Comparison of the Airline Networks of India with ANI Based on Network Parameters

2019 ◽  
pp. 74-81
Author(s):  
Dimpee Baruah ◽  
Ankur Bharali
Keyword(s):  
Network Parameters ◽  
Airline Networks

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).

Effect of Crosslinking on the Network Parameters, Swelling and Mechanical Properties of PVA-Borax and Poly (AM-co-HEMA) Double Network (DN) Hydrogels

2019 ◽  
Vol 35 (3) ◽  
pp. 371-391
Author(s):  
AKANSHA DIXIT ◽  
◽  
DIBYENDU S. BAG ◽  
DHIRENDRA KUMAR SHARMA ◽  
HARJEET SINGH ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Double Network ◽  
Network Parameters

Models of network formation

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Degree Distribution ◽  
Network Formation ◽  
Preferential Attachment ◽  
Network Size ◽  
Large Network ◽  
Citation Networks ◽  
Airline Networks ◽  
Attachment Model ◽  
Delivery Networks

This chapter describes models of the growth or formation of networks, with a particular focus on preferential attachment models. It starts with a discussion of the classic preferential attachment model for citation networks introduced by Price, including a complete derivation of the degree distribution in the limit of large network size. Subsequent sections introduce the Barabasi-Albert model and various generalized preferential attachment models, including models with addition or removal of extra nodes or edges and models with nonlinear preferential attachment. Also discussed are node copying models and models in which networks are formed by optimization processes, such as delivery networks or airline networks.

scholarly journals Estimation of the influence of spiking neural network parameters on classification accuracy using a genetic algorithm

2018 ◽  
Vol 145 ◽  
pp. 488-494 ◽  
Author(s):  
Aleksandr Sboev ◽  
Alexey Serenko ◽  
Roman Rybka ◽  
Danila Vlasov ◽  
Andrey Filchenkov
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Classification Accuracy ◽  
Spiking Neural Network ◽  
Network Parameters

scholarly journals Network parameters quantify loss of assemblage structure in human‐impacted lake ecosystems

2019 ◽  
Vol 25 (11) ◽  
pp. 3871-3882 ◽  
Author(s):  
Rong Wang ◽  
John A. Dearing ◽  
C. Patrick Doncaster ◽  
Xiangdong Yang ◽  
Enlou Zhang ◽  
...  
Keyword(s):  
Assemblage Structure ◽  
Lake Ecosystems ◽  
Network Parameters
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