Relevant bibliographies by topics / Mathematical modeling - science

Academic literature on the topic 'Mathematical modeling - science'

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Published: 26 July 2024

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Journal articles on the topic "Mathematical modeling - science"

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Abdimurotovna, Nigora Kholmirzayeva. "SPECIFIC CHARACTERISTICS OF THE APPLICATION OF MATHEMATICAL MODELING IN SOIL SCIENCE." European International Journal of Multidisciplinary Research and Management Studies 02, no. 09 (September 1, 2022): 112–16. http://dx.doi.org/10.55640/eijmrms-02-09-25.

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The article talks about the use of mathematical modeling in the field of soil science. Empirical, semi-empirical, theoretical models are used in soil science, as well as their specific features. An overview, advantages and disadvantages of empirical, semi-empirical and theoretical models are analyzed. Necessary formulas and algorithms for mathematical modeling of heat transfer in the soil are compiled and their features are described.
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Casetti, Emilio. "SPATIAL MATHEMATICAL MODELING AND REGIONAL SCIENCE." Papers in Regional Science 74, no. 1 (January 14, 2005): 3–11. http://dx.doi.org/10.1111/j.1435-5597.1995.tb00625.x.

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Ash, C. "Mathematical modeling of infectious diseases." Science 347, no. 6227 (March 12, 2015): 1213. http://dx.doi.org/10.1126/science.347.6227.1213-j.

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Szekely, Julian. "Mathematical Modeling in Materials Science and Engineering." MRS Bulletin 19, no. 1 (January 1994): 11–13. http://dx.doi.org/10.1557/s0883769400038793.

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During the past two decades, mathematical modeling has been gaining acceptance as a legitimate part of materials science and engineering. However, as common to all relatively new disciplines, we still lack a realistic perspective regarding the uses, limitations, and even the optimal methodologies of mathematical modeling techniques.The term “mathematical modeling” covers a broad range of activities, including molecular dynamics, other atomistic scale systems, continuum fluid and solid mechanics, deformation processing, systems analysis, input-output models, and lifecycle analyses. The common point is that we use algebraic expressions or differential equations to represent physical systems to varying degrees of approximation and then manipulate these equations, using computers, to obtain graphical output.While it is becoming an accepted fact that some kind of mathematical modeling will be needed to make most research programs complete, there is still considerable ambiguity as to what form this should take and what might be the actual usefulness of such an effort.Among the more seasoned and successful practitioners of this art, clear guidelines have emerged regarding the uses and limitations of the mathematical modeling approach. We seek to illustrate these uses through the successful modeling examples presented by some leading practitioners. Some general principles may be worth repeating as an introduction to this interesting collection of articles.
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Weigend, Michael. "Mathematical Modeling and Programming in Science Education." Computer Tools in Education, no. 2 (June 28, 2019): 55–64. http://dx.doi.org/10.32603/2071-2340-2019-2-55-64.

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Gelrud, Yakov D., and Lyudmila I. Shestakova. "Fundamentals of mathematical modeling in political science." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 22, no. 1 (January 2022): 116–24. http://dx.doi.org/10.14529/ctcr220110.

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Political processes are a complex system of organizational type. In this article, we are considering certain aspects, which stem from the principle of the system approach and are directly related to management of complex organizational systems. At the same time, the main attention is paid to the close connection of the principle of the system approach and the mathematical modeling of the systems of orga¬nizational management. Goals and objectives. The main goal of the article is to consider the ideas of the system approach, which imply the focus of attention on the quality and properties inherent to the system in general. The behavior of separate elements of the system is analyzed only in the context in which these are related to the achievement of the goal and to the effectiveness of the system’s functioning on the whole. Mathematical modeling ensures the fulfillment of the system approach for management organization taking into account the feedback principle. Methods. Mathematical model allows to form a logically harmonious formalized description of the managerial tasks. The following elements of decision-making are distinguished in the formal structure: goals, controllable variables, external variables, uncontrolled parameters, limitations, decision, efficiency criterion. The development of a mathematical model includes the determi¬ning of the interrelations between all the elements of the formal structure of the task and portraying them as mathematical expressions (equations, inequalities, etc.). Results. The article presents a decomposition of the process of developing a managerial solution comprising the following stages: verbal task setting (problem statement), forming of a mathematical model, task solving, solution analysis, model correction (if necessary) and finding a corrected solution, implementation of the final decision made in the management practice. In the end of the article, we consider an example of solving a managerial task in accordance with all the listed stages. Conclusion. The use of mathematical modeling and methods of solving managerial tasks in professional activity of a political figure allows to improve the effectiveness of the decisions made by this person and provides him/her with communication means, thanks to using the professional language of mathematics.
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Il’in, V. P. "Mathematical Modeling and the Philosophy of Science." Herald of the Russian Academy of Sciences 88, no. 1 (January 2018): 81–88. http://dx.doi.org/10.1134/s1019331618010021.

