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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Базилевский, М. П. "SYNTHESIS OF LINEAR REGRESSION MODEL AND EIV-MODEL." МОДЕЛИРОВАНИЕ, ОПТИМИЗАЦИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ 7, no. 1(24) (February 9, 2019): 33–34. http://dx.doi.org/10.26102/2310-6018/2019.24.1.033.

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Данная работа посвящена синтезу модели парной линейной регрессии и простейшей EiV-модели (Errors-In-Variables model), более известной как регрессия Деминга. EIV-модель – это регрессия, в которой все переменные содержат случайные ошибки. Такие модели имеют ряд существенных недостатков, что затрудняет работу с ними. Предлагаемый в работе синтез, названный двухфакторной моделью полносвязной линейной регрессии, не только лишен этих недостатков, но и имеет определенные достоинства. Рассмотрены основные этапы построения и анализа двухфакторных моделей полносвязной линейной регрессии. Предложенная модель полносвязной линейной регрессии имеет много общего с классической моделью множественной регрессии, однако в основе этих двух видов лежат совершенно разные подходы. Если множественная регрессия строится по принципу «независимые переменные влияют на зависимую», то принципом полносвязной регрессии является «все переменные влияют друг на друга». Установлено, что аппроксимационные способности полносвязных моделей не превосходят способностей множественных регрессий, но зато первые имеют гораздо более разнообразную интерпретацию. Разработанный синтез можно использовать при построении множественных моделей как инструмент для решения задач снижения размерности данных, устранения мультиколлинеарности и отбора информативных регрессоров. This paper is devoted to a synthesis of pair-wise linear regression model and simplest EiV-model (Errors-In-Variables model), better known as the Deming regression. The EIV model is a regression in which all variables contain random errors. Such models have a number of significant drawbacks, which makes it difficult to work with them. The synthesis proposed in the paper, called the two-factor model of a fully connected linear regression, is not only devoid of these shortcomings, but also has certain advantages. The main stages of the construction and analysis of two-factor models of fully connected linear regression are considered. The proposed fully connected linear regression model has much in common with the classical multiple regression model; however, these two types are based on completely different approaches. If multiple regression is based on the principle “independent variables affect the dependent one”, then the principle of fully connected regression is “all variables influence each other”. It is established that the approximation abilities of fully connected models do not exceed the capabilities of multiple regressions, but the former have a much more diverse interpretation. The developed synthesis can be used in the construction of multiple models as a tool for solving problems of reducing the dimensionality of data, eliminating multicollinearity and selecting informative regressors.
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12

Yang, Linda, Ani Orchanian-Cheff, Melanie Anderson, Ashley Farrell, and Tim Tripp. "Implementing a Three-Tiered Service Model for Knowledge Syntheses at an Academic Teaching Hospital." Journal of the Canadian Health Libraries Association / Journal de l'Association des bibliothèques de la santé du Canada 41, no. 2 (July 30, 2020): 46–66. http://dx.doi.org/10.29173/jchla29436.

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With increasing interest in publishing systematic reviews and other syntheses comes increasing numbers of researchers who want to perform a synthesis, but are unfamiliar with the rigorous methods and requirements of this kind of review. In response to increasing demand, and problems observed in working with researchers new to knowledge synthesis, UHN Library and Information Services designed and implemented a new Knowledge Synthesis Service model to meet the demand while providing an opportunity to educate researchers about guidelines for KS methodology and reporting standards, as well as a mechanism for librarians to control the information published about the search methods, and withdraw from projects that do not meet standards.
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13

Lee, Nelson, Julius O. Smith, and Vesa Valimaki. "Analysis and Synthesis of Coupled Vibrating Strings Using a Hybrid Modal-Waveguide Synthesis Model." IEEE Transactions on Audio, Speech, and Language Processing 18, no. 4 (May 2010): 833–42. http://dx.doi.org/10.1109/tasl.2009.2033979.

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14

KASUYA, Hideki. "A MODEL OF SPEECH SYNTHESIS." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 22, no. 1 (1995): 22–29. http://dx.doi.org/10.2333/jbhmk.22.22.

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15

Chianchana, Chaiwichit. "Research Synthesis on Educational Model." 11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES 11, no. 1 (December 9, 2020): 14. http://dx.doi.org/10.35609/gcbssproceeding.2020.11(14).

