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Статті в журналах з теми "Historical modeling"

Автор: Grafiati

Опубліковано: 28 жовтня 2023

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1

Okorokova, Vira. "The problem of virtual modeling of historical processes in modern science." Bulletin of Luhansk Taras Shevchenko National University, no. 6 (337) (2020): 4–13. http://dx.doi.org/10.12958/2227-2844-2020-6(337)-4-13.

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Анотація:

The article is devoted to the study of the problem of virtual modeling of historical events and processes. It is noted that the modeling of social and historical processes began to be developed as a method for studying society only from the 70s-80s of the XX century. At the turn of the XX - XXI century, such an interdisciplinary direction as cliodynamics, devoted to the modeling of historical processes based on mathematical methods, appeared. The emergence of this scientific direction shows that the topic of modeling historical processes is based on the methodology of mathematical modeling. The article draws special attention to the virtualization of modern society as a factor in improving the modeling method. Computer technologies are becoming the main means, which greatly simplifies the modeling technology. Problems in creating a model of historical processes are noted, which is associated with a source study basis, the use of additional technologies, and it is also necessary to take into account the complexity, irreversibility, nonlinearity of the historical process itself. Also, as an example, ABM (agent-based models) are given, as an example of imitation and visualization of objects, phenomena. Among the individual characteristics of virtual modeling, the author identifies the ability to create a plausible imitation of an event, interactivity, information content, the ability to change / correct the intended nature of the process or the result of an event, unlimited time and space. This is the advantage of virtual modeling as a method of modern reconstruction of historical events, especially those that do not have accurate data, are debatable. Moreover, the article points out that this type of modeling has already embraced even those historical sciences that were more problematic in this regard (archeology, paleontology).

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2

Moskvin, Aleksei, Mariia Moskvina, and Victor Kuzmichev. "Parametric modeling of historical mannequins." International Journal of Clothing Science and Technology 32, no. 3 (December 24, 2019): 366–89. http://dx.doi.org/10.1108/ijcst-06-2019-0093.

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Purpose Digital technologies are widely used for digitization of museum and archival heritage and creation of digital, multimedia and online exhibitions, especially in terms of costume history. Digital exhibitions require historical dress forms which were used in the past for costume presentation. The purpose of this paper is to develop a new method for parametric modeling of the nineteenth century dress forms in accordance with fashionable body shape. Design/methodology/approach Due to limited number of body measurements in historical sizing tables, it is impossible to redesign the morphology of old fashionable body with high accuracy by means of contemporary CAD. The developed method is based on two sources of information: first, historical sizing tables with body measurements; second, historical corsets. By combining both resources and applying virtual try-on technology, the full anthropometric database about the nineteenth century fashionable body shape has been organized and the parametric model of historical dress form has been generated. Findings The digital replica of deformable parametric dress form was created automatically in accordance with the historical sizing systems and the corsets construction. The process of reproduction of a historical dress form has been done with high accuracy due to substantial advantages of contemporary software. Originality/value This study shows new way of anthropometric data generating from the construction of close-fitting and compression undergarments. The developed method and the new database can be applied for each type of dress forms which were used in the second part of the nineteenth century to generate its digital replica in virtual reality. The new approach is joining the digital technologies and the professional knowledge as an important part of cultural heritage for studying, recreating and presenting historical costume.

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3

Clubine-Ito, Christopher. "Multilevel Modeling for Historical Data." Historical Methods: A Journal of Quantitative and Interdisciplinary History 37, no. 1 (January 1, 2004): 5–22. http://dx.doi.org/10.3200/hmts.37.1.5-22.

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4

Parent, Eric, and Jacques Bernier. "Bayesian POT modeling for historical data." Journal of Hydrology 274, no. 1-4 (April 2003): 95–108. http://dx.doi.org/10.1016/s0022-1694(02)00396-7.

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5

Garozzo, R., F. Murabito, C. Santagati, C. Pino, and C. Spampinato. "CULTO: AN ONTOLOGY-BASED ANNOTATION TOOL FOR DATA CURATION IN CULTURAL HERITAGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W5 (August 18, 2017): 267–74. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w5-267-2017.

