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Journal articles on the topic 'Modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 November 2024

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1

Rahnev, Mariyan. "TRANSPORTATION SYSTEMS MODELLING." Journal Scientific and Applied Research 18, no. 1 (March 3, 2020): 28–40. http://dx.doi.org/10.46687/jsar.v18i1.277.

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As it is with every activity, the transport network can be organized in many ways by using different technical means and technologies. Taking certain management decisions is connected with the choice of one of the many possible options for realization of the transportation process. This is done with the help of one or a few indicators which serve as a criterion of efficiency, e.g. exploitation costs, profit, safety, time, etc. The research of the transport objects functioning and the optimization of their parameters is a very complicated task in most of the cases. In such cases the solutions of the problems which concern us are derived by the research and experimentation with a substitute (analogue) of the real object, specially designed for this purpose. This analogue is called a model and the process of its creation is called modelling.

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2

Qumer Gill, Asif, and Muhammad Atif Qureshi. "Adaptive Enterprise Architecture Modelling." Journal of Software 10, no. 5 (May 2015): 628–38. http://dx.doi.org/10.17706/jsw.10.5.628-638.

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3

Ivanov, Sabin. "MODELLING OF GEOGRAPHICAL REALITY." Journal Scientific and Applied Research 20, no. 1 (November 15, 2020): 33–39. http://dx.doi.org/10.46687/jsar.v20i1.302.

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From a cartographic point of view, mapping modeling can be defined as a method of creating mathematical models that are similar copies of objects of reality. They are divided into descriptive (visual) and predictive. This is the general classification of cartographic models. Descriptive models show existing objects or phenomena, as well as the links between them, presenting the results in an appropriate form that allows the user to identify them immediately. This type of model is simple and easy to create, and this reason makes it the most commonly used. The second type of cartographic model shows the predictive possibilities of the descriptive model and is called a predictive cartographic model. Predictive models require the introduction of factors and parameters that are important for the functioning of phenomena appearing in a particular territory.

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4

Y, Kovalyov, and Kalashnikova V. "Human life cycle modelling." Modern problems of modeling 25 (June 19, 2023): 110–22. http://dx.doi.org/10.33842/2313-125x-2023-25-110-122.

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5

Jørgensen, Sven Erik. "Ecological Modelling by `Ecological Modelling'." Ecological Modelling 100, no. 1-3 (December 1997): 5–10. http://dx.doi.org/10.1016/s0304-3800(97)00158-0.

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6

Bench-Capon, T. J. M., and A. M. McEnery. "Modelling devices and modelling speakers." Interacting with Computers 1, no. 2 (August 1989): 220–24. http://dx.doi.org/10.1016/0953-5438(89)90029-5.

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7

Adcock, Chris. "Modelling reality and personal modelling." International Journal of Forecasting 10, no. 3 (November 1994): 466–69. http://dx.doi.org/10.1016/0169-2070(94)90078-7.

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8

Chiorescu, Dan, Gheorghe Nagîț, Oana Dodun, and Ștefan Mihalache. "The Influence of Dimensional-Type Mathematical Model for Cylindrical Deep Drawing on the Distribution of Extreme Unitary Stresses." Applied Mechanics and Materials 657 (October 2014): 168–72. http://dx.doi.org/10.4028/www.scientific.net/amm.657.168.

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The The 3D modelling, compared to the 2D-symmetrical rotation (axial) modelling, is much more complex and one of the reasons for this, with a view to plastic anisotropy, is that 3D modelling adopts normal anisotropy while 2D modelling adopts symmetrical rotational anisotropy. When the finite element method is used for numerical solving, the number of nodes in the discretization network is much larger in the 3D modelling and even when using last generation PCs the processing time is much longer. For this reason, for expedite calculations, as those needed to establish, in a first approximation, the optimal parameters of a deep drawing process I analysed in this paper the possibility to use the 2D-symmetrical rotation (axial) modelling. In a first phase, we intend to create a representative set of deep drawing problems and then to solve them through numerical simulations using Ansys package, using both the 3D modelling, in cartesian coordinates, and the 2D-symmetrical rotation (axial) modelling, in cylindrical coordinates. Runnings shall be carried out for various refinement levels of discretization network in finite elements. The calculation times shall be compared for these two modellings and following the comparative analysis of the results we can deduce the errors entered in the 2D modelling. These errors shall be assessed by analysing and comparing the extreme unitary stresses as follows: normal stress by the Ox and Oy axes , in the 3D modelling, and in the 2D modelling by the Ox / Oy axis; shear stresses by the XZ and YZ planes, in the 3D modelling and in the 2D modelling by the XZ plane.