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Abiad, Fouad. "Mathematical Modeling of the Strategy of the Early Islamic Wars." International Journal of Social Science Research and Review 3, no. 1 (March 10, 2020): 1–14. http://dx.doi.org/10.47814/ijssrr.v3i1.29.

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A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in the natural sciences (such as physics, biology, earth science, chemistry) and engineering disciplines (such as computer science, electrical engineering), as well as in the social sciences (such as economics, psychology, sociology, political science).The main activities involved in this procedure are observation followed by mathematical modeling; simulation, analysis, optimization and back to observation, Mathematics has been applied to all sciences; and religious and military sciences are no exception, and mathematics can be used highly to design different war operations and solve battlefield equations to gain relative or absolute superiority over the enemy. We can also see clearly the application of mathematics in the Game Theory of war in abundance. In this applied research, conducted in a library method, the challenges between the army of Amir al-Mu’minin, ʿAlī ibn Abī Ṭālib (as), and the army of Muʿāwiya ibn Abī Sufyān in the Battle of Siffin have been modeled using Game Theory and the strategies of each of these two fronts are compared.
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Dibdin, George H. "Mathematical Modeling of Biofilms." Advances in Dental Research 11, no. 1 (April 1997): 127–32. http://dx.doi.org/10.1177/08959374970110010301.

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A set of mathematical equations constitutes a mathematical model if it aims to represent a real system and is based on some theory of that system's operation. On this definition, mathematical models, some very simple, are everywhere in science. A complex system like a biofilm requires modeling by numerical methods and, because of inevitable uncertainties in its theoretical basis, may not be able to make precise predictions. Nevertheless, such models almost always give new insight into the mechanisms involved, and stimulate further investigation. The way in which diffusion coefficients are measured for use in a model, particularly whether they include effects of reversible reaction, is a key element in the modeling. Reasons are given for separating diffusion from reversible reaction effects and dealing with them in a separate subroutine of the model.
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Pandey, Hemant, and Romi Bala. "Mathematical Approaches to Network Science: Modeling and Analysis." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 11, no. 1 (April 30, 2020): 1668–73. http://dx.doi.org/10.61841/turcomat.v11i1.14629.

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Network science, a multidisciplinary field, employs mathematical approaches to model and analyze complex systems as networks or graphs. This paper provides an overview of the fundamental concepts, mathematical modeling techniques, analysis methods, and applications of network science. It emphasizes the importance of mathematical approaches in understanding the structure and dynamics of networks in various domains, including social, biological, and technological networks. The paper also discusses challenges such as scalability and incorporating dynamics, along with future research directions. Overall, mathematical approaches are essential for advancing network science and unlocking new insights into complex systems.
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Dissertations / Theses on the topic "Mathematical modeling - science"

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Gupta, Shailesh. "Mathematical Modeling of Thin Strip Casting Processes." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1391679731.

