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Academic literature on the topic 'Network measures'

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Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Network measures"

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Kincaid, Rex K., and David J. Phillips. "Network topology measures." Wiley Interdisciplinary Reviews: Computational Statistics 3, no. 6 (June 14, 2011): 557–65. http://dx.doi.org/10.1002/wics.180.

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Zhang, Wen Jie. "Network Security Vulnerabilities and Preventive Measures." Applied Mechanics and Materials 433-435 (October 2013): 1674–78. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.1674.

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As the arrival times network economy and social networks, computers and computer networks popularity indicates that a ubiquitous network will go into not the state. As the use of network and the virus has become increasingly serious, virus writers from the original to show off to obtain invalid income, the resulting harm is incalculable. This situation not only jeopardize the current development of the Internet but also undermined the reality of social stability and unity, therefore, this paper is on how the network vulnerabilities, how to survive and how to protection, so that there are loopholes in our network deeper understanding of network vulnerability and protection so that we have a new breakthrough for the network to provide a good environment for development.
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Aytaç, Aysun, and Tufan Turaci. "Vulnerability Measures of Transformation Graph Gxy+." International Journal of Foundations of Computer Science 26, no. 06 (September 2015): 667–75. http://dx.doi.org/10.1142/s0129054115500379.

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Several factors have to be taken into account in the design of large interconnection networks. Optimal design is important both to achieve good performance and to reduce the cost of construction and maintenance. Practical communication networks are exposed to failures of network components. Failures between nodes and connections happen and it is desirable that a network is robust in the sense that a limited number of failures does not break down the whole system. Robustness of the network topology is a key aspect in the design of computer networks. A variety of measures have been proposed in the literature to quantify the robustness of networks and a number of graph-theoretic parameters have been used to derive formulas for calculating network reliability. In this paper, we study the vulnerability of interconnection networks to the failure of individual nodes, using a graph-theoretic concept of domination and strong-weak domination numbers of the transformation graph Gxy+ as a measure of network robustness.
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Boehmke, Frederick J., Olga Chyzh, and Cameron G. Thies. "Addressing Endogeneity in Actor-Specific Network Measures." Political Science Research and Methods 4, no. 1 (August 24, 2015): 123–49. http://dx.doi.org/10.1017/psrm.2015.34.

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The study of international relations (IR), and political science more broadly, has derived great benefits from the recent growth of conceptualizing and modeling political phenomena within their broader network contexts. More than just a novel approach to evaluating old puzzles, network analysis provides a whole new way of theoretical thinking. Challenging the traditional dyad-driven approach to the study of IR, networks highlight actor interdependence that goes beyond dyads and emphasizes that many traditional IR variables, such as conflict, trade, alliances, or international organization memberships must be treated and studied as networks. Properties of these networks (e.g., polarization, density), and of actor positions within them (e.g., similarity, centrality), will then reveal important insights about international events. Network analysis, however, is not yet fully adapted to account for important methodological issues common to IR research, specifically the issue of endogeneity or possible nonindependence between actors’ position within international networks and the outcomes of interest: for example, alliance network may be nonindependent from the conflict or trade network. We adopt an instrumental variable approach to explore and address the issue of endogeneity in network context. We illustrate the issue and the advantages of our approach with Monte Carlo analysis, as well as with several empirical examples from IR literature.
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Kansky, Karl, and Pascal Danscoine. "Measures of network structure." Flux 5, no. 1 (1989): 89–121. http://dx.doi.org/10.3406/flux.1989.913.

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Banisch, Ralf, Péter Koltai, and Kathrin Padberg-Gehle. "Network measures of mixing." Chaos: An Interdisciplinary Journal of Nonlinear Science 29, no. 6 (June 2019): 063125. http://dx.doi.org/10.1063/1.5087632.

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Li, Yan. "Network Security Protection Measures." Advanced Materials Research 971-973 (June 2014): 1659–62. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1659.

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Safety is the premise of network operation, network security is not only a single point of security, but the safety of the information network, need to be done from various solid protection. Analyzed the current form and face all kinds of LAN network security threats and network security precautions, technology, this paper expounds the LAN the importance of the current network security in our lives.
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Vardi, Yehuda, and Cun-Hui Zhang. "Measures of Network Vulnerability." IEEE Signal Processing Letters 14, no. 5 (May 2007): 313–16. http://dx.doi.org/10.1109/lsp.2006.888290.

