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Journal articles on the topic 'Conceptual Modelling'

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Published: 4 June 2021
Last updated: 10 March 2023

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1

Thagard, Paul. "Modelling Conceptual Revolutions." Dialogue 35, no. 1 (1996): 155–59. http://dx.doi.org/10.1017/s0012217300008131.

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2

Maciá-Pérez, Francisco, Iren Lorenzo-Fonseca, Jose Vicente Berná-Martinez, and Jose Manuel Sánchez-Bernabeu. "Conceptual Modelling of Complex Network Management Systems." Journal of Computers 10, no. 5 (2015): 309–20. http://dx.doi.org/10.17706/jcp.10.5.309-320.

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3

Robinson, S. "Conceptual modelling for simulation Part II: a framework for conceptual modelling." Journal of the Operational Research Society 59, no. 3 (March 2008): 291–304. http://dx.doi.org/10.1057/palgrave.jors.2602369.

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4

Weber, Ron. "Conceptual Modelling and Ontology." Journal of Database Management 14, no. 3 (July 2003): 1–20. http://dx.doi.org/10.4018/jdm.2003070101.

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5

Maltsev, Eduard. "Conceptual modelling of organizations." Scientific Papers NaUKMA. Economics 1, no. 1 (December 1, 2016): 118–24. http://dx.doi.org/10.18523/2519-4739112016124825.

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6

Ågerfalk, Pär J., and Owen Eriksson. "Action-oriented conceptual modelling." European Journal of Information Systems 13, no. 1 (March 2004): 80–92. http://dx.doi.org/10.1057/palgrave.ejis.3000486.

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7

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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8

Guizzardi, Giancarlo, and Terry Halpin. "Ontological foundations for conceptual modelling." Applied Ontology 3, no. 1-2 (2008): 1–12. http://dx.doi.org/10.3233/ao-2008-0049.

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9

Papadimitriou, Fivos. "Conceptual Modelling of Landscape Complexity." Landscape Research 35, no. 5 (September 27, 2010): 563–70. http://dx.doi.org/10.1080/01426397.2010.504913.

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10

Paton, N. W., S. A. Khan, A. Hayes, F. Moussouni, A. Brass, K. Eilbeck, C. A. Goble, S. J. Hubbard, and S. G. Oliver. "Conceptual modelling of genomic information." Bioinformatics 16, no. 6 (June 1, 2000): 548–57. http://dx.doi.org/10.1093/bioinformatics/16.6.548.

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11

Krause, F. L., J. Lüddemann, and A. Striepe. "Conceptual Modelling for Industrial Design." CIRP Annals 44, no. 1 (1995): 137–40. http://dx.doi.org/10.1016/s0007-8506(07)62292-6.

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12

Bornberg-Bauer, E. "Conceptual data modelling for bioinformatics." Briefings in Bioinformatics 3, no. 2 (January 1, 2002): 166–80. http://dx.doi.org/10.1093/bib/3.2.166.

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13

Chan, Christine W. "Knowledge acquisition by conceptual modelling." Applied Mathematics Letters 5, no. 3 (May 1992): 7–12. http://dx.doi.org/10.1016/0893-9659(92)90027-7.

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14

Battista, Giuseppe Di, Hannu Kangassalo, and Roberto Tamassia. "Definition libraries for conceptual modelling." Data & Knowledge Engineering 4, no. 3 (September 1989): 245–60. http://dx.doi.org/10.1016/0169-023x(89)90022-0.

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15

ter Hofstede, A. H. M., and Th P. van der Weide. "Expressiveness in conceptual data modelling." Data & Knowledge Engineering 10, no. 1 (February 1993): 65–100. http://dx.doi.org/10.1016/0169-023x(93)90020-p.

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16

Meghini, C., F. Rabitti, and C. Thanos. "Conceptual document modelling and retrieval." Computer Standards & Interfaces 11, no. 3 (March 1991): 195–213. http://dx.doi.org/10.1016/0920-5489(91)90071-7.

