Relevant bibliographies by topics / Model synthesis

Contents

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

Academic literature on the topic 'Model synthesis'

Author: Grafiati
Published: 30 November 2024

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Journal articles on the topic "Model synthesis"

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KAMBUSHEV, Martin, Stefan BILIDEROV, and Yavor VARBANOV. "SYNTHESIS AND STUDY OF THE MATHEMATICAL MODEL OF A TRICOPTER." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (June 24, 2016): 149–58. http://dx.doi.org/10.19062/2247-3173.2016.18.1.19.

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Avramenko, A. S., and S. V. Golub. "Decrease of time of model synthesis in intellectual monitoring systems." Mathematical machines and systems 3 (2019): 129–34. http://dx.doi.org/10.34121/1028-9763-2019-3-129-134.

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Merrell, Paul, and Dinesh Manocha. "Continuous model synthesis." ACM Transactions on Graphics 27, no. 5 (December 2008): 1–7. http://dx.doi.org/10.1145/1409060.1409111.

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Hill, D., K. R. W. Bell, D. McMillan, and D. Infield. "A vector auto-regressive model for onshore and offshore wind synthesis incorporating meteorological model information." Advances in Science and Research 11, no. 1 (May 14, 2014): 35–39. http://dx.doi.org/10.5194/asr-11-35-2014.

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Abstract. The growth of wind power production in the electricity portfolio is striving to meet ambitious targets set, for example by the EU, to reduce greenhouse gas emissions by 20% by 2020. Huge investments are now being made in new offshore wind farms around UK coastal waters that will have a major impact on the GB electrical supply. Representations of the UK wind field in syntheses which capture the inherent structure and correlations between different locations including offshore sites are required. Here, Vector Auto-Regressive (VAR) models are presented and extended in a novel way to incorporate offshore time series from a pan-European meteorological model called COSMO, with onshore wind speeds from the MIDAS dataset provided by the British Atmospheric Data Centre. Forecasting ability onshore is shown to be improved with the inclusion of the offshore sites with improvements of up to 25% in RMS error at 6 h ahead. In addition, the VAR model is used to synthesise time series of wind at each offshore site, which are then used to estimate wind farm capacity factors at the sites in question. These are then compared with estimates of capacity factors derived from the work of Hawkins et al. (2011). A good degree of agreement is established indicating that this synthesis tool should be useful in power system impact studies.
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Vu-An, Hien, and Tatyana Yagodkina. "Synthesis of invariant systems of modal model identification." Актуальные направления научных исследований XXI века: теория и практика 3, no. 7 (December 10, 2015): 232–35. http://dx.doi.org/10.12737/14846.

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Brdjanin, Drazen, Danijela Banjac, Goran Banjac, and Slavko Maric. "Automated two-phase business model-driven synthesis of conceptual database models." Computer Science and Information Systems 16, no. 2 (2019): 657–88. http://dx.doi.org/10.2298/csis181010014b.

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Existing approaches to business process model-driven synthesis of data models are characterized by a direct synthesis of a target model based on source models represented by concrete notations, where the synthesis is supported by monolithic (semi)automatic transformation programs. This article presents an approach to automated two-phase business process model-driven synthesis of conceptual database models. It is based on the introduction of a domain specific language (DSL) as an intermediate layer between different source notations and the target notation, which splits the synthesis into two phases: (i) automatic extraction of specific concepts from the source model and their DSL-based representation, and (ii) automated generation of the target model based on the DSL-based representation of the extracted concepts. The proposed approach enables development of modular transformation tools for automatic synthesis of the target model based on business process models represented by different concrete notations. In this article we present an online generator, which implements the proposed approach. The generator is implemented as a web-based, service-oriented tool, which enables automatic generation of the initial conceptual database model represented by the UML class diagram, based on business models represented by two concrete notations.
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Wong, K. P., W. Derek Humpage, T. T. Nguyen, and K. K. K. Ho. "Dynamic load model synthesis." IEE Proceedings C Generation, Transmission and Distribution 132, no. 4 (1985): 179. http://dx.doi.org/10.1049/ip-c.1985.0032.

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Abbott, B., T. Bapty, C. Biegl, G. Karsai, and J. Sztipanovits. "Model-based software synthesis." IEEE Software 10, no. 3 (May 1993): 42–52. http://dx.doi.org/10.1109/52.210602.

