Relevant bibliographies by topics / Network modelling

Academic literature on the topic 'Network modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Network modelling"

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Maciá-Pérez, Francisco, Iren Lorenzo-Fonseca, Jose Vicente Berná-Martinez, and Jose Manuel Sánchez-Bernabeu. "Conceptual Modelling of Complex Network Management Systems." Journal of Computers 10, no. 5 (2015): 309–20. http://dx.doi.org/10.17706/jcp.10.5.309-320.

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Smirnov, Alexander, and Nikolay Shilov. "Business Network Modelling." International Journal of Information System Modeling and Design 1, no. 4 (October 2010): 77–91. http://dx.doi.org/10.4018/jismd.2010100104.

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Business networks have appeared as a reaction to changes taking place in the world economy and logistic networks can be considered as examples of such networks. The approach proposed in the paper is based on the idea to represent the business network members with services provided by them, and to achieve interoperability via application of the SOA standards. The approach is based on usage of such technologies as Web services, ontology, and context management. Web services enable interoperability at the technological level. Ontologies are used for description of knowledge domains and enable interoperability at the level of semantics. The purpose of the context is to represent only relevant information from the large amount of the information and the application of the approach is demonstrated on the case study from the area of dynamic logistics. The considered problem takes into account a continuously changing problem environment and requires nearly real-time solving.
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Pugacheva, E. "Social Network Modelling." Мiждисциплiнарнi дослiдження складних систем, no. 6 (2015): 49–62. http://dx.doi.org/10.31392/2307-4515/2015-6.2.

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Clark, J. W. "Neural network modelling." Physics in Medicine and Biology 36, no. 10 (October 1, 1991): 1259–317. http://dx.doi.org/10.1088/0031-9155/36/10/001.

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Lambert, Jean, and Béatrice Stéphan. "Modelling network profiles." Computer Communications 18, no. 9 (September 1995): 600–608. http://dx.doi.org/10.1016/0140-3664(95)99803-k.

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Tumbas, Pere, Predrag Matkovic, and Marton Sakal. "Modelling cross-border regional network for innovative development." Perspectives of Innovations, Economics and Business 13, no. 3 (July 16, 2013): 16–24. http://dx.doi.org/10.15208/pieb.2013.13.

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Tarapata, Zbigniew. "Modelling and analysis of transportation networks using complex networks: Poland case study." Archives of Transport 36, no. 4 (December 31, 2015): 55–65. http://dx.doi.org/10.5604/08669546.1185207.

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In the paper a theoretical bases and empirical results deal with analysis and modelling of transportation networks in Poland using complex networks have been presented. Properties of complex networks (Scale Free and Small World) and network's characteristic measures have been described. In this context, results of empirical researches connected with characteristics of passenger air links network, express railway links network (EuroCity and InterCity) and expressways/highways network in Poland have been given. For passenger air links network in Poland results are compared with the same networks in USA, China, India, Italy and Spain. In the conclusion some suggestions, observations and perspective dealing with complex network in transportation networks have been presented.
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Cebolledo Gutierrez, Edgar Omar, and Olga De Troyer. "Modelling Social Network Interactions in Games." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 11, no. 4 (June 24, 2021): 82–88. http://dx.doi.org/10.1609/aiide.v11i4.12831.

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Social Networks, like Facebook, have become an important part of life for millions of people, with many people using them on a daily basis. While there are games that simulate life-to-life interactions, there are not as many that simulate social network interactions, and even fewer where social network interactions are an important part of the gameplay. Having models for the simulation of interactions on social networks is the first step needed to be able to create games where a social network is an important component of the gameplay. In this paper we present a model to create dy-namic and believable interactions in social networks and in-dicate how it was used in a serious game about cyberbullying. The model is based on personality models and Berne’s so-called Social Games.
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Mondragón, Raúl J. "Topological modelling of large networks." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1872 (March 6, 2008): 1931–40. http://dx.doi.org/10.1098/rsta.2008.0008.