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9

Ketova, K. V., I. G. Rusyak, and D. D. Vavilova. "MATHEMATICAL MODELLING OF WORKFORCE POTENTIAL." European Journal of Natural History, no. 3 2020 (2020): 65–69. http://dx.doi.org/10.17513/ejnh.34088.

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10

Peregudov, Dmitriy, Anatoly Soloviev, Igor Yashin, and Victor Shutenko. "GALACTIC COSMIC RAY ANISOTROPY MODELLING." Solar-Terrestrial Physics 6, no. 1 (April 1, 2020): 29–34. http://dx.doi.org/10.12737/stp-61202003.

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We calculate the angular distribution of cosmic rays at a given point of the heliosphere under the assumption that the incoming flux from outer space is isotropic. The static magnetic field is shown to cause no anisotropy provided that the observation point is situated out of the trapped particle area. We consider a coronal ejection model in the form of a static cylinder with an axial homogeneous magnetic field inside. We calculate angular distribution samples in the trapped particle area (inside the cylinder) and show that there is a certain cone of directions with a reduced flux. For the same model with the moving cylinder, the angular distribution samples are calculated for different positions of the observation point outside the cylinder. Anisotropy of order of the ejection to light velocity ratio is shown to arise. The calculated samples are in qualitative agreement with URAGAN muon hodoscope data.

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11

C, Garcia Lirios. "Modelling of Perception Covid-19." Virology & Immunology Journal 5, no. 1 (January 12, 2021): 1–8. http://dx.doi.org/10.23880/vij-16000273.

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Mitigation policies, as their objective is the informative control of the pandemic in terms of its effects on public health, stand out because they consider risks as inherent to social communication. In this sense, the objective of this work was modeling the social perception of the risks associated with the SARS CoV-2 and Covid-19 pandemics. Axes, trajectories and relationships between categories were established that explain and anticipate the effects of confinement and social distancing strategies, alluding to the extension of the study in confinement and high-risk settings such as hospitals, the adoption of self-care and adherence to treatment from the impact of the pandemic on the parties involved.

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12

Ameedeen, Mohamed Ariff. "Multi-paradigm Modelling via XSLT." International Journal of Computer Theory and Engineering 8, no. 4 (August 2016): 332–35. http://dx.doi.org/10.7763/ijcte.2016.v8.1067.

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13

Dziewonski, Adam M. "Modelling the Earth's Deep Interior." Global Tectonics and Metallogeny 4, no. 1-2 (January 1, 1991): 53–58. http://dx.doi.org/10.1127/gtm/4/1991/53.

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14

Okamoto, Takashi. "Theoretical Modelling of Ammonite Morphogenesis." Neues Jahrbuch für Geologie und Paläontologie - Abhandlungen 190, no. 2-3 (December 22, 1993): 183–90. http://dx.doi.org/10.1127/njgpa/190/1993/183.

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15

Catlow, Richard, and Alastair Cormack. "Modelling." Current Opinion in Solid State and Materials Science 5, no. 5 (October 2001): 425. http://dx.doi.org/10.1016/s1359-0286(01)00040-7.

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16

Randerson, P. F., W. J. Mitsch, M. Straskraba, and S. E. Jorgensen. "Wetland Modelling. Developments in Environmental Modelling." Journal of Ecology 77, no. 1 (March 1989): 314. http://dx.doi.org/10.2307/2260935.

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17

Wortmann, J. C., H. M. H. Hegge, and J. B. M. Goossenaerts. "Understanding enterprise modelling from product modelling." Production Planning & Control 12, no. 3 (January 2001): 234–44. http://dx.doi.org/10.1080/095372801300107725.

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18

Galison, Peter. "Feynman’s War: Modelling Weapons, Modelling Nature." Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 29, no. 3 (September 1998): 391–434. http://dx.doi.org/10.1016/s1355-2198(98)00013-6.

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19

Lee, Kunwoo, and Ho Sang Lim. "Efficient solid modelling via sheet modelling." Computer-Aided Design 27, no. 4 (April 1995): 255–62. http://dx.doi.org/10.1016/0010-4485(95)91135-8.

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20

Behrens, B. A. Prof, S. Koch, M. Pleßow, G. Wrobel, R. Scheffler, and D. Bauer. "Eine neue Modellierung von Tiefziehwerkzeugen*/A new modelling of deep drawing tools - From parameter-based 3D-CAD-Model to the new graphical language for deep drawing tools." wt Werkstattstechnik online 106, no. 10 (2016): 690–94. http://dx.doi.org/10.37544/1436-4980-2016-10-16.