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SULÍR, Martin, and Jozef JUHÁR. "HIDDEN MARKOV MODEL BASED SPEECH SYNTHESIS SYSTEM IN SLOVAK LANGUAGE WITH SPEAKER INTERPOLATION." Acta Electrotechnica et Informatica 15, no. 4 (December 1, 2015): 8–12. http://dx.doi.org/10.15546/aeei-2015-0029.

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Cid Fernandes, Roberto, and Rosa M. González Delgado. "Testing evolutionary synthesis models: Empirical feedback to model makers." Proceedings of the International Astronomical Union 5, S262 (August 2009): 69–72. http://dx.doi.org/10.1017/s1743921310002541.

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AbstractIntegrated spectra of star clusters are the best test beds for predictions of evolutionary synthesis models. We present spectral fits of star cluster using a variety of recent models. All models allow good spectral fits, but newer ones tend to be better. Ages estimated through spectral fits are not strongly model dependent, but metallicities can differ a lot from one model to another. For some clusters, multi-population fits suggest a combination of very old (1010 yr) and very young (< 108) populations, an artifact of the lack of old and blue stars in the models.
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Dissertations / Theses on the topic "Model synthesis"

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Andriushchenko, Roman. "Computer-Aided Synthesis of Probabilistic Models." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417269.

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Předkládaná práce se zabývá problémem automatizované syntézy pravděpodobnostních systémů: máme-li rodinu Markovských řetězců, jak lze efektivně identifikovat ten který odpovídá zadané specifikaci? Takové rodiny často vznikají v nejrůznějších oblastech inženýrství při modelování systémů s neurčitostí a rozhodování i těch nejjednodušších syntézních otázek představuje NP-těžký problém. V dané práci my zkoumáme existující techniky založené na protipříklady řízené induktivní syntéze (counterexample-guided inductive synthesis, CEGIS) a na zjemňování abstrakce (counterexample-guided abstraction refinement, CEGAR) a navrhujeme novou integrovanou metodu pro pravděpodobnostní syntézu. Experimenty nad relevantními modely demonstrují, že navržená technika je nejenom srovnatelná s moderními metodami, ale ve většině případů dokáže výrazně překonat, někdy i o několik řádů, existující přístupy.
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Merrell, Paul C. Manocha Dinesh N. "Model synthesis." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2009. http://dc.lib.unc.edu/u?/etd,2752.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2009.
Title from electronic title page (viewed Mar. 10, 2010). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science." Discipline: Computer Science; Department/School: Computer Science.
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Jung, Yong-Kyu. "Model-based processor synthesis." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/14451.

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Sather, Paula Joan. "Synthesis of cholesterol based model glycolipids." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29876.