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In a complex network, there is a strong interaction between the network's topology and its functionality. A good topological network model is a practical tool as it can be used to test ‘what-if’ scenarios and it can provide predictions of the network's evolution. Modelling the topology structure of a large network is a challenging task, since there is no agreement in the research community on which properties of the network a model should be based, or how to test its accuracy. Here we present recent results on how to model a large network, the autonomous system (AS)-Internet, using a growth model. Based on a nonlinear preferential growth model and the reproduction of the network's rich club, the model reproduces many of the topological characteristics of the AS-Internet. We also identify a recent method to visualize the network's topology. This visualization technique is simple and fast and can be used to understand the properties of a large complex network or as a first step to validate a network model.
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Anderson, Taylor, and Suzana Dragićević. "Representing Complex Evolving Spatial Networks: Geographic Network Automata." ISPRS International Journal of Geo-Information 9, no. 4 (April 20, 2020): 270. http://dx.doi.org/10.3390/ijgi9040270.

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Many real-world spatial systems can be conceptualized as networks. In these conceptualizations, nodes and links represent system components and their interactions, respectively. Traditional network analysis applies graph theory measures to static network datasets. However, recent interest lies in the representation and analysis of evolving networks. Existing network automata approaches simulate evolving network structures, but do not consider the representation of evolving networks embedded in geographic space nor integrating actual geospatial data. Therefore, the objective of this study is to integrate network automata with geographic information systems (GIS) to develop a novel modelling framework, Geographic Network Automata (GNA), for representing and analyzing complex dynamic spatial systems as evolving geospatial networks. The GNA framework is implemented and presented for two case studies including a spatial network representation of (1) Conway’s Game of Life model and (2) Schelling’s model of segregation. The simulated evolving spatial network structures are measured using graph theory. Obtained results demonstrate that the integration of concepts from geographic information science, complex systems, and network theory offers new means to represent and analyze complex spatial systems. The presented GNA modelling framework is both general and flexible, useful for modelling a variety of real geospatial phenomena and characterizing and exploring network structure, dynamics, and evolution of real spatial systems. The proposed GNA modelling framework fits within the larger framework of geographic automata systems (GAS) alongside cellular automata and agent-based modelling.
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Dissertations / Theses on the topic "Network modelling"

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Gudmundsson, Gudmundur Stefan. "Essays in network modelling." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/663096.

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This thesis consists of two chapters on time series modelling. The first chapter introduces a class of vector autoregressive (VAR) models with a community structure for large panels of time series. In the model, the series are parti-tioned into latent groups such that spillovers are stronger within groups than between them. We then propose an algorithm that uses the eigenvectors of a function of the estimated autoregressive matrices to recover the communities. We study the properties of the procedure and establish its consistency. The algorithm motivates us to suggest a regularised VAR estimator, which per-forms favourably relative to a number of alternatives in a forecasting exercise. The methodology is applied to study clustering in industrial production for a set of major economies. The second chapter introduces a class of partial correlation network models with a community structure. The series form unknown groups, where correlation is higher within groups than otherwise. We propose an algorithm that consistently detects the communities using the eigenvectors of the sample covariance matrix. The procedure is used to analyse real activity clustering in the U.S. and Europe.
Aquesta tesi consisteix en dos capítols sobre models de dades de sèries temporals. El primer capítol introdueix una classe de models de vector autoregressius (VAR) amb una estructura de comunitat per panels de dades de sèries temporals. En el model, les sèries es parteixen en grups latents de tal manera que els spillover són ées forts dins de grups que entre ells. Llavors proposem un algoritme que utilitza el vector d’eigen d’una funció de les matrius autoregressives estimades per recuperar les comunitats. Estudiem les propietats del procediment i establim la seva consistència. L’algoritme ens motiva a suggerir un estimador regulat del VAR, el qual actua favorablement en relació a un nombre d’alternatives en una exercici d’ estimació. La metodologia s’aplica per estudiar el clustering en la producció industrial per un conjunt d’economies importants. El segon capítol introdueix una classe de models de xarxa de correlació parcials amb una estructura de comunitat. La èerie forma grups desconeguts, on la correlació és més alta dins de grups que altrament. Proposem un algoritme que detecta consistentment les comunitats que utilitzen els vectors d’eigen de la matriu de mostra de covariáncia. El procediment s’utilitza per analitzar el clustering en l’activitat real en els EUA i Europa.
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Filion, Yves R. "Extended dynamic network modelling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ58667.pdf.

