THE OPTIMUM OF SYNCHRONIZABILITY IN COMPLEX NETWORKS

2010 ◽  
Vol 21 (10) ◽  
pp. 1255-1261 ◽  
Author(s):  
PEI-JIE MA ◽  
BING-HONG WANG
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Coupling Strength ◽  
Laplacian Matrix ◽  
Weight Matrix ◽  
Exact Form ◽  
Eigenvalues And Eigenvectors ◽  
Optimal Network ◽  
The One ◽  
Insight Into

In this brief report, we investigate the synchronizability of the complex network. In order to optimize the synchronizability, we propose a method by introducing a weight matrix, which makes the synchronized states stable for the widest range of the overall coupling strength. We give a proof in mathematics and gain the exact form of the weight matrix, which is equal to Lβ. Matrix L is the one that describes the optimal network and matrix β is constructed by the eigenvalues and eigenvectors of the usual Laplacian matrix. This result may provide us insight into the synchronization of complex network more deeply.

scholarly journals Subsymbolic methods for data mining in hydraulic engineering

2000 ◽  
Vol 2 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Anthony W. Minns
Keyword(s):  
Experimental Data ◽  
Data Mining ◽  
A Priori ◽  
Empirical Relation ◽  
Exact Form ◽  
Symbolic Form ◽  
Process Characteristics ◽  
Evolutionary Force ◽  
The One ◽  
Insight Into

This paper describes the results of experiments with artificial neural networks (ANNs) and genetic programming (GP) applied to some problems of data mining. It is shown how these subsymbolic methods can discover usable relations in measured and experimental data with little or no a priori knowledge of the governing physical process characteristics. On the one hand, the ANN does not explicitly identify a form of model but this form is implicit in the ANN, being encoded within the distribution of weights. However, in cases where the exact form of the empirical relation is not considered as important as the ability of the formula to map the experimental data accurately, the ANN provides a very efficient approach. Furthermore, it is demonstrated how numerical schemes, and thus partial differential equations, may be derived directly from data by interpreting the weight distribution within a trained ANN. On the other hand, GP evolutionary force is directed towards the creation of models that take a symbolic form. The resulting symbolic expressions are generally less accurate than the ANN in mapping the experimental data, however, these expressions may sometimes be more easily examined to provide insight into the processes that created the data. An example is used to demonstrate how GP can generate a wide variety of formulae, of which some may provide genuine insight while others may be quite useless.

scholarly journals Eigenvalue-based entropy in directed complex networks

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251993
Author(s):  
Yan Sun ◽  
Haixing Zhao ◽  
Jing Liang ◽  
Xiujuan Ma
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Network Models ◽  
Small World ◽  
Laplacian Matrix ◽  
Directed Network ◽  
Small World Network ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network

Entropy is an important index for describing the structure, function, and evolution of network. The existing research on entropy is primarily applied to undirected networks. Compared with an undirected network, a directed network involves a special asymmetric transfer. The research on the entropy of directed networks is very significant to effectively quantify the structural information of the whole network. Typical complex network models include nearest-neighbour coupling network, small-world network, scale-free network, and random network. These network models are abstracted as undirected graphs without considering the direction of node connection. For complex networks, modeling through the direction of network nodes is extremely challenging. In this paper, based on these typical models of complex network, a directed network model considering node connection in-direction is proposed, and the eigenvalue entropies of three matrices in the directed network is defined and studied, where the three matrices are adjacency matrix, in-degree Laplacian matrix and in-degree signless Laplacian matrix. The eigenvalue-based entropies of three matrices are calculated in directed nearest-neighbor coupling, directed small world, directed scale-free and directed random networks. Through the simulation experiment on the real directed network, the result shows that the eigenvalue entropy of the real directed network is between the eigenvalue entropy of directed scale-free network and directed small-world network.

scholarly journals The Dominant Nodes Index in Shortest Paths (DNISP) as A Local Measure of Source Looking for the Target in Complex Networks

2020 ◽  
Vol 14 (19) ◽  
pp. 97
Author(s):  
Hussein L. Hasan ◽  
Salah A. Albermany
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Shortest Path ◽  
Information Diffusion ◽  
Shortest Paths ◽  
Local Scale ◽  
Information Flows ◽  
Local Measure ◽  
Control Value ◽  
Insight Into

