Relevant bibliographies by topics / Multi-model model

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Multi-model model'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Multi-model model"

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Li, Jiyun, Chenxi Jia, and Chen Qian. "Progressive Breast Cancer Diagnosis Model Based on Multi-classifier and Multi-modal Fusion." International Journal of Machine Learning and Computing 11, no. 6 (November 2021): 387–92. http://dx.doi.org/10.18178/ijmlc.2021.11.6.1066.

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Lee, Jae Moon, and Thien Nguyen Phu. "Multi-Stream Fused Model: A Novel Real-Time Botnet Detecting Model." Bonfring International Journal of Data Mining 7, no. 2 (March 31, 2017): 06–10. http://dx.doi.org/10.9756/bijdm.8331.

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Kim. "Development of Multisite Spatio-Temporal Downscaling Model for Rainfall Using GCM Multi Model Ensemble." Journal of the Korean Society of Civil Engineers 35, no. 2 (2015): 327. http://dx.doi.org/10.12652/ksce.2015.35.2.0327.

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Alashhab, Mohamed Sayed, and Ehab A. Mlybari. "Developing a multi-item, multi-product, and multi-period supply chain planning optimization model." Indian Journal of Science and Technology 14, no. 37 (October 5, 2021): 2850–59. http://dx.doi.org/10.17485/ijst/v14i37.867.

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Prasad, G. Shyam Chandra, and K. Adi Narayana Reddy. "Sentiment Analysis Using Multi-Channel CNN-LSTM Model." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (December 31, 2019): 489–94. http://dx.doi.org/10.5373/jardcs/v11sp12/20193243.

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Vala, Mr Manish, Kajal Patel, and Harsh Lad. "Multi Model Biometrics Data Retrieval Through: Big-Data." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (October 31, 2018): 1273–77. http://dx.doi.org/10.31142/ijtsrd15933.

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Stünkel, Patrick, Harald König, Adrian Rutle, and Yngve Lamo. "Multi-Model Evolution through Model Repair." Journal of Object Technology 20, no. 1 (2021): 1:1. http://dx.doi.org/10.5381/jot.2021.20.1.a2.

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Duvall, Marshall, James B. Riggs, and Peter Lee. "Multi-model decoupled Generic Model Control." Control Engineering Practice 9, no. 5 (May 2001): 471–81. http://dx.doi.org/10.1016/s0967-0661(01)00007-7.

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Stoica, Petre, Yngve Selén, and Jian Li. "Multi-model approach to model selection." Digital Signal Processing 14, no. 5 (September 2004): 399–412. http://dx.doi.org/10.1016/j.dsp.2004.03.002.

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Lu, Jiaheng, and Irena Holubová. "Multi-model Databases." ACM Computing Surveys 52, no. 3 (July 27, 2019): 1–38. http://dx.doi.org/10.1145/3323214.

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Dissertations / Theses on the topic "Multi-model model"

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Anastasopoulos, Achilles. "Cross model access in the multi-lingual, multi-model database management system." Thesis, Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/8178.

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Relational, hierarchical, network, functional, and object oriented databases support its corresponding query language, SQL, DL/I, CODASYL-DML, DAPLEX, and OO-DML, respectively. However, each database type may be accessed only by its own language. The goal of M2DBMS is to provide a heterogeneous environment in which any supported database is accessible by any supported query language. This is known as cross model access capability. In this thesis, relational to object oriented database cross model access is successfully implemented for a test database. Data from the object oriented database EWIROODB is accessed and retrieved, using an SQL query from the relational database EWIROODB. One problem is that the two interfaces (object oriented and relational) create catalog files with different formation, which makes the cross model access impossible, initially. In this thesis the relational created catalog file is used, and the cross model access capability is achieved. The object oriented catalog file must be identical with the relational one. Therefore, work yet to be done is to write a program that automatically reformats the object oriented catalog file into an equivalent relational catalog file
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Blackburn, Ian Russell. "A conceptual multi-model HCI model for the blind." Thesis, Curtin University, 2011. http://hdl.handle.net/20.500.11937/575.