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Der Fachbeitrag konzentriert sich auf die parametergerechte 3D-CAD-Modellierung von Tiefziehwerkzeugen und deren Beschreibung in einer neuen grafischen Sprache. Die neu zu entwickelnde Modellierungssprache für die Domäne der Tiefziehwerkzeuge soll die Kommunikation zwischen Konstrukteur und CAD-Programm vereinfachen. Die Modellierung von CAD-Modellen für Tiefziehwerkzeuge wird damit flexibler und zeiteffizienter gestaltet.   This study focuses on parameter-based 3D CAD modelling of deep drawing tools as well as their description in a new graphical modelling language. The newly developed modelling language for the domain of the deep drawing tools should simplify the communication between designer and CAD program, whereby the CAD modelling of deep drawing tools should be more flexible and more time-efficient.

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21

Duering, Andreas. "Modelling massacres. The agent-based modelling of catastrophic events using skeletal data from archaeological excavations." Anthropologischer Anzeiger 76, no. 3 (September 1, 2019): 217–21. http://dx.doi.org/10.1127/anthranz/2019/0907.

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22

Rezaldi, Muhammad Yudhi, RABIAH ABDUL KADIR, Mohamad Taha Ijab, and Apip Apip. "Aesthetics 3D Geovisualization For Flood Disaster Based on XYZ Coordinate." Journal of Applied Research and Technology 21, no. 4 (August 31, 2023): 688–706. http://dx.doi.org/10.22201/icat.24486736e.2023.21.4.1706.

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Geovisualization can convert spatial and non-spatial data into an accurate visualization of flood modelling but less realistic. Contrarily, Multimedia can produce realistic visualizations by applying aesthetic parameters, but not based on data, inaccurate. This research successfully combined both Geovisualization and Multimedia that created an accurate and realistic visualization of flood modelling. An experimental methodology was used for the flood transformation data through geovisualization technique and carried out the 3D mapping objects through photogrammetry by using drones. Both modellings were combined by overlapping the X, Y, Z coordinates. Multimedia techniques were used to remodeling, animate, design interface, action script, and to apply aesthetic parameters. The success of this study was measured through a comparative evaluation; comparing between the model of this research, and two other models from previous studies. The result was 84.6% of the respondents chose this research modelling. The researcher used Alpha Cronbach's reliability test with SPSS for validity checking. The result showed a significant reliability value of 0.935. In the theoretical contribution, this research modelling produced visualizations of flood modelling based on accurate data and aesthetic values. While in practical contribution, this modelling can be used as a source of information for the decision-makers for flood mitigation plans.

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23

Ilham, M. Syirojudin, R. Margiono, A. Marsono, and N. Ardiana. "Indonesian Earth’s Lithospheric Magnetic Field modelling using Spherical Cap Harmonic Analysis Method." IOP Conference Series: Earth and Environmental Science 873, no. 1 (October 1, 2021): 012030. http://dx.doi.org/10.1088/1755-1315/873/1/012030.

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Abstract The earth’s lithospheric magnetic field is part of the main earth’s magnetic field. The lithospheric field has a very small value compared to the Earth’s main magnetic field, approximately less than 1%, and this field is generated at the earth’s crust and upper mantle. Modelling of lithospheric field is useful mainly for predicting the distribution of the value of lithospheric fields and to determine the magnetic anomaly. In this research, modelling the Earth’s lithospheric magnetic field uses Spherical Cap Harmonic Analysis (SCHA) method and this method can do modelling using regional magnetic data. The data used for the modelling are magnetic repeat station data in Indonesia region (BMKG’s Epoch) and SWARM satellite data. The results of the modelling using integrated SWARM satellite and repeat station data produce RMSE values of 64.0834 nT and the expansion of index K is 70. In addition, the results of the modelling resolution is 1.50. The value’s range of modelling’s result are -987.192 – 998.239 nT for X component, -968.189 – 949.438 nT for Y component, -981.266 – 608.676 nT for Z component, and -904.151 – 997.389 nT for total intensity are.

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24

Klimenko, Alexander Y. "From Modelling Turbulence to General Systems Modelling." AppliedMath 2, no. 2 (May 26, 2022): 247–60. http://dx.doi.org/10.3390/appliedmath2020015.