<p>When there are multiple alternate shortest paths between any two nodes in a complex network, there is a need to know details about the content of the paths and the dominance of the nodes within it, this need comes to maximize, control and speed of the information diffusion. This paper discusses the creation of a new special measure as a local scale for any X node in the network. This measure will give each neighbour of the node X a domination value to access the rest of the network, in other words any nodes included in the shortest path (X,Y) will be given a control value, taking into account the existence of more than one shortest path between (X,Y). Such a measure is called a DNISP, which stands for Dominant Nodes Index in Shortest Paths. The X-node needs to examine all shortest paths that connect it with any other nodes across the ones that are directly associated with it. This measure provides an insight into how information flows between nodes according to dominant values with each node.</p>

scholarly journals New Pinning Synchronization of Complex Networks with Time-Varying Coupling Strength and Nondelayed and Delayed Coupling

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Guoliang Wang ◽  
Zhongbao Yue ◽  
Feng Wang
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Coupling Strength ◽  
Time Varying ◽  
Numerical Example ◽  
Synchronization Problem ◽  
Delayed Coupling

The pinning synchronization problem for a class of complex networks is studied by a stochastic viewpoint, in which both time-varying coupling strength and nondelayed and delayed coupling are included. Different from the traditionally similar methods, its interval is separated into two subintervals and described by a Bernoulli variable. Both bounds and switching probability of such subintervals are contained. Particularly, the nondelayed and delayed couplings occur alternately in which another independent Bernoulli variable is introduced. Then, a new kind of pinning controller without time-varying coupling strength signal is developed, in which only its bounds and probabilities are contained. When such probabilities are unavailable, two different kinds of adaption laws are established to make the complex network globally synchronous. Finally, the validity of the presented methods is proved through a numerical example.

When Romania met the Cohesion Policy. Regional governance in-between national conventions and European ideals

2018 ◽  
Vol 18 (2) ◽  
pp. 127-148 ◽  
Author(s):  
Alexandru Brad
Keyword(s):  
Regional Policy ◽  
Development Planning ◽  
Regional Governance ◽  
Theoretical Ground ◽  
Cohesion Policy ◽  
Redistributive Policy ◽  
Policy Context ◽  
Core Areas ◽  
The One ◽  
Insight Into

This article is about the practice of territorial governance emerging at the junction of European Union-sanctioned ideals and Romanian development-planning traditions. On the one hand, the European agenda emphasises a smart, inclusive, sustainable model of economic growth. However, the persisting centralised workings of the Romanian state significantly alters the scope of regional interventions. As such, while core cities grew their economies swiftly, peripheral places were left in an unrelenting stagnation. My first aim is to provide a theoretical ground for a practicecentred approach to understanding territorial governance. Second, by drawing on Romania’s regional policy context as an example, I give an insight into how practices of partnership and competition fare in a context of ongoing territorial polarisation. I conclude by emphasising the need for a regional redistributive policy mechanism, one which should enable and assist non-core areas to access capacities for defining and implementing development projects.

Marx, Silk Poems, and the Pretext of Qualities

2020 ◽  
Vol 151 (1) ◽  
pp. 96-126
Author(s):  
Kathryn Crim
Keyword(s):  
The Other ◽  
Use Value ◽  
Working Day ◽  
The One ◽  
Insight Into

Karl Marx’s comments on silk manufacture in “The Working Day” chapter of Capital, volume 1, demonstrate how “quality”—usually associated with “use value”—has been mobilized by capital to naturalize industrialized labor. Putting his insight into conversation with a recent multimedia poetic project, Jen Bervin’s Silk Poems (2016–17), this essay examines the homology between, on the one hand, poetry’s avowed task of fitting form to content and, on the other, the ideology of labor that fits specific bodies to certain materials and tasks.

Information on evolutionary age in redundancy of complex network

2019 ◽  
Vol 33 (27) ◽  
pp. 1950331
Author(s):  
Shiguo Deng ◽  
Henggang Ren ◽  
Tongfeng Weng ◽  
Changgui Gu ◽  
Huijie Yang
Keyword(s):  
Principal Component Analysis ◽  
Complex Networks ◽  
Metabolic Network ◽  
Complex Network ◽  
Cellular Networks ◽  
Topological Structure ◽  
Quantitative Measure ◽  
Principal Component ◽  
Evolutionary Information ◽  
Local Patterns

Evolutionary processes of many complex networks in reality are dominated by duplication and divergence. This mechanism leads to redundant structures, i.e. some nodes share most of their neighbors and some local patterns are similar, called redundancy of network. An interesting reverse problem is to discover evolutionary information from the present topological structure. We propose a quantitative measure of redundancy of network from the perspective of principal component analysis. The redundancy of a community in the empirical human metabolic network is negatively and closely related with its evolutionary age, which is consistent with that for the communities in the modeling protein–protein network. This behavior can be used to find the evolutionary difference stored in cellular networks.

scholarly journals CNFE-SE: a novel approach combining complex network-based feature engineering and stacked ensemble to predict the success of intrauterine insemination and ranking the features

