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Articoli di riviste sul tema "Model solutions"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

Sapaty, P. S. "Mosaic Warfare: from philosophy to model to solutions." Mathematical machines and systems 3 (2019): 17–34. http://dx.doi.org/10.34121/1028-9763-2019-3-17-34.

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2

Hillert, Mats. "A modified regular-solution model for terminal solutions." Metallurgical Transactions A 17, no. 10 (1986): 1878–79. http://dx.doi.org/10.1007/bf02817285.

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3

Zemlyanukhin, A. I., and A. V. Bochkarev. "Analytical Properties and Solutions of the FitzHugh – Rinzel Model." Nelineinaya Dinamika 15, no. 1 (2019): 3–12. http://dx.doi.org/10.20537/nd190101.

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4

Valentová, H., S. Škrovánková, Z. Panovská, and J. Pokorný. "Determination of astringent taste in model solutions and in beverages." Czech Journal of Food Sciences 19, No. 5 (2013): 196–200. http://dx.doi.org/10.17221/6607-cjfs.

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The astringent taste is important for the sensory quality of beverages. Perception thresholds of two important astringent compounds &ndash; tannic acid and (+)-catechin were determined using two procedures. The concentration-intensity dependence was linear at low concentrations and up to medium intensities of the astringent taste if unstructured graphical scales were used, but the saturation threshold was soon attained in the case of tannic acid. Recording the results on printed forms gave similar results as using a touch-sensitive monitor. The optimum tasting was achieved at swallowing af

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5

Leong, Wai Yie, and Chen Hui Zhao. "Optimisation Solutions and Simple Innovative Solution Research on ResNet50 Model." ASM Science Journal 20, no. 1 (2025): 1–9. https://doi.org/10.32802/asmscj.2025.2002.

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This review explores optimisation strategies and innovative modifications to the ResNet50 model, a widely used deep learning architecture in computer vision. ResNet50, with its hallmark skip connections, addresses vanishing gradient issues in deep networks, enabling efficient feature extraction. However, the model's performance can be enhanced through various optimisation solutions. This paper systematically reviews existing approaches, including pruning, quantisation, hyperparameter tuning, and advanced training techniques such as knowledge distillation and transfer learning. Additionally, th

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6

Cieplińska, Jagienka, and Agnieszka Szmelter-Jarosz. "Toward Most Valuable City Logistics Initiatives: Crowd Logistics Solutions’ Assessment Model." Central European Management Journal 28, no. 2 (2020): 38–56. http://dx.doi.org/10.7206/cemj.2658-0845.21.

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Introduction: Crowd logistics is a widely accepted concept in times of the growing popularity of sharing economy solutions. The popularity of e-commerce and a tendency to provide same-day delivery are the main reasons for their development. Developing those trends requires new products and services, now available on the market, known in the transport area as crowd logistics solutions. Purpose: The purpose of the paper is to provide a tool for assessing crowd-logistics solutions, taking into consideration customers’ requirements. The text includes groups of environmental, economic, and social c

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7

Alisherovich, Alisherov Akramboy. "MATHEMATICAL MODEL AND NUMERICAL METHODS OF FILTRATION PROCESSES OF LIQUID SOLUTIONS." American Journal of Applied Science and Technology 4, no. 10 (2024): 43–47. http://dx.doi.org/10.37547/ajast/volume04issue10-07.

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Filtration processes of liquid solutions are fundamental in many natural and industrial applications, such as environmental protection, chemical engineering, water purification, and petroleum extraction. This article develops a mathematical model for describing filtration processes and explores various numerical methods for solving the governing equations. The model is based on Darcy’s law, continuity equation, and constitutive relations of liquid solutions in porous media. Numerical methods, including finite difference, finite element, and finite volume approaches, are discussed with applicat

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8

McNaughton, Alastair. "Model Solutions to Quadratic Equations." Mathematics Teacher 79, no. 5 (1986): 332–36. http://dx.doi.org/10.5951/mt.79.5.0332.

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Here is a method of representing quadratic functions by three-dimensional wire models. It enables one to form a simple geometric concept of the location of the imaginary zeros. I have been using this material with my students and have been delighted with the ease with which they respond to it. As a result, their confidence in dealing with complex numbers has increased, their concept of functions has shown much improvement, and they are attacking problems with real insight.