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Roadknight, C. M. "Transparent neural network modelling." Thesis, Nottingham Trent University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314107.

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Dalton, Sarah. "Modelling the Perinatal Network System." Thesis, University of Westminster, 2018. https://westminsterresearch.westminster.ac.uk/item/q559v/modelling-the-perinatal-network-system.

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The topic is that hospital capacity for patient beds runs short. We wish to predict when this will occur. An inter-disciplinary approach to this problem is taken incorporating a Management Science/Operational Research perspective. The subject is the Perinatal Network System, which is described, analysed and modelled. An illustrative Case Study is taken of an English local neonatal unit, where new-born babies are cared for. The focus is High dependency cots. Recommendations produced are subject to human factors and implementation difficulties. In this work, Systems Thinking facilitates an understanding of relationships; Enterprise Architecture helps embed the context and address complexity; while Clinical Medicine underpins decision-making for individual patients. Research outputs include the Conceptual Research Framework, a Quality Metric, a Cot Predictor Tool and a Markovian model Design, which can be adapted in the future. Furthermore there is the milieu or connective ‘glue’, to provide unity. The methodology or Enterprise Modelling helps address the issue by facilitating understanding of both overview and detail.
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Liu, Wei 1975. "Network traffic modelling and analysis." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82613.

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In all-photonic networks, both transmission and switching is performed in the optical domain, without optoelectronic conversion for the data traversing the network. An accurate traffic model is critical in an agile all-photonic network (AAPN) which has the ability to dynamically allocate bandwidth to traffic flows as the demand varies.
This thesis focuses on traffic modelling and analysis. A novel traffic model is proposed which can capture the traffic behaviours in all-photonic networks. The new model is based on a study of existing traffic modelling literature. It combines the time-varying Poisson model, gravity model and fractional Gaussian noise. This model can be used for the short-range traffic prediction. We examine Long-Range Dependence and test the time constancy of scaling parameters using the tools designed by Abry and Veitch, to analyze empirical and synthesized traffic traces.
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Bergmann, Daniel. "Genetic network modelling and inference." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11209/.

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Modelling and reconstruction of genetic regulatory networks has developed in a wide field of study in the past few decades, with the application of ever sophisticated techniques. This thesis looks at how models for genetic networks have been developed from simple Boolean representations to more complicated models that take into account the inherent stochasticity of the biological system they are modelling. Statistical techniques are used to help predict the interaction between genes from microarray data in order to recover genetic regulatory networks and provide likely candidates for interactions that can be experimentally verified. The use of Granger causality is applied to statistically assess the effect of one gene upon another and modifications to this are presented, with bootstrapping used to understand the variability present within the parameters. Given the large amounts of data to be analysed from microarray experiments, clustering techniques are used to help reduce the computational burden and novel algorithms are developed to make use of such clustered data. Variability within clusters is also considered, by developing a novel approach with the use of principal component analysis. These algorithms that are developed are implemented with an observed dataset from Xenopus Laevis that has many genes but few timepoints in order to assess their effectiveness under such limited data. Predictions of likely interactions between genes are provided from the algorithms developed and their limitations discussed. Using extra information is considered, where a further dataset of gene knockout data is used to verify the predictions made for one particular gene.
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Zadik, Daniel. "Network modelling of canine metabolism." Thesis, University of Nottingham, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.546533.

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Attenborough, F. R. "The modelling of network polymers." Thesis, University of Liverpool, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243243.

