s):  
Social Network ◽  
Gastrointestinal Tract ◽  
Older Persons ◽  
Goodness Of Fit ◽  
Prediction Models ◽  
Respiratory Infections ◽  
Goodness Of Fit Test ◽  
Predictive Tool ◽  
Network Parameters ◽  
Tract Infections

AbstractThe ability to predict upper respiratory infections (URI), lower respiratory infections (LRI), and gastrointestinal tract infections (GI) in independently living older persons would greatly benefit population and individual health. Social network parameters have so far not been included in prediction models. Data were obtained from The Maastricht Study, a population-based cohort study (N = 3074, mean age (±s.d.) 59.8 ± 8.3, 48.8% women). We used multivariable logistic regression analysis to develop prediction models for self-reported symptomatic URI, LRI, and GI (past 2 months). We determined performance of the models by quantifying measures of discriminative ability and calibration. Overall, 953 individuals (31.0%) reported URI, 349 (11.4%) LRI, and 380 (12.4%) GI. The area under the curve was 64.7% (95% confidence interval (CI) 62.6–66.8%) for URI, 71.1% (95% CI 68.4–73.8) for LRI, and 64.2% (95% CI 61.3–67.1%) for GI. All models had good calibration (based on visual inspection of calibration plot, and Hosmer–Lemeshow goodness-of-fit test). Social network parameters were strong predictors for URI, LRI, and GI. Using social network parameters in prediction models for URI, LRI, and GI seems highly promising. Such parameters may be used as potential determinants that can be addressed in a practical intervention in older persons, or in a predictive tool to compute an individual's probability of infections.

The Network Parameters Of The T-System In Frog Muscle Measured With The High Voltage Electron Microscope.

1975 ◽  
Vol 33 ◽  
pp. 550-551 ◽  
Author(s):  
Brenda R. Eisenberg ◽  
Lee D. Peachey
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
High Voltage ◽  
Sartorius Muscle ◽  
High Voltage Electron Microscopy ◽  
Network Parameters ◽  
Voltage Electron ◽  
High Voltage Electron Microscope ◽  
High Voltage Electron ◽  
T System

Analysis of the electrical properties of the t-system requires knowledge of the geometry of the t-system network. It is now possible to determine the network parameters experimentally by use of high voltage electron microscopy. The t-system was marked with exogenous peroxidase. Conventional methods of electron microscopy were used to fix and embed the sartorius muscle from four frogs. Transverse slices 0.5-1.0 μm thick were viewed at an accelerating voltage of 1000 kV using the JEM-1000 high voltage electron microscope at Boulder, Colorado and prints at x5000 were used for analysis.The length of a t-branch (t) from node to node (Fig. 1a) was measured with a magnifier; at least 150 t-branches around 30 myofibrils were measured from each frog. The mean length of t is 0.90 ± 0.11 μm and the number of branches per myofibril is 5.4 ± 0.2 (mean ± SD, n = 4 frogs).

Relationships Between Subjective Ratings and Objective Measures of Performance in Speechreading Sentences

1997 ◽  
Vol 40 (4) ◽  
pp. 900-911 ◽  
Author(s):  
Marilyn E. Demorest ◽  
Lynne E. Bernstein
Keyword(s):  
Hearing Impairment ◽  
Performance Evaluations ◽  
Objective Measures ◽  
Large Individual ◽  
Subjective Ratings ◽  
Objective Performance ◽  
Phonetic Distance ◽  
Stimulus Length ◽  
Measures Of Performance ◽  
Confidence Scale

Ninety-six participants with normal hearing and 63 with severe-to-profound hearing impairment viewed 100 CID Sentences (Davis & Silverman, 1970) and 100 B-E Sentences (Bernstein & Eberhardt, 1986b). Objective measures included words correct, phonemes correct, and visual-phonetic distance between the stimulus and response. Subjective ratings were made on a 7-point confidence scale. Magnitude of validity coefficients ranged from .34 to .76 across materials, measures, and groups. Participants with hearing impairment had higher levels of objective performance, higher subjective ratings, and higher validity coefficients, although there were large individual differences. Regression analyses revealed that subjective ratings are predictable from stimulus length, response length, and objective performance. The ability of speechreaders to make valid performance evaluations was interpreted in terms of contemporary word recognition models.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social
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