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This paper proposes CulTO, a software tool relying on a computational ontology for Cultural Heritage domain modelling, with a specific focus on religious historical buildings, for supporting cultural heritage experts in their investigations. It is specifically thought to support annotation, automatic indexing, classification and curation of photographic data and text documents of historical buildings. CULTO also serves as a useful tool for Historical Building Information Modeling (H-BIM) by enabling semantic 3D data modeling and further enrichment with non-geometrical information of historical buildings through the inclusion of new concepts about historical documents, images, decay or deformation evidence as well as decorative elements into BIM platforms. CulTO is the result of a joint research effort between the Laboratory of Surveying and Architectural Photogrammetry “Luigi Andreozzi” and the PeRCeiVe Lab (Pattern Recognition and Computer Vision Lab) of the University of Catania,

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6

CARVALHO, JOAQUIM, RUI L. LOPES, and JOÃO TOJO. "MODELING SETTLEMENT PATTERNS IN REAL TERRITORIES." Advances in Complex Systems 14, no. 04 (August 2011): 549–65. http://dx.doi.org/10.1142/s021952591100313x.

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This paper, describes an agent based model of the spreading of a population over a territory. The models aims at reproducing a distribution of settlements with statistical and spatial characteristics similar to a historically produced pattern. The model operates on a representation of a real territory, taking into account hydrography and relief. The two main goals are to obtain a rank size distribution of the size of settlements which corresponds to a power law (also known as the Zipf Law of settlements) and to place the settlements in the territory in patterns that are close to the real ones, in zones where settlements were the result of a long historical process. The goal of the project was to demonstrate that a set of relatively simple rules could produce a complex pattern, similar to the result of a long and complex historical process. Therefore, it is an assumed reductionist approach. Our conclusions show that a simple territorial logic, taking into account the quality of land, accessibility, population growth and migration preferences could reproduce Zipf distributions and interesting patterns of agent flow among the settlements created. However, achieving spatial patterns closer to the historical record needs an extra dimension involving field of sight. The best results were achieved by creating an artifical population which chooses to create settlements in places where a wide field of view exists of quality territory.

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7

Chang-Martínez, Laura, Jean-François Mas, Nuria Valle, Pedro Torres, and William Folan. "Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling." ISPRS International Journal of Geo-Information 4, no. 4 (September 24, 2015): 1791–812. http://dx.doi.org/10.3390/ijgi4041791.

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8

Besuievsky, Gonzalo, and Gustavo Patow. "Procedural modeling historical buildings for serious games." Virtual Archaeology Review 4, no. 9 (November 5, 2013): 160. http://dx.doi.org/10.4995/var.2013.4268.

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<p>In this paper we target the goal of obtaining detailed historical virtual buildings, like a castle or a city old town, through a methodology that facilitates their reconstruction. We allow having in a short time an approximation model that is flexible for being explored, analyzed and eventually modified. This is crucial for serious game development pipelines, whose objective is focused not only on accuracy and realism, but also on transmitting a sense of immersion to the player.</p>

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9

Nesvorný, David, Fernando Roig, and William F. Bottke. "Modeling the Historical Flux of Planetary Impactors." Astronomical Journal 153, no. 3 (February 9, 2017): 103. http://dx.doi.org/10.3847/1538-3881/153/3/103.

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10

Âgren, John. "Modeling of the Solidification Process—Historical Survey." MRS Bulletin 11, no. 5 (October 1986): 31–33. http://dx.doi.org/10.1557/s0883769400054476.

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The modeling of solidification processes is a broad field covering many different types of activities. On one level, technical aspects of casting processes are investigated by computer simulations. The modeling is then a tool for the designer and the calculations may even be integrated with a CAD/CAM system. A more fundamental level may consider how the microstructure develops during solidification and how it can be controlled. This article gives a brief historical survey of the modeling of solidification processes.A well-known rule of thumb, often given in textbooks, states that the solidification time for a simple casting is proportional to its squared volume-to-area ratio. This rule is named after Chovrinov, who verified it experimentally in 1940. The mathematical treatment of solidification, however, has a much older tradition started more than 100 year s earlier in 1831 when Lamé and Clapeyron analyzed the growth of a solid crust generated by cooling a liquid. Their analysis showed that the thickness of the solid is proportional to the square root of time, which is also the essence of Chovrinov's rule. Their basic idea was that the solidification rate was controlled by the removal of latent heat. That idea may seem quite obvious to us, but a necessary pre-equisite for it is the concept of heat as quantifiable and transportable. Actually, Fourier had made his mathematical analysis of heat propagation only 20 years earlier and had won the prize of the French Academy of Sciences in 1811 for his contribution.