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The synthesis of glycolipids containing a variable length polyethylene glycol spacer group between a glucuronic acid (glu) headgroup and a cholesterol (chol) tail glu-0CH₂(CH₂OCH₂ )nCH₂O-chol is described. The homologs (n=2,3,5) were prepared by reaction of an excess of commercially available tri, tetra and hexaethylene glycols with cholesteryl-p-toluene sulfonate. 3-O-(8-hydroxy-3,6-dioxaoctyl) cholest-5-ene (2), 3-O-(ll-hydroxy-3,6,9-trioxaundecyl)cholest-5-ene (3) and 3-O-(17-hydroxy-3,6,9,12,15-pentaoxaheptadecyl)cholest-5-ene (4) were produced, and yields were dependent on the amount of excess used. The headgroup was prepared by esterification and acetylation of glucuronolactone to produce methyl (1, 2, 3, 4-tetra-O-acetyl-β-D-glucopyran)uronate which was then brominated at the anomeric carbon to produce methyl (2, 3, 4-tri-O-acetyl-α-D-glucopyranosyl bromide)uronate (1). The headgroup was coupled to the cholesteroxy oligoethylene glycols by a Koenig Knorr type reaction using freshly prepared silver carbonate as the catalyst. Methyl[3-O-(3,6-dioxaoctyl)cholest-5-en-3β-y1-2,3,4-tri-O-acetyl-β-D-glucopyranosid] uronate (5), Methyl[3-O-(3,6,9-trioxaundecyl) cholest-5-en-3β-yl-2,3,4-tri-0-acetyl-β-D-glucopyranosid] uronate (6), and Methyl[3-O-(3,6,9,12,15-pentaoxaheptadecyl)cholest-5-en-3β-yl-2, 3, 4-tri-O -acetyl-β-D-glucopyranosid] uronate (7) were produced with yields of up to 30%. The removal of the methyl ester and acetate protecting groups on the headgroup was accomplished using NaOH in a mixture of solvents followed by acidification with HCl to produce 3-O-(3,6-dioxaoctyl)cholest-5-en-3β-yl-β-D-glucopyranosiduronic acid (8) and 3-O-(3,6,9-trioxaundecyl)cholest-5-en-3β-yl-β-D-glucopyranosiduronic acid (9). Octaethylene glycol and dodecaethylene glycol were prepared using a solid supported synthesis. The solid polymer used was a trityl chloride functionalized polystyrene 1% divinyl benzene. Mono protected tetraethylene glycol was prepared and attached to the polymer. The protecting group was removed, and the hydroxy terminal was converted to a mesylate leaving group by reaction with methane sulfonyl chloride. To elongate the chain, the anion of tetraethylene glycol was prepared using sodium hydride in DMF. The tetraethylene glycol bound resin was added, and reaction continued at 120 °C for 24 hours. Cleavage of the resultant product from the polymer support yielded octaethylene glycol. Repetition of the mesylation and elongation steps followed by cleavage yielded dodecaethylene glycol. The oligoethylene glycols were purified by passage through a Fractogel 40S gel permeation column. Two different protecting groups for the tetraethylene glycol were tried. Trialkyl silyl groups were first attempted, but were abandoned due to reduced reactivity and monitoring difficulties during the deprotection. An acetate protecting group was finally used and deprotection was monitored with infrared spectroscopy.
Science, Faculty of
Chemistry, Department of
Graduate
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Varejao, Jorge Manuel Tavares Branco. "Towards the synthesis of model peroxidases." Thesis, University of Liverpool, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343702.

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Bennett, Fiona Catherine. "Design and synthesis of model peptides." Thesis, King's College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299882.

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Biris, Brilhante Virginia. "Ontology and reuse in model synthesis." Thesis, University of Edinburgh, 2003. http://hdl.handle.net/1842/25164.

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A much pursued ontological capability is knowledge reuse and sharing. One aspect of this is reuse of ontologies across different applications, including construction of other ontologies. Another aspect is the reuse of knowledge that is founded on ontologies, which, in principle, is attainable in that an ontology renders well-defined and accessible the meaning of concepts that underly the knowledge. In this thesis we address both these aspects of reuse, grounding the study in the problem of synthesis of structural ecological models. One basis for the design of ecological models, along with human expertise, is data properties. This motivated the construction of a formal ontology - Ecolingua - where we define concepts of the ecological data domain. The diversity of the domain led us to use the Ontolingua Server as an ontology design tool, since it makes available an extensive library of shareable ontologies. We reused definitions from several of these ontologies to design Ecolingua. However, Ecolingua's specification in the representation language of the Ontolingua Server did not easily translate into a manageable, executable specification in our choice of implementation language, which required us to develop our own complementary tools for scope reduction and translation. Still, a great deal of manual re-specification was necessary to achieve an operational, useful ontology. In sum, reuse of multiple ontologies in ontology construction employing state-of-the-art tools proved impractical. We analyse the practical problems in reuse of heterogeneous ontologies for the purpose of developing large, combined ones. In its operational form, Ecolingua is used to describe ecological data to give what we call metadata, or, said differently, instantiated ontological concepts. Synthesis is achieved by connecting metadata to model structure. Two approaches were developed to do this. The first, realised in the Synthesis-0 system, uses metadata alone as synthesis resource, while the second, realised in the Synthesis-R system, exploits Ecolingua to reuse existing models as an additional synthesis resource. Both Synthesis-0 and Synthesis-R are working systems implemented as logic programs. The systems were empirically evaluated and compared on run time efficiency criteria. Results show a remarkable efficiency gain in SynthesisR, the system with the reuse feature. We generalise the results to systems for synthesis of structural models informed by domain data. Once a data ontology and ontology-constrained synthesis mechanisms are in place, existing models can efficiently be reused to produce new models for new data.
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Addazi, Lorenzo. "Automated Synthesis of Model Comparison Benchmarks." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44333.

