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Статті в журналах з теми "Data modelling frameworks"
Murray, S. G., C. Power, and A. S. G. Robotham. "Modelling Galaxy Populations in the Era of Big Data." Proceedings of the International Astronomical Union 10, S306 (May 2014): 304–6. http://dx.doi.org/10.1017/s1743921314010710.
Повний текст джерелаUrquhart, Christine, and Dina Tbaishat. "Reflections on the value and impact of library and information services." Performance Measurement and Metrics 17, no. 1 (April 11, 2016): 29–44. http://dx.doi.org/10.1108/pmm-01-2016-0004.
Повний текст джерелаHerath, Herath Mudiyanselage Viraj Vidura, Jayashree Chadalawada, and Vladan Babovic. "Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling." Hydrology and Earth System Sciences 25, no. 8 (August 11, 2021): 4373–401. http://dx.doi.org/10.5194/hess-25-4373-2021.
Повний текст джерелаStøa, Bente, Rune Halvorsen, Sabrina Mazzoni, and Vladimir I. Gusarov. "Sampling bias in presence-only data used for species distribution modelling: theory and methods for detecting sample bias and its effects on models." Sommerfeltia 38, no. 1 (October 1, 2018): 1–53. http://dx.doi.org/10.2478/som-2018-0001.
Повний текст джерелаOden, J. Tinsley. "Adaptive multiscale predictive modelling." Acta Numerica 27 (May 1, 2018): 353–450. http://dx.doi.org/10.1017/s096249291800003x.
Повний текст джерелаChartier, Jean-François, Davide Pulizzotto, Louis Chartrand, and Jean-Guy Meunier. "A data-driven computational semiotics: The semantic vector space of Magritte’s artworks." Semiotica 2019, no. 230 (October 25, 2019): 19–69. http://dx.doi.org/10.1515/sem-2018-0120.
Повний текст джерелаShivakumar, Abhishek, Thomas Alfstad, and Taco Niet. "A clustering approach to improve spatial representation in water-energy-food models." Environmental Research Letters 16, no. 11 (October 29, 2021): 114027. http://dx.doi.org/10.1088/1748-9326/ac2ce9.
Повний текст джерелаaus der Beek, T., M. Flörke, D. M. Lapola, R. Schaldach, F. Voß, and E. Teichert. "Modelling historical and current irrigation water demand on the continental scale: Europe." Advances in Geosciences 27 (September 7, 2010): 79–85. http://dx.doi.org/10.5194/adgeo-27-79-2010.
Повний текст джерелаWilbert, Niko, Tiziano Zito, Rike-Benjamin Schuppner, Zbigniew Jędrzejewski-Szmek, Laurenz Wiskott, and Pietro Berkes. "Building extensible frameworks for data processing: The case of MDP, Modular toolkit for Data Processing." Journal of Computational Science 4, no. 5 (September 2013): 345–51. http://dx.doi.org/10.1016/j.jocs.2011.10.005.
Повний текст джерелаLedien, Julia, Zulma M. Cucunubá, Gabriel Parra-Henao, Eliana Rodríguez-Monguí, Andrew P. Dobson, Susana B. Adamo, María-Gloria Basáñez, and Pierre Nouvellet. "Linear and machine learning modelling for spatiotemporal disease predictions: Force-of-infection of Chagas disease." PLOS Neglected Tropical Diseases 16, no. 7 (July 19, 2022): e0010594. http://dx.doi.org/10.1371/journal.pntd.0010594.
Повний текст джерелаДисертації з теми "Data modelling frameworks"
Bryan-Kinns, Nicholas Jonathan. "A framework for modelling video content." Thesis, Queen Mary, University of London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287876.
Повний текст джерелаHempel, Arne-Jens, and Steffen F. Bocklisch. "Parametric Fuzzy Modelling Framework for Complex Data-Inherent Structures." Universitätsbibliothek Chemnitz, 2009. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200901487.
Повний текст джерелаSerpeka, Rokas. "Analyzing and modelling exchange rate data using VAR framework." Thesis, KTH, Matematik (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-94180.
Повний текст джерелаSilverwood, Richard Jonathan. "Issues in modelling growth data within a life course framework." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2008. http://researchonline.lshtm.ac.uk/682377/.
Повний текст джерелаEkaterina, Guseva. "The Conceptual Integration Modelling Framework: Semantics and Query Answering." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33464.
Повний текст джерелаMgbemena, Chidozie Simon. "A data-driven framework for investigating customer retention." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13175.