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11

McCardle, Kaitlin. "Modeling historical impacts of fisheries on biomass." Nature Computational Science 1, no. 11 (November 2021): 707. http://dx.doi.org/10.1038/s43588-021-00162-4.

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12

Trofimova, Yu M. "COHESION IN COGNITIVE MODELING A HISTORICAL TEXT." Voprosy Kognitivnoy Lingvistiki, no. 1 (2019): 82–90. http://dx.doi.org/10.20916/1812-3228-2019-1-82-90.

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13

JOHNSON, C. DAVID. "Modeling Historical Ecology, Thinking about Contemporary Systems." American Anthropologist 107, no. 1 (March 2005): 96–107. http://dx.doi.org/10.1525/aa.2005.107.1.096.

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14

Hazen, G. S. "FastShip & NURBS modeling: a historical note." Computer-Aided Design 34, no. 7 (June 2002): 541–43. http://dx.doi.org/10.1016/s0010-4485(01)00123-3.

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15

Sýkora, J. "Modeling of degradation processes in historical mortars." Advances in Engineering Software 72 (June 2014): 203–12. http://dx.doi.org/10.1016/j.advengsoft.2014.01.004.

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16

Schmidt, Jochen, and Richard Dikau. "Modeling historical climate variability and slope stability." Geomorphology 60, no. 3-4 (June 2004): 433–47. http://dx.doi.org/10.1016/j.geomorph.2003.11.001.

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17

Gimmi, Urs, and Harald Bugmann. "Preface: integrating historical ecology and ecological modeling." Landscape Ecology 28, no. 5 (March 27, 2013): 785–87. http://dx.doi.org/10.1007/s10980-013-9884-y.

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18

Serkova, Vera, and Alla Safonova. "Biography as a historical problem." OOO "Zhurnal "Voprosy Istorii" 2021, no. 02 (February 1, 2021): 146–58. http://dx.doi.org/10.31166/voprosyistorii202102statyi17.

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Biography as a historical description is possible in different forms: as historical evidence, as a value or value judgment, as modeling history according to the principle “als ob” (“as if”). The latter type of biography can be accepted as a heuristic and hypothetical model of events in the absence of reliable evidence, when the biography is created from indirect sources. Modeling by the principle “als ob” was invented by Hans Feichinger, a little-known original follower of the philosophy of I. Kant.

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19

Kuzmichev, V. E., A. Yu Moskvin, and M. V. Moskvina. "Modeling of Digital Twins of Historical Fashionable Bodies." Proceedings of Higher Education Institutions. Textile Industry Technology, no. 1 (2021): 144–50. http://dx.doi.org/10.47367/0021-3497_2021_1_144.

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20

Kim, Yongku, and Hyeonjeong Kim. "Stochastic precipitation modeling based on Korean historical data." Journal of the Korean Data and Information Science Society 23, no. 6 (November 30, 2012): 1309–17. http://dx.doi.org/10.7465/jkdi.2012.23.6.1309.

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21

Malkin, Stanislav Gennadyevich. "Methodological features of asymmetric conflicts historical modeling studying." Samara Journal of Science 7, no. 2 (June 15, 2018): 215–18. http://dx.doi.org/10.17816/snv201872216.

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Анотація:

The following paper deals with methodological features of studying of empires legacy role in policy of the leading powers in the countries of the third world through a prism of asymmetric conflicts historical modeling. The author pays special attention to the role of Great Britain and the USA foreign policy course defining after World War II during Cold War in the second half of the 20th century and Global War on Terror at the beginning of the 21st century. The author pays attention to methodological traps (such as the probability of the research problem on the given variable and terminological confusion) as well as to research opportunities which are opened by such approach in the field of the historical and political analysis (for example, evolution of the international relations theory and practice in the conditions of the world order transformation after World War II). Special attention is given to the value of such methodological reception as asymmetric conflicts historical modeling in expert estimates of the leading powers foreign policy. The paper also deals with the role of expert community and academic expertize as an important component of that analytical operation which is carried out within historical simulation of the asymmetrical conflicts.