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Ramírez, Marco Aurelio (Ramírez-Argáez) 1970. "Mathematical modeling of D.C. electric arc furnace operations." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8847.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2000.
Vita.
Includes bibliographical references (leaves 236-240).
A fundamental study of the Direct Current Electric Arc Furnace (DC-EAF) for steel-making has been carried out through the development of a rigorous mathematical model. The mathematical representation involves the simultaneous solution of Maxwell's equations for the electromagnetic fields, and the turbulent fluid flow and heat transfer equations. In solving the arc and bath regions it was assumed ( and justified) that the arc-bath interactions are dominated by the behavior of the arc. In contrast to previous modeling investigations, this work relaxes some critical assumptions and provides a more realistic and comprehensive representation of the system. This work also examines and compares the relative merits of alternative electromagnetic and turbulence formulations, and addresses the role of induced currents and compressibility effects in the representation of the arc. Furthermore, due allowance was made to represent and analyze the effect of gas injection, the presence of a slag layer in the bath and changes in anode configuration at the bottom of the reactor. Because of a lack of experimental information on actual or pilot plant DC-EAF systems, different aspects of the model were validated using several sources of experimental data reported in the literature for related systems. These included measurements on welding arcs, laboratory scale high-intensity carbon arcs, electromagnetically driven metallic systems, and ladle metallurgy physical models. It was found that, in general, the agreement between measurements and predictions was good. A detailed analysis was carried out to examine the effect of process parameters (e.g., arc current, arc length, bath dimensions, anode arrangements, etc) on the behavior of the furnace (e.g., heat transfer to the bath, heating efficiency, mixing times in the bath, etc). Predictions from the arc model show that all the arc characteristics are strongly coupled and that the arc physics is governed by the expansion of the arc. From a parametric study it was found that when the arc region (defined by the 10,000 K isotherm) is plotted in dimensionless form, a universal shape for the arc can be defined, regardless of the values of arc current or arc length. This universality was restricted to the range of conditions analyzed in this thesis, to arcs struck between graphite cathodes in air, and does not include the jet impingement region on the bath surface. This common arc expansion behavior suggested the universal nature of other arc characteristics. Universal maps of temperature, magnetic: flux density, and axial velocity are also reported in terms of simple analytical expressions. The practical effects of the two main process parameters of the arc region,. i.e. the arc current and the arc length, were analyzed. It was found that increasing the arc length significantly increases the arc resistance and, consequently, the arc power, although this behavior reached asymptotic values at larger arc lengths. Increasing the arc current, however, does not affect the arc voltage. Thus, it is found that increasing the arc power increases the amount of energy transferred into the bath, but the heat transfer efficiency decreases. Therefore, the shorter the arc the more efficient is the heat transfer to the bath. It is also recognized that heat transfer from the arc to the bath is controlled by convection, although radiation can become an important mechanism, especially for large arc lengths. Results of the bath model indicate that, in the absence of inert gas stirring and with no slag present in the system, electromagnetic body forces dominate and are responsible for the fluid flow patterns in the system. The effects of the arc determine the distributions of temperature and other mixing characteristics in the bath. The bath model was used to evaluate the effect of the main process parameters and design variables on mixing, refractory wear, temperature stratification, and heat transfer efficiency. An increase in the arc length is detrimental to mixing but increases the rate of heating in the melt as a result of the increased arc power. Increasing arc current improves mixing and the heat transferred to the bath, but is likely to be detrimental to the life of the bottom refractory. The results also suggest that high furnace aspect ratios (taller and thinner arc furnaces) are highly recommended because an increase in the aspect ratio increases mixing, prevents refractory wear, and promotes arc heating efficiency. The arc configuration in the furnace can be changed to control fluid flow patterns in the bath to meet specific needs, such as better mixing, or to prevent refractory wear. The presence of a top layer of slag reduces mixing and increases overall liquid temperatures. Injection of gases through the bottom in eccentric operations generates complex flow patterns that improve mixing in regions away from the symmetry axis. It is the author's belief that this model is a useful tool for process analysis in the DC-EAF. It has the capability to address many issues of current and future concern and represents one component of a fundamental approach to the optimization of DC-EAF operations.
by Marco Aurelio Ramírez.
Ph.D.
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Weens, William. "Mathematical modeling of liver tumor." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00779177.