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9

Zhang, Ruifeng, Nan Liu, and Man An. "Analytical solutions of Skyrme model." Discrete and Continuous Dynamical Systems - Series S 9, no. 6 (2016): 2201–11. http://dx.doi.org/10.3934/dcdss.2016092.

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10

Shi, Chang-Guang, and Minoru Hirayama. "Solitonic solutions of Faddeev model." Journal of Mathematical Physics 53, no. 2 (2012): 022301. http://dx.doi.org/10.1063/1.3682246.

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11

Bhadeshia, H. K. D. H. "Quasichemical model for interstitial solutions." Materials Science and Technology 14, no. 4 (1998): 273–76. http://dx.doi.org/10.1179/mst.1998.14.4.273.

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12

Kosmidis, Leonidas. "METASAT's Model Based Design Solutions." ACM SIGAda Ada Letters 44, no. 1 (2024): 51–52. https://doi.org/10.1145/3706601.3706608.

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METASAT is a recently started project (January 2023) in the Horizon Europe programme, in the SPACE call, coordinated by the Barcelona Supercomputing Center (BSC). METASAT will develop model-based design (MBD) solutions for high performance on-board processors such as multicores, Graphics Processing Units (GPUs) and Artificial Intelligence (AI) Accelerators. While the developed tools and methodologies are particularly focusing on the space domain, reusability to other safety critical domains is also a project goal. This talk will provide an overview of the solutions which will be developed duri

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13

Kasperchik, V. P., and A. V. Bil'dyukevich. "Ultrafiltration of model heparin solutions." Pharmaceutical Chemistry Journal 29, no. 4 (1995): 294–96. http://dx.doi.org/10.1007/bf02219558.

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14

Han, I. S., and M. Cheryan. "Nanofiltration of model acetate solutions." Journal of Membrane Science 107, no. 1-2 (1995): 107–13. http://dx.doi.org/10.1016/0376-7388(95)00107-n.

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15

Bijalwan, Naveen. "Exact solutions: classical electron model." Astrophysics and Space Science 336, no. 2 (2011): 485–89. http://dx.doi.org/10.1007/s10509-011-0796-5.

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16

Zarea, Sana’a A. "NEW SOLUTIONS FOR BIOLOGICAL MODEL." Advances in Differential Equations and Control Processes 17, no. 3 (2016): 213–29. http://dx.doi.org/10.17654/de017030213.

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17

Storbacka, Kaj. "A solution business model: Capabilities and management practices for integrated solutions." Industrial Marketing Management 40, no. 5 (2011): 699–711. http://dx.doi.org/10.1016/j.indmarman.2011.05.003.

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18

Li, Jiequan, and Gerald Warnecke. "On measure solutions to the Zero-pressure gas model and their uniqueness." Mathematica Bohemica 127, no. 2 (2002): 265–73. http://dx.doi.org/10.21136/mb.2002.134173.

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19

Kislenko, Volodymyr, Liliya Oliynyk, and Svyatoslav Ivanyshyn. "The Model of Metal Oxide Particle Formation from Water Solutions of Salts." Chemistry and Chemical Technology 4, no. 2 (2010): 95–100. http://dx.doi.org/10.23939/chcht04.02.095.

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The model describing the formation of metal oxide particles from water solutions of salts was suggested. Dependence of instability constants of metal complexes and ionization constants of oxygen containing inorganic acids on the electron density upon the central ion or atom allows to calculate these values for metal hydroxides. Equations describing the number of metal ions in polyion, the concentration of polyions in solution, the number of metal ions in primary metal oxide particles and their concentration in the system were suggested.

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20

Bogdanov, Andrey. "A DISTRIBUTION SYSTEM DESIGN MODEL." Journal Scientific and Applied Research 25, no. 1 (2023): 59–69. http://dx.doi.org/10.46687/jsar.v25i1.381.

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21

Perry, R. L., J. D. Massie, and P. T. Cummings. "An analytic model for aqueous electrolyte solutions based on fluctuation solution theory." Fluid Phase Equilibria 39, no. 3 (1988): 227–66. http://dx.doi.org/10.1016/0378-3812(88)85007-6.

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22

Cranston, Michael. "Properties of the Parabolic Anderson Model and the Anderson Polymer Model." ISRN Probability and Statistics 2013 (March 19, 2013): 1–21. http://dx.doi.org/10.1155/2013/857984.