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Bibi, Fizza, Hikmat Khan, Tassawar Iqbal, Muhammad Farooq, Irfan Mehmood, and Yunyoung Nam. "Ranking Authors in an Academic Network Using Social Network Measures." Applied Sciences 8, no. 10 (October 4, 2018): 1824. http://dx.doi.org/10.3390/app8101824.

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Online social networks are widely used platforms that enable people to connect with each other. These social media channels provide an active communication platform for people, and they have opened new venues of research for the academic world and business. One of these research areas is measuring the influential users in online social networks; and the same is true for academic networks where finding influential authors is an area of interest. In an academic network, citation count, h-index and their variations are used to find top authors. In this article, we propose the adoption of established social network measures, including centrality and prestige, in an academic network to compute the rank of authors. For the empirical analysis, the widely-used dataset of the Digital Bibliography and Library Project (DBLP) is exploited in this research, and the micro-level properties of the network formed in the DBLP co-authorship network are studied. Afterwards, the results are computed using social network measures and evaluated using the standard ranking performance evaluation measures, including Kendall correlation, Overlapping Similarlity (OSim) and Spearman rank-order correlation. The results reveal that the centrality measures are significantly correlated with the citation count and h-index. Consequently, social network measures have potential to be used in an academic network to rank the authors.
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Lordan, Oriol, and Jose M. Sallan. "Dynamic measures for transportation networks." PLOS ONE 15, no. 12 (December 3, 2020): e0242875. http://dx.doi.org/10.1371/journal.pone.0242875.

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Most complex network analyses of transportation systems use simplified static representations obtained from existing connections in a time horizon. In static representations, travel times, waiting times and compatibility of schedules are neglected, thus losing relevant information. To obtain a more accurate description of transportation networks, we use a dynamic representation that considers synced paths and that includes waiting times to compute shortest paths. We use the shortest paths to define dynamic network, node and edge measures to analyse the topology of transportation networks, comparable with measures obtained from static representations. We illustrate the application of these measures with a toy model and a real transportation network built from schedules of a low-cost carrier. Results show remarkable differences between measures of static and dynamic representations, demonstrating the limitations of the static representation to obtain accurate information of transportation networks.
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Dissertations / Theses on the topic "Network measures"

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Traore, Abdoulaye S. "Mixed Network Interference Management with Multi-Distortion Measures." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/604294.

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ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California
This paper presents a methodology for the management of interference and spectrum for iNET. It anticipates a need for heavily loaded test environments with Test Articles (TAs) operating over the horizon. In such cases, it is anticipated that fixed and ad hoc networks will be employed, and where spectrum reuse and interference will limit performance. The methodology presented here demonstrates how this can be accomplished in mixed networks.
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Grando, Felipe. "Methods for the approximation of network centrality measures." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/186166.

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Medidas de centralidades são um mecanismo importante para revelar informações vitais sobre redes complexas. No entanto, essas métricas exigem um alto custo computacional que prejudica a sua aplicação em grandes redes do mundo real. Em nosso estudo propomos e explicamos que através do uso de redes neurais artificiais podemos aplicar essas métricas em redes de tamanho arbitrário. Além disso, identificamos a melhor configuração e metodologia para otimizar a acurácia do aprendizado neural, além de apresentar uma maneira fácil de obter e gerar um número suficiente de dados de treinamento substanciais através do uso de um modelo de redes complexas que é adaptável a qualquer aplicação. Também realizamos um comparativo da técnica proposta com diferentes metodologias de aproximação de centralidade da literatura, incluindo métodos de amostragem e outros algoritmos de aprendizagem, e, testamos o modelo gerado pela rede neural em casos reais. Mostramos com os resultados obtidos em nossos experimentos que o modelo de regressão gerado pela rede neural aproxima com sucesso as métricas é uma alternativa eficiente para aplicações do mundo real. A metodologia e o modelo de aprendizagem de máquina que foi proposto usa apenas uma fração do tempo de computação necessário para os algoritmos de aproximação baseados em amostragem e é mais robusto que as técnicas de aprendizagem de máquina testadas
Centrality measures are an important analysis mechanism to uncover vital information about complex networks. However, these metrics have high computational costs that hinder their applications in large real-world networks. I propose and explain the use of artificial neural learning algorithms can render the application of such metrics in networks of arbitrary size. Moreover, I identified the best configuration and methodology for neural learning to optimize its accuracy, besides presenting an easy way to acquire and generate plentiful and meaningful training data via the use of a complex networks model that is adaptable for any application. In addition, I compared my prosed technique based on neural learning with different centrality approximation methods proposed in the literature, consisting of sampling and other artificial learning methodologies, and, I also tested the neural learning model in real case scenarios. I show in my results that the regression model generated by the neural network successfully approximates the metric values and is an effective alternative in real-world applications. The methodology and machine learning model that I propose use only a fraction of computing time with respect to other commonly applied approximation algorithms and is more robust than the other tested machine learning techniques.
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Pellegrinet, Sarah <1988&gt. "Systemic Risk Measures and Connectedness: a network approach." Master's Degree Thesis, Università Ca' Foscari Venezia, 2015. http://hdl.handle.net/10579/6009.

