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Artykuły w czasopismach na temat "Network analysis"

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Kilkenny, Maureen, and Nerys Fuller Love. "Network analysis and business networks." International Journal of Entrepreneurship and Small Business 21, no. 3 (2014): 303. http://dx.doi.org/10.1504/ijesb.2014.060894.

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Jadhav, Pranavati, and Dr Burra Vijaya Babu. "Detection of Community within Social Networks with Diverse Features of Network Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (2019): 366–71. http://dx.doi.org/10.5373/jardcs/v11sp12/20193232.

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CVS, Rajesh, and Nadikoppula Pardhasaradhi. "Analysis of Artificial Neural-Network." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (2018): 418–28. http://dx.doi.org/10.31142/ijtsrd18482.

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KalaiSelvi, Dr B., and Aruna K. "Network Traffic Analysis Using Wireshark." International Journal of Research Publication and Reviews 4, no. 12 (2023): 1960–65. http://dx.doi.org/10.55248/gengpi.4.1223.123506.

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Karimi, Faezeh, David Green, Petr Matous, Manos Varvarigos, and Kaveh R. Khalilpour. "Network of networks: A bibliometric analysis." Physica D: Nonlinear Phenomena 421 (July 2021): 132889. http://dx.doi.org/10.1016/j.physd.2021.132889.

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Ashlesha, S. Nagdive, Tugnayat Rajkishor, and Peshkar Atharva. "Social Network Analysis of Terrorist Networks." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2553–59. https://doi.org/10.35940/ijeat.C5431.029320.

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Terrorist Activities worldwide has led to the development of sophisticated methodologies for analyzing terrorist groups and networks. Ongoing and past research has found that Social Network Analysis (SNA) is most effective method for predictive counter-terrorism. Social Network Analysis (SNA) is an approach towards analyzing the terrorist networks to better understand the underlying structure of a network and to detect key players within the network and their links throughout the network. It is also need of the hour to convert available raw data into valuable information for the purpose of glo
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Lobastova, M., A. Matyukhin, and A. Muthanna. "Analysis of Network Reliability of Network Synchronization." Telecom IT 8, no. 4 (2020): 93–99. http://dx.doi.org/10.31854/2307-1303-2020-8-4-93-99.

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This article describes the challenges of modern communication networks reliability, analyses ITU-T recommendations and regulations governing the communication networks reliability in Russian Federation. The network clock network is an integral part of digital communication networks. Therefore, the issue of the synchronization network reliability should be given great attention. Research subject. In this article, we discussed the reliability of the clock synchronization network. Method. The main mathematical tools are graph theory and probability theory. To implement the proposed method for ass
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Hafner-Burton, Emilie M., Miles Kahler, and Alexander H. Montgomery. "Network Analysis for International Relations." International Organization 63, no. 3 (2009): 559–92. http://dx.doi.org/10.1017/s0020818309090195.

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International relations research has regarded networks as a particular mode of organization, distinguished from markets or state hierarchies. In contrast, network analysis permits the investigation and measurement of network structures—emergent properties of persistent patterns of relations among agents that can define, enable, and constrain those agents. Network analysis offers both a toolkit for identifying and measuring the structural properties of networks and a set of theories, typically drawn from contexts outside international relations, that relate structures to outcomes. Network analy
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PELLEGRINI, Lilla, Monica LEBA, and Alexandru IOVANOVICI. "CHARACTERIZATION OF URBAN TRANSPORTATION NETWORKS USING NETWORK MOTIFS." Acta Electrotechnica et Informatica 20, no. 4 (2020): 3–9. http://dx.doi.org/10.15546/aeei-2020-0019.

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We use tools and techniques specific to the field of complex networks analysis for the identification and extraction of key parameters which define ”good” patterns and practices for designing public transportation networks. Using network motifs we analyze a set of 18 cities using public data sets regarding the topology of network and discuss each of the identified motifs using the concepts and tools of urban planning.
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Nasution, Mahyuddin K. M., Rahmad Syah, and Marischa Elveny. "Social Network Analysis: Towards Complexity Problem." Webology 18, no. 2 (2021): 449–61. http://dx.doi.org/10.14704/web/v18i2/web18332.

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Social network analysis is a advances from field of social networks. The structuring of social actors, with data models and involving intelligence abstracted in mathematics, and without analysis it will not present the function of social networks. However, graph theory inherits process and computational procedures for social network analysis, and it proves that social network analysis is mathematical and computational dependent on the degree of nodes in the graph or the degree of social actors in social networks. Of course, the process of acquiring social networks bequeathed the same complexit
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Rozprawy doktorskie na temat "Network analysis"

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Oesterheld, Matthias. "Analysis of biomolecular networks using a generic network analysis suite." kostenfrei, 2008. http://mediatum2.ub.tum.de/doc/646475/646475.pdf.