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17

DOONER, M. "Conceptual modelling of manufacturing flexibility." International Journal of Computer Integrated Manufacturing 4, no. 3 (May 1991): 135–44. http://dx.doi.org/10.1080/09511929108944489.

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18

Insfrán, E., O. Pastor, and R. Wieringa. "Requirements Engineering-Based Conceptual Modelling." Requirements Engineering 7, no. 2 (June 2002): 61–72. http://dx.doi.org/10.1007/s007660200005.

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19

Moulin, Bernard, and Peter Creasy. "Extending the conceptual graph approach for data conceptual modelling." Data & Knowledge Engineering 8, no. 3 (July 1992): 223–48. http://dx.doi.org/10.1016/0169-023x(92)90024-6.

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20

Ruan, Mingchaun, and Jan B. M. Wiggers. "Modelling sewer emission using simulink." Water Science and Technology 36, no. 5 (September 1, 1997): 185–92. http://dx.doi.org/10.2166/wst.1997.0194.

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A dynamic programming package SIMULINK has been used to develop a conceptual emission model named SEWSIM for both event-based and continuous simulations of urban sewer systems. The model variables are mostly vectorized for simulation efficiency. The impervious catchment and the sewer network are schematised as two linear dynamic reservoirs. The physical processes that are conceptually modelled include solids buildup and washoff (catchment surface) and sediment erosion and deposition (sewer network). The conceptual model calibrated using measurements or simulation results of hydrodynamic models is able to predict the sewer emission using a long series of historical rainfall records.
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21

Gürlebeck, Klaus, Dmitrii Legatiuk, Henrik Nilsson, and Kay Smarsly. "Conceptual modelling: Towards detecting modelling errors in engineering applications." Mathematical Methods in the Applied Sciences 43, no. 3 (December 9, 2019): 1243–52. http://dx.doi.org/10.1002/mma.5934.

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22

Bouraoui, Zied, Jose Camacho-Collados, Luis Espinosa-Anke, and Steven Schockaert. "Modelling Semantic Categories Using Conceptual Neighborhood." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7448–55. http://dx.doi.org/10.1609/aaai.v34i05.6241.

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While many methods for learning vector space embeddings have been proposed in the field of Natural Language Processing, these methods typically do not distinguish between categories and individuals. Intuitively, if individuals are represented as vectors, we can think of categories as (soft) regions in the embedding space. Unfortunately, meaningful regions can be difficult to estimate, especially since we often have few examples of individuals that belong to a given category. To address this issue, we rely on the fact that different categories are often highly interdependent. In particular, categories often have conceptual neighbors, which are disjoint from but closely related to the given category (e.g. fruit and vegetable). Our hypothesis is that more accurate category representations can be learned by relying on the assumption that the regions representing such conceptual neighbors should be adjacent in the embedding space. We propose a simple method for identifying conceptual neighbors and then show that incorporating these conceptual neighbors indeed leads to more accurate region based representations.
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23

Gonzalez-Perez, Cesar, and Patricia Martín-Rodilla. "Teaching Conceptual Modelling in Cultural Heritage." Revista de Humanidades Digitales 1 (October 6, 2017): 408. http://dx.doi.org/10.5944/rhd.vol.1.2017.16128.

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24

Schnieder, E., L. Schnieder, and J. R. Müller. "Conceptual foundation of dependable systems modelling." IFAC Proceedings Volumes 42, no. 5 (June 2009): 198–202. http://dx.doi.org/10.3182/20090610-3-it-4004.00039.

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25

Kleidorfer, M., G. Leonhardt, and W. Rauch. "Identifiability analysis in conceptual sewer modelling." Water Science and Technology 66, no. 7 (October 1, 2012): 1467–74. http://dx.doi.org/10.2166/wst.2012.330.