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22

Bidoki, Neda Hajiakhoond, Madeline Schiappa, Gita Sukthankar, and Ivan Garibay. "Modeling social coding dynamics with sampled historical data." Online Social Networks and Media 16 (March 2020): 100070. http://dx.doi.org/10.1016/j.osnem.2020.100070.

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23

Lulewicz, Jacob. "Radiocarbon Data, Bayesian Modeling, and Alternative Historical Frameworks." Advances in Archaeological Practice 6, no. 1 (November 15, 2017): 58–71. http://dx.doi.org/10.1017/aap.2017.29.

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ABSTRACTThis article employs comparative Bayesian chronology building to formally evaluate the quality of a legacy radiocarbon dataset from the southern Appalachian region of the southeastern United States and to interrogate the assumptions that form the basis of the extant chronological narrative for the region. By incorporating alternative assumptions into Bayesian models, a number of alternative chronological frameworks are developed and compared to one another to yield insights into the development of sociopolitical complexity across southern Appalachia between AD 600 and 1600. The treatment of alternative chronological models as working hypotheses concerning the timing, tempo, and nature of sociopolitical transformations makes use of legacy radiocarbon datasets in developing new research trajectories including the encouragement of renewed field- and lab-based investigations. As such, this article provides a case study to illustrate the value of Bayesian chronological modeling in assessing legacy radiocarbon datasets and reevaluating extant chronological frameworks. Beyond initial evaluation of extant datasets and narratives, the methods and procedures outlined below can be used to form baseline models against which newly acquired data can be formally incorporated and interpreted.

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24

Lulewicz, Jacob. "Radiocarbon Data, Bayesian Modeling, and Alternative Historical Frameworks." Advances in Archaeological Practice 6, no. 1 (December 18, 2017): 88. http://dx.doi.org/10.1017/aap.2017.36.

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25

Song, Lingguang, and Simaan M. AbouRizk. "Measuring and Modeling Labor Productivity Using Historical Data." Journal of Construction Engineering and Management 134, no. 10 (October 2008): 786–94. http://dx.doi.org/10.1061/(asce)0733-9364(2008)134:10(786).

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26

Poling, Lisa L., Nirmala Naresh, and Tracy Goodson-Espy. "Empowering Mathematicians through Modeling." Mathematics Teaching in the Middle School 24, no. 3 (November 2018): 138–46. http://dx.doi.org/10.5951/mathteacmiddscho.24.3.0138.

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27

Clark, Martyn P., Marc F. P. Bierkens, Luis Samaniego, Ross A. Woods, Remko Uijlenhoet, Katrina E. Bennett, Valentijn R. N. Pauwels, Xitian Cai, Andrew W. Wood, and Christa D. Peters-Lidard. "The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism." Hydrology and Earth System Sciences 21, no. 7 (July 11, 2017): 3427–40. http://dx.doi.org/10.5194/hess-21-3427-2017.

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Abstract. The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

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28

Kaniyamattam, Karun. "71 Agent-Based Modeling: A Historical Perspective and Comparison to Other Modeling Techniques." Journal of Animal Science 100, Supplement_3 (September 21, 2022): 32–33. http://dx.doi.org/10.1093/jas/skac247.062.

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Abstract The earliest known history of agent-based modeling (ABM) is traced back to Von Neumann’s self-reproducing cellular automata, designed in the 1940s. The usage of ABM in different scientific fields accelerated in the 1990s, supported by the phenomenal increase in computing capabilities. ABM is gaining acceptance in animal systems, as daily decision-making is becoming complex due to multiple competing outcomes of interest to food systems stakeholders. ABM typically replicates complex real-world systems, for example, a herd of animals that dynamically interact based on simple rules. ABM simulate the heterogenous, stochastic characteristics of agents observed in the real-world. The dynamic interaction of agents replicates the observable real-world complex system patterns. Application of ABM in animal systems ranges from modeling cell behavior, precision nutrition and herd management to predicting the spread of epidemics, and food animal supply chain optimization. Animal science's most widely used alternative modeling techniques include system dynamic models, differential equations-based models, and statistical modeling. The list of unrealistic assumptions that limit the utility of these modeling techniques includes the assumptions of linearity, homogeneity, normality, and stationarity. The advantageous characteristics of an agent in ABM that set it apart from other techniques include being identifiable, capable of existing in an environment where it interacts with other agents while being autonomous and self-directed, goal-oriented behavior, flexible learning, and capability of adaptations in its behavior over time, based on experience. Identifying the purpose of the model, the questions the model will answer, and the potential users are the key decision variables modelers should ponder upon before embarking on building ABM. The commonly used ABM software includes Repast, Swarm, Netlogo, and MASON. Developing an ABM has several highly interleaved stages: concept development, requirements definition, design, implementation, and operationalization, each of which will be illustrated during the hands-on training session on ABM.

