Letteratura scientifica selezionata sul tema "Online knowledge networks"
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Articoli di riviste sul tema "Online knowledge networks"
Angiani, Giulio, Paolo Fornacciari, Eleonora Iotti, Monica Mordonini e Michele Tomaiuolo. "Participation in Online Social Networks". International Journal of Interactive Communication Systems and Technologies 8, n. 2 (luglio 2018): 36–55. http://dx.doi.org/10.4018/ijicst.2018070103.
Testo completoMelton, James, Robert Miller e Michelle Salmona. "Online Social Networks". International Journal of Information Systems and Social Change 3, n. 2 (aprile 2012): 24–38. http://dx.doi.org/10.4018/ijissc.2012040102.
Testo completoLi, Yongning, Lun Zhang e Ye Wu. "Understanding the Dynamics of Knowledge Building Process in Online Knowledge-Sharing Platform: A Structural Analysis of Zhihu Tag Network". Complexity 2022 (28 maggio 2022): 1–11. http://dx.doi.org/10.1155/2022/7392186.
Testo completoPreusse, Julia, Jérôme Kunegis, Matthias Thimm, Steffen Staab e Thomas Gottron. "Structural Dynamics of Knowledge Networks". Proceedings of the International AAAI Conference on Web and Social Media 7, n. 1 (3 agosto 2021): 506–15. http://dx.doi.org/10.1609/icwsm.v7i1.14402.
Testo completoWu, Guile, e Shaogang Gong. "Peer Collaborative Learning for Online Knowledge Distillation". Proceedings of the AAAI Conference on Artificial Intelligence 35, n. 12 (18 maggio 2021): 10302–10. http://dx.doi.org/10.1609/aaai.v35i12.17234.
Testo completoZhang GuoYin, e Li Heng. "Research on Semantic Networks Based Online Learning Knowledge Management". International Journal of Digital Content Technology and its Applications 6, n. 8 (31 maggio 2012): 126–34. http://dx.doi.org/10.4156/jdcta.vol6.issue8.15.
Testo completoYang, Bo, Lulu Wang e Bayan Omar Mohammed. "Improving the organizational knowledge sharing through online social networks". Kybernetes 49, n. 11 (2 dicembre 2019): 2615–32. http://dx.doi.org/10.1108/k-07-2019-0508.
Testo completoMussina, A. B., S. S. Aubakirov e P. Trigo. "Architecture for enduring knowledge-extraction from online social networks". BULLETIN of the L N Gumilyov Eurasian National University MATHEMATICS COMPUTER SCIENCE MECHANICS Series 140, n. 3 (2022): 23–32. http://dx.doi.org/10.32523/2616-7182/bulmathenu.2022/3.3.
Testo completoCrowne, Kerri Anne, Richard J. Goeke e Mary Shoemaker. "Enhancing international assignees’ performance with online social networks". Journal of Global Mobility 3, n. 4 (14 dicembre 2015): 397–417. http://dx.doi.org/10.1108/jgm-09-2014-0045.
Testo completoGao, Liang, Xu Lan, Haibo Mi, Dawei Feng, Kele Xu e Yuxing Peng. "Multistructure-Based Collaborative Online Distillation". Entropy 21, n. 4 (2 aprile 2019): 357. http://dx.doi.org/10.3390/e21040357.
Testo completoTesi sul tema "Online knowledge networks"
Schmitz-Justen, Felix J. "Knowledge factors : how to animate members of online communities to create knowledge-relevant content /". Frankfurt am Main [u.a.] : Lang, 2006. http://www.loc.gov/catdir/toc/fy0710/2006047271.html.
Testo completoRay, Aaron Parker. "Planning Connected: Using Online Social Networks to Improve Knowledge about Places and Communities". DigitalCommons@CalPoly, 2011. https://digitalcommons.calpoly.edu/theses/580.