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The concept of study management according to the National Study Plan, based on the key principles of study management, consists of: Principles of Education Management for The Nation Principles of Education Management for Equality and General. The philosophy of sufficiency economy and the principle of participation in all sectors of society. It also adheres to sustainable development goals. Domestic issues such as the quality of people of all ages. Changes to the country's population structure Inequality of income distribution and environmental crisis. The national strategy is a key framework for the creation of a national education plan from 2017 to 2036, and the findings in the study's quality plan have also found that the development results are not satisfactory, as the basic academic achievements are significantly lower than average and lower than many Asian countries (Office of the Education Council, 2017). From that plan, Education is extremely important and must continue to develop across all dimensions. Keywords: Research systhesis, Educational Model
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16

Srinivasan, Venkatesh, Ara Vartanian, and Thomas Reps. "Model-assisted machine-code synthesis." Proceedings of the ACM on Programming Languages 1, OOPSLA (October 12, 2017): 1–26. http://dx.doi.org/10.1145/3133885.

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17

Stroud, C. E., R. R. Munoz, and D. A. Pierce. "Behavioral model synthesis with Cones." IEEE Design & Test of Computers 5, no. 3 (June 1988): 22–30. http://dx.doi.org/10.1109/54.7960.

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18

Coleman, William F. "Molecular Model of Creatine Synthesis." Journal of Chemical Education 83, no. 11 (November 2006): 1657. http://dx.doi.org/10.1021/ed083p1657.

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19

Dietz, Paul H. "Model‐based trumpet tone synthesis." Journal of the Acoustical Society of America 85, S1 (May 1989): S79. http://dx.doi.org/10.1121/1.2027149.

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20

Mota, Alexandre, Juliano Iyoda, and Heitor Maranhão. "Program synthesis by model finding." Information Processing Letters 116, no. 11 (November 2016): 701–5. http://dx.doi.org/10.1016/j.ipl.2016.06.003.

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21

Akiyama, Tomohiro, Hiromichi Isogai, and Jun-ichiro Yagi. "Mathematical model of combustion synthesis." AIChE Journal 44, no. 3 (March 1998): 695–700. http://dx.doi.org/10.1002/aic.690440317.

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22

Wolfe, Barbara L., and Jere R. Behrman. "The synthesis economic fertility model." Journal of Population Economics 5, no. 1 (February 1992): 1–16. http://dx.doi.org/10.1007/bf00160326.

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23

Jagannadharao, Yaddanapudi, and Dabir S. Viswanath. "A model for diazacyclopropane synthesis." Journal of Applied Chemistry and Biotechnology 26, no. 1 (May 29, 2007): 488–98. http://dx.doi.org/10.1002/jctb.5020260169.

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24

Curini, Massimo, Francesco Epifano, Maria?C Marcotullio, Ornelio Rosati, Ming Guo, Yousheng Guan, and Ernest Wenkert. "Hydrindanone Synthesis: An Incisterol Model." Helvetica Chimica Acta 88, no. 2 (February 2005): 330–38. http://dx.doi.org/10.1002/hlca.200590016.

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25

Kelleher, J. K., and T. M. Masterson. "Model equations for condensation biosynthesis using stable isotopes and radioisotopes." American Journal of Physiology-Endocrinology and Metabolism 262, no. 1 (January 1, 1992): E118—E125. http://dx.doi.org/10.1152/ajpendo.1992.262.1.e118.

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Important syntheses in living systems occur by condensation reactions of the type nA----1B (where n is the number of A molecules needed to synthesize 1 molecule of B). Quantitative relationships for estimating the rate of synthesis of B from radioactive and stable isotope tracers are compared. With radioisotope tracers, only a single quantity is detected, the amount of radioactivity in B. In contrast, isotopes of varying mass produce multiple mass isotopomers B that are detected using mass spectrometry. The analysis demonstrates that the rate of synthesis of B is identifiable from stable isotope data but not from radioisotope data. This results because the isotopomer distribution of B at any time after tracer addition is a function of only the multinomial distribution representing the synthesis of B from n molecules of A and two parameters representing the fractional fluxes of isotopically enriched molecules to the sampled compartment of B. The model considers the possibility that the sampled compartment of B may not reach isotopic steady state during the experiment. A graphical method for obtaining initial estimates of the two parameters is presented.
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26

Wu, Qin, and Peizi Zhou. "Advertisement Synthesis Network for Automatic Advertisement Image Synthesis." International Journal of Antennas and Propagation 2024 (March 18, 2024): 1–10. http://dx.doi.org/10.1155/2024/8030907.