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29

TSUTSUI, Hiroaki, Atsushi KUROSAKI, and Tomohiko SATO. "Nonlinear Modeling Technique Using Historical Data for Case TCBM: Topological Case Based Modeling." Transactions of the Society of Instrument and Control Engineers 33, no. 9 (1997): 947–54. http://dx.doi.org/10.9746/sicetr1965.33.947.

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30

Shpirko, Sergey. "Probabilistic approach to modeling historical settlement systems: traditional view." Историческая информатика, no. 4 (April 2021): 79–86. http://dx.doi.org/10.7256/2585-7797.2021.4.36618.

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In the process of studying the systems of historical settlement, researchers are increasingly drawing on ideas and methods of mathematical modeling. The most popular - the probabilistic approach - is based on the idea that a random factor plays a predominant role in the process of spatial distribution of the population. In particular, according to the widely used Poisson model, events involving the emergence of new (and the disappearance of old) settlements on disjoint sites and time intervals are independent of each other, and the probability of two or more such events at one site is extremely small (the corresponding random variable is distributed according to Poisson's law). The purpose of this article is to familiarize the reader with the basic traditional principles of this approach, with the features of its methodology, current limits and possible new horizons for probabilistic modeling of historical settlement systems. To do this, our paper examines two studies, foreign and domestic, devoted to modeling the systems of historical settlement of different eras. In particular, it is pointed to the critical dependence of the approach, presented in these studies, on the scale and uniformity of the conditions of the territory under consideration. The way out of this situation is presented to the author of this paper by involving new types of data from historical sources for modeling, revising and rejecting unnecessary assumptions about the specific nature of the settlement process.

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31

Аникеева, Ольга, and Olga Anikyeyeva. "Development of Socio-Historical Models as a Cognitive Process: A Cross-Disciplinary Analysis." Servis Plus 8, no. 2 (June 3, 2014): 4–9. http://dx.doi.org/10.12737/3886.

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The article analyses the problems of modeling as a means of socio-historical cognition. The major discrepancy lies in the fact that the practice of cognition, as well as change-oriented activity, frequently employ modeling, while the principles and methods of model-development have not been clearly defined. The article considers the correlation between modeling and the conventional methods of historical research, and identifies the common and specific aspects of their implementation, the peculiarities of socio-historical modeling and its Junctions. Modern science regards a model as analogous to a protoimage (a fact, an event, a process), its symbolic representation, or an idealized pattern (actions, behavior). The article highlights the basic principles underlying the development of socio-historical models: a model is representational (reflecting the ontologicalfeatures of the protoimage), relevant, both conditional and autonomous, moreover, a model has its individual life cycle, with the existence and development of the model determined by its cognitive value. Modeling as a cognitive method emerged in response to the new perspective which viewed socio-historical processes as products of the meaningful activity of the agent. One of the most significant constituents of the model is its axiological motivation, which reflects the axiological system and the ideology immanent to the protoimage, and, thus, accounts for both the specifics and the essence of modeling. Another peculiarity and forte of modeling is the possibility and tolerance of the quantification of socio-historical processes, that is, translating qualitative characteristics onto the quantitative plane and developing mathematical models which lend themselves to mathematical study and interpretation, reducing ideological and axiological influences.

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32

Yakar, M., M. Uysal, A. S. Toprak, and N. Polat. "3D MODELING OF HISTORICAL DOGER CARAVANSARIES BY DIGITAL PHOTOGRAMMETRY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W2 (July 22, 2013): 695–98. http://dx.doi.org/10.5194/isprsarchives-xl-5-w2-695-2013.