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Post, David L. "Network Management: Assessing Internet Network-Element Fault Status Using Neural Networks." Ohio : Ohio University, 2008. http://www.ohiolink.edu/etd/view.cgi?ohiou1220632155.

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Lim, Kok Seng. "Analysis of network management protocols in optical networks." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Mar%5FLim%5FK.pdf.

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Silva, do Monte Lima Jennifer. "Performance analysis of network composition in ambient networks." Universidade Federal de Pernambuco, 2007. https://repositorio.ufpe.br/handle/123456789/2637.

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Made available in DSpace on 2014-06-12T15:59:50Z (GMT). No. of bitstreams: 2 arquivo5648_1.pdf: 4215564 bytes, checksum: a4f0b99c7dc76ce7283ee541003ccb8a (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2007<br>Conselho Nacional de Desenvolvimento Científico e Tecnológico<br>Atualmente, o compartilhamento de recursos e oferta de serviços entre redes são permitidos apenas através de intensa configuração manual e acordos prévios entre as redes envolvidas. Devido às diferentes tecnologias de acesso, à heterogeneidade dos dispositivos e dos
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Woodbury, Nathan Scott. "Network Reconstruction and Vulnerability Analysis of Financial Networks." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6370.

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Passive network reconstruction is the process of learning a structured (networked) representation of a dynamic system through the use of known information about the structure of the system as well as data collected by observing the inputs into a system along with the resultant outputs. This work demonstrates an improvement on an existing network reconstruction algorithm so that the algorithm is capable of consistently and perfectly reconstructing a network when system inputs and outputs are measured without error. This work then extends the improved network reconstruction algorithm so that it
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Junuthula, Ruthwik Reddy. "Modeling, Evaluation and Analysis of Dynamic Networks for Social Network Analysis." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1544819215833249.

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Hassan, Aamir, and Fida Mohammad. "Network Security Analysis." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-4002.

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<p>Security  is  the second step after  that a successful network has been deployed. There are many  types  of  attacks  that  could  potentially  harm  the  network  and  an  administrator should  carefully  document  and  plan  the  weak  areas,  where  the  network  could  be compromised. Attackers use special tools and techniques to find out all the possible ways of defeating the network security.  This  thesis  addresses  all  the  possible  tools  and  techniques  that  attackers  use  to compromise the network. The purpose for exploring these tools will help an administrator to find the
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Mei, Jonathan B. "Principal Network Analysis." Research Showcase @ CMU, 2018. http://repository.cmu.edu/dissertations/1175.

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Many applications collect a large number of time series, for example, temperature continuously monitored by weather stations across the US or neural activity recorded by an array of electrical probes. These data are often referred to as unstructured. A first task in their analytics is often to derive a low dimensional representation { a graph or discrete manifold { that describes the inter relations among the time series and their intrarelations across time. In general, the underlying graphs can be directed and weighted, possibly capturing the strengths of causal relations, not just the binary
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Zhou, Lin. "Active network management and uncertainty analysis in distribution networks." Thesis, University of Bath, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675697.

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In distribution networks, the traditional way to eliminate network stresses caused by increasing generation and demand is to reinforce the primary network assets. A cheaper alternative is active network management (ANM) which refers to real-time network control to resolve power flow, voltage, fault current and security issues. However, there are two limitations in ANM. First, previous ANM strategies investigated generation side and demand side management separately. The generation side management evaluates the value from ANM in terms of economic generation curtailment. It does not consider the
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鄧沛權 and Pui-kuen Tang. "Business network: network marketing : analysis of network marketing using business network theories." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31268316.

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Książki na temat "Network analysis"

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Brandes, Ulrik, and Thomas Erlebach, eds. Network Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b106453.

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Combined Higher Education Software Team., Environmental Systems Research Institute, and Manchester Computing Centre, eds. Network analysis. Manchester Computing Centre, 1993.

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Hodgson. Novell Netware protocol and network analysis. University of Manchester, Department of Computer Science, 1996.

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Freeman, Linton. Social Network Analysis. SAGE Publications Ltd, 2008. http://dx.doi.org/10.4135/9781446263464.

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Knoke, David, and Song Yang. Social Network Analysis. SAGE Publications, Inc., 2008. http://dx.doi.org/10.4135/9781412985864.

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Xu, Kuai. Network Behavior Analysis. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8325-1.

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Holt, Alan. Network Performance Analysis. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84628-823-4.

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Fellin, Tommaso, and Michael Halassa, eds. Neuronal Network Analysis. Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-633-3.