Testo completoTeigland, Robin. "Knowledge networking : structure and performance in networks of practice". Doctoral thesis, Handelshögskolan i Stockholm, Institute of International Business (IIB), 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-1958.
Testo completoMushonga, Cleopatra Tsungai. "Social networking for knowledge management : group features as personal knowledge management tools". Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86315.
Testo completoENGLISH ABSTRACT: With the emergence of Web 2.0 (social network platforms) some Knowledge Management theorists saw the potential for incorporating its collaborative and networking features in Knowledge Management Systems. However, the consensus is that harnessing Web 2.0 features for Knowledge Management is still in its infancy and according to some it seems that Web 2.0 success in the social sphere is hard to translate to the work context. The thesis argues that Web 2.0 primarily facilitates Personal Knowledge Management (PKM) and in this way indirectly contributes to Organisational Knowledge Management. Furthermore not all Web 2.0 features are equally useful in facilitating Personal Knowledge Management. The thesis identifies the group features of social network platforms as the prime locations for networking and learning. The thesis is theoretically based on Cheong and Tsui's PKM 2.0 model, in particular the Interpersonal Knowledge Transferring phase that in turn is based on Nonaka's SECI model of knowledge conversion. The thesis starts out with considering the distinction and relationship between Organisational Knowledge Management (OKM) and Personal Knowledge Management (PKM). Thereafter Cheong and Tsui's PKM 2.0 model is described as well as Nonaka's SECI model. The Web 2.0 phenomenon is introduced through a literature review of various studies on the usefulness of social network platforms and the group features are specifically highlighted. A survey is conducted among users of a particular Web 2.0 group feature, based on questions developed from the SECI and PKM 2.0 models. The thesis comes to the conclusion that the group features of Web 2.0 social network platforms are useful for Knowledge Management, because it is indeed a component of users' Personal Knowledge Management.
AFRIKAANSE OPSOMMING: Sekere Kennisbestuursteoretici het met die opkoms van Web 2.0 (sosiale netwerk-platforms) die moontlikheid waargeneem om die samewerks- en netwerk-funksionaliteit van Web 2.0 platforms met bestaande Kennisbestuurstelsels te integreer. Die konsensus is egter dat sulke pogings nog veel tekortskiet en sommige waarnemers meen dat dit baie moeilik sal wees om Web 2.0 se sukses in die sosiale sfeer in die werksplek in te span. Die tesis argumenteer dat Web 2.0 hoofsaaklik Persoonlike Kennisbestuur (PKB) fasiliteer en langs hierdie ompad 'n bydrae lewer tot Organisatoriese Kennisbestuur (OKB). Verder lewer alle funksionaliteite van Web 2.0 nie 'n bruikbare bydra tot Kennisbestuur nie, maar is dit hoofsaaklik die groepsfunksies wat bruikbaar is in terme van netwerking en leer. Die tesis is teoreties gewortel in Cheong en Tsui se PKB 2.0 model, veral die Interpersoonlike Kennisoordragsfase wat weer op Nonaka se SEKI model gebaseer is. Die tesis oorweeg aanvanklik die onderskeid en verhouding tussen Organisatoriese Kennisbestuur (OKB) en Persoonlike Kennisbestuur (PKB). Daarna word Cheong en Tsui se PKB 2.0 model en Nonaka se SEKI model bespreek. Die Web 2.0 fenomeen word beskryf aan die hand van 'n literatuurstudie van navorsing oor die bruikbaarheid van Web 2.0 platforms en die groepsfunksionaliteit word spesifiek belig. 'n Vraelys, gebaseer op die SEKI en PKB 2.0 modelle, is onder gebruikers van 'n spesifieke Web 2.0 groepsfunksie geadministreer. Die tesis kom tot die konklusie dat die groepsfunksies van Web 2.0 sosiale netwerk-platforms bruikbaar is vir Kennisbestuur, want dit is inderdaad 'n komponent van gebruikers se Persoonlike Kennisbestuur (PKB).