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Comme démontre récemment pour la régénération du foie après un dommage cause par intoxication, l'organisation et les processus de croissance peuvent être systématiquement analyses par un protocole d'expériences, d'analyse d'images et de modélisation [43]. Les auteurs de [43] ont quantitativement caractérise l'architecture des lobules du foie, l'unité fonctionnelle fondamentale qui constitue le foie, et en ont conçu un modèle mathématique capable de prévoir un mécanisme jusqu'alors inconnu de division ordonnée des cellules. La prédiction du modèle fut ensuite validée expérimentalement. Dans ce travail, nous étendons ce modèle a l'échelle de plusieurs lobules sur la base de résultats expérimentaux sur la carcinogène dans le foie [15]. Nous explorons les scénarios possibles pouvant expliquer les différents phénotypes de tumeurs observés dans la souris. Notre modèle représente les hépatocytes, principal type de cellule dans le foie, comme des unités individuels avec un modèle a base d'agents centré sur les cellules et le système vasculaire est représenté comme un réseau d'objets extensibles. L'équation de Langevin qui modélise le mouvement des objets est calculée par une discrétisation explicite. Les interactions mécaniques entre cellules sont modélisées avec la force de Hertz ou de JKR. Le modèle est paramètre avec des valeurs mesurables a l'échelle de la cellule ou du tissue et ses résultats sont directement comparés avec les résultats expérimentaux. Dans une première étape fondamentale, nous étudions si les voies de transduction du signal de Wnt et Ras peuvent expliquer les observations de [15] où une prolifération instantanée dans les souris mutées est observée seulement si 70% des hépatocytes sont dépourvues d'APC. Dans une deuxième étape, nous présentons une analyse de sensibilité du modèle sur la rigidité de la vasculature et nous la mettons en relation avec un phénotype de tumeur (observe expérimentalement) où les cellules tumorales sont bien différentiées. Nous intégrons ensuite dans une troisième 'étape la destruction de la vasculature par les cellules tumorales et nous la mettons en relation avec un autre phénotype observe expérimentalement caractérise par l'absence de vaisseaux sanguins. Enfin, dans la dernière étape de notre étude nous montrons que des effets qui sont détectables dans les petits nodules tumoraux et qui reflètent les propriétés des cellules tumorales, ne sont plus présents dans la forme ou dans le phénotype des tumeurs d'une taille excédant la moitié de celle d'un lobule.
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Badekas, Paris. "Mathematical modeling of en route ATC intervention rates." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14746.

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Deering, Scott E. (Scott Earl) 1967. "Mathematical and physical modeling of flip-chip soldering processes." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11115.

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Saxena, Amit. "Mathematical modeling of horizontal twin roll thin strip casting process." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1392309532.

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Groshong, Kimberly A. "Defining mathematical modeling for K-12 education." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1534374871189434.

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Muthukumaran, Arun. "Foam-mat freeze drying of egg white and mathematical modeling." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=18301.

