scholarly journals Emergence of Chimera in Multiplex Network

2016 ◽  
Vol 26 (07) ◽  
pp. 1650120 ◽  
Author(s):  
Saptarshi Ghosh ◽  
Sarika Jalan
Keyword(s):  
Real World ◽  
Coupling Strength ◽  
Network Size ◽  
Initial Condition ◽  
Control Parameters ◽  
Critical Coupling ◽  
Individual Layer ◽  
Chimera State ◽  
Multiplex Network ◽  
Multilayer Architecture

Chimera is a relatively new emerging phenomenon where coexistence of synchronous and asynchronous states is observed in symmetrically coupled dynamical units. We report the observation of the chimera state in multiplex networks where individual layer is represented by 1-d lattice with nonlocal interactions. While, multiplexing does not change the type of the chimera state and retains the multi-chimera state displayed by the isolated networks, it changes the regions of the incoherence. We investigate the emergence of coherent–incoherent bifurcation upon varying the control parameters, namely, the coupling strength and the network size. Additionally, we investigate the effect of initial condition on the dynamics of the chimera state. Using a measure based on the differences between the neighboring nodes which distinguishes smooth and nonsmooth spatial profiles, we find the critical coupling strength for the transition to the chimera state. Observing chimera in a multiplex network with one-to-one inter layer coupling is important to gain insight to many real world complex systems which inherently posses multilayer architecture.

scholarly journals Lightweight and Efficient Image Dehazing Network Guided by Transmission Estimation from Real-World Hazy Scenes

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 960
Author(s):  
Zhan Li ◽  
Jianhang Zhang ◽  
Ruibin Zhong ◽  
Bir Bhanu ◽  
Yuling Chen ◽  
...  
Keyword(s):  
Real World ◽  
Evaluation Criteria ◽  
Synthetic Data ◽  
Network Size ◽  
Image Dehazing ◽  
Depth Data ◽  
Network Training ◽  
Dark Channel ◽  
Processing Techniques ◽  
Transmission Estimation

In this paper, a transmission-guided lightweight neural network called TGL-Net is proposed for efficient image dehazing. Unlike most current dehazing methods that produce simulated transmission maps from depth data and haze-free images, in the proposed work, guided transmission maps are computed automatically using a filter-refined dark-channel-prior (F-DCP) method from real-world hazy images as a regularizer, which facilitates network training not only on synthetic data, but also on natural images. A double-error loss function that combines the errors of a transmission map with the errors of a dehazed image is used to guide network training. The method provides a feasible solution for introducing priors obtained from traditional non-learning-based image processing techniques as a guide for training deep neural networks. Extensive experimental results demonstrate that, in terms of several reference and non-reference evaluation criteria for real-world images, the proposed method can achieve state-of-the-art performance with a much smaller network size and with significant improvements in efficiency resulting from the training guidance.

Influence of parameters inhomogeneity on the existence of chimera states in a ring of nonlocally coupled maps

2021 ◽  
Vol 29 (6) ◽  
pp. 943-952
Author(s):  
Vasiliy Nechaev ◽  
◽  
Elena Rybalova ◽  
Galina Strelkova ◽  
◽  
...  
Keyword(s):  
Coupling Strength ◽  
Noise Intensity ◽  
Initial Conditions ◽  
Random Variable ◽  
Inhomogeneous Distribution ◽  
Control Parameters ◽  
Chimera States ◽  
Intensity Parameters ◽  
Different Characteristics ◽  
Ring Elements

The aim of the research is to study the influence of inhomogeneity in a control parameter of all partial elements in a ring of nonlocally coupled chaotic maps on the possibility of observing chimera states in the system and to compare the changes in regions of chimera realization using different methods of introducing the inhomogeneity. Methods. In this paper, snapshots of the system dynamics are constructed for various values of the parameters, as well as spatial distributions of cross-correlation coefficient values, which enable us to determine the regime observed in the system for these parameters. To improve the accuracy of the obtained results, the numerical studies are carried out for fifty different realizations of initial conditions of the ring elements. Results. It is shown that a fixed inhomogeneous distribution of the control parameters with increasing noise intensity leads to an increase in the range of the coupling strength where chimera states are observed. With this, the boundary lying in the region of strong coupling changes more significantly as compared with the case of weak coupling strength. The opposite effect is provided when the control parameters are permanently affected by noise. In this case increasing the noise intensity leads to a decrease in the interval of existence of chimera states. Additionally, the nature of the random variable distribution (normal or uniform one) does not strongly influence the observed changes in the ring dynamics. The regions of existence of chimera states are constructed in the plane of «coupling strength – noise intensity» parameters. Conclusion. We have studied how the region of existence of chimeras changes when the coupling strength between the ring elements is varied and when different characteristics of the inhomogeneous distribution of the control parameters are used. It has been shown that in order to increase the region of observing chimera states, the control parameters of the elements must be distributed inhomogeneously over the entire ensemble. To reduce this region, a constant noise effect on the control parameters should be used.