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This thesis considers the modelling of two and three dimensional molecular networks with a view to being able to predict how the geometry of a network will affect the elastic constants and specifically the Poisson's ratios of the network. Materials with negative Poisson's ratios have much better engineering properties then those with positive Poisson's ratios. Theory states that a network polymer, with negative Poisson's ratios at a molecular level, would have much better properties than most materials with negative Poisson's ratios made to date. Molecular modelling has been used to examine the elastic constants of those two and three dimensional network polymers which are most likely to be synthesised in the near future. Such networks have been predicted to have either large positive or large negative Poisson's ratios depending on the molecular arrangement of the network. Poisson's ratios varying between 0.96 and -0.86 for the three dimensional cases and between -0.9 and 1.26 for the two dimensional cases have been calculated. Young's moduli in the order of 1 GPa have been observed for the three dimensional networks as compared to Young's moduli in the order of 20 - 400 kPa which have been experimentally measured for foam materials. Comparison with local density functional calculations for two 2-D networks with the molecular modelling have confirmed the negative Poisson's ratio in these networks and shown that it is not a function of the molecular modelling packages or force field used. The off-axis properties for both the two and three dimensional networks have been calculated. These show that whilst the networks with a positive Poisson's ratio in the principal axis directions always have a positive Poisson's ratio, those networks with a negative Poisson's ratio in the principal axis directions have off-axis Poisson's ratios that vary between large and positive and large and negative. In general the networks with positive Poisson's ratios are much more isotropic than those with negative Poisson's ratios. Analytical models which model the networks using simple beam theory have been produced for various two and three dimensional networks. These models can be used to predict the elastic constants of a network without the need to do time consumingmolecular modelling calculations to a first approximation. Comparison of the molecular models and analytical models has led to the development a library of force constants for two dimensional networks which can be used to more accurately predict the elastic constants of a network based on a knowledge of the geometry of the network and the constituent `sub-units' from which it is made
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Wang, Hao. "Performance modelling of network management schemes for mobile wireless networks." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/13192.

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Baronikian, Haig. "Modelling and analysis of a computer conferencing system." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63756.

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Books on the topic "Network modelling"

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S, Mohan. Artificial neural network modelling. Roorkee: Indian National Committee on Hydrology, 2007.

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Filion, Yves R. Extended dynamic network modelling. Ottawa: National Library of Canada, 2001.

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Shanmuganathan, Subana, and Sandhya Samarasinghe, eds. Artificial Neural Network Modelling. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28495-8.

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van As, Harmen R., and Admela Jukan, eds. Optical Network Design and Modelling. New York, NY: Springer US, 1998. http://dx.doi.org/10.1007/978-0-387-35361-6.

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Casson, Mark. Modelling inter-firm networks. Reading, England: University of Reading, Dept. of Economics, 1993.

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Casson, Mark. Modelling inter-firm networks. Reading: University of Reading, 1993.

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Bianco, Andrea, and Fabio Neri, eds. Next Generation Optical Network Design and Modelling. New York, NY: Springer US, 2003. http://dx.doi.org/10.1007/978-0-387-35670-9.

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Brydon, D. A. Neural network modelling of a binary distillation column. Manchester: UMIST, 1994.

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Eiichi, Taniguchi, ed. City logistics: Network modelling and intelligent transport systems. Amsterdam: Pergamon, 2001.

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Nuzzolo, Agostino. Transit network modelling: The schedule- based dynamic approach. Milano: F. Angeli, 2003.

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Book chapters on the topic "Network modelling"

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Poler, Raúl, Josefa Mula, and Manuel Díaz-Madroñero. "Network Modelling." In Operations Research Problems, 115–39. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5577-5_4.

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Muth, Thomas. "Logical Network Modelling." In Modeling Telecom Networks and Systems Architecture, 103–218. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56845-9_3.

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Muth, Thomas. "Physical Network Modelling." In Modeling Telecom Networks and Systems Architecture, 219–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56845-9_4.