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For a sufficient calibration of an environmental model not only parameter sensitivity but also parameter identifiability is an important issue. In identifiability analysis it is possible to analyse whether changes in one parameter can be compensated by appropriate changes of the other ones within a given uncertainty range. Parameter identifiability is conditional to the information content of the calibration data and consequently conditional to a certain measurement layout (i.e. types of measurements, number and location of measurement sites, temporal resolution of measurements etc.). Hence the influence of number and location of measurement sites on the number of identifiable parameters can be investigated. In the present study identifiability analysis is applied to a conceptual model of a combined sewer system aiming to predict the combined sewer overflow emissions. Different measurement layouts are tested and it can be shown that only 13 of the most sensitive catchment areas (represented by the model parameter ‘effective impervious area’) can be identified when overflow measurements of the 20 highest overflows and the runoff to the waste water treatment plant are used for calibration. The main advantage of this method is very low computational costs as the number of required model runs equals the total number of model parameters. Hence, this method is a valuable tool when analysing large models with a long runtime and many parameters.
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26

KARAFİSTAN, Aysel. "Conceptual modelling of Lake Manyas, Turkey." TURKISH JOURNAL OF ENGINEERING AND ENVIRONMENTAL SCIENCES 37 (2013): 306–17. http://dx.doi.org/10.3906/muh-1212-10.

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27

Ross, P. auline, Deidre Tronson, and R. aymond J. Ritchie. "Modelling Photosynthesis to Increase Conceptual Understanding." Journal of Biological Education 40, no. 2 (March 2006): 84–88. http://dx.doi.org/10.1080/00219266.2006.9656019.

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28

Kop, Christian. "Conceptual modelling tool for novice designers." International Journal of Metadata, Semantics and Ontologies 3, no. 2 (2008): 151. http://dx.doi.org/10.1504/ijmso.2008.021893.

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29

Greca, Ileana Maria, and Marco Antonio Moreira. "Mental models, conceptual models, and modelling." International Journal of Science Education 22, no. 1 (January 2000): 1–11. http://dx.doi.org/10.1080/095006900289976.

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30

Kaklauskas, Arturas, Edmundas Kazimieras Zavadskas, and Jonas Šaparauskas. "CONCEPTUAL MODELLING OF SUSTAINABLE VILNIUS DEVELOPMENT." Technological and Economic Development of Economy 15, no. 1 (March 31, 2009): 154–77. http://dx.doi.org/10.3846/1392-8619.2009.15.154-177.

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This research consists of 5 stages: comparative description of the sustainable urban development in developed countries and in Vilnius; a comparison and contrast of sustainable urban development in developed countries and Vilnius; a development of some of the general recommendations as how to improve the efficiency levels for a sustainable Vilnius; submission of particular recommendations for the city of Vilnius; a multiple criteria analysis of sustainable urban development's components and a selection of the most efficient version of sustainable urban development life cycle. The obtained results have partially confirmed the available data, and interesting trends of the development of established cities have been noted. In order to demonstrate the application of the above research, concrete examples of Vilnius will be considered in this paper. Santrauka Šis tyrimas apima penkias pakopas: išsivysčiusių šalių miestų ir Vilniaus darnaus vystymosi lyginamasis aprašymas; išsivysčiusių šalių miestų ir Vilniaus darnaus vystymosi skirtumų nustatymas; bendrų pasiūlymų, kaip pagerinti Vilniaus darnos lygį, kūrimas; konkrečių pasiūlymų pateikimas Vilniaus miestui; miestų darnaus vystymosi komponentų daugiakriterinė analizė ir efektyviausio miesto darnaus vystymosi gyvavimo ciklo varianto parinkimas. Tyrimų rezultatus iš dalies patvirtina turimi duomenys, aprašytos kai kurios žinomų miestų vystymosi tendencijos. Tyrimas iliustruojamas Vilniaus pavyzdžiu.
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31

Menq, Jau-yeu, Pan-chio Tuan, and Ta-sheng Liu. "Conceptual Lanchester-type Decapitation Warfare Modelling." Defence Science Journal 57, no. 4 (July 20, 2007): 449–61. http://dx.doi.org/10.14429/dsj.57.1793.

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32

Juristo, Natalia, and Ana M. Moreno. "Introductory paper: Reflections on Conceptual Modelling." Data & Knowledge Engineering 33, no. 2 (May 2000): 103–17. http://dx.doi.org/10.1016/s0169-023x(99)00047-6.