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The ability for blind people to read and write Braille aids literacy development. A good level of literacy enables a person to function well in society in terms of employment, education and daily living. The learning of Braille has traditionally been done with hard copy Braille produced by manual and more recently electronic Braille writers and printers. Curtin University is developing an electronic Braille writer and the research on an interface for Braille keyboard devices, presented in this thesis, forms part of the Curtin University Brailler project.The Design Science approach was the research method chosen for this research because of the flexibility of the approach and because it focuses upon the building of artefacts and theory development. The small sample size meant that both individual interviews and a focus group were employed to gather relevant data from respondents. The literature review covers a variety of areas related to computer interfaces and Braille keyboard devices. A key finding is that the interaction paradigm for Braille keyboard devices needs to differ to interfaces for sighted individuals because of the audio, tactile and serial nature of the information gathering strategies employed by blind people as compared with the visual and spatial information gathering strategies employed by sighted individuals. In terms of usability attributes designed to evaluate the interface consistency was found to be a key factor because of its importance to learning and memory retention.However, two main functions carried out on a computer system are navigating and editing. Thus the model of interface for Braille keyboard devices presented in this thesis focuses upon navigation support and editing support.Feedback was sort from by interviews with individuals and a focus group. Individual interviews were conducted face to face and via the telephone and the focus group was conducted via Skype conference call to enable participants from all over the world to provide feedback on the model.The model was evaluated using usability attributes. Usability was important to the respondents, in particular consistency, learnability, simplicity and ease of use were important. The concept of rich navigation and infinitely definable key maps were understood by respondents and supported. Braille output is essential including the ability to show formatting information in Braille.The limitations of the research included the few respondents to the interviews and the choice to focus upon a theoretical model rather than implementing the model on an actual device. Future research opportunities include implementing the interface concepts from the model on to touch screen devices to aid further development of the interface and implementing the interface on a physical device such as the Curtin University Brailler.
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Francisco-Revilla, Luis. "Multi-model adaptive spatial hypertext." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1444.

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Information delivery on the Web often relies on general purpose Web pages that require the reader to adapt to them. This limitation is addressed by approaches such as spatial hypermedia and adaptive hypermedia. Spatial hypermedia augments the representation power of hypermedia and adaptive hypermedia explores the automatic modification of the presentation according to user needs. This dissertation merges these two approaches, combining the augmented expressiveness of spatial hypermedia with the flexibility of adaptive hypermedia. This dissertation presents the Multi-model Adaptive Spatial Hypermedia framework (MASH). This framework provides the theoretical grounding for the augmentation of spatial hypermedia with dynamic and adaptive functionality and, based on their functionality, classifies systems as generative, interactive, dynamic or adaptive spatial hypermedia. Regarding adaptive hypermedia, MASH proposes the use of multiple independent models that guide the adaptation of the presentation in response to multiple relevant factors. The framework is composed of four parts: a general system architecture, a definition of the fundamental concepts in spatial hypermedia, an ontological classification of the adaptation strategies, and the philosophy of conflict management that addresses the issue of multiple independent models providing contradicting adaptation suggestions. From a practical perspective, this dissertation produced WARP, the first MASH-based system. WARP’s novel features include spatial transclusion links as an alternative to navigational linking, behaviors supporting dynamic spatial hypermedia, and personal annotations to spatial hypermedia. WARP validates the feasibility of the multi-model adaptive spatial hypermedia and allows the exploration of other approaches such as Web-based spatial hypermedia, distributed spatial hypermedia, and interoperability issues between spatial hypermedia systems. In order to validate the approach, a user study comparing non-adaptive to adaptive spatial hypertext was conducted. The study included novice and advanced users and produced qualitative and quantitative results. Qualitative results revealed the emergence of reading behaviors intrinsic to spatial hypermedia. Users moved and modified the objects in order to compare and group objects and to keep track of what had been read. Quantitative results confirmed the benefits of adaptation and indicated a possible synergy between adaptation and expertise. In addition, the study created the largest spatial hypertext to date in terms of textual content.
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Raimondi, Franco. "Model checking multi-agent systems." Thesis, University College London (University of London), 2006. http://discovery.ucl.ac.uk/5627/.

