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Books on the topic 'Network Correlations'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Armitage, Emily G., Helen L. Kotze, and Kaye J. Williams. Correlation-based network analysis of cancer metabolism. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0615-4.

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2

Armitage, Emily G. Correlation-based network analysis of cancer metabolism: A new systems biology approach in metabolomics. New York: Springer, 2014.

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3

Hammami, Manel. Level Doubling Network and Ripple Correlation Control MPPT Algorithm for Grid-Connected Photovoltaic Systems. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10492-4.

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4

Aizer, Anna. Networks or neighborhoods?: Correlations in the use of publicly-funded maternity care in California. Cambridge, MA: National Bureau of Economic Research, 2002.

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5

O'Callaghan, Peter. Demonstration of combination of expert system paradigms for telecommunications network alarm correlation and fault diagnosis. (s.l: The Author), 1996.

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6

Intrusion detection: An introduction to Internet surveillance, correlation, traps, trace back, and response. Sparta, N.J: Intrusion.Net Books, 1998.

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7

History now: Online explorations in western civilization : correlation guide with access code for western civilization. Sputhbank, Victoria, Australia: Thomson Wadsworth, 2005.

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8

Die Berechnung der Welt: Von der Weltformel zu Big Data. München: C.H. Beck, 2014.

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9

Cronley, Thomas J. The use of neural networks as a method of correlating thermal fluid data to provide useful information on thermal systems. Monterey, Calif: Naval Postgraduate School, 2000.

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10

Ikryannikov, Valentin, and Aleksey Barykin. Problems of standardization in the implementation of the provisions of the Technical regulations of the Russian Federation. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1194152.

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The book provides the results of a study of standardization in the implementation of national technical regulations of the Russian Federation "About fire safety", "On safety of buildings and structures", "On safety of gas distribution networks and gas consumption, On the safety of marine transport", "On safety of inland water transport" and the Technical regulations on tobacco products. The study was the analysis and correlation of the objects and requirements of technical regulations, the approved lists of documents for standardization adopted in 2016-2020 codes of practice, national, intergovernmental, international and regional standards, codes, national standards, the collection of information on enforcement practices and suggestions from industry stakeholders and generalization of the obtained data. According to the results of the study, the key and organizational and methodological problems of standardization in the field of technical regulation are identified, and current directions for improving standardization and national technical regulations are identified. It is of interest to a wide range of specialists in the field of standardization, technical regulation and public administration, and can be used in the preparation of training programs and manuals for bachelor's, master's, additional professional education and MBA programs.

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11

Pawar, Akhilesh. Probability And Statistics. New Delhi, India: Campus Books International, 2011.

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12

Bianconi, Ginestra. Structural Correlations of Multiplex Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0007.

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Multiplex networks encode relevant information in their correlated structure, including interlayer degree correlation, link overlap, weight–topology correlations in weighted multiplex networks and activity of the nodes. Interlayer degree correlations among a pair of layers indicates for instance whether or not the hub nodes of one layer are also hub nodes in the other. Link overlap indicates that a finite fraction of nodes are connected in more than one layer. Weight–topology correlations of weighted complex networks reveal that the weight of the links is not random, but often correlated with the link overlap. Finally, the nodes of a multiplex network might be connected only in a subset of the network, leading to a heterogeneity node activity. This chapter identifies the main multiplex network measures for characterizing these correlations, and evaluates their significance using statistical and information theory methods and novel multiplex network measures, including multilinks and multidegrees.

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13

Central Autonomic Network: Functional Organization and Clinical Correlations. Futura Publishing Company, 1997.

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14

Bianconi, Ginestra. Multilayer Network Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0010.

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This chapter presents the existing modelling frameworks for multiplex and multilayer networks. Multiplex network models are divided into growing multiplex network models and null models of multiplex networks. Growing multiplex networks are here shown to explain the main dynamical rules responsible to the emergent properties of multiplex networks, including the scale-free degree distribution, interlayer degree correlations and multilayer communities. Null models of multiplex networks are described in the context of maximum-entropy multiplex network ensembles. Randomization algorithms to test the relevant of network properties against null models are here described. Moreover, Multi-slice temporal networks Models capturing main properties of real temporal network data are presented. Finally, null models of general multilayer networks and networks of networks are characterized.

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15

Bianconi, Ginestra. Interdependent Multilayer Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0011.