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Muth, Thomas. "Protocol Network Modelling." In Modeling Telecom Networks and Systems Architecture, 253–321. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56845-9_5.

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Selvalingam, S., S. L. Ong, and S. Y. Liong. "Irrigation Network Modelling." In Engineering Software IV, 683–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-662-21877-8_55.

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Michalski, Radosław, Sebastian Palus, Piotr Bródka, Przemysław Kazienko, and Krzysztof Juszczyszyn. "Modelling Social Network Evolution." In Lecture Notes in Computer Science, 283–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24704-0_30.

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Cieśla, Maria, Jerzy Margielewicz, and Damian Gąska. "Intermodal Terminals Network Modelling." In Modelling of the Interaction of the Different Vehicles and Various Transport Modes, 185–231. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11512-8_5.

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Hinton, Kerry James, Robert Ayre, and Jeffrey Cheong. "Network Power Consumption Modelling." In Modeling the Power Consumption and Energy Efficiency of Telecommunications Networks, 235–62. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780429287817-8.

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Ritter, Daniel. "A Network-Centric BPMN Model for Business Network Management." In Modelling Foundations and Applications, 152–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39013-5_11.

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Nogueira, António, Paulo Salvador, Rui Valadas, and António Pacheco. "Markovian Modelling of Internet Traffic." In Network Performance Engineering, 98–124. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-02742-0_5.

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Conference papers on the topic "Network modelling"

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Majovská, Renata, and Petr Fiala. "MODELLING OF SUPPLY NETWORK DESIGN." In The 19th International Conference on Modelling and Applied Simulation. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.mas.004.

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The paper is dedicated to proposed modelling approach for supply networks. The original structure of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin. The structure is clarified by expert opinion with use of DEMATEL method. The suitability of supply networks can be measured by multiple objectives, such as economic, environmental, social, and others. Traditional concepts of optimality focus on valuation of already given systems. We propose to use a methodology for optimal system design. As a methodology of optimal system design can be employed De Novo Multi-objective Linear Programming for reshaping feasible sets in linear systems.
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Medoh, C., and A. Telukdarie. "Modelling Water Network Behaviors: Agent-based Modelling." In 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2021. http://dx.doi.org/10.1109/ieem50564.2021.9672976.

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Morovati, Vahid, Mohammad Ali Saadat, and Roozbeh Dargazany. "Modelling Stress Softening and Necking Phenomena in Double Network Hydrogels." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-12253.

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Abstract Double network (DN) gels are three-dimensional polymer matrices formed by interpenetrating networks. In contrast to the conventional single-network gels, DN gels have significant toughness, which makes them a promising material for different biomedical and biological applications. However, DN gels show complicated inelastic behavior including the Mullins effect and necking instability. Despite extensive efforts on modelling different aspects of the damage process in gels, the micro-mechanical modelling of the mechanisms that lead to necking in DN gels remains to be a challenging task. Here, a constitutive model is proposed to understand and describe the mechanical behavior of DN gels based on statistical micro-mechanics of interpenetrating polymer networks. DN gels behavior is divided into three parts including pre-necking, necking, and hardening. The first network is dominant in the response of the gel in the pre-necking stage. The breakage of the first network to smaller network fractions (clusters) induces the stress softening observed in this stage. The interaction of both networks and the second network are also considered as main contributors to the response of gel in necking and hardening stages, respectively. The contribution of clusters decreases during the necking as the second network starts hardening. The numerical results of the proposed model are validated and compared by uni-axial cyclic tensile experimental data of DN gels.
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Syed, Mansoor, Peter Pong, and Bob Hutchinson. "Battlespace communications network-of-networks interface modelling." In 2017 Annual IEEE International Systems Conference (SysCon). IEEE, 2017. http://dx.doi.org/10.1109/syscon.2017.7934706.

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Shi, Zhanqun, Yibo Fan, Fengshou Gu, Abdul-Hannan Ali, and Andrew Ball. "Neural Network Modelling Applied for Model-Based Fault Detection." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58197.