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A multi-agent system (MAS) is usually understood as a system composed of interacting autonomous agents. In this sense, MAS have been employed successfully as a modelling paradigm in a number of scenarios, especially in Computer Science. However, the process of modelling complex and heterogeneous systems is intrinsically prone to errors: for this reason, computer scientists are typically concerned with the issue of verifying that a system actually behaves as it is supposed to, especially when a system is complex. Techniques have been developed to perform this task: testing is the most common technique, but in many circumstances a formal proof of correctness is needed. Techniques for formal verification include theorem proving and model checking. Model checking techniques, in particular, have been successfully employed in the formal verification of distributed systems, including hardware components, communication protocols, security protocols. In contrast to traditional distributed systems, formal verification techniques for MAS are still in their infancy, due to the more complex nature of agents, their autonomy, and the richer language used in the specification of properties. This thesis aims at making a contribution in the formal verification of properties of MAS via model checking. In particular, the following points are addressed: • Theoretical results about model checking methodologies for MAS, obtained by extending traditional methodologies based on Ordered Binary Decision Diagrams (OBDDS) for temporal logics to multi-modal logics for time, knowledge, correct behaviour, and strategies of agents. Complexity results for model checking these logics (and their symbolic representations). • Development of a software tool (MCMAS) that permits the specification and verification of MAS described in the formalism of interpreted systems. • Examples of application of MCMAS to various MAS scenarios (communication, anonymity, games, hardware diagnosability), including experimental results, and comparison with other tools available.
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Kwon, Ky-Sang. "Multi-layer syntactical model transformation for model based systems engineering." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42835.

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This dissertation develops a new model transformation approach that supports engineering model integration, which is essential to support contemporary interdisciplinary system design processes. We extend traditional model transformation, which has been primarily used for software engineering, to enable model-based systems engineering (MBSE) so that the model transformation can handle more general engineering models. We identify two issues that arise when applying the traditional model transformation to general engineering modeling domains. The first is instance data integration: the traditional model transformation theory does not deal with instance data, which is essential for executing engineering models in engineering tools. The second is syntactical inconsistency: various engineering tools represent engineering models in a proprietary syntax. However, the traditional model transformation cannot handle this syntactic diversity. In order to address these two issues, we propose a new multi-layer syntactical model transformation approach. For the instance integration issue, this approach generates model transformation rules for instance data from the result of a model transformation that is developed for user model integration, which is the normal purpose of traditional model transformation. For the syntactical inconsistency issue, we introduce the concept of the complete meta-model for defining how to represent a model syntactically as well as semantically. Our approach addresses the syntactical inconsistency issue by generating necessary complete meta-models using a special type of model transformation.
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Strack, Beata. "Multi-column multi-layer computational model of neocortex." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3279.

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We present a multi-layer multi-column computational model of neocortex that is built based on the activity and connections of known neuronal cell types and includes activity-dependent short term plasticity. This model, a network of spiking neurons, is validated by showing that it exhibits activity close to biology in terms of several characteristics: (1) proper laminar flow of activity; (2) columnar organization with focality of inputs; (3) low-threshold-spiking (LTS) and fast-spiking (FS) neurons function as observed in normal cortical circuits; and (4) different stages of epileptiform activity can be obtained with either increasing the level of inhibitory blockade, or simulation of NMDA receptor enhancement. The aim of this research is to provide insight into the fundamental properties of vertical and horizontal inhibition in neocortex and their influence on epileptiform activity. The developed model was used to test novel ideas about modulation of inhibitory neuronal types in a developmentally malformed cortex. The novelty of the proposed research includes: (1) design and implementation of a multi-layer multi-column model of the cortex with multiple neuronal types and short-time plasticity, (2) modification of the Izhikevich neuron model in order to model biological maximum firing rate property, (3) generating local field potential (LFP) and EEG signals without modeling multiple neuronal compartments, (4) modeling several known conditions to validate that the cortex model matches the biology in several aspects,(5) modeling different abnormalities in malformed cortex to test existing and to generate novel hypotheses.
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Titman, Andrew Charles. "Model diagnostics in multi-state models of biological systems." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612189.

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Kelly, R. J. "Mathematical model of multi-phase snowmelt." Thesis, University of East Anglia, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377740.

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Schagerström, Lukas. "Valideringsstudie av Multi-Zone Fire Model." Thesis, Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-78682.