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sima Ranjbari ◽  
Toktam Khatibi ◽  
Ahmad Vosough Dizaji ◽  
Hesamoddin Sajadi ◽  
Mehdi Totonchi ◽  
...  
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Semen Quality ◽  
Intrauterine Insemination ◽  
Machine Learning Algorithms ◽  
Semen Parameters ◽  
Feature Engineering ◽  
Operating Characteristics ◽  
Scoring Method ◽  
Novel Approach

Abstract Background Intrauterine Insemination (IUI) outcome prediction is a challenging issue which the assisted reproductive technology (ART) practitioners are dealing with. Predicting the success or failure of IUI based on the couples' features can assist the physicians to make the appropriate decision for suggesting IUI to the couples or not and/or continuing the treatment or not for them. Many previous studies have been focused on predicting the in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) outcome using machine learning algorithms. But, to the best of our knowledge, a few studies have been focused on predicting the outcome of IUI. The main aim of this study is to propose an automatic classification and feature scoring method to predict intrauterine insemination (IUI) outcome and ranking the most significant features. Methods For this purpose, a novel approach combining complex network-based feature engineering and stacked ensemble (CNFE-SE) is proposed. Three complex networks are extracted considering the patients' data similarities. The feature engineering step is performed on the complex networks. The original feature set and/or the features engineered are fed to the proposed stacked ensemble to classify and predict IUI outcome for couples per IUI treatment cycle. Our study is a retrospective study of a 5-year couples' data undergoing IUI. Data is collected from Reproductive Biomedicine Research Center, Royan Institute describing 11,255 IUI treatment cycles for 8,360 couples. Our dataset includes the couples' demographic characteristics, historical data about the patients' diseases, the clinical diagnosis, the treatment plans and the prescribed drugs during the cycles, semen quality, laboratory tests and the clinical pregnancy outcome. Results Experimental results show that the proposed method outperforms the compared methods with Area under receiver operating characteristics curve (AUC) of 0.84 ± 0.01, sensitivity of 0.79 ± 0.01, specificity of 0.91 ± 0.01, and accuracy of 0.85 ± 0.01 for the prediction of IUI outcome. Conclusions The most important predictors for predicting IUI outcome are semen parameters (sperm motility and concentration) as well as female body mass index (BMI).

Relational Chase Procedures Interpreted as Resolution with Paramodulation1

1991 ◽  
Vol 15 (2) ◽  
pp. 123-138
Author(s):  
Joachim Biskup ◽  
Bernhard Convent
Keyword(s):  
Alternative Interpretation ◽  
Order Logic ◽  
First Order Logic ◽  
Inference Problem ◽  
First Order ◽  
Inference Problems ◽  
The One ◽  
The Relationship ◽  
Theoretical Foundations ◽  
Insight Into

In this paper the relationship between dependency theory and first-order logic is explored in order to show how relational chase procedures (i.e., algorithms to decide inference problems for dependencies) can be interpreted as clever implementations of well known refutation procedures of first-order logic with resolution and paramodulation. On the one hand this alternative interpretation provides a deeper insight into the theoretical foundations of chase procedures, whereas on the other hand it makes available an already well established theory with a great amount of known results and techniques to be used for further investigations of the inference problem for dependencies. Our presentation is a detailed and careful elaboration of an idea formerly outlined by Grant and Jacobs which up to now seems to be disregarded by the database community although it definitely deserves more attention.

Performance limitation of networked systems with controller and communication filter co-design

2016 ◽  
Vol 40 (4) ◽  
pp. 1167-1176 ◽  
Author(s):  
Jie Wu ◽  
Xi-Sheng Zhan ◽  
Xian-He Zhang ◽  
Tao Han ◽  
Hong-Liang Gao
Keyword(s):  
Networked Systems ◽  
Channel Noise ◽  
Frequency Domain Method ◽  
Minimum Phase ◽  
Error Signal ◽  
Optimal Network ◽  
Performance Limitation ◽  
The One ◽  
Theoretical Results ◽  
Two Parameter

This paper addresses the performance limitation problem of networked systems by co-designing the controller and communication filter. The tracking performance index is measured by the energy of the error signal. Explicit expressions of the performance limitation are obtained by applying the controller and communication filter co-design, and the optimal network filter is obtained by applying the frequency domain method. It is shown that the performance limitation is closely related to the unstable poles and the non-minimum phase zeros of a given plant under the one-parameter compensator structure, whereas, under the two-parameter compensator structure, the performance limitation is unrelated to the unstable poles of a given plant. It is also demonstrated that the performance limitation can be improved and the effect of the channel noise can be eliminated by using the controller and communication filter co-design. Finally, some typical examples are presented to illustrate the theoretical results.

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