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33

Mec, Pavel, Jana Daňková, and Tereza Murínová. "Modeling of Historical Timber Roof Truss of Želiv Monastery." Advanced Materials Research 688 (May 2013): 201–6. http://dx.doi.org/10.4028/www.scientific.net/amr.688.201.

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Historical timber roof trusses are illustration of carpentry skills of an old era. Complexity of created structures is problem even in nowadays full usage of computer aided design. Especially in area of modeling joints and interaction of structural elements are ambiguities and inaccurate interpretations. The above issue is illustrated on 300 years old timber roof truss in Želiv monastery. The structure is Queen post shape with main trusses and secondary trusses. Especially static modeling of main trusses is problematic and difficult with utilization of beam or truss elements. Complex static model shows stiffness properties of joints as well as resistance of the whole truss structure against to climate loads and loads from rehabilitation intervention like replacement of roofing.

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34

Herold, Hendrik, Martin Behnisch, Robert Hecht, and Stefan Leyk. "Geospatial Modeling Approaches to Historical Settlement and Landscape Analysis." ISPRS International Journal of Geo-Information 11, no. 2 (January 19, 2022): 75. http://dx.doi.org/10.3390/ijgi11020075.

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Landscapes and human settlements evolve over long periods of time. Land change, as one of the drivers of the ecological crisis in the Anthropocene, therefore, needs to be studied with a long-term perspective. Over the past decades, a substantial body of research has accumulated in the field of land change science. The quantitative geospatial analysis of land change, however, still faces many challenges; be that methodological or data accessibility related. This editorial introduces several scientific contributions to an open-access Special Issue on historical settlement and landscape analysis. The featured articles cover all phases of the analysis process in this field: from the exploration and geocoding of data sources and the acquisition and processing of data to the adequate visualization and application of the retrieved historical geoinformation for knowledge generation. The data used in this research include archival maps, cadastral and master plans, crowdsourced data, airborne LiDAR and satellite-based data products. From a geographical perspective, the issue covers urban and rural regions in Central Europe and North America as well as regions subject to highly dynamic urbanization in East Asia. In the view of global environmental challenges, both the need for long-term studies on land change within Earth system research and the current advancement in AI methods for the retrieval, processing and integration of historical geoinformation will further fuel this field of research.

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35

Stein, Peter J. "Modeling thermal fracturing of sea ice, a historical view." Journal of the Acoustical Society of America 138, no. 3 (September 2015): 1744. http://dx.doi.org/10.1121/1.4933500.

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36

Rodi, Wolfgang. "Turbulence Modeling and Simulation in Hydraulics: A Historical Review." Journal of Hydraulic Engineering 143, no. 5 (May 2017): 03117001. http://dx.doi.org/10.1061/(asce)hy.1943-7900.0001288.

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37

McElvenny, James. "Evaluating Cartesian Linguistics: From historical antecedents to computational modeling." Historiographia Linguistica 42, no. 1 (May 26, 2015): 169–72. http://dx.doi.org/10.1075/hl.42.1.10mce.

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38

Kai, Sheng, Liu Zhong, and Zhou Dechao. "Modeling Historical Trajectory Data Based on Multi-Sensors Environment." Journal of Computational and Theoretical Nanoscience 14, no. 5 (May 1, 2017): 2457–64. http://dx.doi.org/10.1166/jctn.2017.6017.

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39

Lahmiri, Salim. "Modeling and predicting historical volatility in exchange rate markets." Physica A: Statistical Mechanics and its Applications 471 (April 2017): 387–95. http://dx.doi.org/10.1016/j.physa.2016.12.061.

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40

Egger, C., A. Scheidegger, P. Reichert, and M. Maurer. "Sewer deterioration modeling with condition data lacking historical records." Water Research 47, no. 17 (November 2013): 6762–79. http://dx.doi.org/10.1016/j.watres.2013.09.010.

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41

Molinié, Philippe. "Modeling static charge dissipation on solids: An historical perspective." Journal of Electrostatics 71, no. 3 (June 2013): 591–96. http://dx.doi.org/10.1016/j.elstat.2012.12.001.