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Det finns ett flertal brandsimuleringsprogram på marknaden som används i olika utsträckning varav ett är Fire Dynamics Simulator (FDS). En av nackdelarna med FDS är att det kan ta mycket tid att göra en brandsimulering. Det finns brandsimuleringsprogram som med stor sannolikhet utför brandsimuleringar snabbare än FDS. För några av dessa brandsimuleringsprogram finns det inte någon dokumentation om hur resultaten som brandsimuleringsprogrammen producerar ställer sig mot det som skulle hända i verkligheten vid en brand, något som kallas att vara valideratdet vill säga programmen är inte validerade. Ett av dessa brandsimuleringsprogram är Multi-Zone Fire Model (MZ-Fire Model). Brandsimuleringsprogrammet MZ-Fire Model bygger på ett multizonkoncept framtaget av Suzuki et al. Multizonkonceptet har validerats i tidigare studier varav ett är en brand i tunnel men även bränder i mindre lokaler har prövats. Det finns utrymme för ökad kunskap om hur multizonkonceptet hanterar bränder i stora rumslokaler då det inte finns någon känd dokumentation kring detta. Det finns i dagsläget inte en enda studie som behandlar brandsimuleringsprogrammet MZ-Fire Model. I rapporten redogörs för simulerande av en brand i 4 olika rum av brandsimuleringsprogrammen MZ-Fire Model och FDS, dess simulerade värden är sedan jämförda mot varandra.
There are a number of fire simulation programs on the market that are used to varying degrees, one of which is Fire Dynamics Simulator (FDS). One of the disadvantages of FDS is that it can take a lot of time to do a fire simulation. There are fire simulation programs that are very likely to perform fire simulations faster than FDS. For some of these fire simulation programs, there is no documentation on how the results produced by the programs compare with what would happen in the event of a real fire, something called to bethat is they are not validated. One of these fire simulation programs is Multi-Zone Fire Model (MZ-Fire Model). The fire simulation program MZ-Fire Model is based on a multi-zone concept developed by Suzuki et al. The multi-zone concept has been validated in previous studies, one of which is a fire in a tunnel but fires in smaller premises have also been tested. There is room for increased knowledge about how the multi-zone concept handles fires in large rooms, as there is no known documentation on this. Currently, there is not a single study dealing with the MZ-Fire Model program. The report describes the simulation of a fire in 4 different rooms by the programs MZ-Fire Model and FDS, its simulated values ​​are then compared against each other.
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Breschi, Valentina. "Model learning from data: from centralized multi-model regression to distributed cloud-aided single-model estimation." Thesis, IMT Alti Studi Lucca, 2018. http://e-theses.imtlucca.it/256/1/Breschi_phdthesis.pdf.

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This thesis presents a collection of methods for learning models from data, looking at this problem from two perspectives: learning multiple models from a single data source and how to switch among them, and learning a single model from data collected from multiple sources. Regarding the first, to describe complex phenomena with simple but yet complete models, we propose a computationally efficient method for Piecewise Affine (PWA) regression. This approach relies on the combined use (i) multi-model Recursive Least-Squares (RLS) and (ii) piecewise linear multi- category discrimination, and shows good performances when used for the identification of Piecewise Affine dynamical systems with eXogenous inputs (PWARX) and Linear Parameter Varying (LPV) models. The technique for PWA regression is then extended to handle the problem of black-box identification of Discrete Hybrid Automata (DHA) from input/output observations, with hidden operating modes. The method for DHA identification is based on multi-model RLS and multicategory discrimination and it can approximate both the continuous affine dynamics and the Finite State Machine (FSM) governing the logical dynamics of the DHA. Two more approaches are presented to tackle the problem of learning models that jump over time. While the technique designed to learn Rarely Jump Models (RJMs) from data relies on the combined solution of a convex optimization problem and the use of Dynamic Programming, the method proposed for Markov Jump Models (MJMs) learning is based on the joint use of clustering plus multi-model RLS and a probabilistic clustering technique. The results of the tests performed on the method for RJMs learning have motivated the design of two techniques for Non-Intrusive Load Monitoring, i.e., to estimate the power consumed by the appliances in an household from aggregated measurements, which are also presented in the thesis. In particular, methods based on (i) the optimization of a least-square error cost function, modified to account for the changes in the appliances operating regime, and relying on (ii) multi-model Kalman filters are proposed. Regarding the second perspective, we propose methods for cloud-aided consensus-based parameter estimation over a multitude of similar devices (such as a mass production). In particular, we focus on the design of RLS-based estimators, which allow to handle (i) linear and (ii) nonlinear consensus constraints and (iii) multi-class estimation.
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Books on the topic "Multi-model model"

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Anastasopoulos, Achilles. Cross model access in the multi-lingual, multi-model database management system. Monterey, Calif: Naval Postgraduate School, 1997.