Повний текст джерелаMouline, Ludovic. "Towards a modelling framework with temporal and uncertain data for adaptive systems." Thesis, Rennes 1, 2019. https://ged.univ-rennes1.fr/nuxeo/site/esupversions/32c7a604-bdf6-491e-ba8f-1a9f2a1c0b8b.
Повний текст джерелаSelf-Adaptive Systems (SAS) optimise their behaviours or configurations at runtime in response to a modification of their environments or their behaviours. These systems therefore need a deep understanding of the ongoing situation which enables reasoning tasks for adaptation operations. Using the model-driven engineering (MDE) methodology, one can abstract this situation. However, information concerning the system is not always known with absolute confidence. Moreover, in such systems, the monitoring frequency may differ from the delay for reconfiguration actions to have measurable effects. These characteristics come with a global challenge for software engineers: how to represent uncertain knowledge that can be efficiently queried and to represent ongoing actions in order to improve adaptation processes? To tackle this challenge, this thesis defends the need for a unified modelling framework which includes, besides all traditional elements, temporal and uncertainty as first-class concepts. Therefore, a developer will be able to abstract information related to the adaptation process, the environment as well as the system itself. Towards this vision, we present two evaluated contributions: a temporal context model and a language for uncertain data. The temporal context model allows abstracting past, ongoing and future actions with their impacts and context. The language, named Ain’tea, integrates data uncertainty as a first-class citizen
Förster, Stefan. "A formal framework for modelling component extension and layers in distributed embedded systems /." Dresden : TUDpress, 2007. http://www.loc.gov/catdir/toc/fy0803/2007462554.html.
Повний текст джерелаDuong, Thi V. T. "Efficient duration modelling in the hierarchical hidden semi-Markov models and their applications." Thesis, Curtin University, 2008. http://hdl.handle.net/20.500.11937/1408.
Повний текст джерелаDuong, Thi V. T. "Efficient duration modelling in the hierarchical hidden semi-Markov models and their applications." Curtin University of Technology, Dept. of Computing, 2008. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=18610.
Повний текст джерелаMost importantly, it has four superior features over existing semi-Markov modelling: the parameter space is compact, computation is fast (almost the same as the HMM), close-formed estimation can be derived, and the Coxian is flexible enough to approximate a large class of distributions. Next, we exploit hierarchical decomposition in the data by borrowing analogy from the hierarchical hidden Markov model in [Fine et al., 1998, Bui et al., 2004] and introduce a new type of shallow structured graphical model that combines both duration and hierarchical modelling into a unified framework, termed the Coxian Switching Hidden Semi-Markov Models (CxSHSMM). The top layer is a Markov sequence of switching variables, while the bottom layer is a sequence of concatenated CxHSMMs whose parameters are determined by the switching variable at the top. Again, we provide a thorough analysis along with inference and learning machinery. We also show that semi-Markov models with arbitrary depth structure can easily be developed. In all cases we further address two practical issues: missing observations to unstable tracking and the use of partially labelled data to improve training accuracy. Motivated by real-world problems, our application contribution is a framework to recognize complex activities of daily livings (ADLs) and detect anomalies to provide better intelligent caring services for the elderly.
Coarser activities with self duration distributions are represented using the CxHSMM. Complex activities are made of a sequence of coarser activities and represented at the top level in the CxSHSMM. Intensive experiments are conducted to evaluate our solutions against existing methods. In many cases, the superiority of the joint modeling and the Coxian parameterization over traditional methods is confirmed. The robustness of our proposed models is further demonstrated in a series of more challenging experiments, in which the tracking is often lost and activities considerably overlap. Our final contribution is an application of the switching Coxian model to segment education-oriented videos into coherent topical units. Our results again demonstrate such segmentation processes can benefit greatly from the joint modeling of duration and hierarchy.
Книги з теми "Data modelling frameworks"
Vanrolleghem, Peter A. Modelling aspects of water framework directive implementation. London: IWA Pub., 2010.
Знайти повний текст джерелаStefan, Förster. A formal framework for modelling component extension and layers in distributed embedded systems. Dresden: TUDpress, 2007.
Знайти повний текст джерелаRamackers, Guustaaf Jan. Integrated object modelling: An executable specification framework for business analysis and information system design. Amsterdam: Thesis Publishers, 1994.
Знайти повний текст джерела1968-, Lawry Jonathan, Shanahan James G, and Ralescu Anca L. 1949-, eds. Modelling with words: Learning, fusion, and reasoning within a formal linguistic representation framework. Berlin: Springer, 2003.
Знайти повний текст джерелаVanrolleghem, Peter A. Modelling Aspects of Water Framework Directive Implementation. IWA Publishing, 2010.