scholarly journals Online social network size is reflected in human brain structure

2011 ◽  
Vol 279 (1732) ◽  
pp. 1327-1334 ◽  
Author(s):  
R. Kanai ◽  
B. Bahrami ◽  
R. Roylance ◽  
G. Rees
Keyword(s):  
Social Network ◽  
Social Networking ◽  
Real World ◽  
Brain Structure ◽  
Grey Matter ◽  
Online Social Network ◽  
Network Size ◽  
Matter Density ◽  
Web Based ◽  
Social Network Size

The increasing ubiquity of web-based social networking services is a striking feature of modern human society. The degree to which individuals participate in these networks varies substantially for reasons that are unclear. Here, we show a biological basis for such variability by demonstrating that quantitative variation in the number of friends an individual declares on a web-based social networking service reliably predicted grey matter density in the right superior temporal sulcus, left middle temporal gyrus and entorhinal cortex. Such regions have been previously implicated in social perception and associative memory, respectively. We further show that variability in the size of such online friendship networks was significantly correlated with the size of more intimate real-world social groups. However, the brain regions we identified were specifically associated with online social network size, whereas the grey matter density of the amygdala was correlated both with online and real-world social network sizes. Taken together, our findings demonstrate that the size of an individual's online social network is closely linked to focal brain structure implicated in social cognition.

scholarly journals Crawling the Community Structure of Multiplex Networks

2019 ◽  
Vol 33 ◽  
pp. 168-175 ◽  
Author(s):  
Ricky Laishram ◽  
Jeremy D. Wendt ◽  
Sucheta Soundarajan
Keyword(s):  
Community Structure ◽  
Real World ◽  
Multiplex Networks ◽  
Data Collector ◽  
Multiplex Network ◽  
Multiple Levels ◽  
Novel Algorithm ◽  
Collection Costs

We examine the problem of crawling the community structure of a multiplex network containing multiple layers of edge relationships. While there has been a great deal of work examining community structure in general, and some work on the problem of sampling a network to preserve its community structure, to the best of our knowledge, this is the first work to consider this problem on multiplex networks. We consider the specific case in which the layers of a multiplex network have different query (collection) costs and reliabilities; and a data collector is interested in identifying the community structure of the most expensive layer. We propose MultiComSample (MCS), a novel algorithm for crawling a multiplex network. MCS uses multiple levels of multi-armed bandits to determine the best layers, communities and node roles for selecting nodes to query. We test MCS against six baseline algorithms on real-world multiplex networks, and achieved large gains in performance. For example, after consuming a budget equivalent to sampling 20% of the nodes in the expensive layer, we observe that MCS outperforms the best baseline by up to 49%.

scholarly journals An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Emir Žunić ◽  
Dženana Đonko ◽  
Emir Buza
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Prediction Method ◽  
Transportation Systems ◽  
Data Driven ◽  
Support Vector ◽  
Control Parameters ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Benchmark Instances

Transportation occupies one-third of the amount in the logistics costs, and accordingly transportation systems largely influence the performance of the logistics system. This work presents an adaptive data-driven innovative modular approach for solving the real-world vehicle routing problems (VRPs) in the field of logistics. The work consists of two basic units: (i) an innovative multistep algorithm for successful and entirely feasible solving of the VRPs in logistics and (ii) an adaptive approach for adjusting and setting up parameters and constants of the proposed algorithm. The proposed algorithm combines several data transformation approaches, heuristics, and Tabu search. Moreover, as the performance of the algorithm depends on the set of control parameters and constants, a predictive model that adaptively adjusts these parameters and constants according to historical data is proposed. A comparison of the acquired results has been made using the decision support system with predictive models: generalized linear models (GLMs) and support vector machine (SVM). The algorithm, along with the control parameters, which uses the prediction method, was acquired and was incorporated into a web-based enterprise system, which is in use in several big distribution companies in Bosnia and Herzegovina. The results of the proposed algorithm were compared with a set of benchmark instances and validated over real benchmark instances as well. The successful feasibility of the given routes, in a real environment, is also presented.