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Bonald, Thomas, and Mathieu Feuillet. Network Performance Analysis. John Wiley & Sons, Inc, 2011. http://dx.doi.org/10.1002/9781118602911.

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Horvath, Steve. Weighted Network Analysis. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8819-5.

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Części książek na temat "Network analysis"

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Cellerino, Alessandro, and Michele Sanguanini. "Network analysis." In Transcriptome Analysis. Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_7.

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Brinkmeier, Michael, and Thomas Schank. "Network Statistics." In Network Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31955-9_11.

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Baur, Michael, and Marc Benkert. "Network Comparison." In Network Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31955-9_12.

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Baumann, Nadine, and Sebastian Stiller. "Network Models." In Network Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31955-9_13.

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Costantini, Giulio, and Marco Perugini. "Network Analysis." In The Wiley Handbook of Personality Assessment. John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781119173489.ch6.

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Rennels, Donald C., and Hobart M. Hudson. "Network Analysis." In Pipe Flow. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118275276.ch5.

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Costantini, Giulio, and Marco Perugini. "Network Analysis." In Encyclopedia of Personality and Individual Differences. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_1332.

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Vanhoucke, Mario. "Network Analysis." In Integrated Project Management Sourcebook. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27373-0_3.

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Gallupe, Owen. "Network Analysis." In The Handbook of Measurement Issues in Criminology and Criminal Justice. John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781118868799.ch25.

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Morrissey, Sean. "Network Analysis." In iOS Forensic Analysis for iPhone, iPad, and iPod touch. Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3343-5_10.

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Streszczenia konferencji na temat "Network analysis"

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Wang, Yonghui, Jin Liu, Zhe Li, Jiaqi Ren, and Weili Li. "Analysis of Network Resilience for Physical-Logical Dual-Layer Networks in Network Management Nodes." In 2024 10th International Conference on Big Data and Information Analytics (BigDIA). IEEE, 2024. https://doi.org/10.1109/bigdia63733.2024.10808482.

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K, Arun Kumar, Barath C, J. Merlin Mary Jenitha, and L. Mary Gladence. "An Analysis on Generative Adversarial Networks Integrated Network Intrusion Detection System." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933451.

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Melo, Renato Silva, and André Luís Vignatti. "Preprocessing Rules for Target Set Selection in Complex Networks." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/brasnam.2020.11167.

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In the Target Set Selection (TSS) problem, we want to find the minimum set of individuals in a network to spread information across the entire network. This problem is NP-hard, so find good strategies to deal with it, even for a particular case, is something of interest. We introduce preprocessing rules that allow reducing the size of the input without losing the optimality of the solution when the input graph is a complex network. Such type of network has a set of topological properties that commonly occurs in graphs that model real systems. We present computational experiments with real-worl
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Bursztyn, Victor S., Marcelo Granja Nunes, and Daniel R. Figueiredo. "How Congressmen Connect: Analyzing Voting and Donation Networks in the Brazilian Congress." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6451.

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The goal of this work is to analyze two of the most central activities in the life of a congressman: raising funds and voting bills. We investigate the Brazilian Congress to shed light on the relationships between the donations received by congressmen elected in 2014 and their voting behaviors during the year of 2015. We merged publicly available data obtained from the Brazilian House of Representatives and the Superior Electoral Court (TSE) in order to create a tripartite network containing campaign donors, elected congressmen, and legal bills. Using this data, we create two projected network
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Maruyama, William Takahiro, and Luciano Antonio Digiampietri. "Co-authorship prediction in academic social network." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6445.

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The prediction of relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating the most promising partnerships. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents an approach to predict coauthorships combining artificial intelligence techniques with the state-of-the-art metrics for link predicting in social networks.
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Brandão, Michele A., Matheus A. Diniz, and Mirella M. Moro. "Using Topological Properties to Measure the Strength of Co-authorship Ties." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6455.

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Studying the strength of ties in social networks allows to identify impact at micro-macro levels in the network, to analyze how distinct relationships play different roles, and so on. Indeed, the strength of ties has been investigated in many contexts with different goals. Here, we aim to address the problem of measuring ties strength in co-authorship social networks. Specifically, we present four case studies detailing problems with current metrics and propose a new one. Then, we build a co-authorship social network by using a real digital library and identify how the strength of ties relates
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Soares, Rafael Henrique Santos, Jorge H. C. Fernandes, and Ricardo Sampaio. "Formal Information Flows Among Top Authorities of the Brazilian Federal Government based on Co-word Analysis of Data Published in the Official Gazette." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/brasnam.2016.6450.