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Model-driven engineering promotes the migration from code-centric to model-based software development. Systems consist of model collections integrating different concerns and perspectives, while semi-automated model transformations generate executable code combining the information from these. Increasing the abstraction level to models required appropriate management technologies supporting the various software development activities. Among these, model comparison represents one of the most challenging tasks and plays an essential role in various modelling activities. Its hardness led researchers to propose a multitude of approaches adopting different approximation strategies and exploiting specific knowledge of the involved models. However, almost no support is provided for their evaluation against specific scenarios and modelling practices. This thesis presents Benji, a framework for the automated generation of model comparison benchmarks. Given a set of differences and an initial model, users generate models resulting from the application of the first on the latter. Differences consist of preconditions, actions and postconditions expressed using a dedicated specification language. The generator converts benchmark specifications to design-space exploration problems and produces the final solutions along with a model-based description of their differences with respect to the initial model. A set of representative use cases is used to evaluate the framework against its design principles, which resemble the essential properties expected from model comparison benchmark generators.
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Ligon, Thomas (Thomas Crumrine). "Automated inter-model parameter connection synthesis for simulation model integration." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39887.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.
Includes bibliographical references (p. 73-75).
New simulation modeling environments have been developed such that multiple models can be integrated into a single model. This conglomeration of model data allows designers to better understand the physical phenomenon being modeled. Models are integrated together by creating connections between their interface parameters, referred to as parameter mapping, that are either shared by common models or flow from the output of one model to the input of a second model. However, the process of integrating simulation models together is time consuming, and this development time can outweigh the benefit of the increased understanding. This thesis presents two algorithms that are designed to automatically generate and suggest these parameter mappings. The first algorithm attempts to identify previously built integration model templates that have a similar function. Model interfaces and integration models are represented by attributed graphs. Interface graph nodes represent interface parameters and arcs relate the input and output parameters, and integration models graph nodes represent interface graphs and arc represent parametric connections between interface graph nodes.
(cont.) A similarity based pattern matching algorithm initially compares interface graphs in two integration model graphs. If the interface graphs are found to match, the algorithm attempts to apply the template integration model's parameter mappings to the new integration model. The second algorithm compares model interface parameters directly. The algorithm uses similarity measures developed for the pattern matching algorithm to compare model parameters. Parameter pairs that are found to be very similar are processed using a set of model integration rules and logic and those pairs that fit these criteria are mapped together. These algorithms were both implemented in JAVA and integrated into the modeling environment DOME (Distributed Object-based Modeling Environment). A small set of simulation models were used to build both new and template integration models in DOME. Tests were conducted by recording the time required to build these integration models manually and using the two proposed algorithms. Integration times were generally ten times faster but some inconsistencies and mapping errors did occur. In general the results are very promising, but a wider variety of models should be used to test these two algorithms.
by Thomas Ligon.
S.M.
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Troeng, Tor. "Frequency Response Analysis using Component Mode Synthesis." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-37809.

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Solutions to physical problems described by Differential Equationson complex domains are in except for special cases almost impossibleto find. This turns our interest toward numerical approaches. Sincethe size of the numerical models tends to be very large when handlingcomplex problems, the area of model reduction is always a hot topic. Inthis report we look into a model reduction method called ComponentMode Synthesis. This can be described as dividing a large and complexdomain into smaller and more manageable ones. On each of thesesubdomains, we solve an eigenvalue problem and use the eigenvectorsas a reduced basis. Depending on the required accuracy we mightwant to use many or few modes in each subdomain, this opens for anadaptive selection of which subdomains that affects the solution most.We cover two numerical examples where we solve Helmholtz equationin a linear elastic problem. The first example is a truss and the othera gear wheel. In both examples we use an adaptive algorithm to refinethe reduced basis and compare the results with a uniform refinementand with a classic model reduction method called Modal Analysis. Wealso introduce a new approach when computing the coupling modesonly on the adjacent subdomains.
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Books on the topic "Model synthesis"

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Kirby, Anthony J. From enzyme models to model enzymes. Cambridge: Royal Society of Chemistry, 2009.