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This chapter characterizes interdependent multilayer networks and their increased fragility. Interdependent networks are stylized models that can represent different complex systems, ranging from global infrastructures to molecular networks in the cell. When a fraction of nodes is initially damaged, interdependent networks are affected by dramatic cascades of failures that suddenly dismantle the multilayer network. The theory beyond this phenomenology is discussed in a pedagogical way by characterizing the percolation, discontinuous and hybrid transitions. The interplay between structure and function is studied in this context by considering multiplex networks without and with link overlap, and the effect of built-in correlations in the multilayer network structure. Finally, partial interdependencies and redundant interdependencies are discussed as major strategies to reduce the fragility of interdependent networks.

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16

Newman, Mark. The configuration model. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805090.003.0012.

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A discussion of the most fundamental of network models, the configuration model, which is a random graph model of a network with a specified degree sequence. Following a definition of the model a number of basic properties are derived, including the probability of an edge, the expected number of multiedges, the excess degree distribution, the friendship paradox, and the clustering coefficient. This is followed by derivations of some more advanced properties including the condition for the existence of a giant component, the size of the giant component, the average size of a small component, and the expected diameter. Generating function methods for network models are also introduced and used to perform some more advanced calculations, such as the calculation of the distribution of the number of second neighbors of a node and the complete distribution of sizes of small components. The chapter ends with a brief discussion of extensions of the configuration model to directed networks, bipartite networks, networks with degree correlations, networks with high clustering, and networks with community structure, among other possibilities.

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17

Bianconi, Ginestra. Classical Percolation, Generalized Percolation and Cascades. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0012.

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This chapter characterizes the robustness of multiplex and multilayer networks using classical percolation, directed percolation and antagonistic percolation. Classical percolation determines whether a finite fraction of nodes of the multilayer networks are connected by any type of connection. Classical percolation can be affected by multiplexity since the degree correlations among different layers can modulate the robustness of the entire multilayer network. Directed percolation describes the propagation of a disease requiring cooperative infection from different layers of the multiplex network. It displays a rich phase diagram including both continuous and discontinuous phase transitions. Antagonist percolation on a duplex network describes the competition between two layers and can give rise to hysteresis loops corresponding to phases that either one layer or the other can percolate Avalanches generated by the generalized Sandpile Model and Watts–Strogatz Model are also discussed, emphasizing their relevance for studying the stability of power grids and financial systems.

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18

Soramäki, Kimmo. Computational Models of Financial Networks, Risk, and Regulatory Policies. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.16.

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This chapter introduces the concept of financial networks and reviews research in three of the most active research areas of financial systems: interbank payment networks, interbank exposure networks, and asset correlation networks. The financial crisis of 2007-2008 revealed the intertwined nature of modern financial systems. A promising methodology for capturing and modeling connections in the financial system is provided by network theory. The intricate structure of linkages between financial institutions, among sectors of the economy, and across financial systems can conveniently be captured by using a network representation. Empirical research on describing existing networks is presented, as well as new modeling and simulation approaches for financial risk that take into account the complex structure of financial markets and infrastructures.

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19

Visualising Financial Correlation Networks Through Multiple Views. United Kingdom: SAGE Publications, Ltd., 2021. http://dx.doi.org/10.4135/9781529778458.

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20

Correlation Analysis of Fleet Information Warfare Center Network Incidents. Storming Media, 2001.

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21

Intrusion Detection and Correlation Advances in Information Security. Springer, 2010.

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22

Intrusion Detection and Correlation: Challenges and Solutions (Advances in Information Security). Springer, 2004.

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23

Comparisons of neural networks to standard techniques for image classification and correlation. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1994.

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24

Hammami, Manel. Level Doubling Network and Ripple Correlation Control MPPT Algorithm for Grid-Connected Photovoltaic Systems. Springer, 2019.

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25

Coolen, A. C. C., A. Annibale, and E. S. Roberts. Definitions and concepts. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0002.

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A network is specified by its links and nodes. However, it can be described by a much wider range of interesting and important topological features. This chapter introduces how a network can be characterized by its microscopic topological features and macroscopic topological features. Microscopic features introduced are degree and clustering coefficients. Macroscopic topological features introduced are the degree distribution; correlation between degrees of connected nodes; modularity; and, the eigenvalue spectrum (which counts the number of closed paths in the graph).

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26

Yamagishi, Toshio. Individualism-Collectivism, the Rule of Law, and General Trust. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190630782.003.0011.