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Анотація:
Image advertising is widely used by companies to advertise their products and increase awareness of their brands. With the constant development of image generation techniques, automatic compositing of advertisement images has also been widely studied. However, the existing algorithms cannot synthesise consistent-looking advertisement images for a given product. The key challenge is to stitch a given product into a scene that matches the style of the product while maintaining a consistent-looking. To solve this problem, this paper proposes a new two-stage automatic advertisement image generation model, called Advertisement Synthesis Network (ASNet), which explores a two-stage generation framework to synthesise consistent-looking product advertisement images. Specifically, ASNet first generates a preliminary target product scene using Pre-Synthesis and then extracts scene features using Pseudo-Target Object Encoder (PTOE) and true target features using Real Target Object Encoder (RTOE), respectively. Finally, we inject the acquired features into the pretrained diffusion model and reconstruct them in the preliminary generated target goods scene. Extensive experiments have shown that the method achieves better results in all three performance metrics related to the quality of the synthesised image compared to other methods. In addition, we have done a simple and preliminary study on the effect of synthetic advertisement images on real consumers’ purchase intention and brand perception. The results of the study show that the advertisement images synthesised by the model proposed in this paper have a positive impact on consumer purchase intention and brand perception.
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27

Leweling, Klaus-Ulrich, and Benno Stein. "Hybrid Constraints in Automated Model Synthesis and Model Processing." Electronic Notes in Discrete Mathematics 4 (January 2000): 68. http://dx.doi.org/10.1016/s1571-0653(05)80107-6.

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28

Edlund, Kristian, Tommy Mølbak, and Jan Dimon Bendtsen. "Simple Models for Model-based Portfolio Load Balancing Controller Synthesis." IFAC Proceedings Volumes 42, no. 9 (2009): 173–78. http://dx.doi.org/10.3182/20090705-4-sf-2005.00032.

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29

Prokopev, Andrey P., Vladimir I. Ivanchura, and Rurik T. Emelyanov. "Parametric Synthesis Model Controller for Nonlinear System Modal Control Method." Journal of Siberian Federal University. Engineering & Technologies 10, no. 4 (June 2017): 497–507. http://dx.doi.org/10.17516/1999-494x-2017-10-4-497-507.

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30

Inayat, Abrar, Muhammad A. B. Ahmad, Mohsin Raza, Chaouki Ghenai, Salman Raza Naqvi, and Muhammad Ayoub. "Development of Reaction Kinetics Model for the Production of Synthesis Gas from Dry Methane Reforming." Bulletin of Chemical Reaction Engineering & Catalysis 16, no. 2 (May 5, 2021): 440–45. http://dx.doi.org/10.9767/bcrec.16.2.10510.440-445.

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Анотація:
The energy supply systems dependent on fossils and municipal solid waste (MSW) materials are primarily responsible for releasing greenhouse (GHG) gases and their related environmental hazards. The increasing amount of methane (CH4) and carbon dioxide (CO2) is the scientific community's main concern in this context. Reduction in the emission amount of both gases combined with the conversion technologies that would convert these total threat gases (CO2 and CH4) into valuable feedstocks will significantly lower their hazardous impact on climate change. The conversion technique known as dry methane reforming (DMR) utilizes CO2 and CH4 to produce a combustible gas mixture (CO+H2), popularly known as synthesis gas/or syngas. Therefore, this research study aims to explore and enlighten the characteristics of the DMR mechanism. The conversion behaviour of CO2 and CH4 was studied with modelling and simulation of the DMR process using MATLAB. The results showed that inlet gas flow has a significant impact on the reactions. In contrast, the inlet molar composition ratio of the reactions was found to have no substantial effect on the mechanism of DMR. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).
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31

Ding, Li Jie, Jun Wang, and Ying Liu. "A Synthesis Load Model with Distribution Network." Applied Mechanics and Materials 380-384 (August 2013): 2161–64. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.2161.

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Equivalent induction motors with equivalent static loads are applied in load models. However, load appliances are installed on low voltage buses in power grid and the distribution network impedances cannot be neglected. A synthesis load model considering the distribution network can describe the load structure more completely and precisely. A comparison including the composite load model simulated powers and the synthesis load model simulated powers with the measures are described in this paper.
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32

Klepper, L. Ya. "Synthesis of radiological models and radiological invariants (constants). Part 3: Synthesis of population-phenomenological models and Klepper model." Biomedical Engineering 40, no. 3 (May 2006): 130–34. http://dx.doi.org/10.1007/s10527-006-0061-3.

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33

Klepper, L. Ya. "Synthesis of radiological models and radiological constants. Part 4: Synthesis of population-phenomenological models and the Lyman model." Biomedical Engineering 40, no. 5 (September 2006): 251–55. http://dx.doi.org/10.1007/s10527-006-0092-9.

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34

Ryu, Joonjae, and Christos T. Maravelias. "A generalized distillation network synthesis model." Chemical Engineering Science 244 (November 2021): 116766. http://dx.doi.org/10.1016/j.ces.2021.116766.