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This paper aims to combine neural network modelling with model-based fault detection. An accurate and robust model is critical in model-based fault detection. However, the development of such a model is the most difficult task especially when a non-linear system is involved. The problem comes not only from the lack of concerned information about model parameters, but also from the inevitable linearization. In order to solve this problem, neural networks are introduced in this paper. Instead of using conventional neural network modelling, the neural network is only used to approximate the non-linear part of the system, leaving the linear part to be represented by a mathematical model. This new scheme of integration between neural network and mathematical model (NNMM) allows the compensation of the error from conventional modelling methods. Simultaneously, it keeps the residual signatures physically interpretable.
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Alzubi, Saif, Frederic T. Stahl, and Mohamed M. Gaber. "Towards Intrusion Detection Of Previously Unknown Network Attacks." In 35th ECMS International Conference on Modelling and Simulation. ECMS, 2021. http://dx.doi.org/10.7148/2021-0035.

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Advances in telecommunication network technologies have led to an ever more interconnected world. Accordingly, the types of threats and attacks to intrude or disable such networks or portions of it are continuing to develop likewise. Thus, there is a need to detect previously unknown attack types. Supervised techniques are not suitable to detect previously not encountered attack types. This paper presents a new ensemble-based Unknown Network Attack Detector (UNAD) system. UNAD proposes a training workflow composed of heterogeneous and unsupervised anomaly detection techniques, trains on attack-free data and can distinguish normal network flow from (previously unknown) attacks. This scenario is more realistic for detecting previously unknown attacks than supervised approaches and is evaluated on telecommunication network data with known ground truth. Empirical results reveal that UNAD can detect attacks on which the workflows have not been trained on with a precision of 75% and a recall of 80%. The benefit of UNAD with existing network attack detectors is, that it can detect completely new attack types that have never been encountered before.
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Färber, Johannes. "Network game traffic modelling." In the 1st workshop. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/566500.566508.

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Nehinbe, Joshua Ojo, and Peter Damuut. "Security issues in Sensor Networks and gathering admissible evidence in Network Forensics." In 2011 European Modelling Symposium (EMS). IEEE, 2011. http://dx.doi.org/10.1109/ems.2011.95.

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Gertsbakh, I. B., and Y. Shpungin. "Network Reliability Design: Combinatorial and Monte Carlo Approach." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.696-048.

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Peng, Jinzhu, and Rickey Dubay. "Wiener-Type Neural Network for Nonlinear System Identification." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.735-072.

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Reports on the topic "Network modelling"

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Nechaev, V., Володимир Миколайович Соловйов, and A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.

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One of the well-known results of the theory of management is the fact, that multi-stage hierarchical organization of management is unstable. Hence, the ideas expressed in a number of works by Don Tapscott on advantages of network organization of businesses over vertically integrated ones is clear. While studying the basic tendencies of business organization in the conditions of globalization, computerization and internetization of the society and the results of the financial activities of the well-known companies, the authors arrive at the conclusion, that such companies, as IBM, Boeing, Mercedes-Benz and some others companies have not been engaged in their traditional business for a long time. Their partner networks performs this function instead of them. The companies themselves perform the function of system integrators. The Tapscott’s idea finds its confirmation within the framework of a new powerful direction of the development of the modern interdisciplinary science – the theory of the complex networks (CN) [2]. CN-s are multifractal objects, the loss of multifractality being the indicator of the system transition from more complex state into more simple state. We tested the multifractal properties of the data using the wavelet transform modulus maxima approach in order to analyze scaling properties of our company. Comparative analysis of the singularity spectrumf(®), namely, the difference between maximum and minimum values of ® (∆ = ®max ¡ ®min) shows that IBM company is considerably more fractal in comparison with Apple Computer. Really, for it the value of ∆ is equal to 0.3, while for the vertically integrated company Apple it only makes 0.06 – 5 times less. The comparison of other companies shows that this dependence is of general character. Taking into consideration the fact that network organization of business has become dominant in the last 5-10 years, we carried out research for the selected companies in the earliest possible period of time which was determined by the availability of data in the Internet, or by historically later beginning of stock trade of computer companies. A singularity spectrum of the first group of companies turned out to be considerably narrower, or shifted toward the smaller values of ® in the pre-network period. The latter means that dynamic series were antipersistant. That is, these companies‘ management was rigidly controlled while the impact of market mechanisms was minimized. In the second group of companies if even the situation did changed it did not change for the better. In addition, we discuss applications to the construction of portfolios of stock that have a stable ratio of risk to return.
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Kompaniets, Alla, Hanna Chemerys, and Iryna Krasheninnik. Using 3D modelling in design training simulator with augmented reality. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3740.