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42

Adegbola, A. A. "Historical rainfall-runoff modeling of river Ogunpa, Ibadan, Nigeria." Indian Journal of Science and Technology 5, no. 5 (May 20, 2012): 1–4. http://dx.doi.org/10.17485/ijst/2012/v5i5.5.

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43

Heymann, Matthias, and Amy Dahan Dalmedico. "Epistemology and Politics in Earth System Modeling: Historical Perspectives." Journal of Advances in Modeling Earth Systems 11, no. 5 (May 2019): 1139–52. http://dx.doi.org/10.1029/2018ms001526.

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44

Nisticò, N., S. Gambarelli, A. Fascetti, and G. Quaranta. "Experimental Dynamic Testing and Numerical Modeling of Historical Belfry." International Journal of Architectural Heritage 10, no. 4 (January 23, 2015): 476–85. http://dx.doi.org/10.1080/15583058.2014.1003622.

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45

McDonald, Cory P., Noel R. Urban, and Colin M. Casey. "Modeling historical trends in Lake Superior total nitrogen concentrations." Journal of Great Lakes Research 36, no. 4 (December 2010): 715–21. http://dx.doi.org/10.1016/j.jglr.2010.07.008.

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46

Jaquette, Matthew, Andrew J. Sánchez Meador, David W. Huffman, and Matthew A. Bowker. "Mid-Scale Drivers of Variability in Dry Mixed-Conifer Forests of the Mogollon Rim, Arizona." Forests 12, no. 5 (May 14, 2021): 622. http://dx.doi.org/10.3390/f12050622.

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The structure and composition of southwestern dry mixed-conifer forests have changed significantly, decreasing forest resiliency to uncharacteristic disturbances which also threaten ecosystem services. Restoration of these forests can be informed by historical conditions; however, managers and researchers still lack a full understanding of how environmental factors influence forest conditions. We investigated historical and contemporary variability in dry mixed-conifer forests in northern Arizona and identified important environmental drivers. We utilized forest sample plots and dendrochronological reconstruction modelling to describe forest conditions in 1879 and 2014, respectively. We used correlogram analysis to compare spatial autocorrelation of average diameter, basal area and tree density, and structural equation modeling to partition the causal pathways between forest structure, forest composition, and a suite of environmental factors reflecting climate, topography, and soil. Historical (1879) reconstructed forests had significantly fewer trees, lower basal area, and higher average diameter than contemporarily (2014). Composition has shifted from ponderosa pine dominance towards a more mixed-species composition. Historically, forest structure did not exhibit strong spatial autocorrelation, but contemporary tree density and diameter were strongly autocorrelated. Environmental factors described little variation in historical forest conditions but are more important for contemporary conditions. Managers can utilize this increased understanding of variation to tailor silvicultural prescriptions to environmental templates.

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47

Plehkanovska, Alla Myxajlivna. "METHOD OF DISTANCES OF THE HISTORICAL CITY HISTORY HISTORICAL AND ARCHITECTURAL POTENTIAL." GEOGRAPHY AND TOURISM, no. 49 (2019): 90–108. http://dx.doi.org/10.17721/2308-135x.2019.49.90-108.

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Goal. The article presents the author's method for differentiating the territory of the city according to its historical and architectural potential, in order to determine the most investment-attractive sites for the placement of tourist infrastructure objects. Method. Historical, grapho-analytical methods of research, methods of mathematical modeling and method of expert evaluation were used. Using the historical method, the presence of cultural heritage objects within the settlement is established and a historical and architectural support plan is developed. With the help of the grapho-analytical method and mathematical modeling, a qualimetric assessment of the quality of the placement of cultural heritage objects in the planning structure of the city is determined. Taking into account their importance, obtained on the basis of expert evaluation, the historical and architectural potential of the city’s territories and their investment attractiveness for locating various functional objects, in particular, tourist infrastructure objects, is determined. Results. A new method of qualitative and quantitative assessment of the historical and architectural potential of the territory of a small historical city has been developed. Scientific novelty. A new grapho-analytical method has been developed for the qualimetric assessment of the territory of a historical settlement according to its historical and architectural potential, taking into account the spatial localization and significance of cultural heritage sites. A generalized quantitative assessment of the historical settlement on the nature of the placement of cultural heritage in its planning structure is proposed. Practical significance. The application of the method will allow for the establishment of the most investment-attractive territories of the historical city in order to develop a system of tourist infrastructure facilities, reconstruction and new construction of objects of various functional purposes. Testing is performed on the example of the city of Tulchin, Vinnitsa region, Ukraine.