Effects of Damping Ratio and Critical Coupling Strength on Pogo Instability

2016 ◽  
Vol 53 (2) ◽  
pp. 370-379 ◽  
Author(s):  
Shujun Tan ◽  
Qingwei Wang ◽  
Zhigang Wu
Keyword(s):  
Coupling Strength ◽  
Damping Ratio ◽  
Critical Coupling

scholarly journals Enhancing synchrony in multiplex network due to rewiring frequency

2019 ◽  
Vol 475 (2230) ◽  
pp. 20190460 ◽  
Author(s):  
Sarbendu Rakshit ◽  
Bidesh K. Bera ◽  
Jürgen Kurths ◽  
Dibakar Ghosh
Keyword(s):  
Numerical Simulations ◽  
Local Stability ◽  
Lorenz System ◽  
Stability Conditions ◽  
Network Architectures ◽  
Stability Function ◽  
Individual Layer ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Different Types

Most of the previous studies on synchrony in multiplex networks have been investigated using different types of intralayer network architectures which are either static or temporal. Effect of a temporal layer on intralayer synchrony in a multilayered network still remains elusive. In this paper, we discuss intralayer synchrony in a multiplex network consisting of static and temporal layers and how a temporal layer influences other static layers to enhance synchrony simultaneously. We analytically derive local stability conditions for intralayer synchrony based on the master stability function approach. The analytically derived results are illustrated by numerical simulations on up to five-layers multiplex networks with the paradigmatic Lorenz system as the node dynamics in each individual layer.

A new parameter setting-based modified differential evolution for function optimization

2020 ◽  
Vol 11 (04) ◽  
pp. 2050029
Author(s):  
Sukanta Nama ◽  
Apu Kumar Saha
Keyword(s):  
Performance Evaluation ◽  
Differential Evolution ◽  
Real World ◽  
Population Based ◽  
Function Optimization ◽  
Mutation Operator ◽  
Control Parameters ◽  
Test Results ◽  
Parameter Setting ◽  
De Algorithm

The population-based efficient iterative evolutionary algorithm (EA) is differential evolution (DE). It has fewer control parameters but is useful when dealing with complex problems of optimization in the real world. A great deal of progress has already been made and implemented in various fields of engineering and science. Nevertheless, DE is prone to the setting of control parameters in its performance evaluation. Therefore, the appropriate adjustment of the time-consuming control parameters is necessary to achieve optimal DE efficiency. This research proposes a new version of the DE algorithm control parameters and mutation operator. For the justifiability of the suggested method, several benchmark functions are taken from the literature. The test results are contrasted with other literary algorithms.

scholarly journals Phase Synchronization Stability of Non-Homogeneous Low-Voltage Distribution Networks with Large-Scale Distributed Generations

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1257 ◽  
Author(s):  
Shi Chen ◽  
Hong Zhou ◽  
Jingang Lai ◽  
Yiwei Zhou ◽  
Chang Yu
Keyword(s):  
Power Law ◽  
Coupling Strength ◽  
Large Scale ◽  
Phase Synchronization ◽  
Distribution Networks ◽  
Critical Coupling ◽  
Power Law Distribution ◽  
Distributed Generations ◽  
Strength Formula ◽  
The Impact

The ideal distributed network composed of distributed generations (DGs) has unweighted and undirected interactions which omit the impact of the power grid structure and actual demand. Apparently, the coupling relationship between DGs, which is determined by line impedance, node voltage, and droop coefficient, is generally non-homogeneous. Motivated by this, this paper investigates the phase synchronization of an islanded network with large-scale DGs in a non-homogeneous condition. Furthermore, we explicitly deduce the critical coupling strength formula for different weighting cases via the synchronization condition. On this basis, three cases of Gaussian distribution, power-law distribution, and frequency-weighted distribution are analyzed. A synthetical analysis is also presented, which helps to identify the order parameter. Finally, this paper employs the numerical simulation methods to test the effectiveness of the critical coupling strength formula and the superiority over the power-law distribution.

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