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The article is devoted to the theoretical consideration of the problem and the use of innovative technologies in the educational process in the educational establishment of secondary education in the process of studying the school course of computer science. The main advantages of using educational simulators in the educational process are considered, based on the new state standard of basic and complete general secondary education. Based on the analysis of scientific and methodological literature and network sources, the features of the development of simulators for educational purposes are described. Innovative tools for simulator development have been investigated, as augmented reality with the use of three-dimensional simulation. The peculiarities of using a simulator with augmented reality when studying the topic of algorithmization in the course of studying a school computer science are considered. The article also describes the implementation of augmented reality simulator for the formation of algorithmic thinking skills by students, presents the results of development and describes the functionality of the software product. In the further prospects of the study, it is planned to conduct an experimental study to determine the effectiveness of the use of software development in the learning process.
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Millis, Andrew. Many Body Methods from Chemistry to Physics: Novel Computational Techniques for Materials-Specific Modelling: A Computational Materials Science and Chemistry Network. Office of Scientific and Technical Information (OSTI), November 2016. http://dx.doi.org/10.2172/1332662.

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Gurieiev, Viktor, Yulii Kutsan, Anna Iatsyshyn, Andrii Iatsyshyn, Valeriia Kovach, Evgen Lysenko, Volodymyr Artemchuk, and Oleksandr Popov. Simulating Systems for Advanced Training and Professional Development of Energy Specialists in Power Sector. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4456.

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The crisis of the system of professional development and personnel training in the energy sector exists not only in Ukraine but also all over the world. The article describes the concept of development and functioning of the industry system of personnel training in the energy sector of Ukraine. The importance of using modern web-oriented technologies to improve the skills of operational and dispatching personnel in the energy sector of Ukraine is substantiated. The meth- ods of distributed power system operating modes modelling are presented. De- velopment and software tools for the construction of distributed simulating sys- tems and particular features of cloud technologies application for the creation of a virtual training centers network in the energy sector, as well as the ways to automate the process of simulating scenarios development are described. The ex- perience of introducing remote training courses for energy specialists and remote web-based training simulators based on a comprehensive model of the energy system of Ukraine is presented. An important practical aspect of the research is the application of software and data support for the development of personnel key competencies in the energy sector for rapid recognition of accidents and, if necessary, accident management. This will allow them to acquire knowledge and practical skills to solve the problems of analysis, modelling, forecasting, and monitoring data visualization of large power systems operating modes.
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Kroeger, P. G., R. J. Kennett, J. Colman, and T. Ginsberg. THATCH: A computer code for modelling thermal networks of high- temperature gas-cooled nuclear reactors. Office of Scientific and Technical Information (OSTI), October 1991. http://dx.doi.org/10.2172/6239042.

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MUNICH UNIV (GERMANY F R). International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. Volume 6 Number 1, February 1993. Fort Belvoir, VA: Defense Technical Information Center, February 1993. http://dx.doi.org/10.21236/ada264051.

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Davies, Will. Improving the engagement of UK armed forces overseas. Royal Institute of International Affairs, January 2022. http://dx.doi.org/10.55317/9781784135010.

