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  • 1
    Online Resource
    Online Resource
    On partial information retrieval: the unconstrained 100 prisoner problem
    Springer Science and Business Media LLC ; 2023
    In:  Acta Informatica Vol. 60, No. 2 ( 2023-06), p. 179-208
    Details
    In: Acta Informatica, Springer Science and Business Media LLC, Vol. 60, No. 2 ( 2023-06), p. 179-208
    Type of Medium: Online Resource
    ISSN: 0001-5903 , 1432-0525
    URL: Article
    DOI: 10.1007/s00236-022-00436-y
    RVK:
    SA 1075
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 1389024-4
    detail.hit.zdb_id: 120032-X
    SSG: 24,1
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  • 2
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    Divisibility patterns of natural numbers on a complex network
    Springer Science and Business Media LLC ; 2015
    In:  Scientific Reports Vol. 5, No. 1 ( 2015-09-16)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 5, No. 1 ( 2015-09-16)
    Abstract: Investigation of divisibility properties of natural numbers is one of the most important themes in the theory of numbers. Various tools have been developed over the centuries to discover and study the various patterns in the sequence of natural numbers in the context of divisibility. In the present paper, we study the divisibility of natural numbers using the framework of a growing complex network. In particular, using tools from the field of statistical inference, we show that the network is scale-free but has a non-stationary degree distribution. Along with this, we report a new kind of similarity pattern for the local clustering, which we call “stretching similarity”, in this network. We also show that the various characteristics like average degree, global clustering coefficient and assortativity coefficient of the network vary smoothly with the size of the network. Using analytical arguments we estimate the asymptotic behavior of global clustering and average degree which is validated using numerical analysis.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/srep14280
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2015
    detail.hit.zdb_id: 2615211-3
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  • 3
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    Complex networks with scale-free nature and hierarchical modularity
    Springer Science and Business Media LLC ; 2015
    In:  The European Physical Journal B Vol. 88, No. 9 ( 2015-9)
    Details
    In: The European Physical Journal B, Springer Science and Business Media LLC, Vol. 88, No. 9 ( 2015-9)
    Type of Medium: Online Resource
    ISSN: 1434-6028 , 1434-6036
    URL: Article
    DOI: 10.1140/epjb/e2015-60501-y
    RVK:
    UA 3858.B
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2015
    detail.hit.zdb_id: 1459068-2
    detail.hit.zdb_id: 1397768-4
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  • 4
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    Effect of money heterogeneity on resource dependency in complex networks
    IOP Publishing ; 2022
    In:  Europhysics Letters Vol. 139, No. 5 ( 2022-09-01), p. 51003-
    Details
    In: Europhysics Letters, IOP Publishing, Vol. 139, No. 5 ( 2022-09-01), p. 51003-
    Abstract: Exchange of resources among individual components of a system is fundamental to systems like a social network of humans and a network of cities and villages. For various reasons, the human society has come up with the notion of money as a proxy for the resources. Here we extend the model of resource dependencies in networks that was recently proposed by one of us, by incorporating the concept of money so that the vertices of a network can sell and buy required resources among themselves. We simulate the model using the configuration model as a substrate for homogeneous as well as heterogeneous degree distributions and using various exchange strategies. We show that a moderate amount of initial heterogeneity in the money on the vertices can significantly improve the survivability of Scale-free networks but not that of homogeneous networks like the Erdős-Rényi network. Our work is a step towards understanding the effect of presence of money on the resource distribution dynamics in complex networks.
    Type of Medium: Online Resource
    ISSN: 0295-5075 , 1286-4854
    URL: Article
    DOI: 10.1209/0295-5075/ac882a
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 1465366-7
    detail.hit.zdb_id: 165776-8
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  • 5
    Online Resource
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    A random interacting network model for complex networks
    Springer Science and Business Media LLC ; 2015
    In:  Scientific Reports Vol. 5, No. 1 ( 2015-12-11)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 5, No. 1 ( 2015-12-11)
    Abstract: We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/srep18183
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2015
    detail.hit.zdb_id: 2615211-3
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  • 6
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    Detecting abnormality in heart dynamics from multifractal analysis of ECG signals
    Springer Science and Business Media LLC ; 2017
    In:  Scientific Reports Vol. 7, No. 1 ( 2017-11-09)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 7, No. 1 ( 2017-11-09)
    Abstract: The characterization of heart dynamics with a view to distinguish abnormal from normal behavior is an interesting topic in clinical sciences. Here we present an analysis of the Electro-cardiogram (ECG) signals from several healthy and unhealthy subjects using the framework of dynamical systems approach to multifractal analysis. Our analysis differs from the conventional nonlinear analysis in that the information contained in the amplitude variations of the signal is being extracted and quantified. The results thus obtained reveal that the attractor underlying the dynamics of the heart has multifractal structure and the variations in the resultant multifractal spectra can clearly separate healthy subjects from unhealthy ones. We use supervised machine learning approach to build a model that predicts the group label of a new subject with very high accuracy on the basis of the multifractal parameters. By comparing the computed indices in the multifractal spectra with that of beat replicated data from the same ECG, we show how each ECG can be checked for variations within itself. The increased variability observed in the measures for the unhealthy cases can be a clinically meaningful index for detecting the abnormal dynamics of the heart.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-017-15498-z