Ogbamichael, Hermon Berhane. "Information & knowledge sharing within virtual communities of practice (VCoPs)". Thesis, Cape Peninsula University of Technology, 2017. http://hdl.handle.net/20.500.11838/2799.
Testo completoThe concept of virtual community of practice (VCoP) emanates from the need to create a new mode of learning and knowledge creation. It is found that highly structured forums are not necessarily the best way to assist people to learn and improve their knowledge. This then, requires organisations to seek alternative informal ways to share knowledge. The significance of optimising knowledge sharing results in VCoPs receiving considerable attention while searching for new ways to draw on expertise dispersed across global operations. This impacts organisations, thereby enabling them to respond more speedily to the demands of their stakeholders. The fast pace of change in their business environments is also a factor to contend with. Within this context, the use of VCoPs to optimise both, tacit and explicit knowledge sharing within stakeholders, is the central theme of this research. The findings from literature enables the researcher to explore scientific based models that may have the potential to enhance knowledge sharing in an enterprise. The Life Cycle knowledge flow model is found to be the most comprehensive compared to two other models – namely, a Spiral knowledge flow model and Dynamic knowledge flow model. The outflow from the findings in literature is that the Life Cycle knowledge flow model is selected as the basis to conduct two surveys to determine if the model could be adapted to improve knowledge sharing within VCoPs in particular, and in an enterprise in general. The result of the two surveys conducted (in 2011/2012 and 2016), leads to establishing an extended Life Cycle knowledge flow model. The established model enhances knowledge sharing within VCoPs, and in turn, assists when optimising knowledge sharing in an enterprise. This extended model covers six phases of knowledge development to improve knowledge sharing within VCoPs. The first phase enhances the creation of both, tacit and explicit knowledge. The second phase enables to optimise the organisation of knowledge. The third phase enables the formalisation of tacit knowledge, that is, conversion of tacit to explicit knowledge. The fourth phase improves the distribution of knowledge. The fifth phase enables to optimise the application of knowledge and the final phase enables the evolution or continuous development of knowledge. The contribution of this research proposes that a comprehensive knowledge flow model, namely the Life Cycle knowledge flow model found in literature, served as the basis for this research. However, this model was never tested or verified if it indeed optimises knowledge sharing within VCoPs. The two surveys (Survey One 2011/12 and Survey Two 2016) were developed and distributed to respondents to verify the model’s suitability to VcoPs. As a result of responses received from the two surveys, the researcher was then able to develop an extended Life Cycle knowledge flow model that particularly, optimises knowledge sharing within VCoPs. This research further contributes in formulating a scientific based knowledge flow model that can be adapted to social networks. Therefore, this research also creates the foundation to further study to investigate the optimisation of knowledge sharing in social networks. In recent literature, social networks are established as one of the informal mechanisms to share and enhance knowledge sharing in an enterprise.
Stuckey, Bronwyn. "Growing online community core conditions to support successful development of community in internet-mediated communities of practice /". Access electronically, 2007. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20080911.092048/index.html.
Testo completoLaw, Pui Man. "Fostering knowledge contribution in online communities : and examination of social capital, social capital building, and the role of IT artifacts". HKBU Institutional Repository, 2012. https://repository.hkbu.edu.hk/etd_ra/1395.
Testo completoBuranaburivast, Vorapoj. "Applying social capital to electronic networks of practice : blog communities". UWA Business School, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0209.
Testo completoKurka, David Burth 1988. "Online social networks = knowledge extraction from information diffusion and analysis of spatio-temporal phenomena = Redes sociais online: extração de conhecimento e análise espaço-temporal de eventos de difusão de informação". [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259074.