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In this article we examine some properties of the solutions of the parabolic Anderson model. In particular we discuss intermittency of the field of solutions of this random partial differential equation, when it occurs and what the field looks like when intermittency doesn't hold. We also explore the behavior of a polymer model created by a Gibbs measure based on solutions to the parabolic Anderson equation.

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23

Abbott, Steve, and Teunis C. Dorlas. "Statistical Mechanics: Fundamentals and Model Solutions." Mathematical Gazette 84, no. 500 (2000): 375. http://dx.doi.org/10.2307/3621734.

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24

Berdnikov, V. I., and Yu A. Gudim. "THREE-PARAMETER MODEL OF SUBREGULAR SOLUTIONS." Izvestiya Visshikh Uchebnykh Zavedenii. Chernaya Metallurgiya = Izvestiya. Ferrous Metallurgy 58, no. 4 (2015): 226. http://dx.doi.org/10.17073/0368-0797-2015-4-226-229.

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25

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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26

Kuznetsov, V. D., and N. S. Dzhalilov. "Anisotropic MHD model and some solutions." Plasma Physics Reports 36, no. 9 (2010): 788–93. http://dx.doi.org/10.1134/s1063780x10090059.

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27

Brihaye, Y., and T. N. Tomaras. "The Goldstone model static solutions onS1." Nonlinearity 12, no. 4 (1999): 867–76. http://dx.doi.org/10.1088/0951-7715/12/4/307.

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28

Barbato, David, Francesco Morandin, and Marco Romito. "Smooth solutions for the dyadic model." Nonlinearity 24, no. 11 (2011): 3083–97. http://dx.doi.org/10.1088/0951-7715/24/11/004.

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29

Amari, Yuki, Paweł Klimas, Nobuyuki Sawado, and Yuta Tamaki. "Solutions in the CPNSkyrme type model." Journal of Physics: Conference Series 670 (January 25, 2016): 012002. http://dx.doi.org/10.1088/1742-6596/670/1/012002.

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30

Leung, Kevin, and Félix S. Csajka. "Lattice Model for Metal Ammonia Solutions." Physical Review Letters 78, no. 19 (1997): 3721–24. http://dx.doi.org/10.1103/physrevlett.78.3721.

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31

Chen, Ching L. "Analytic Solutions for Tidal Model Testing." Journal of Hydraulic Engineering 115, no. 12 (1989): 1707–14. http://dx.doi.org/10.1061/(asce)0733-9429(1989)115:12(1707).

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32

Xiong, Weiwen. "Solutions: A Mixed-Error Component Model." Econometric Theory 12, no. 2 (1996): 401–2. http://dx.doi.org/10.1017/s0266466600006721.

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33

Pan, Feng, and J. P. Draayer. "Analytical solutions for the LMG model." Physics Letters B 451, no. 1-2 (1999): 1–10. http://dx.doi.org/10.1016/s0370-2693(99)00191-4.

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34

Kučera, V., J. C. Martínez García, and M. Malabre. "Partial Model Matching: Parametrization of Solutions." IFAC Proceedings Volumes 29, no. 1 (1996): 1199–204. http://dx.doi.org/10.1016/s1474-6670(17)57828-3.

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35

Kučera, V., J. C. Martínez García, and M. Malabre. "Partial model matching: Parametrization of solutions." Automatica 33, no. 5 (1997): 975–77. http://dx.doi.org/10.1016/s0005-1098(96)00252-x.

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36

Ying, Lung-An. "Entropy solutions of a combustion model." Communications in Mathematical Sciences 1, no. 3 (2003): 393–407. http://dx.doi.org/10.4310/cms.2003.v1.n3.a1.

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37

Ingram, A., and S. Motta. "Solutions to the relativistic precession model." Monthly Notices of the Royal Astronomical Society 444, no. 3 (2014): 2065–70. http://dx.doi.org/10.1093/mnras/stu1585.

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38

CHUAN, LE HUY, TOHRU TSUJIKAWA, and ATSUSHI YAGI. "STATIONARY SOLUTIONS TO FOREST KINEMATIC MODEL." Glasgow Mathematical Journal 51, no. 1 (2009): 1–17. http://dx.doi.org/10.1017/s0017089508004485.