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33

Wang, W., and R. J. Brooks. "Improving the understanding of conceptual modelling." Journal of Simulation 1, no. 3 (August 2007): 153–58. http://dx.doi.org/10.1057/palgrave.jos.4250024.

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34

Neagu, Gabriel. "Conceptual Modelling in Generic Prototyping Approach." IFAC Proceedings Volumes 30, no. 1 (February 1997): 345–50. http://dx.doi.org/10.1016/s1474-6670(17)44656-8.

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35

van Elsas, PA, and JSM Vergeest. "Displacement feature modelling for conceptual design." Computer-Aided Design 30, no. 1 (January 1998): 19–27. http://dx.doi.org/10.1016/s0010-4485(97)00049-3.

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36

Wimmer, Klaus, and Nancy Wimmer. "Conceptual modelling based on ontological principles." Knowledge Acquisition 4, no. 4 (December 1992): 387–406. http://dx.doi.org/10.1016/1042-8143(92)90002-i.

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37

de Gelder, Johan. "Conceptual modelling of building regulation knowledge." Artificial Intelligence in Engineering 11, no. 3 (July 1997): 273–84. http://dx.doi.org/10.1016/s0954-1810(96)00043-x.

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38

Haxeltine, Alex, Lorraine Whitmarsh, Noam Bergman, Jan Rotmans, Michel Schilperoord, and Jonathan Kohler. "A Conceptual Framework for transition modelling." International Journal of Innovation and Sustainable Development 3, no. 1/2 (2008): 93. http://dx.doi.org/10.1504/ijisd.2008.018195.

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39

La-Ongsri, Somluck, John F. Roddick, and Denise de Vries. "Accommodating mesodata into conceptual modelling methodologies." Information and Software Technology 50, no. 5 (April 2008): 424–35. http://dx.doi.org/10.1016/j.infsof.2007.05.001.

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40

Salgado, Mauricio, José A. Noguera, and Francisco J. Miguel. "Modelling Cooperation Mechanisms: Some Conceptual Issues." Journal of Archaeological Method and Theory 21, no. 2 (October 26, 2013): 325–42. http://dx.doi.org/10.1007/s10816-013-9186-3.

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41

Löwe, Benedikt, and Thomas Müller. "Data and phenomena in conceptual modelling." Synthese 182, no. 1 (July 4, 2009): 131–48. http://dx.doi.org/10.1007/s11229-009-9621-x.

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42

Theodoulidis, Charalampos I., and Pericles Loucopoulos. "The time dimension in conceptual modelling." Information Systems 16, no. 3 (January 1991): 273–300. http://dx.doi.org/10.1016/0306-4379(91)90002-q.

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43

Mason, Geoffrey L. "A conceptual basis for organizational modelling." Systems Research and Behavioral Science 14, no. 5 (September 1997): 331–45. http://dx.doi.org/10.1002/(sici)1099-1743(199709/10)14:5<331::aid-sres156>3.0.co;2-q.

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44

Schewe, Klaus-Dieter, and Bernhard Thalheim. "Conceptual modelling of web information systems." Data & Knowledge Engineering 54, no. 2 (August 2005): 147–88. http://dx.doi.org/10.1016/j.datak.2004.08.005.

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45

Opdahl, Andreas L., and Guttorm Sindre. "FACET MODELLING: AN APPROACH TO FLEXIBLE AND INTEGRATED CONCEPTUAL MODELLING." Information Systems 22, no. 5 (July 1997): 291–323. http://dx.doi.org/10.1016/s0306-4379(97)00016-1.

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46

Pokorny, Jaroslav. "Modelling of Graph Databases." Journal of Advanced Engineering and Computation 1, no. 1 (June 8, 2017): 04. http://dx.doi.org/10.25073/jaec.201711.44.