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In the absence of legal protection, people establish collectivist social orders by forming strong ties with closely related individuals. When legal institutions which safeguard people’s rights outside closed relationships do not function, the need for mutual protection within a network of strong ties increases. Individualistic pursuits of opportunities outside the security of closed relationships requires universalistic legal protection. The rule of law thus promotes individualistic social orders that free people from dependence on such networks of strong ties to survive. This chapter proposes that in societies where the rule of law is deeply established, general trust encourages opportunity-seeking activities mediated by weak ties. Macro-level data show a positive correlation between general trust and the national mean individualism score. Furthermore, the degree of a nation’s political stability is positively linked to general trust in countries with a firm rule of law, but not in countries with a weak one.

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27

Amoroso, Edward G. Intrusion Detection: An Introduction to Internet Surveillance, Correlation, Trace Back, Traps, and Response. Intrusion.Net Books, 1999.

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28

Coolen, A. C. C., A. Annibale, and E. S. Roberts. Graphs with hard constraints: further applications and extensions. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0007.

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This chapter looks at further topics pertaining to the effective use of Markov Chain Monte Carlo to sample from hard- and soft-constrained exponential random graph models. The chapter considers the question of how moves can be sampled efficiently without introducing unintended bias. It is shown mathematically and numerically that apparently very similar methods of picking out moves can give rise to significant differences in the average topology of the networks generated by the MCMC process. The general discussion in complemented with pseudocode in the relevant section of the Algorithms chapter, which explicitly sets out some accurate and practical move sampling approaches. The chapter also describes how the MCMC equilibrium probabilities can be purposely deformed to, for example, target desired correlations between degrees of connected nodes. The mathematical exposition is complemented with graphs showing the results of numerical simulations.

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29

Anderson, James A. Association. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.003.0009.

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Association is the only concept in cognition that is as general, simple, and useful as classic theories in physics. Aristotle claimed that sensory-based events were the elementary units of memory. Such memories then became linked together through learning. The process of linkage—association—led to a powerful, creative computational structure. The ability to form networks of associations was unique to humans. William James extended Aristotle’s ideas by proposing a cognitive system that moved well beyond rote linkage in power and flexibility. Some of the mechanics of associative memory can be explained by synaptic change mechanisms such as the correlational Hebb synapse. Also discussed are examples of the problems caused by a “too good” memory along with use of associative memory aids like mnemonics.

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30

Rossi, Simone, Stefano F. Cappa, and Paolo Maria Rossini. Higher cognitive functions: memory and reasoning. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0032.

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Transcranial magnetic stimulation (TMS) is a sophisticated approach for interfering with human memory and reasoning due to its ability to transiently interfere with the functions of the specialized cortical network, especially when applied as repetitive (r)TMS. This article reviews TMS studies dealing with short-term retention, working memory, and with the episodic component of declarative memory. It also considers certain aspects of semantic memory and nonverbal reasoning. Furthermore, it discusses methodological considerations about the experimental designs, which can be used for the investigation of human cognitive functions. This article emphasizes the fact that higher cognitive functions provide an example as to how underlying physiological mechanisms cannot be fully disclosed by investigations based on a single technique. Studies to develop a true multimodal approach are being undertaken. In this light, behavioural interference studies will gain new power in combination with disruptive and correlational methodologies, establishing causality in a more sophisticated manner.

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31

Zucker, Robert A., and Sandra A. Brown, eds. The Oxford Handbook of Adolescent Substance Abuse. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199735662.001.0001.

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This Handbook explores the origins, development, and course of substance use as it emerges and unfolds in adolescence. Given the large causal network involved in adolescent substance use and abuse as well as its powerful impact, both at the time of use and in terms of the long term outcomes and complications of use, the domains covered by this volume range from infancy to adulthood, and from molecular genetics to social policy. The book is organized into eight sections, beginning with a review of the conceptual framework. It explains why a developmental framework is essential in understanding the adolescent period and goes on to discuss the epidemiology of substance use and abuse. It then examines the similarities and differences among the different drugs of abuse, namely: nicotine, alcohol, marijuana, prescription drugs, and other illicit drugs. The remaining sections deal with etiology and course in the context of adolescent development; the correlation between developmental tasks and adolescent substance abuse; clinical symptomatology and comorbidity; and the different assessment and intervention methods that have been developed to address the problem of adolescent alcohol and other drug abuse. These interventions include targeted prevention approaches, family-based treatments, twelve-step approaches, and inpatient and outpatient models. The book concludes with a chapter that analyzes the multi-level structure of public policy for the prevention of alcohol, tobacco, and drug problems among the youth.

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