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Eggs are a rich source of high-quality proteins as they contain all amino acids necessary for the human body. They also contain all vitamins (except for vitamin C) and many essential minerals. Eggs mainly consist of egg white (albumen) and egg yolk. Egg white is mainly made up of proteins and has excellent foaming properties; it is widely used in the baking and confectionary industries (e.g., cake mixtures, meringue). Dehydration is widely used for the preservation of egg. Dehydrated egg products usually have a shelf life of one year under refrigeration. Spray drying and pan drying are widely used for producing egg powder. The higher drying temperature associated with these drying methods could adversely affect the nutritional value of egg. Freeze drying is well known for its excellent dehydrated product quality. The high cost of operation associated with freeze drying restricts its usage to high value products like coffee. Foam-mat drying can be used for the products that can be foamed to increase the surface area to improve the mass transfer rate. But the higher drying temperature involved in this method is not suitable for producing a high quality dehydrated product. Foam-mat freeze drying is one of the promising methods of drying, which tries to utilize the advantages of both freeze drying and foam-mat drying to produce better quality egg white powder. Preliminary experiments showed that the stability of foams made with egg white alone is not adequate for foam-mat freeze drying. Experiments were thus conducted using different stabilizers (Methyl cellulose, Propylene glycol alginate and Xanthan gum) to optimize foam stability. Bubble size distribution was determined using microscopy to understand foam structure. The results showed that Xanthan gum at 0.125% provide sufficient stability for freeze drying. Experiments were conducted to study foam-mat freeze drying of egg white, in an effort to determine the suitability of this method. The results showed that th
Les œufs sont une bonne source de protéines de haute qualité, puisqu’ils contiennent tous les acides aminés nécessaires au corps humain. Les œufs contiennent aussi toutes les vitamines (à l’exception de la vitamine C), ainsi que plusieurs minéraux essentiels. Les œufs sont principalement constitués de l’albumine (blanc d’œuf) ainsi que le jaune d’œuf. L’albumine est principalement consituée de protéines et a d’excellentes propriétés de moussage. Elle est utilisée à grande échelle dans les industries boulangère et de la confiserie, par exemple dans les mélanges à gâteaux et de la meringue. On utilise beaucoup la déshydratation pour préserver les oeufs. Réfrigérés, les produits d’œuf déshydraté se conservent pendant un an. Le séchage par atomisation et le séchange par conduction sont couramment utilisés pour produire de la poudre d’œuf. Par contre, les températures élevées associées à ces méthodes de séchage pourraient compromettre la valeur nutritive des œufs. La cryodessication donne un produit déshydraté de très haute qualité, mais les coûts d’opération élevés limitent son utilisation qu’aux produits de haute valeur, tel le café. Le séchage par émulsion peut être utilisé lorsque les produits à sécher peuvent mousser, ce qui accroît la surface de contact et augmente le coefficient d'échange thermique. Cependant, les températures élevées associées à cette méthode ne conviennent pas à la production d’un produit déshydraté de haute qualité. La cryodessication par émulsion est une méthode de séchage prometteuse, puisqu’elle tire des avantages liés à la cryodessication et au séchage par émulsion pour produire de la poudre d’albumine de meilleure qualité. Des essais en laboratoire ont démontré que la stabilité des mousses de blanc d’œuf ne convient pas au séchage par émulsion. Des expériences ont donc été entreprises dans le but de trouver un stabiliseu
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Kriek, Andre. "RoboCup formation modeling." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2810.

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Thesis (MSc (Mathematical Sciences. Computer Science))--University of Stellenbosch, 2009.
Since the late 1990s, the Robot Soccer World Cup has been used as a testing ground for new technology in the eld of robotic design and arti cial intelligence. This research initiative pits two teams of robots against each other in a game of soccer. It is hoped that the technology gained will enable the construction of a fully autonomous team of robot players to play a normal soccer game against a human team by the year 2050. In robot soccer matches, as in real soccer matches, inferring an opponent's strategy can give a team a major advantage. One important aspect of a team's strategy is the formation the team uses. Knowing the formations that an opposing team tends to take, enables a team to prepare appropriate countermeasures. This thesis will investigate methods to extract formation information from a completed soccer game. The results show that these methods can be used to infer a classical team formation, as well as other distinguishing characteristics of the players, such as which areas on the eld the players tend to occupy, or the players' movement patterns - both valuable items of information for a future opposition team.
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Yau, Shuk-Han Ada. "Numerical analysis of finite difference schemes in automatically generated mathematical modeling software." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35407.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
Includes bibliographical references (leaves 64-65).
by Shuk-Han Ada Yau.
M.S.
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Books on the topic "Mathematical modeling - science"

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Buckmaster, John D., and Tadao Takeno, eds. Mathematical Modeling in Combustion Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-19181-x.

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Adam, Gheorghe, Ján Buša, and Michal Hnatič, eds. Mathematical Modeling and Computational Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28212-6.

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Gang, Bao, Cowsar Lawrence, and Masters Wen, eds. Mathematical modeling in optical science. Philadelphia, Pa: Society for Industrial and Applied Mathematics, 2001.

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Herrera, Ismael, and George F. Pinder. Mathematical Modeling in Science and Engineering. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118207239.