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The main objective of the thesis is the construction of a systemic risk indicator based on the dispersion of the risk measures of the individual institutions of the system. The thesis presents a brief introduction to the literature on systemic risk measures, focusing on the Marginal Expected Shortfall (MES) and the delta CoVaR, which consider not only the yield of an individual firm, but also the effect of its performance on the whole system, and on the connectedness measure between the financial institutions, which measures the relationship between the institutions. We apply the systemic risk and the connectedness measures to the daily returns of the European financial institutions from the 1St January 1985 to 12th May 2014. Finally, to aggregate the risk measures and build a systemic risk indicator, we estimate the measure entropy and find that the indicator has good forecasting abilities for the financial crisis.
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Benbrook, Jimmie Glen 1943. "A SYSTEM ANALYSIS OF A MULTILEVEL SECURE LOCAL AREA NETWORK (COMPUTER)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/275531.

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Kim, Hyoungshick. "Complex network analysis for secure and robust communications." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610134.

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Fu, Zehua. "Confidence measures in deep neural network based stereo matching." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEC014.

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Malgré des décennies d’amélioration depuis la première proposition de Barnard et Fischler, les approches d’appariement stéréo souffrent encore d’imprécision, notamment en présence d’occlusion, des conditions d’éclairage extrêmes et d’ambiguïté. Pour pallier ces imprécisions, de nombreuses méthodes, appelées mesures de confiance, ont été proposées permettant d’évaluer l’exactitude des appariements. Dans cette thèse, nous étudions les mesures de confiance de l’état de l’art et proposons deux mesures, à bases de réseaux neurones et d’apprentissage profond, permettant d’améliorer les performances de l’appariement stéréo. Une première approche proposée utilise des données multimodales comprenant la disparité initiale et des images RGB de référence. Cette architecture multimodale est par la suite améliorée en élargissant le champ d’activation efficace (Effective Receptive Field-ERF) permettant un apprentissage avec davantage d’informations contextuelles et conduisant ainsi à une meilleure détection d’erreur d’appariement. Évaluée sur les données de KITTI2012 et KITTI2015, notre approche multimodale a atteint les meilleures performances du moment. Comme seconde approche, un réseau de neurones récurrent (Recurrent Neural Network-RNN) est proposée afin de raffiner pas à pas le résultat de l’appariement. Les réseaux de neurones récurrents à portes incorporés (Gated Recurrent Unit-GRU), combinés avec notre réseau de confiance multimodal à convolution dilatée, utilisent les informations d’une étape pour guider le raffinement dans une étape suivante. À notre connaissance, il s’agit de la première approche de raffinement proposée basée sur un réseau de neurones récurrent. L’approche proposée est aisément applicable à différents réseaux de neurones convolutifs (Convolutional Neural Network-CNN) d’appariement stéréo afin de produire une solution, de bout en bout, efficace et précise. Les résultats expérimentaux prouvent des améliorations significatives à la fois sur la base stéréo KITTI 2012 et sur KITTI 2015
Despite decades of enhancement since the first proposal of Barnard and Fischler’s, stereo matching approaches still suffer from imprecision, especially in the presence of occlusion, extreme lighting conditions and ambiguity. To overcome these inaccuracies, many methods, called confidence measures, have been proposed to assess the accuracy of the matching. In this thesis, we study state-of-the-art confidence measures and propose two measures, based on neural networks and deep learning, to improve the performance of stereo matching. A first proposed approach uses multi-modal data including the initial disparity and reference RGB images. The multi-modal architecture is subsequently improved by enlarging the Effective Receptive Field (ERF) enabling learning with more contextual information and thus leading to better detection of matching errors. Evaluated on KITTI2012 and KITTI2015 datasets, our multi-modal approach had achieved the best performance during the time. As a second approach, a Recurrent Neural Network (RNN) is proposed in order to refine the result of the stereo matching, step by step. The Gated Recurrent Units (GRU), combined with our multi-modal dilated convolutional network, use information from one step to guide refinement in the next. To the best of our knowledge, this is the first attempt to refine stereo matching based on an RNN. The proposed approach is easily applicable to different Convolutional Neural Networks (CNNs) in stereo matching to produce an effective and precise end-to-end solution. The experimental results prove significant improvements both on KITTI2012 and KITTI2015 datasets
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Olsson, Eric J. "Literature survey on network concepts and measures to support research in network-centric operations." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Jun%5FOlsson.pdf.