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This paper describes a methodology for modeling social networks of formal communications among top authorities of the Brazilian Federal Government grounded on data available in the government official gazette (Diário Oficial da União). The text of a large number of official publications such as presidential decrees, ministerial orders and authority nominations was analyzed for identification of citations to organizations and persons. The co-occurrence of names of persons in such publications created a network of relations among such persons. An ego-network was built around the president Dilma
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Oliveira, Davi Alves, Erica dos Santos Rodrigues, and Hernane Borges de Barros Pereira. "Affinity Networks as a Tool for Assessing Writing Processes: A Novel Method Utilizing Pause-Based Visibility Graphs." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/brasnam.2023.229991.

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This study proposes utilizing affinity networks to characterize writing profiles by examining pausing behavior during writing tasks. Data from 34 participants was collected using Inputlog. Pauses were used to create visibility graphs, and the resulting graph metrics were used to build an affinity network. The network was then analyzed to group writers based on their pausing behavior. Results indicate that this method can be used to identify different writing profiles of writers with distinct proficiency in text production. Future research should investigate if changes in pausing behavior can i
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Silva, Mariana O., Gabriel P. Oliveira, and Mirella M. Moro. "Analyzing Character Networks in Portuguese-language Literary Works." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/brasnam.2023.230585.

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Literary works are complex narratives with multifaceted character relationships. Studying these relationships can reveal important insights into the story’s structure and each character’s contribution to the plot development. This research investigates character networks in Portuguese-language literature using two main analytical approaches: structural network analysis and character importance metrics. Our analyses emphasize the significance of character networks in understanding the narrative structure of literary works and reveal the intricate interplay between characters in Portuguese-langu
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Popescu, Daniela, Elena Serban, Carmen-Ema Panaite, and Abel Herna´ndez-Guerrero. "Hydraulic Analysis of a District Heating Network." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59352.

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The aim of this work is to study the influence of pressure loss parameters from a district heating system on the distribution of fluid flow rates. The research was finalized by improving the mathematical model of a district heating network, which comprises an algebraic non-linear system that synthesizes flow balance equations of a stationary flow. This enhanced model indicates the influence of every consumer’s heat demand supplied from a district heating network on the fluid flow rates distribution based on the means of the implicit function theorem. The originality of the method consists of c
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Raporty organizacyjne na temat "Network analysis"

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Snijders, Tom. Longitudinal Social Network Analysis. Instats Inc., 2024. https://doi.org/10.61700/zimra7qjrsnu11850.

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This three-day workshop provides an introductory overview of longitudinal social network analysis using the RSiena package, focusing on the application of Stochastic Actor-oriented Models to study network dynamics and the co-evolution of networks and behavior. Participants will gain practical skills in modeling network panel data, as well as modeling co-evolution of networks and behavior, for application of these techniques across various academic disciplines.
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Kalb, Jeffrey L., and David S. Lee. Network topology analysis. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/1028919.

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Bonnett, Michaela, Chimdi Ezeigwe, Meaghan Kennedy, and Teri Garstka. Using Social Network Analysis to Link Community Health and Network Strength. Orange Sparkle Ball, 2023. http://dx.doi.org/10.61152/scsf6662.

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Social network analysis (SNA) is a technique used to analyze social networks, whether it be composed of people, organizations, physical locations, or objects. It is being increasingly applied across a variety of sectors to gain insight into patterns of behavior and connectivity, the flow of information and behaviors, and to track and predict the effectiveness of interventions or programs. A key area associated with network strength using SNA is the health and wellness of individuals and communities. Both network strength and health and wellness are measured in many ways, which can obfuscate th
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R.T. Rosche. IDCS NETWORK ALTERNATIVES ANALYSIS. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/883443.

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Meyer, Robert A., and David A. Perreault. Communication Network Software Analysis. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada281019.

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Zinilli, Antonio. From Basic to Advanced Network Analysis in R. Instats Inc., 2024. http://dx.doi.org/10.61700/t68209rotxkow930.

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This 2-day workshop offers a comprehensive understanding of network analysis and its application in R. Tailored for PhD students, professors, and professional researchers, this workshop provides a strong theoretical foundation and hands-on experience in visualizing and analyzing complex networks in socio-economic contexts, equipping participants with practical skills needed to apply network analysis in their own research.
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Lee, Hyun-Jung, HyunJu Shin, Kyu-Hye Lee, Seulah Lee, and Ye-Jin In. Semantic Network Analysis of Gorpcore. Iowa State University. Library, 2019. http://dx.doi.org/10.31274/itaa.8218.

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Christie, Alan M. Network Survivability Analysis Using Easel. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada413664.

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Johannes, James D., Tim Lewis, Kyle Hoover, Andrew Fanning, and Chad Williams. Computer Network Analysis and Implementation. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada391962.

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Powell, Bruce C. Artificial Neural Network Analysis System. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada392390.

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