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2615211-3
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  • 7
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    Modelling the first wave of COVID-19 in India
    Public Library of Science (PLoS) ; 2022
    In:  PLOS Computational Biology Vol. 18, No. 10 ( 2022-10-24), p. e1010632-
    Details
    In: PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 10 ( 2022-10-24), p. e1010632-
    Abstract: Estimating the burden of COVID-19 in India is difficult because the extent to which cases and deaths have been undercounted is hard to assess. Here, we use a 9-component, age-stratified, contact-structured epidemiological compartmental model, which we call the INDSCI-SIM model, to analyse the first wave of COVID-19 spread in India. We use INDSCI-SIM, together with Bayesian methods, to obtain optimal fits to daily reported cases and deaths across the span of the first wave of the Indian pandemic, over the period Jan 30, 2020 to Feb 15, 2021. We account for lock-downs and other non-pharmaceutical interventions (NPIs), an overall increase in testing as a function of time, the under-counting of cases and deaths, and a range of age-specific infection-fatality ratios. We first use our model to describe data from all individual districts of the state of Karnataka, benchmarking our calculations using data from serological surveys. We then extend this approach to aggregated data for Karnataka state. We model the progress of the pandemic across the cities of Delhi, Mumbai, Pune, Bengaluru and Chennai, and then for India as a whole. We estimate that deaths were undercounted by a factor between 2 and 5 across the span of the first wave, converging on 2.2 as a representative multiplier that accounts for the urban-rural gradient. We also estimate an overall under-counting of cases by a factor of between 20 and 25 towards the end of the first wave. Our estimates of the infection fatality ratio (IFR) are in the range 0.05—0.15, broadly consistent with previous estimates but substantially lower than values that have been estimated for other LMIC countries. We find that approximately 35% of India had been infected overall by the end of the first wave, results broadly consistent with those from serosurveys. These results contribute to the understanding of the long-term trajectory of COVID-19 in India.
    Type of Medium: Online Resource
    ISSN: 1553-7358
    URL: Article
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    DOI: 10.1371/journal.pcbi.1010632
    DOI: 10.1371/journal.pcbi.1010632.g001
    DOI: 10.1371/journal.pcbi.1010632.g002
    DOI: 10.1371/journal.pcbi.1010632.g003
    DOI: 10.1371/journal.pcbi.1010632.g004
    DOI: 10.1371/journal.pcbi.1010632.g005
    DOI: 10.1371/journal.pcbi.1010632.g006
    DOI: 10.1371/journal.pcbi.1010632.g007
    DOI: 10.1371/journal.pcbi.1010632.t001
    DOI: 10.1371/journal.pcbi.1010632.t002
    DOI: 10.1371/journal.pcbi.1010632.t003
    DOI: 10.1371/journal.pcbi.1010632.t004
    DOI: 10.1371/journal.pcbi.1010632.t005
    DOI: 10.1371/journal.pcbi.1010632.s001
    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2022
    detail.hit.zdb_id: 2193340-6
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  • 8
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    Resource dependency and survivability in complex networks
    American Physical Society (APS) ; 2020
    In:  Physical Review E Vol. 102, No. 6 ( 2020-12-8)
    Details
    In: Physical Review E, American Physical Society (APS), Vol. 102, No. 6 ( 2020-12-8)
    Type of Medium: Online Resource
    ISSN: 2470-0045 , 2470-0053
    URL: Article
    DOI: 10.1103/PhysRevE.102.062304
    RVK:
    UA 6500.3.E
    Language: English
    Publisher: American Physical Society (APS)
    Publication Date: 2020
    detail.hit.zdb_id: 2844562-4
    SSG: 12
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  • 9
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    Do zealots increase or decrease the polarization of social networks?
    Oxford University Press (OUP) ; 2020
    In:  Journal of Complex Networks Vol. 8, No. 4 ( 2020-10-09)
    Details
    In: Journal of Complex Networks, Oxford University Press (OUP), Vol. 8, No. 4 ( 2020-10-09)
    Abstract: Zealots are the vertices in a social network who do not change their opinions under social pressure and are crucial to the study of opinion dynamics on complex networks. In this article, we study the effect of zealots on the polarization dynamics of a deterministic majority rule model using the configuration model as a substrate. To this end, we propose a novel quantifier, called ‘correlated polarization’, for measuring the amount of polarization in the network when vertices can exist in two opposite states. The quantifier takes into account not only the fraction of vertices with each opinion but also how they are connected to each other. We then show that the presence of zealots does not have a fixed effect on the polarization, and can change it in positive, negative or neutral way depending upon their topological characteristics like degree, their total fraction in the network, density and degree heterogeneity of the network and the type of initial conditions of the dynamics. Our results particularly highlight the importance of the role played by the initial conditions in drifting the polarization towards lower or higher values as the total number of zealots is increased.
    Type of Medium: Online Resource
    ISSN: 2051-1329
    URL: Article
    DOI: 10.1093/comnet/cnz036
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
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  • 10
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    Importance of initial conditions in the polarization of complex networks
    IOP Publishing ; 2018
    In:  EPL (Europhysics Letters) Vol. 122, No. 3 ( 2018-06-19), p. 38002-
    Details
    In: EPL (Europhysics Letters), IOP Publishing, Vol. 122, No. 3 ( 2018-06-19), p. 38002-
    Type of Medium: Online Resource
    ISSN: 1286-4854
    URL: Article
    DOI: 10.1209/0295-5075/122/38002
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2018
    detail.hit.zdb_id: 1465366-7
    detail.hit.zdb_id: 165776-8
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