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Fuloria, Shailendra. "Robust security for the electricity network." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610100.

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Woldearegay, Yonas, and Oumar Traore. "Optimization of Nodes in Mixed Network Using Three Distance Measures." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595764.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada
This paper presents a method for the management of mixed networks as envisioned in future iNET applications and develops a scheme for global optimal performance for features that include signal to Noise Ratio (SNR), Quality of service (QoS), and Interference. This scheme demonstrates potential for significant enhancement of performance for dense traffic environments envisioned in future telemetry applications. Previous research conducted at Morgan State University has proposed a cellular and Ad hoc mixed network for optimum capacity and coverage using two distance measures: QoS and SNR. This paper adds another performance improvement technique, interference, as a third distance measure using an analytical approach and using extensive simulation with MATLAB. This paper also addresses solutions where performance parameters are correlated and uncorrelated. The simulations show the optimization of mixed network nodes using distance, traffic and interference measures all at one time. This has great potential in mobile communication and iNET.
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Mooi, Roderick David. "A model for security incident response in the South African National Research and Education network." Thesis, Nelson Mandela Metropolitan University, 2014. http://hdl.handle.net/10948/d1017598.

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This dissertation addresses the problem of a lack of a formal incident response capability in the South African National Research and Education Network (SA NREN). While investigating alternatives it was found that no clear method exists to solve this problem. Therefore, a second problem is identified: the lack of a definitive method for establishing a Computer Security Incident Response Team (CSIRT) or Computer Emergency Response Team (CERT) in general. Solving the second problem is important as we then have a means of knowing how to start when building a CSIRT. This will set the basis for addressing the initial problem, resulting in a prepared, improved and coordinated response to IT security incidents affecting the SANREN. To commence, the requirements for establishing a CSIRT are identified via a comprehensive literature review. These requirements are categorized into five areas, namely, the basic business requirements followed by the four Ps of the IT Infrastructure Library (ITIL). That is, People, Processes, Product and Partners, adapted to suit the CSIRT context. Through the use of argumentation, the relationships between the areas are uncovered and explored. Thereafter, a Design Science Research-based process is utilised to develop a generic model for establishing a CSIRT. The model is based on the interactions uncovered between the business requirements and the adapted four Ps. These are summarised through two views -- strategic and tactical -- together forming an holistic model for establishing a CSIRT. The model highlights the decisions required for the business requirements, services, team model and staff, policies and processes, tools and technologies, and partners of a CSIRT respectively. Finally, to address the primary objective, the generic model is applied to the SANREN environment. Thus, the second artefact is an instantiation, a specific model, which can be implemented to create a CSIRT for the SA NREN. To produce the specific model, insight into the nature of the SANREN environment was required. The status quo was revealed through the use of a survey and argumentative analysis of the results. The specific decisions in each area required to establish an SA NREN CSIRT are explored throughout the development of the model. The result is a comprehensive framework for implementing a CSIRT in the SA NREN, detailing the decisions required in each of the areas. This model additionally acts as a demonstration of the utility of the generic model. The implications of this research are twofold. Firstly, the generic model is useful as a basis for anyone wanting to establish a CSIRT. It helps to ensure that all factors are considered and that no important decisions are neglected, thereby enabling an holistic view. Secondly, the specific model for the SA NREN CSIRT serves as a foundation for implementing the CSIRT going forward. It accelerates the process by addressing the important considerations and highlighting the concerns that must be addressed while establishing the CSIRT.
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Books on the topic "Network measures"

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Hunt, Craig. Network Security. Sebastopol, CA: O’Reilly Media, 1998.

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R, Simon Alan, ed. Network security. Boston: AP Professional, 1994.