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Complex adaptive and evolutionary systems can, at least in principle, be modelled in ways that are similar to modelling of complex mechanical (or physical) systems. While quantitative modelling of turbulent reacting flows has been developed over many decades due to availability of experimental data, modelling of complex evolutionary systems is still in its infancy and has huge potential for further development. This work analyses recent trends, points to the similarity of modelling approaches used in seemingly different areas, and suggests a basic classification for such approaches. Availability of data in the modern computerised world allows us to use tools previously developed in physics and applied mathematics in new domains of scientific inquiry that previously were not amendable by quantitative evaluation and modelling, while raising concerns about the associated ethical and legal issues. While the utility of big data has been repeatedly demonstrated in various practical applications, these applications, as far as we can judge, do not involve the scientific goal of conceptual modelling of emergent collective behaviour in complex evolutionary systems.

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25

Madsen, Bodil Nistrup, and Hanne Erdman Thomsen. "Terminological concept modelling and conceptual data modelling." International Journal of Metadata, Semantics and Ontologies 4, no. 4 (2009): 239. http://dx.doi.org/10.1504/ijmso.2009.029228.

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26

Cacho, Oscar J. "Systems modelling and bioeconomic modelling in aquaculture." Aquaculture Economics & Management 1, no. 1-2 (March 1997): 45–64. http://dx.doi.org/10.1080/13657309709380202.

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27

Rossiter, J. A., and B. Kouvaritakis. "Modelling and implicit modelling for predictive control." International Journal of Control 74, no. 11 (January 2001): 1085–95. http://dx.doi.org/10.1080/00207170110054129.

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28

Horácek, Petr. "Neuro-Fuzzy Modelling – Architecture and Modelling Issues." IFAC Proceedings Volumes 33, no. 17 (July 2000): 1161–66. http://dx.doi.org/10.1016/s1474-6670(17)39569-1.

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29

Perrykkad, Kelsey, and Jakob Hohwy. "Modelling Me, Modelling You: the Autistic Self." Review Journal of Autism and Developmental Disorders 7, no. 1 (May 16, 2019): 1–31. http://dx.doi.org/10.1007/s40489-019-00173-y.

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30

Ved`, Valeriy, Leonid Tovazhnyanskiy, Yevgeniy Krasnokutskiy, and Vadim Koshchiy. "Modelling of Hydrocarbons Catalytic Conversion Process." Chemistry & Chemical Technology 9, no. 1 (March 15, 2015): 101–6. http://dx.doi.org/10.23939/chcht09.01.101.

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31

Mohieldeen, Sahar Ismael, and Adil M. A. Elsinnari. "Inception Modelling for Sudan Investment Map." International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (February 28, 2019): 609–25. http://dx.doi.org/10.31142/ijtsrd21457.

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32

Ramana, T. Venkata, Sagam Kunta Subhash, and Sangem Devendra Kumar Vanga Balakrishna. "Modelling and 3D Printing of Crankshaft." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1039–43. http://dx.doi.org/10.31142/ijtsrd23224.

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33

Slimani, K., M. Zaaf, and H. Bendjama. "Simplified Modelling of Tandem Cold Rolling." METALLOFIZIKA I NOVEISHIE TEKHNOLOGII 40, no. 11 (December 20, 2018): 1509–20. http://dx.doi.org/10.15407/mfint.40.11.1509.

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34

Leandro, Francisco. "Education Modelling for the Common Good." Journal of Management and Training for Industries 5, no. 2 (October 1, 2018): 37–49. http://dx.doi.org/10.12792/jmti.5.2.37.

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35

Cautenet, Guy, Frédéric Guillard, Béatrice Marticorena, Gilles Bergametti, Francois Dulac, and Jérôme Edy. "Modelling of the Saharan dust event." Meteorologische Zeitschrift 9, no. 4 (September 20, 2000): 221–30. http://dx.doi.org/10.1127/metz/9/2000/221.

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36

Verdeja-González, L. F., M. F. Barbés-Fernández, R. González-Ojeda, G. A. Castillo, and R. Colás. "Thermal modelling of a torpedo-car." Revista de Metalurgia 41, no. 6 (December 30, 2005): 449–55. http://dx.doi.org/10.3989/revmetalm.2005.v41.i6.236.

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37

KOVÁČ, Viliam, Ján PASTIRČAK, and Lukáš FRIGA. "Brief Guide for Agent-Based Modelling." Acta Electrotechnica et Informatica 14, no. 2 (June 1, 2014): 19–27. http://dx.doi.org/10.15546/aeei-2014-0013.

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38

Kambarbekov, G. М., and A. Ye Baimaganbetov. "USING ARTIFICIAL INTELLIGENCE FOR HYDROLOGICAL MODELLING." Geography and water resources, no. 1 (March 28, 2024): 58–62. http://dx.doi.org/10.55764/2957-9856/2024-1-58-62.8.