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Olderog, Ernst-Rüdiger, Bernhard Steffen, and Wang Yi, eds. Model Checking, Synthesis, and Learning. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91384-7.

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Koča, J., M. Kratochvíl, L. Matyska, V. Kvasnička, and J. Pospíchal. Synthon Model of Organic Chemistry and Synthesis Design. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-93416-2.

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Jaroslav, Koča, ed. Synthon model of organic chemistry and synthesis design. Berlin: Springer-Verlag, 1989.

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Jansson, Marie. Model compounds for prostacyclin: Synthesis and kinetic studies. Göteborg: Dept. of Organic Chemistry, Chalmers Univ. of Technology u.a., 1987.

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Tai, H. Computed structures of polyimides model compounds. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.

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Lidholt, Kerstin. A new model for the biosynthesis of heparin. Uppsala: Swedish University of Agricultural Sciences, Faculty of Veterinary Medical Chemistry, Dept. of Veterinary Medical Chemistry, 1991.

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Tirkkonen, Birgit. Stereoselective syntheses in the corynantheine series and of related model compounds. Helsinki: Suomalainen Tiedeakatemia, 1994.

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Rodier, Caroline. Model-based transportation performance: A comparative framework and literature synthesis. San Jose, CA: Mineta Transportation Institute, College of Business, San José State University, 2012.

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Henke, Dion Stephen. Synthesis of model compounds related to products of cellulose degradation. Birmingham: University of Birmingham, 1996.

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Book chapters on the topic "Model synthesis"

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Layer, Edward. "Model Synthesis." In Modelling of Simplified Dynamical Systems, 43–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56098-9_4.

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Cellier, François E. "Automated Model Synthesis." In Continuous System Modeling, 703–41. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4757-3922-0_15.

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Courcelles, Eulalie, Marc Horner, Payman Afshari, Alexander Kulesza, Cristina Curreli, Cristina Vaghi, Enrique Morales-Orcajo, et al. "Model Credibility." In Synthesis Lectures on Biomedical Engineering, 43–66. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-48284-7_4.

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AbstractThe need for a framework to justify that a model has sufficient credibility to be used as a basis for internal or external (typically regulatory) decision-making is a primary concern when using modelling and simulation (M&S) in healthcare. This chapter reviews published standards on verification, validation, and uncertainty quantification (VVUQ) as well as regulatory guidance that can be used to establish model credibility in this context, providing a potential starting point for a globally harmonised model credibility framework.
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Kulesza, Alexander, Axel Loewe, Andrea Stenti, Chiara Nicolò, Enrique Morales-Orcajo, Eulalie Courcelles, Fianne Sips, et al. "Model Development." In Synthesis Lectures on Biomedical Engineering, 25–42. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-48284-7_3.

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Webster, George C. "Protein synthesis." In Drosophila as a Model Organism for Ageing Studies, 119–28. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4899-2683-8_9.

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Alimguzhin, Vadim, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "On-the-Fly Control Software Synthesis." In Model Checking Software, 61–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39176-7_5.

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Singh, Shikhar, Mengshi Zhang, and Sarfraz Khurshid. "Learning Guided Enumerative Synthesis for Superoptimization." In Model Checking Software, 172–92. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30923-7_10.

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Nguyen, Thanh Son, Ben Jones, and Zvonimir Rakamarić. "Synthesis of Rigorous Floating-Point Predicates." In Model Checking Software, 44–60. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15077-7_3.

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Doyle, F. J., R. K. Pearson, and B. A. Ogunnaike. "Model-Based Controller Synthesis." In Identification and Control Using Volterra Models, 163–77. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0107-9_6.

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Golze, Ulrich. "Synthesis of Gate Model." In VLSI Chip Design with the Hardware Description Language VERILOG, 163–203. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61001-1_8.

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Conference papers on the topic "Model synthesis"

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Babić, Lepa, Boris Kordić, and Jovana Babić. "Model organizacione socijalizacije." In Synthesis 2015. Belgrade, Serbia: Singidunum University, 2015. http://dx.doi.org/10.15308/synthesis-2015-332-335.

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Ribeiro dos Santos, Cesar Augusto, Amr Hany Saleh, Tom Schrijvers, and Mike Nicolai. "CONDEnSe: Contract Based Design Synthesis." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS). IEEE, 2019. http://dx.doi.org/10.1109/models.2019.00009.