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35

Pasetto, Stefano, Eva K. Grebel, Cesare Chiosi, Denija Crnojević, Peter Zeidler, Giorgia Busso, Letizia P. Cassarà, Lorenzo Piovan, Rosaria Tantalo, and Claudio Brogliato. "GalMod: A Galactic Synthesis Population Model." Astrophysical Journal 860, no. 2 (June 19, 2018): 120. http://dx.doi.org/10.3847/1538-4357/aac1bb.

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36

Nanda, Sambhudutta, Prasanna Kumar Sahu, and Rabindra Kishore Mishra. "Surrogate-based model for metamaterial synthesis." International Journal of Computer Aided Engineering and Technology 15, no. 4 (2021): 565. http://dx.doi.org/10.1504/ijcaet.2021.118473.

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37

Nanda, Sambhudutta, Rabindra Kishore Mishra, and Prasanna Kumar Sahu. "Surrogate-based model for metamaterial synthesis." International Journal of Computer Aided Engineering and Technology 15, no. 4 (2021): 565. http://dx.doi.org/10.1504/ijcaet.2021.10041016.

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38

McAuliffe, Rebecca D., Victoria Petrova, Matthew J. McDermott, Jameson Landon Tyler, Ethan C. Self, Kristin A. Persson, Ping Liu, and Gabriel M. Veith. "Synthesis of model sodium sulfide films." Journal of Vacuum Science & Technology A 39, no. 5 (September 2021): 053404. http://dx.doi.org/10.1116/6.0001069.

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39

Ananiashvili, Iuri, and Vladimer Papava. "Macroeconomic Model of Laffer-Keynesian Synthesis." Problems of Economic Transition 54, no. 12 (April 1, 2012): 22–39. http://dx.doi.org/10.2753/pet1061-1991541202.

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40

Strosnider, J. K., P. Nandi, S. Kumaran, S. Ghosh, and A. Arsnajani. "Model-driven synthesis of SOA solutions." IBM Systems Journal 47, no. 3 (2008): 415–32. http://dx.doi.org/10.1147/sj.473.0415.

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41

Blair, Eunice M. "Nursing and administration: A Synthesis model." Nursing Administration Quarterly 13, no. 2 (1989): 1–11. http://dx.doi.org/10.1097/00006216-198901320-00003.

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Ziller, Roberto, and Klaus Schneider. "Combining supervisor synthesis and model checking." ACM Transactions on Embedded Computing Systems 4, no. 2 (May 1, 2005): 331–62. http://dx.doi.org/10.1145/1067915.1067920.

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Membiela, Pedro, Pilar Latorre, María Xosé Camba, and Mari Carmen Cid. "A model for demonstrating protein synthesis." Journal of Biological Education 27, no. 2 (June 1993): 92–95. http://dx.doi.org/10.1080/00219266.1993.9655312.

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Kepner, Jeremy. "High Performance Computing Productivity Model Synthesis." International Journal of High Performance Computing Applications 18, no. 4 (November 2004): 505–16. http://dx.doi.org/10.1177/1094342004048542.

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Liceras, Juana M. "Linguistic theory and the Synthesis Model." Epistemological issue with keynote article “The development of bimodal bilingualism: Implications for linguistic theory” by Diane Lillo-Martin, Ronice Müller de Quadros and Deborah Chen Pichler 6, no. 6 (December 31, 2016): 776–81. http://dx.doi.org/10.1075/lab.6.6.06lic.

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Santarsiero, M., R. Borghi, and V. Ramírez-Sánchez. "Synthesis of electromagnetic Schell-model sources." Journal of the Optical Society of America A 26, no. 6 (May 26, 2009): 1437. http://dx.doi.org/10.1364/josaa.26.001437.

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Mollá, M., M. L. García-Vargas, and A. Bressan. "PopStar I: evolutionary synthesis model description." Monthly Notices of the Royal Astronomical Society 398, no. 1 (September 1, 2009): 451–70. http://dx.doi.org/10.1111/j.1365-2966.2009.15160.x.

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Yang, Liu, and Antoine Rauzy. "Model synthesis using boolean expression diagrams." Reliability Engineering & System Safety 186 (June 2019): 78–87. http://dx.doi.org/10.1016/j.ress.2019.02.019.

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de Bruyn, Pauline J., Audrey S. C. Lim, Mark G. Looney, and David H. Solomon. "Strategic synthesis of model novolac resins." Tetrahedron Letters 35, no. 26 (June 1994): 4627–30. http://dx.doi.org/10.1016/s0040-4039(00)60747-5.

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