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Albanese, Massimiliano (Computer scientist), author and Jajodia Sushil author, eds. Network hardening: An automated approach to improving network security. Cham: Springer, 2014.

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John, Mallery, ed. Hardening network security. New York: McGraw-Hill/Osborne, 2005.

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Eric, Cole, ed. Network security fundamentals. Hoboken, N.J: Wiley, 2008.

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Network security foundations. San Francisco, Calif: SYBEX, 2004.

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Network defense. Clifton Park, NY: Course Technology, Cengage Learning, 2011.

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Russ, Rogers, Criscuolo Paul, and Petruzzi Mike, eds. Nessus network auditing. 2nd ed. Burlington, MA: Syngress, 2008.

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Network security auditing. Indianapolis, Ind: Cisco Press, 2010.

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Network Perimeter Security. London: Taylor and Francis, 2003.

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Book chapters on the topic "Network measures"

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Horvath, Steve. "Association Measures and Statistical Significance Measures." In Weighted Network Analysis, 249–77. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8819-5_10.

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Zweig, Katharina A. "Classic Network Analytic Measures." In Lecture Notes in Social Networks, 91–108. Vienna: Springer Vienna, 2016. http://dx.doi.org/10.1007/978-3-7091-0741-6_4.

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Miyazaki, Syuji. "Gibbs measures for the network." In Emergent Intelligence of Networked Agents, 129–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71075-2_10.

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Al-khateeb, Samer, and Nitin Agarwal. "Social Network Measures and Analysis." In SpringerBriefs in Cybersecurity, 27–44. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13690-1_2.

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He, Baozhu, and Zhen He. "Centrality Measures in Telecommunication Network." In Advanced Research on Electronic Commerce, Web Application, and Communication, 337–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20370-1_55.

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Zweig, Katharina A. "Understanding and Designing Network Measures." In Lecture Notes in Social Networks, 215–42. Vienna: Springer Vienna, 2016. http://dx.doi.org/10.1007/978-3-7091-0741-6_8.

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Aleskerov, Fuad, Sergey Shvydun, and Natalia Meshcheryakova. "Centrality Indices in Network Analysis." In New Centrality Measures in Networks, 1–38. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003203421-1.

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Mulekar, Madhuri S., and C. Scott Brown. "Distance and Similarity Measures." In Encyclopedia of Social Network Analysis and Mining, 1–16. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_141-1.

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Mulekar, Madhuri S., and C. Scott Brown. "Distance and Similarity Measures." In Encyclopedia of Social Network Analysis and Mining, 385–400. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_141.

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Mulekar, Madhuri S., and C. Scott Brown. "Distance and Similarity Measures." In Encyclopedia of Social Network Analysis and Mining, 647–62. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_141.

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Conference papers on the topic "Network measures"

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Singh, Gurpreet, Srinath Balaji, Jami J. Shah, David Corman, Ron Howard, Raju Mattikalli, and D. Stuart. "Evaluation of Network Measures as Complexity Metrics." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70483.

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Modern automotive and aerospace products are large cyber-physical system consisting of software, mechanical, electrical and electronic components. The increasing complexity of such systems is a major concern as it impacts development time and effort, as well as, initial and operational costs. Although much literature exists on complexity metrics, very little work has been done in determining if metrics correlate with real world products. Aspects of complexity include the product structure, development process and manufacturing. Since all these aspects can be uniformly represented in the form of networks, we examine common network based complexity measures in this paper. Network metrics are grouped into three categories: size complexity, numeric complexity (degree of coupling) and technological complexity (solvability). Several empirical studies were undertaken to determine the efficacy of various metrics. One approach was to survey project engineers in an aerospace company to gauge their perception of complexity. The second was through case studies of alternative designs to perform equivalent functions. The third was to look at actual time, labor data from past projects. Data structures and fast algorithms for complexity calculations for large cyber physical systems were also implemented.
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Zheng, Xiaoxia. "Computer network security and measures." In Mechanical Engineering and Information Technology (EMEIT). IEEE, 2011. http://dx.doi.org/10.1109/emeit.2011.6023622.

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Hou, Lvlin, Gang Liu, Songyang Lao, and Liang Bai. "Measures of network topology invulnerability." In 2012 2nd International Conference on Applied Robotics for the Power Industry (CARPI 2012). IEEE, 2012. http://dx.doi.org/10.1109/carpi.2012.6356504.