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Comparing graph databases with traditional,e.g., relational databases, some important database features are often missing there. Particularly, a graph database schema including integrity constraints is mostly not explicitly defined, also a conceptual modelling is not used. It is hard to check a consistency of the graph database, because almost no integrity constraints are defined or only their very simple representatives can be specified. In the paper, we discuss these issues and present current possibilities and challenges in graph database modelling. We focus also on integrity constraints modelling and propose functional dependencies between entity types, which reminds modelling functional dependencies known from relational databases. We show a number of examples of often cited GDBMSs and their approach to database schemas and ICs specification. Also a conceptual level of a graph database design is considered. We propose a sufficient conceptual model based on a binary variant of the ER model and show its relationship to a graph database model, i.e. a mapping conceptual schemas to database schemas. An alternative based on the conceptual functions called attributes is presented. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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47

Tolstova, A. A. "CONCEPTUAL MODELLING IN ENVIRONMENTAL DESIGN: CONTENT AND MANAGEMENT MODEL." Arts education and science 2, no. 31 (2022): 57–69. http://dx.doi.org/10.36871/hon.202202008.

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Theoretical backgrounds of environmental design as a special design area have numerous gaps, therefore, the subject of research — conceptual modelling process — is highly challenging. The goal of the study is to explore the content and to develop a model for the management of conceptual modelling in environmental design. The hypothesis of the research suggests that effective management can be ensured by influencing the key homeostatic conflict between structural elements of conceptual modelling. In the course of the work, the following methods were applied: "Simple Compensatory Homeostasis"; "Expanded Compensatory Homeostasis". Outcomes: a system of models showing conceptual modelling in environmental design; a model for managing the conceptual modelling in environmental design. Conclusions: effective management of this process can be based on the principles of homeostasis through the impact on the key conflict that emerges and operates between its elements. The outcomes can be applied: in scientific theory — to understand the process of conceptual modelling in environmental design; in methodology — to contribute to the development of the environmental design methods by involving homeostatic ones; in practice — to develop a methodology for conceptual modelling in environmental design as a special design area.
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48

Freni, Gabriele, Giorgio Mannina, and Gaspare Viviani. "Stormwater infiltration trenches: a conceptual modelling approach." Water Science and Technology 60, no. 1 (July 1, 2009): 185–99. http://dx.doi.org/10.2166/wst.2009.324.

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In recent years, limitations linked to traditional urban drainage schemes have been pointed out and new approaches are developing introducing more natural methods for retaining and/or disposing of stormwater. These mitigation measures are generally called Best Management Practices or Sustainable Urban Drainage System and they include practices such as infiltration and storage tanks in order to reduce the peak flow and retain part of the polluting components. The introduction of such practices in urban drainage systems entails an upgrade of existing modelling frameworks in order to evaluate their efficiency in mitigating the impact of urban drainage systems on receiving water bodies. While storage tank modelling approaches are quite well documented in literature, some gaps are still present about infiltration facilities mainly dependent on the complexity of the involved physical processes. In this study, a simplified conceptual modelling approach for the simulation of the infiltration trenches is presented. The model enables to assess the performance of infiltration trenches. The main goal is to develop a model that can be employed for the assessment of the mitigation efficiency of infiltration trenches in an integrated urban drainage context. Particular care was given to the simulation of infiltration structures considering the performance reduction due to clogging phenomena. The proposed model has been compared with other simplified modelling approaches and with a physically based model adopted as benchmark. The model performed better compared to other approaches considering both unclogged facilities and the effect of clogging. On the basis of a long-term simulation of six years of rain data, the performance and the effectiveness of an infiltration trench measure are assessed. The study confirmed the important role played by the clogging phenomenon on such infiltration structures.
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49

Prabodha Tilakaratna, and Jayantha Rajapakse. "Conceptual and System Modelling with UML: Guidelines." International Journal of Digital Content Technology and its Applications 6, no. 22 (December 31, 2012): 90–97. http://dx.doi.org/10.4156/jdcta.vol6.issue22.9.

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50

Engelseth, Per, and Nina Pereira Kvadsheim. "Conceptual modelling of upstream offshore seaweed supply." International Journal of Design & Nature and Ecodynamics 12, no. 4 (January 1, 2018): 516–24. http://dx.doi.org/10.2495/dne-v12-n4-516-524.

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