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AbstractWe continue the study of a mathematical model for a forest ecosystem which has been presented by Y. A. Kuznetsov, M. Y. Antonovsky, V. N. Biktashev and A. Aponina (A cross-diffusion model of forest boundary dynamics, J. Math. Biol. 32 (1994), 219–232). In the preceding two papers (L. H. Chuan and A. Yagi, Dynamical systemfor forest kinematic model, Adv. Math. Sci. Appl. 16 (2006), 393–409; L. H. Chuan, T. Tsujikawa and A. Yagi, Aysmptotic behavior of solutions for forest kinematic model, Funkcial. Ekvac. 49 (2006), 427–449), the present authors already constructed a dynamical system an

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39

Ranganathan, S. "The entity model of metallic solutions." Calphad 15, no. 2 (1991): 121–30. http://dx.doi.org/10.1016/0364-5916(91)90011-8.

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40

Yen, Yue-Horng, and Munir Cheryan. "Electrodialysis of model lactic acid solutions." Journal of Food Engineering 20, no. 3 (1993): 267–82. http://dx.doi.org/10.1016/0260-8774(93)90068-u.

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41

Blond, Geneviève. "Mechanical properties of frozen model solutions." Journal of Food Engineering 22, no. 1-4 (1994): 253–69. http://dx.doi.org/10.1016/0260-8774(94)90034-5.

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42

Haghtalab, A., and J. H. Vera. "Nonrandom factor model for electrolyte solutions." AIChE Journal 37, no. 1 (1991): 147–49. http://dx.doi.org/10.1002/aic.690370114.

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43

Abascal, J. L. F., and P. Turq. "Cluster structure in model electrolyte solutions." Chemical Physics 153, no. 1-2 (1991): 79–89. http://dx.doi.org/10.1016/0301-0104(91)90008-h.

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44

Williams, A. G., L. R. Dodd, and A. W. Thomas. "The colour-dielectric model: Numerical solutions." Physics Letters B 176, no. 1-2 (1986): 158–62. http://dx.doi.org/10.1016/0370-2693(86)90943-3.

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45

Hernández, Jairo Ernesto Castillo, Alvaro H. Salas, and José Gonzalo Escobar Lugo. "Exact solutions for a nonlinear model." Applied Mathematics and Computation 217, no. 4 (2010): 1646–51. http://dx.doi.org/10.1016/j.amc.2009.09.011.

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46

Aguirre-Ode, Fernando. "Unified model of associated solutions (UMAS)." Fluid Phase Equilibria 30 (January 1986): 315–26. http://dx.doi.org/10.1016/0378-3812(86)80065-6.

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47

Obukhov, Yuri N., and Eugen J. Vlachynsky. "Einstein-Proca model: spherically symmetric solutions." Annalen der Physik 8, no. 6 (1999): 497–509. http://dx.doi.org/10.1002/(sici)1521-3889(199909)8:6<497::aid-andp497>3.0.co;2-5.

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48

Tulebaev, Salavat, and Muhammed Harrasov. "Periodic solutions of Gurel - Rossler model." Izvestiya VUZ. Applied Nonlinear Dynamics 3, no. 1 (1995): 3–10. https://doi.org/10.18500/0869-6632-1995-3-1-3-10.

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Abstract (sommario):

On the basis of the Bogoljubov’s asymptotic methods the existence of selfoscillating modes and a sequence of the period doubling bifurcation in dynamical Gurel - Rossler model are demonstrated. Qualitative results are confirmed by numerical calculations.

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49

Kalorkoti, K. "Model checking in the modal μ-calculus and generic solutions". Journal of Symbolic Computation 46, № 5 (2011): 584–94. http://dx.doi.org/10.1016/j.jsc.2010.10.008.

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50

Mishra, Aamlan Saswat. "Social Acceptance Prediction Model for Generative Architectural Spaces in India." Journal of Advanced Research in Construction and Urban Architecture 6, no. 3 (2021): 50–57. http://dx.doi.org/10.24321/2456.9925.202109.

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Abstract (sommario):

Generative Architectural design is an emerging design process that is evolving due to evolution of computational power of computers and its ability to provide multiple choices of design solutions in architecture. This process, however, has a few drawbacks, some of which are, a high number of solutions which take less time for computers to produce than for their human counterpart to interpret and choose from and the less social acceptance of generative architectural design solutions. Due to the algorithms being unaware of what humans deem as acceptable solutions, these problems persist. A way t

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