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Hydrological modelling plays a critical role in managing water resources, especially in arid and semi-arid regions where water scarcity is a major challenge. With the emergence of artificial intelligence (AI), hydrological modelling has experienced a significant transformation in recent years. This paper reviews the recent advances in AI-based hydrological modelling and examines its potential applications in water resource management. The study highlights the role of AI in enhancing the accuracy of hydrological models and facilitating more efficient and sustainable water management practices. The results suggest that AI-based hydrological models have the potential to revolutionize the way water resources are managed, and that future research in this area is warranted.

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39

Narendra Gokhale, Maitreya. "Hyperelastic Material Modelling of Silicone Rubber." International Journal of Science and Research (IJSR) 12, no. 7 (July 5, 2023): 2069–73. http://dx.doi.org/10.21275/sr23726173228.

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40

KANG, Geun-Taek, and Michio SUGENO. "Fuzzy Modelling." Transactions of the Society of Instrument and Control Engineers 23, no. 6 (1987): 650–52. http://dx.doi.org/10.9746/sicetr1965.23.650.

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41

Hay, Alan M., J. de D. Ortuzar, and L. G. Willumsen. "Modelling Transport." Transactions of the Institute of British Geographers 18, no. 1 (1993): 153. http://dx.doi.org/10.2307/623078.

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42

W. McDonogh, Gary. "Modelling Barcelona." Arxiu d'Etnografia de Catalunya, no. 14 (December 18, 2014): 203. http://dx.doi.org/10.17345/aec14.203-225.

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Este texto panorámico, de carácter introductorio, sirve como presentación de un libro con el mismo título que aparecerá en el mercado norteamericano en los próximos meses. Se trata de una aproximación histórica que, tras identificar en un estilo braudeliano la ubicación de la ciudad en su contexto mediterráneo, pretende destacar las huellas de su conformación como ciudad global a través de las diferentes fases de plenitud y crisis que se han sucedido a lo largo de mil años de historia, forjando las capas que configuran hoy el palimpsesto urbano barcelonés. Las etapas que se narran son las siguientes: 1) la expansión comercial y colonial mediterránea durante la Edad Media hasta su crisis en el siglo xv, 2) los efectos en la ciudad de la vinculación dinástica de Cataluña con Castilla en la era de la expansión colonial americana, 3) la industrialización, etapa de crecimiento urbano, de luchas sociales y de conformación de la ciudad burguesa y de una identidad nacional, 4) la otra Barcelona de la industrialización: luchas sociales, conflicto y contestación urbana, 5) la Barcelona de la era franquista y 6) la Barcelona posmoderna, desde las Olimpiadas hasta la actualidad. Junto a esta visión panorámica, el texto ofrece una abundante selección bibliográfica que abarca desde estudios etnográficos e históricos hasta obras literarias y otras fuentes de documentación social.

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43

Kroboth, Patricia D., Virginia D. Schmith, and Randall B. Smith. "Pharmacodynamic Modelling." Clinical Pharmacokinetics 20, no. 2 (February 1991): 91–98. http://dx.doi.org/10.2165/00003088-199120020-00001.

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44

Philpott, Samantha, and Philomena Corrigan. "Role modelling." Nursing Management 13, no. 1 (April 2006): 10–12. http://dx.doi.org/10.7748/nm.13.1.10.s12.

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45

Zarwin, Zoe, Marija Bjeković, Jean-Marie Favre, Jean-Sébastien Sottet, and Henderik A. Proper. "Natural Modelling." Journal of Object Technology 13, no. 3 (2014): 4:1. http://dx.doi.org/10.5381/jot.2014.13.3.a4.

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46

Anderson, Oliver D., and Warren Gilchrist. "Statistical Modelling." Technometrics 28, no. 4 (November 1986): 403. http://dx.doi.org/10.2307/1268994.

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47

Ziegel, Eric R., G. Seeber, B. Francis, R. Hatzinger, and G. Stechel-Berger. "Statistical Modelling." Technometrics 38, no. 4 (November 1996): 413. http://dx.doi.org/10.2307/1271336.

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48

Hrebik, Radek, and Jaromir Kukal. "Diffusion Modelling." Neural Processing Letters 54, no. 2 (November 1, 2021): 835–52. http://dx.doi.org/10.1007/s11063-021-10660-1.

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49

Bulckaen, Fabrizio, and Alberto Pench. "Modelling congestion." STUDI ECONOMICI, no. 106 (February 2013): 41–51. http://dx.doi.org/10.3280/ste2012-106003.

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50

Müller, Berit, Jens Weibezahn, and Frauke Wiese. "Energy Modelling." European Energy & Climate Journal 8, no. 2 (December 1, 2018): 18–24. http://dx.doi.org/10.4337/eecj.2018.02.04.

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