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Kahani, Nafiseh, Mojtaba Bagherzadeh, and James R. Cordy. "Synthesis of state machine models." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3365438.3410936.

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Lano, K., S. Fang, M. A. Umar, and S. Yassipour-Tehrani. "Enhancing model transformation synthesis using natural language processing." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3421386.

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Sokolić, Milena. "Creativity in Management: creative thinking process and business model canvas." In Synthesis 2015. Belgrade, Serbia: Singidunum University, 2015. http://dx.doi.org/10.15308/synthesis-2015-349-352.

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Barjaktarović, Lidija, Dragan Ilić, and Marko Marković. "Collection management model for corporate clients in the Serbian banking sector." In Synthesis 2015. Belgrade, Serbia: Singidunum University, 2015. http://dx.doi.org/10.15308/synthesis-2015-423-426.

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Gemeinhardt, Felix, Martin Eisenberg, Stefan Klikovits, and Manuel Wimmer. "Model-Driven Optimization for Quantum Program Synthesis with MOMoT." In 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2023. http://dx.doi.org/10.1109/models-c59198.2023.00100.

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Földiák, Máté, Kristóf Marussy, Dániel Varró, and István Majzik. "System architecture synthesis for performability by logic solvers." 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/10.1145/3550355.3552448.

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Temirbulatova, Madina, and Mioara Borza. "The model of business research agritourism potential in rural aeras of developing countries." In Synthesis 2015. Belgrade, Serbia: Singidunum University, 2015. http://dx.doi.org/10.15308/synthesis-2015-486-490.

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Chen, Boqi, Dylan Havelock, Connor Plante, Michael Sukkarieh, Oszkár Semeráth, and Dániel Varró. "Automated video game world map synthesis by model-based techniques." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3422001.

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Reports on the topic "Model synthesis"

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Joseph, Erat S., and Vijay P. Singh. A Continuum Model for Streamf1ow Synthesis. Fort Belvoir, VA: Defense Technical Information Center, August 1995. http://dx.doi.org/10.21236/ada300485.

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Lucey, Taylor K., Nadia Tase, Prakash Nepal, Richard D. Bergman, David L. Nicholls, Poonam Khatri, Kamalakanta Sahoo, and Andrew N. Gray. Harvested wood product carbon model synthesis. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2023. http://dx.doi.org/10.2737/pnw-gtr-1020.

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Conte, Ianina. Evidence Synthesis Programme (ESP) Logic Model. National Institute for Health and Care Research, February 2023. http://dx.doi.org/10.3310/nihropenres.1115203.1.

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Smith, Douglas. Synthesis of Correct Digital Controller Models from Specificationsby Model Transformation. Office of Scientific and Technical Information (OSTI), October 2023. http://dx.doi.org/10.2172/2430261.

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Sztipanovits, Janos, Ben Abbott, and Hubertus Franke. MULTIGRAPH: An Architecture for Model-Based Programming. Model-Based Program Synthesis for Parallel Computing. PREMOS: Programming Environment for Model-Based Program Synthesis. Version 01.00.00,. Fort Belvoir, VA: Defense Technical Information Center, March 1994. http://dx.doi.org/10.21236/ada276949.

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Hirschon, A. S., M. Asaro, and J. Bottaro. Synthesis of model compounds for coal liquefaction research. Office of Scientific and Technical Information (OSTI), November 1990. http://dx.doi.org/10.2172/7113040.

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Kwong, C. D. Synthesis of a naphthalene-hydroxynaphthalene polymer model compound. Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/7149929.

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Sen, P. K. Synthesis of model compounds for coal liquification research. Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/6444779.

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Hirschon, A. S., M. Asaro, and J. Bottaro. Synthesis of model compounds for coal liquefaction research. Office of Scientific and Technical Information (OSTI), November 1990. http://dx.doi.org/10.2172/6133254.

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Kwong, C. D. Synthesis of a naphthalene-hydroxynaphthalene polymer model compound. Office of Scientific and Technical Information (OSTI), January 1991. http://dx.doi.org/10.2172/6884708.

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You might also be interested in the extended bibliographies on the topic 'Model synthesis' for particular source types:
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