Testo completoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
Made available in DSpace on 2018-08-27T03:14:35Z (GMT). No. of bitstreams: 1 Kurka_DavidBurth_M.pdf: 1660677 bytes, checksum: 7258daf8129b4dac9d1f647195775d3c (MD5) Previous issue date: 2015
Resumo: Com o surgimento e a popularização de Redes Sociais Online e de Serviços de Redes Sociais, pesquisadores da área de computação têm encontrado um campo fértil para o desenvolvimento de trabalhos com grande volume de dados, modelos envolvendo múltiplos agentes e dinâmicas espaço-temporais. Entretanto, mesmo com significativo elenco de pesquisas já publicadas no assunto, ainda existem aspectos das redes sociais cuja explicação é incipiente. Visando o aprofundamento do conhecimento da área, este trabalho investiga fenômenos de compartilhamento coletivo na rede, que caracterizam eventos de difusão de informação. A partir da observação de dados reais oriundos do serviço online Twitter, tais eventos são modelados, caracterizados e analisados. Com o uso de técnicas de aprendizado de máquina, são encontrados padrões nos processos espaço-temporais da rede, tornando possível a construção de classificadores de mensagens baseados em comportamento e a caracterização de comportamentos individuais, a partir de conexões sociais
Abstract: With the advent and popularization of Online Social Networks and Social Networking Services, computer science researchers have found fertile field for the development of studies using large volumes of data, multiple agents models and spatio-temporal dynamics. However, even with a significant amount of published research on the subject, there are still aspects of social networks whose explanation is incipient. In order to deepen the knowledge of the area, this work investigates phenomena of collective sharing on the network, characterizing information diffusion events. From the observation of real data obtained from the online service Twitter, we collect, model and characterize such events. Finally, using machine learning and computational data analysis, patterns are found on the network's spatio-temporal processes, making it possible to classify a message's topic from users behaviour and the characterization of individual behaviour, from social connections
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica
Köhler, Thomas, Nina Kahnwald e Eric Schoop. "Wissensgemeinschaften 2015: 18. GeNeMe-Workshop, TU Dresden, 25./26.06.2015: GeNeMe 2015, Gemeinschaften in Neuen Medien". Technische Universität Dresden, 2015. https://tud.qucosa.de/id/qucosa%3A28972.
Testo completoLibri sul tema "Online knowledge networks"
Johnson, J. David. Managing knowledge networks. New York: Cambridge University Press, 2009.
Cerca il testo completoJohnson, J. David. Managing knowledge networks. Cambridge, UK: Cambridge University Press, 2009.
Cerca il testo completoHars, Alexander. From publishing to knowledge networks: Reinventing online knowledge infrastructures. Berlin: Springer, 2003.
Cerca il testo completoHars, Alexander. From publishing to knowledge networks: Reinventing online knowledge infrastructures. Berlin: Springer-Verlag, 2010.
Cerca il testo completoBruggemann, Stefan, e Claudia d'Amato. Collaboration and the Semantic Web: Social networks, knowledge networks and knowledge resources. Hershey, PA: Information Science Reference, 2012.
Cerca il testo completoSchmitz-Justen, Felix J. Knowledge factors: How to animate members of online communities to create knowledge-relevant content. Frankfurt am Main, Germany: Lang, 2006.
Cerca il testo completoTakseva, Tatjana. Social software and the evolution of user expertise: Future trends in knowledge creation and dissemination. Hershey, PA: Information Science Reference, 2013.
Cerca il testo completoWeller, Katrin. Knowledge representation in the social semantic Web. New York: De Gruyter Saur, 2010.
Cerca il testo completo1977-, Sun Chen, Cheng Jun 1964- e Ohira Takashi 1955-, a cura di. Handbook on advancements in smart antenna technologies for wireless networks. Hershey, PA: Information Science Reference, 2008.
Cerca il testo completoWilhelm, Daniel B. Nutzerakzeptanz von webbasierten Anwendungen: Modell zur Akzeptanzmessung und Identifikation von Verbesserungspotenzialen. Wiesbaden [Germany]: Springer Gabler Research, 2012.