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Pistikopoulos, Efstratios N., Michael C. Georgiadis, and Vivek Dua, eds. Multi-Parametric Model-Based Control. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2007. http://dx.doi.org/10.1002/9783527631230.

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Lindgren, Peter. The Multi Business Model Innovation Approach. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339755.

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Fund, International Monetary. MULTIMOD: A multi-region econometric model. Washington, D.C: International Monetary Fund, 1988.

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Introduction to multi-disciplinary model-building. Southampton, UK: WIT Press, 2003.

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Powers, M. W. Multi-modal modelling with multi-module mechanics: Autonomy in acomputational model of language learning. Tilburg: Tilburg University, 1992.

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Stam, Jos. A multi-scale stochastic model for computer graphics. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1991.

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Pusat Informatik Untuk Pengelolaan Pendidikan dan Kebudayaan (Indonesia), ed. Model tayangan multi media Departemen Pendidikan dan Kebudayaan. [Jakarta]: Pusat Informatik Untuk Pengelolaan Pendidikan dan Kebudayaan, Badan Penelitian dan Pengembangan Pendidikan dan Kebudayaan, Departemen Pendidikan dan Kebudayaan, 1998.

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(Japan), Ajia Keizai Kenkyūjo. Multi-regional input-output model for China 2000. Chiba-shi, Japan: Institute of Developing Economies, Japan External Trade Organization, 2003.

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C, Georgiadis Michael, Pistikopoulos Efstratios N, and Dua Vivek, eds. Multi-parametric model-based control: Theory and applications. Weinheim: Wiley-VCH, 2007.

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Book chapters on the topic "Multi-model model"

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Döll, Carsten, Jean-François Magni, and Yann Le Gorrec. "A model multi-model approach." In Robust Flight Control, 258–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0113863.

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Mauri, Davide, Silvano Coriani, Anna Hoffman, Sanjay Mishra, and Jovan Popovic. "Multi-model Capabilities." In Practical Azure SQL Database for Modern Developers, 193–233. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6370-9_8.

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Ye, Andre, and Andy Wang. "Multi-model Arrangement." In Modern Deep Learning for Tabular Data, 753–70. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8692-0_11.

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Čontoš, Pavel. "Abstract Model for Multi-model Data." In Database Systems for Advanced Applications, 647–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73200-4_53.

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Bloisi, Domenico D., Alfonso Grillo, Andrea Pennisi, Luca Iocchi, and Claudio Passaretti. "Multi-modal Background Model Initialization." In New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops, 485–92. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23222-5_59.

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Kouramas, Konstantinos, and Vivek Dua. "Hybrid Parametric Model-Based Control." In Multi-Parametric Model-Based Control, 25–48. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527631230.ch2.

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Kouramas, Konstantinos I., Vassilis Sakizlis, and Efstratios N. Pistikopoulos. "Robust Parametric Model-Based Control." In Multi-Parametric Model-Based Control, 49–76. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527631230.ch3.

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Mohs, William F., and Francis A. Kulacki. "Multi-stage Defrost Model." In Heat and Mass Transfer in the Melting of Frost, 21–41. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20508-3_3.

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Labanda, J., J. Llorens, and C. Mans. "Multi-Structural Thixotropic Model." In Progress and Trends in Rheology V, 611–12. Heidelberg: Steinkopff, 1998. http://dx.doi.org/10.1007/978-3-642-51062-5_299.

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Finlay, Steven. "Multi-model (Fusion) Systems." In Credit Scoring, Response Modeling, and Insurance Rating, 264–72. London: Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1057/9781137031693_11.

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Conference papers on the topic "Multi-model model"

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Klare, Heiko. "Multi-model consistency preservation." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3270112.3275335.

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Koupil, Pavel, Sebastián Hricko, and Irena Holubová. "Schema inference for multi-model data." In MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3550355.3552400.

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Westfechtel, Bernhard, and Sandra Greiner. "From Single- to Multi-Variant Model Transformations." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3239372.3239414.

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Riggs, J. B., and P. L. Lee. "Multi-model decoupled generic model control." In Proceedings of 16th American CONTROL Conference. IEEE, 1997. http://dx.doi.org/10.1109/acc.1997.609229.