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48

Kheyroddin, A., M. H. Saghafi, and S. Safakhah. "Strengthening of Historical Masonry Buildings with Fiber Reinforced Polymers (FRP)." Advanced Materials Research 133-134 (October 2010): 903–10. http://dx.doi.org/10.4028/www.scientific.net/amr.133-134.903.

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The historical masonry buildings form widespread spectrum of existing buildings in IRAN. destruction on structures illustrate that historical masonry buildings have maximum damages due earthquake, in addition they don't actuate properly about seismic behavior (the main reason of this is lack of proper ductility). Shear of the masonry walls, is the only structural element of these type buildings, undertake gravity load and lateral load. This is the main reason that leads to researchers think over techniques about improvement and strengthening the walls, and also leads to experiencing real samples and scaled models. In this essay, at the beginning was introduced a method about modeling finite elements unreinforced masonry (URM) wall by using of software (ANSYS). In order to verifying the correctness of modeling, it's require to do experimental test on a sample of wall and then that wall should be modeled by illustrated method. Then correctness of modeling method and analyzing method should be verified by comparing the result of numerical modeling with the result of modeling experimental. The experimental model has been examined at Shiraz University. The result of numerical modeling and analyzing illustrate that lateral load-displacement curve is stiffer than experimental curve. And lateral load carrying capacity has precision about 99.28 percent, and lateral displacement has precision about 94.1 percent. also the numerical results agree reasonably well with the experimental results. In the next stage the masonry walls are strengthened with Carbon Fiber Reinforced Polymer sheets (CFRPs). five different strengthening methods have been used with different thickness. The strengthened walls are affected by vertical loads and in-plane shear. It is found that the critical loads, the critical displacement, the ultimate loads, the ultimate displacements and the ductile coefficients of the masonry walls strengthened with CFRPs improve remarkably.

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49

Petitot, Jean. "Dynamical modeling and morphological analysis." Behavioral and Brain Sciences 21, no. 5 (October 1998): 649. http://dx.doi.org/10.1017/s0140525x98461739.

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After a historical sketch of the dynamical hypothesis, we stress that it is a functionalist hypothesis. We then tackle the point of a dynamical approach to constituent structures and emphasize that dynamical modeling must be coupled with morphological analysis.

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50

Seok, Juheon, B. Wade Brorsen, and Bart Niyibizi. "Modeling calendar spread options." Agricultural Finance Review 78, no. 5 (October 1, 2018): 551–70. http://dx.doi.org/10.1108/afr-09-2017-0088.

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Purpose The purpose of this paper is to derive a new option pricing model for options on futures calendar spreads. Calendar spread option volume has been low and a more precise model to price them could lead to lower bid-ask spreads as well as more accurate marking to market of open positions. Design/methodology/approach The new option pricing model is a two-factor model with the futures price and the convenience yield as the two factors. The key assumption is that convenience follows arithmetic Brownian motion. The new model and alternative models are tested using corn futures prices. The testing considers both the accuracy of distributional assumptions and the accuracy of the models’ predictions of historical payoffs. Findings Panel unit root tests fail to reject the unit root null hypothesis for historical calendar spreads and thus they support the assumption of convenience yield following arithmetic Brownian motion. Option payoffs are estimated with five different models and the relative performance of the models is determined using bias and root mean squared error. The new model outperforms the four other models; most of the other models overestimate actual payoffs. Research limitations/implications The model is parameterized using historical data due to data limitations although future research could consider implied parameters. The model assumes that storage costs are constant and so it cannot separate between negative convenience yield and mismeasured storage costs. Practical implications The over 30-year search for a calendar spread pricing model has not produced a satisfactory model. Current models that do not assume cointegration will overprice calendar spread options. The model used by the Chicago Mercantile Exchange for marking to market of open positions is shown to work poorly. The model proposed here could be used as a basis for automated trading on calendar spread options as well as marking to market of open positions. Originality/value The model is new. The empirical work supports both the model’s assumptions and its predictions as being more accurate than competing models.

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