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The UK government’s Integrated Review of security, defence, development and foreign policy, published in March 2021 alongside a supporting defence command paper, set a new course for UK national security and highlighted opportunities for an innovative approach to international engagement activity. The Integrated Review focused principally on the state threats posed by China’s increasing power and by competitors – including Russia – armed with nuclear, conventional and hybrid capabilities. It also stressed the continuing risks to global security and resilience due to conflict and instability in weakened and failed states. These threats have the potential to increase poverty and inequality, violent extremism, climate degradation and the forced displacement of people, while presenting authoritarian competitors with opportunities to enhance their geopolitical influence. There are moral, security and economic motives to foster durable peace in conflict-prone and weakened regions through a peacebuilding approach that promotes good governance, addresses the root causes of conflict and prevents violence, while denying opportunities to state competitors. The recent withdrawal from Afghanistan serves to emphasize the complexities and potential pitfalls associated with intervention operations in complex, unstable regions. Success in the future will require the full, sustained and coordinated integration of national, allied and regional levers of power underpinned by a sophisticated understanding of the operating environment. The UK armed forces, with their considerable resources and global network, will contribute to this effort through ‘persistent engagement’. This is a new approach to overseas operations below the threshold of conflict, designed as a pre-emptive complement to warfighting. To achieve this, the UK Ministry of Defence (MOD) must develop a capability that can operate effectively in weak, unstable and complex regions prone to violent conflict and crises, not least in the regions on the eastern and southern flanks of the Euro-Atlantic area. The first step must be the development of a cohort of military personnel with enhanced, tailored levels of knowledge, skills and experience. Engagement roles must be filled by operators with specialist knowledge, skills and experience forged beyond the mainstream discipline of combat and warfighting. Only then will individuals develop a genuinely sophisticated understanding of complex, politically driven and sensitive operating environments and be able to infuse the design and delivery of international activities with practical wisdom and insight. Engagement personnel need to be equipped with: An inherent understanding of the human and political dimensions of conflict, the underlying drivers such as inequality and scarcity, and the exacerbating factors such as climate change and migration; - A grounding in social sciences and conflict modelling in order to understand complex human terrain; - Regional expertise enabled by language skills, cultural intelligence and human networks; - Familiarity with a diverse range of partners, allies and local actors and their approaches; - Expertise in building partner capacity and applying defence capabilities to deliver stability and peace; - A grasp of emerging artificial intelligence technology as a tool to understand human terrain; - Reach and insight developed through ‘knowledge networks’ of external experts in academia, think-tanks and NGOs. Successful change will be dependent on strong and overt advocacy by the MOD’s senior leadership and a revised set of personnel policies and procedures for this cohort’s selection, education, training, career management, incentivization, sustainability and support.
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Stark, Gregory B. Modelling the Value of Networked, Small-Hydro Generators for Storage and Dispatch Capability on the Grid: Cooperative Research and Development Final Report, CRADA Number CRD-17-692. Office of Scientific and Technical Information (OSTI), December 2019. http://dx.doi.org/10.2172/1580573.

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Rural NEET Youth Policy Brief - Youth and Mobility in EU Rural Areas. COST Action 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, May 2022. http://dx.doi.org/10.15847/cisrnyn.neetpbym.2022.05.

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This policy brief is based upon findings from the COST Action CA18213: Rural NEET Youth Network: Modelling the Risks Underlying Rural NEETs Social Ex- clusion. This network brings together researchers and practitioners from 31 countries and aims at developing a model of comprehension for rural NEETs’ social exclusion risks and protective factors based on a bio-ecological model. The three specific goals of the action are: 1. upholding future research capacity, with an emphasis on Early Career Investigators, and Inclusiveness Tar- get Countries; 2. creating a rural NEETs’ online observatory; and, 3. fostering use of knowledge by policy makers and practitioners.
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African Open Science Platform Part 1: Landscape Study. Academy of Science of South Africa (ASSAf), 2019. http://dx.doi.org/10.17159/assaf.2019/0047.

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This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.
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