Cerca il testo completoCapitoli di libri sul tema "Online knowledge networks"
Aalberts, Chris, e Maurits Kreijveld. "Knowledge exchange through online political networks". In Knowledge Democracy, 315–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11381-9_21.
Testo completoFei, Luo, Tianxing Wu e Arijit Khan. "Online Updates of Knowledge Graph Embedding". In Complex Networks & Their Applications X, 523–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93413-2_44.
Testo completoRevelle, Matt, Carlotta Domeniconi e Aditya Johri. "Persistent Roles in Online Social Networks". In Machine Learning and Knowledge Discovery in Databases, 47–62. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46227-1_4.
Testo completoHuynh, Tuyen N., e Raymond J. Mooney. "Online Structure Learning for Markov Logic Networks". In Machine Learning and Knowledge Discovery in Databases, 81–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23783-6_6.
Testo completoLi, Xiaoxue, Yanan Cao, Yanmin Shang, Yanbing Liu, Jianlong Tan e Li Guo. "Inferring User Profiles in Online Social Networks Based on Convolutional Neural Network". In Knowledge Science, Engineering and Management, 274–86. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63558-3_23.
Testo completoHu, Yuxuan, Quan Bai e Weihua Li. "Context-Aware Influence Diffusion in Online Social Networks". In Knowledge Management and Acquisition for Intelligent Systems, 153–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30639-7_13.
Testo completoKaushal, Rishabh, Chetna Sharma e Ponnurangam Kumaraguru. "Detection of Misbehaviors in Clone Identities on Online Social Networks". In Mining Intelligence and Knowledge Exploration, 94–103. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-66187-8_10.
Testo completoMilolidakis, Giannis, Chris Kimble e Demosthenes Akoumianakis. "A Practice-Based Analysis of an Online Strategy Game". In Leveraging Knowledge for Innovation in Collaborative Networks, 433–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04568-4_45.
Testo completoKelly, Nick, Marc Clarà, Benjamin Kehrwald e Patrick Alan Danaher. "Developing Teacher Knowledge and Reflection". In Online Learning Networks for Pre-Service and Early Career Teachers, 31–41. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-50302-2_4.
Testo completoLauw, Hady W., Ee-Peng Lim e Ke Wang. "On Mining Rating Dependencies in Online Collaborative Rating Networks". In Advances in Knowledge Discovery and Data Mining, 1054–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01307-2_113.
Testo completoAtti di convegni sul tema "Online knowledge networks"
Lin, Wenye, Yangning Li, Yifeng Ding e Hai-Tao Zheng. "Tree-structured Auxiliary Online Knowledge Distillation". In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9892764.
Testo completoRamachandran, Arthi, e Augustin Chaintreau. "Who Contributes to the Knowledge Sharing Economy?" In COSN'15: Conference on Online Social Networks. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2817946.2817963.
Testo completoJiang, Jiawei, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu e Bin Cui. "Analyzing Online Transaction Networks with Network Motifs". In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3534678.3539096.
Testo completoZhu, Xuan, Wangshu Yao e Kang Song. "Online Knowledge Distillation with Multi-Architecture Peers". In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9892595.
Testo completoLi, Chengcheng, Zi Wang e Hairong Qi. "Online Knowledge Distillation with History-Aware Teachers". In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9892064.
Testo completoMasoumzadeh, Amirreza, e Andrew Cortese. "Towards Measuring Knowledge Exposure in Online Social Networks". In 2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC). IEEE, 2016. http://dx.doi.org/10.1109/cic.2016.080.
Testo completoDu, Xiaocong, Shreyas Kolala Venkataramanaiah, Zheng Li, Jae-sun Seo, Frank Liu e Yu Cao. "Online Knowledge Acquisition with the Selective Inherited Model". In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9206904.