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Rheinwalt, Aljoscha, Norbert Marwan, Jurgen Kurths, Peter Werner, and Friedrich-Wilhelm Gerstengarbe. "Boundary Effects in Network Measures of Spatially Embedded Networks." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.72.

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Scellato, Salvatore, Ilias Leontiadis, Cecilia Mascolo, Prithwish Basu, and Murtaza Zafer. "Understanding robustness of mobile networks through temporal network measures." In IEEE INFOCOM 2011 - IEEE Conference on Computer Communications. IEEE, 2011. http://dx.doi.org/10.1109/infcom.2011.5935006.

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Carneiro, Murillo G., Barbara C. Gama, and Otavio S. Ribeiro. "Complex Network Measures for Data Classification." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533608.

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Huang, Q., Y. Yuan, J. Goncalves, and M. A. Dahleh. "H2 norm based network volatility measures." In 2014 American Control Conference - ACC 2014. IEEE, 2014. http://dx.doi.org/10.1109/acc.2014.6859249.

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Dehmer, Matthias, Stephan Borgert, and Frank Emmert-Streib. "Network Classes and Graph Complexity Measures." In 2008 First International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems. Medical Applications of the Complex Systems. Biomedical Computing (CANS). IEEE, 2008. http://dx.doi.org/10.1109/cans.2008.17.

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Winch, A. "Network performance improvement initiatives: a regional electricity company perspective." In IEE Colloquium on Measures to Prevent Power Blackouts. IEE, 1998. http://dx.doi.org/10.1049/ic:19980480.

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Carter, Martha A., and Mark E. Oxley. "Generalized measures of artificial neural network capabilities." In AeroSense '99, edited by Kevin L. Priddy, Paul E. Keller, David B. Fogel, and James C. Bezdek. SPIE, 1999. http://dx.doi.org/10.1117/12.342875.

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Reports on the topic "Network measures"

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Young, Stanley, and Dennis So Ting Fong. Arterial Network Performance Measures Software. Purdue University, December 2017. http://dx.doi.org/10.5703/1288284316570.

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Frantz, Terrill L., and Kathleen M. Carley. Relating Network Topology to the Robustness of Centrality Measures. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada456108.

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Young, Stanley, Christopher Day, and Dennis So Ting Fong. Network Performance Measures for Arterials—A Systematic Level Perspective. Purdue University, December 2017. http://dx.doi.org/10.5703/1288284316561.

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Duvvuri, Sarvani, and Srinivas S. Pulugurtha. Researching Relationships between Truck Travel Time Performance Measures and On-Network and Off-Network Characteristics. Mineta Transportation Institute, July 2021. http://dx.doi.org/10.31979/mti.2021.1946.

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Trucks serve significant amount of freight tonnage and are more susceptible to complex interactions with other vehicles in a traffic stream. While traffic congestion continues to be a significant ‘highway’ problem, delays in truck travel result in loss of revenue to the trucking companies. There is a significant research on the traffic congestion mitigation, but a very few studies focused on data exclusive to trucks. This research is aimed at a regional-level analysis of truck travel time data to identify roads for improving mobility and reducing congestion for truck traffic. The objectives of the research are to compute and evaluate the truck travel time performance measures (by time of the day and day of the week) and use selected truck travel time performance measures to examine their correlation with on-network and off-network characteristics. Truck travel time data for the year 2019 were obtained and processed at the link level for Mecklenburg County, Wake County, and Buncombe County, NC. Various truck travel time performance measures were computed by time of the day and day of the week. Pearson correlation coefficient analysis was performed to select the average travel time (ATT), planning time index (PTI), travel time index (TTI), and buffer time index (BTI) for further analysis. On-network characteristics such as the speed limit, reference speed, annual average daily traffic (AADT), and the number of through lanes were extracted for each link. Similarly, off-network characteristics such as land use and demographic data in the near vicinity of each selected link were captured using 0.25 miles and 0.50 miles as buffer widths. The relationships between the selected truck travel time performance measures and on-network and off-network characteristics were then analyzed using Pearson correlation coefficient analysis. The results indicate that urban areas, high-volume roads, and principal arterial roads are positively correlated with the truck travel time performance measures. Further, the presence of agricultural, light commercial, heavy commercial, light industrial, single-family residential, multi-family residential, office, transportation, and medical land uses increase the truck travel time performance measures (decrease the operational performance). The methodological approach and findings can be used in identifying potential areas to serve as truck priority zones and for planning decentralized delivery locations.
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Balza, Lenin H., Camilo De Los Rios, Alfredo Guerra, Luis Herrera-Prada, and Osmel Manzano. Unraveling the Network of the Extractive Industries. Inter-American Development Bank, April 2021. http://dx.doi.org/10.18235/0003191.