Знайти повний текст джерелаBianconi, Ginestra. Multilayer Network Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0010.
Повний текст джерелаAbdullah, Ahmad Fikri Bin. Methodology for Processing Raw LIDAR Data to Support Urban Flood Modelling Framework: UNESCO-IHE PhD Thesis. Taylor & Francis Group, 2012.
Знайти повний текст джерелаAbdullah, Ahmad Fikri Bin. Methodology for Processing Raw LIDAR Data to Support Urban Flood Modelling Framework: UNESCO-IHE PhD Thesis. Taylor & Francis Group, 2020.
Знайти повний текст джерелаAbdullah, Ahmad Fikri Bin. Methodology for Processing Raw LIDAR Data to Support Urban Flood Modelling Framework: UNESCO-IHE PhD Thesis. Taylor & Francis Group, 2020.
Знайти повний текст джерелаAbdullah, Ahmad Fikri Bin. Methodology for Processing Raw LIDAR Data to Support Urban Flood Modelling Framework: UNESCO-IHE PhD Thesis. Taylor & Francis Group, 2020.
Знайти повний текст джерелаЧастини книг з теми "Data modelling frameworks"
Farsi, Maryam, Amin Hosseinian-Far, Alireza Daneshkhah, and Tabassom Sedighi. "Mathematical and Computational Modelling Frameworks for Integrated Sustainability Assessment (ISA)." In Strategic Engineering for Cloud Computing and Big Data Analytics, 3–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52491-7_1.
Повний текст джерелаLéonard, Michel, and Ian Prince. "NelleN: A framework for literate data modelling." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 239–56. Cham: Springer International Publishing, 1992. http://dx.doi.org/10.1007/bfb0035135.
Повний текст джерелаDegiannakis, Stavros, and Christos Floros. "Multiple Model Comparison and Hypothesis Framework Construction." In Modelling and Forecasting High Frequency Financial Data, 110–60. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137396495_4.
Повний текст джерелаChen, Yenming J., and Albert Jing-Fuh Yang. "Crowd Density Estimation from Few Radio-Frequency Tracking Devices: I. A Modelling Framework." In Data Mining and Big Data, 390–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61845-6_39.
Повний текст джерелаZieliński, Bartosz. "Modular Term-Rewriting Framework for Artifact-Centric Business Process Modelling." In Model and Data Engineering, 71–78. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66854-3_6.
Повний текст джерелаDíaz Mercado, Vitali. "Methodological framework." In Spatio-Temporal Characterisation of Drought: Data Analytics, Modelling, Tracking, Impact and Prediction, 23–28. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003279655-3.
Повний текст джерелаQin, Zengchang, and Jonathan Lawry. "Knowledge Discovery in a Framework for Modelling with Words." In Soft Computing for Knowledge Discovery and Data Mining, 241–76. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-69935-6_11.
Повний текст джерелаKiran, Deshpande, and Madhuri Rao. "Modelling Auto-scalable Big Data Enabled Log Analytic Framework." In Computer Networks and Inventive Communication Technologies, 857–70. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3035-5_64.
Повний текст джерелаHari Prasad, D., and M. Punithavalli. "An Integrated Framework for Mixed Data Clustering Using Growing Hierarchical Self-Organizing Map (GHSOM)." In Mathematical Modelling and Scientific Computation, 471–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28926-2_53.
Повний текст джерелаOthman, Muhaini, Siti Aisyah Mohamed, Mohd Hafizul Afifi Abdullah, Munirah Mohd Yusof, and Rozlini Mohamed. "A Framework to Cluster Temporal Data Using Personalised Modelling Approach." In Advances in Intelligent Systems and Computing, 181–90. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72550-5_18.
Повний текст джерелаТези доповідей конференцій з теми "Data modelling frameworks"
Bamba, Inshita, Yashika, Jahanvi Singh, Pronika Chawla, and Kritika Soni. "Big Social Data and Modelling Frameworks." In 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS). IEEE, 2021. http://dx.doi.org/10.1109/icais50930.2021.9395935.
Повний текст джерелаLi, Yaqiong, Xuhui Fan, Ling Chen, Bin Li, Zheng Yu, and Scott A. Sisson. "Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/342.
Повний текст джерелаBerryman, Matthew, Rohan Wickramasuriya, Vu Lam Co, Qun Chen, and Pascal Pascal. "Modelling and Data Frameworks for Understanding Infrastructure Systems through a Systems-of-Systems Lens." In International Symposium for Next Generation Infrastructure. University of Wollongong, SMART Infrastructure Facility, 2014. http://dx.doi.org/10.14453/isngi2013.proc.5.