Testo completoDey, Paramita, Agneet Chatterjee e Sarbani Roy. "Knowledge based community detection in online social network". In 2018 10th International Conference on Communication Systems & Networks (COMSNETS). IEEE, 2018. http://dx.doi.org/10.1109/comsnets.2018.8328287.
Testo completoBadri Satya, Prudhvi Ratna, Kyumin Lee, Dongwon Lee, Thanh Tran e Jason (Jiasheng) Zhang. "Uncovering Fake Likers in Online Social Networks". In CIKM'16: ACM Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2983323.2983695.
Testo completoSoon, Lisa, e Campbell Fraser. "Knowledge activities in distance education online group work". In 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN). IEEE, 2011. http://dx.doi.org/10.1109/iccsn.2011.6013849.
Testo completoRapporti di organizzazioni sul tema "Online knowledge networks"
Droogan, Julian, Lise Waldek, Brian Ballsun-Stanton e Jade Hutchinson. Mapping a Social Media Ecosystem: Outlinking on Gab & Twitter Amongst the Australian Far-right Milieu. RESOLVE Network, settembre 2022. http://dx.doi.org/10.37805/remve2022.6.
Testo completoLewis, Dustin, a cura di. International Counterterrorism Efforts: An Initial Mapping. Harvard Law School Program on International Law and Armed Conflict, febbraio 2015. http://dx.doi.org/10.54813/ktkl6017.
Testo completoIto, Rodrigo, Diego Chavarro, Tommaso Ciarli, Robin Cowan e Fabiana Visentin. Connecting the Dots: The Role of Internationally Mobile Scientists in Linking Nonmobile with Foreign Scientists. Inter-American Development Bank, gennaio 2024. http://dx.doi.org/10.18235/0005541.
Testo completoMilek, Karen, e Richard Jones, a cura di. Science in Scottish Archaeology: ScARF Panel Report. Society of Antiquaries of Scotland, settembre 2012. http://dx.doi.org/10.9750/scarf.06.2012.193.
Testo completoZeng, Jing, Qing Liu, Zhengfang Lei, Zhe Sun e Yang Wang. Evaluation of Integrated Neuromuscular Training on the Recovery of Joint Injury: A Meta-Analysis and Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, dicembre 2021. http://dx.doi.org/10.37766/inplasy2021.12.0136.
Testo completoBabenko, Vitalina O., Roman M. Yatsenko, Pavel D. Migunov e Abdel-Badeeh M. Salem. MarkHub Cloud Online Editor as a modern web-based book creation tool. [б. в.], luglio 2020. http://dx.doi.org/10.31812/123456789/3858.
Testo completoBarjum, Daniel. PDIA for Systems Change: Tackling the Learning Crisis in Indonesia. Research on Improving Systems of Education (RISE), settembre 2022. http://dx.doi.org/10.35489/bsg-rise-ri_2022/046.
Testo completoWerny, Rafaela, Marie Reich, Miranda Leontowitsch e Frank Oswald. EQualCare Policy Report Germany : Alone but connected? Digital (in)equalities in care work and generational relationships among older people living alone. Frankfurter Forum für interdisziplinäre Alternsforschung, Goethe-Universität Frankfurt am Main, ottobre 2022. http://dx.doi.org/10.21248/gups.69905.
Testo completoBowman, Steve, Relu Burlacu, John Crofts, Debi Kilb, Keith Koper, Emily Morton e Debbie Worthen. On the Feasibility of Implementing an Earthquake Early Warning (EEW) System in Utah. Utah Geological Survey, gennaio 2024. http://dx.doi.org/10.34191/eew-2023.
Testo completoBrown, Nicholas, Hannah Macdonell, Emilie Stewart-Jones e Stephan Gruber. Permafrost Data Systems: RCOP 2021 Data Workshop Report. NSERC/Carleton University, novembre 2021. http://dx.doi.org/10.22215/pn/10121001.
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