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This paper analyzes extractive industries in Colombia and their connections to other economic activities in the country. We use detailed social security data on all formal employees to create an industry-relatedness measure using labor flows between industries. Drawing on the vast network analysis literature, we exploit centrality measures to reveal the importance of the extractive sector among Colombian industries. Our results show that extractive industries are well connected within the Colombian industrial network, and that they are central overall and within their clusters. We also find that extractive industries have stronger linkages with manufacturing and agriculture than with other sectors. Finally, a higher relatedness to extractive activities is correlated with lower levels of employment, specially of female workers.
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Martínez-Ventura, Constanza, Jorge Ricardo Mariño-Martínez, and Javier Iván Miguélez-Márquez. Redundancy of Centrality Measures in Financial Market Infrastructures. Banco de la República de Colombia, August 2022. http://dx.doi.org/10.32468/be.1206.

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The concept of centrality has been widely used to monitor systems with a network structure because it allows identifying their most influential participants. But this monitoring task can be difficult if the number of system participants is considerably large or if the wide variety of centrality measures currently available produce non-coincident (or mixed) signals. This document uses principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in four financial market infrastructures of Colombia. The results obtained are used to construct general indices of centrality, using the strongest measures of centrality as inputs, and leaving aside those considered redundant.
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Lausche, Barbara, Aaron Laur, and Mary Collins. Marine Connectivity Conservation Rules of Thumb for MPA and MPA Network Design. IUCN WCPA Connectivity Conservation Specialist Group’s Marine Connectivity Working Group, August 2021. http://dx.doi.org/10.53847/jxqa6585.

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Marine Protected Areas (MPAs) are widely used as place-based protective measures for restoring and safeguarding marine biodiversity. When ecological connectivity is taken into account during design and management, the results can lead to more effective and resilient MPAs and MPA networks. This publication provides 13 ‘Rules of Thumb’ to support more consistent efforts by MPA managers and marine conservation professionals to implement connectivity conservation and better measure progress towards global conservation targets. These purpose-built tools are intended to inform more effective management and protection of oceans and coasts by covering a diversity of science and policy issues. They can also be used to progress system-based marine conservation as an essential component of national, transboundary, and global policies that establish greater connectivity across borders and at larger scales.
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Bielinskyi, Andrii O., and Vladimir N. Soloviev. Complex network precursors of crashes and critical events in the cryptocurrency market. [б. в.], December 2018. http://dx.doi.org/10.31812/123456789/2881.

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This article demonstrates the possibility of constructing indicators of critical and crash phenomena in the volatile market of cryptocurrency. For this purpose, the methods of the theory of complex networks have been used. The possibility of constructing dynamic measures of network complexity behaving in a proper way during actual pre-crash periods has been shown. This fact is used to build predictors of crashes and critical events phenomena on the examples of all the patterns recorded in the time series of the key cryptocurrency Bitcoin, the effectiveness of the proposed indicators-precursors of these falls has been identified.
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Hoaglund, Robert, and Walter Gazda. Assessment of Performance Measures for Security of the Maritime Transportation Network. Port Security Metrics: Proposed Measurement of Deterrence Capability. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada471403.

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Duffy-Turner, M., I. M. Nettleton, M. G. Winter, and I. Webber. Forensic Examination of Critical Special Geotechnical Measures: Soil Nails Information Note. TRL, June 2022. http://dx.doi.org/10.58446/eprl1160.

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The effective design, specification and construction of Special Geotechnical Measures (SGMs) is critical to the efficient operation of the National Highways Strategic Road Network (SRN). Given the required performance of the SRN in terms of resilience, reliability, redundancy and recovery it is essential that SGMs are themselves reliable in terms of performance and life; resilient to external conditions such as earthworks deterioration and extraordinary conditions (e.g. climate change). Around 100 different types of SGMs are used on the SRN and the early installations of some SGMs are approaching the end of their design life and the design, specification and application of many of these techniques is based on limited studies. This Information Note on Soil Nails is part of a series that reports on investigations of specific SGMs and makes recommendations on their future use
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