Повний текст джерелаLener, Alberto. "Foundational Study of Artificial Intelligence Reservoir Simulation by Integrating Digital Core Technology and Logging Data to Optimise Recovery." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211066-ms.
Повний текст джерелаHonfi, Dániel, John Leander, Ivar Björnsson, and Oskar Larsson Ivanov. "A practical approach for supporting decisions in bridge condition assessment and monitoring." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.2136.
Повний текст джерелаBohlmann, Sebastian, Matthias Becker, Helena Szczerbicka, and Volkhard Klinger. "A Data Management Framework Providing Online-Connectivity In Symbiotic Simulation." In 24th European Conference on Modelling and Simulation. ECMS, 2010. http://dx.doi.org/10.7148/2010-0302-0308.
Повний текст джерелаKoffi, Itoro Udofort. "A Deep Learning Approach for the Prediction of Oil Formation Volume Factor." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/208627-stu.
Повний текст джерелаSchallenberg, A., W. Nebel, A. Herrholz, P. A. Hartmann, and F. Oppenheimer. "OSSS+R: A framework for application level modelling and synthesis of reconfigurable systems." In 2009 Design, Automation & Test in Europe Conference & Exhibition (DATE'09). IEEE, 2009. http://dx.doi.org/10.1109/date.2009.5090805.
Повний текст джерела"Enhancement of water storage estimates using GRACE data assimilation with particle filter framework." In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.h5.tangdamrongsub.
Повний текст джерелаRubio-Solis, Adrian, George Panoutsos, and Steve Thornton. "A Data-driven fuzzy modelling framework for the classification of imbalanced data." In 2016 IEEE 8th International Conference on Intelligent Systems (IS). IEEE, 2016. http://dx.doi.org/10.1109/is.2016.7737438.
Повний текст джерелаЗвіти організацій з теми "Data modelling frameworks"
Russell, H. A. J., and S. K. Frey. Canada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.
Повний текст джерелаFaverjon, Céline, Angus Cameron, and Marco De Nardi. Modelling framework to quantify the risk of AMR exposure via food products - example of chicken and lettuce. Food Standards Agency, April 2022. http://dx.doi.org/10.46756/sci.fsa.qum110.
Повний текст джерелаDaudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, December 2021. http://dx.doi.org/10.53328/uxuo4751.
Повний текст джерелаNechaev, V., Володимир Миколайович Соловйов, and A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.
Повний текст джерелаMurad, M. Hassan, Stephanie M. Chang, Celia Fiordalisi, Jennifer S. Lin, Timothy J. Wilt, Amy Tsou, Brian Leas, et al. Improving the Utility of Evidence Synthesis for Decision Makers in the Face of Insufficient Evidence. Agency for Healthcare Research and Quality (AHRQ), April 2021. http://dx.doi.org/10.23970/ahrqepcwhitepaperimproving.
Повний текст джерелаSett, Dominic, Florian Waldschmidt, Alvaro Rojas-Ferreira, Saut Sagala, Teresa Arce Mojica, Preeti Koirala, Patrick Sanady, et al. Climate and disaster risk analytics tool for adaptive social protection. United Nations University - Institute for Environment and Human Security, March 2022. http://dx.doi.org/10.53324/wnsg2302.
Повний текст джерелаVerburg, Peter H., Žiga Malek, Sean P. Goodwin, and Cecilia Zagaria. The Integrated Economic-Environmental Modeling (IEEM) Platform: IEEM Platform Technical Guides: User Guide for the IEEM-enhanced Land Use Land Cover Change Model Dyna-CLUE. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003625.
Повний текст джерелаDownes, Jane, ed. Chalcolithic and Bronze Age Scotland: ScARF Panel Report. Society for Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.184.
Повний текст джерелаRankin, Nicole, Deborah McGregor, Candice Donnelly, Bethany Van Dort, Richard De Abreu Lourenco, Anne Cust, and Emily Stone. Lung cancer screening using low-dose computed tomography for high risk populations: Investigating effectiveness and screening program implementation considerations: An Evidence Check rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for the Cancer Institute NSW. The Sax Institute, October 2019. http://dx.doi.org/10.57022/clzt5093.
Повний текст джерелаCOLD FORMED STEEL SHEAR WALL RACKING ANALYSIS THROUGH A MECHANISTIC APPROACH: CFS-RAMA. The Hong Kong Institute of Steel Construction, September 2022. http://dx.doi.org/10.18057/ijasc.2022.18.3.2.
Повний текст джерела