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Prehofer, Christian, Andreas Wagner, and Yucheng Jin. "A model-based approach for multi-device user interactions." In MODELS '16: ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2976767.2976776.

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Diaconescu, Ada, Etienne Houze, Jean-Louis Dessalles, Hans Vangheluwe, and Romain Franceschini. "Multi-scale model-based explanations for cyber-physical systems." In MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3550356.3561554.

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Harbin, James, Simos Gerasimou, Nicholas Matragkas, Athanasios Zolotas, and Radu Calinescu. "Model-Driven Simulation-Based Analysis for Multi-Robot Systems." In 2021 ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2021. http://dx.doi.org/10.1109/models50736.2021.00040.

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Konig, Harald, and Uwe Wolter. "A General Methodology for Internalising Multi-Level Model Typing." In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2021. http://dx.doi.org/10.1109/models-c53483.2021.00080.

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Lu, Qin, Malgorzata Peszynska, and Mary F. Wheeler. "A Parallel Multi-Block Black-Oil Model in Multi-Model Implementation." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 2001. http://dx.doi.org/10.2118/66359-ms.

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SchultheiB, Alexander, Paul Maximilian Bittner, Lars Grunske, Thomas Thum, and Timo Kehrer. "Scalable N-Way Model Matching Using Multi-Dimensional Search Trees." In 2021 ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2021. http://dx.doi.org/10.1109/models50736.2021.00010.

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Reports on the topic "Multi-model model"

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Mallon, Lawrence G. Multi-Modal Terminal Model Documentation. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada460376.

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Hubbard, Joshua Allen, Joshua Santarpia, Christopher M. Brotherton, Michael Alexis Omana, Danielle Rivera, and Gabriel Anthony Lucero. Multi-compartment Aerosol Transport Model. Office of Scientific and Technical Information (OSTI), June 2017. http://dx.doi.org/10.2172/1364755.

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Barhak, Jacob. Supplemental Information: The Reference Model is a Multi-Scale Ensemble Model of COVID-19. Outbreak, May 2021. http://dx.doi.org/10.34235/b7eaa32b-1a6b-444f-9848-76f83f5a733c.

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Abstract:
The COVID-19 pandemic has accelerated research worldwide and resulted in a large number of computational models and initiatives. Models were mostly aimed at forecast and resulted in different predictions partially since models were based on different assumptions. In fact the idea that a computational model is just an assumption attempting to explain a phenomenon has not been sufficiently explored. Moreover, the ability to combine models has not been fully realized. The Reference Model for disease progression was performing this task for years for diabetes models and recently started modeling COVID-19. The Reference Model is an ensemble of models that is optimized to fit observed disease phenomenon. The ensemble has the ability to include model components from different sources that compete and cooperate. The recent advance in this model is the ability to include models calculated in different scales, making the model the first known multi-scale ensemble model. This manuscript will review these capabilities and show how multiple models can improve our ability to comprehend the COVID-19 pandemic.
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Villa, Daniel, Charles Morrow, Johan Vanneste, Emily Gustafson, NREL Sertac Akar, Craig Turchi, and Tzahi Cath. Multi-configuration Membrane Distillation Model (MCMD). Office of Scientific and Technical Information (OSTI), October 2018. http://dx.doi.org/10.2172/1489619.

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Koo, Heeseok, Alexander Brown, Tyler Voskuilen, and Flint Pierce. Rubble Fire Multi-Phase Model Development. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1599979.

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Hamann, Hendrik F. A Multi-scale, Multi-Model, Machine-Learning Solar Forecasting Technology. Office of Scientific and Technical Information (OSTI), May 2017. http://dx.doi.org/10.2172/1395344.

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Hansen, James A. Interpreting, Improving, and Augmenting Multi-Model Ensembles. Fort Belvoir, VA: Defense Technical Information Center, February 2006. http://dx.doi.org/10.21236/ada444387.

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Ray, Jaideep, Katherine Regina Cauthen, Sophia Lefantzi, and Lynne Burks. Conditioning multi-model ensembles for disease forecasting. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1492995.

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Kenamond, Mark A. (U) Multi-Scale Friction Model in FLAG. Office of Scientific and Technical Information (OSTI), June 2014. http://dx.doi.org/10.2172/1133757.

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Hansen, James A. Interpreting, Improving, and Augmenting Multi-Model Ensembles. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada629175.

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