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Glover, David M. Modeling methods for marine science. Cambridge: Cambridge University Press, 2011.

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Lesh, Richard. Modeling Students' Mathematical Modeling Competencies: ICTMA 13. Boston, MA: Springer Science+Business Media, LLC, 2010.

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Temam, Roger. Mathematical modeling in continuum mechanics. Cambridge, UK: Cambridge University Press, 2001.

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Temam, Roger. Mathematical modeling in continuum mechanics. 2nd ed. Cambridge: Cambridge University Press, 2005.

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Pravica, David W. Mathematical modeling for the scientific method. Sudbury, MA: Jones & Bartlett Learning, 2011.

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M, Farid Mohammed, ed. Mathematical modeling of food processing. Boca Raton: Taylor & Francis, 2010.

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Book chapters on the topic "Mathematical modeling - science"

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Hestenes, David. "Modeling Theory for Math and Science Education." In Modeling Students' Mathematical Modeling Competencies, 13–41. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0561-1_3.

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Arganbright, Deane E. "Mathematical Modeling with Spreadsheets." In A Computer Science Reader, 167–79. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4419-8726-6_13.

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Megowan-Romanowicz, M. Colleen. "Modeling Discourse in Secondary Science and Mathematics Classrooms." In Modeling Students' Mathematical Modeling Competencies, 341–52. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0561-1_29.

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Teixeira, A. C. S. C., A. M. Lastre Acosta, A. S. Vianna, and G. A. C. Le Roux. "Mathematical Modeling for SBO Applications." In SpringerBriefs in Molecular Science, 59–71. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14744-4_5.

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Kuneš, Josef. "Mathematical Models." In Similarity and Modeling in Science and Engineering, 131–79. Cambridge: Cambridge International Science Publishing Ltd, 2012. http://dx.doi.org/10.1007/978-1-907343-78-0_5.

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Wiechert, Wolfgang. "Teaching Mathematical Modeling: Art or Science?" In Lecture Notes in Computer Science, 858–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47789-6_89.

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Zavala, Genaro, Hugo Alarcon, and Julio Benegas. "A Professional Development Course with an Introduction of Models and Modeling in Science." In Modeling Students' Mathematical Modeling Competencies, 491–500. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0561-1_42.

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Na, Dokyun, and Doheon Lee. "Mathematical Modeling of Immune Suppression." In Lecture Notes in Computer Science, 182–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11536444_14.

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Op Den Camp, O. M. G. C., E. G. J. Peters, and V. O. Aume. "Mathematical Modeling of Forehearths." In 59th Conference on Glass Problems: Ceramic Engineering and Science Proceedings, Volume 20, Issue 1, 133–41. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2008. http://dx.doi.org/10.1002/9780470294536.ch10.

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Neuwirth, E. "Spreadsheets as Tools in Mathematical Modeling and Numerical Mathematics." In Spreadsheets in Science and Engineering, 87–113. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-80249-2_3.

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Conference papers on the topic "Mathematical modeling - science"

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Volovich, Denis, Konstantin Denisov, and Vadim Kondrashev. "EXPERIENCE OF FRC CSC RAS IN PROVIDING HPC CLOUD SERVICES FOR MATERIALS SCIENCE." In Mathematical modeling in materials science of electronic component. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1510.mmmsec-2020/26-29.

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The article presents the results of scientific research of the Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences in field of providing of cloud services for material science.
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Denisov, Sergey, and Vadim Kondrashev. "EXPERIENCE OF FRC CSC RAS IN CREATION OF HIGH-PERFORMANCE COMPUTING INFRASTRUCTURE FOR SOLVING MATERIALS SCIENCE PROBLEMS." In Mathematical modeling in materials science of electronic component. LCC MAKS Press, 2023. http://dx.doi.org/10.29003/m3578.mmmsec-2023/26-30.

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The paper presents the experience of the stage-by-stage development of high-performance computing infrastructure of the Federal Research Center Computer Science and Control of the Russian Academy of Sciences (FRC CSC RAS), which allowed the сenter's team to use modern technologies of mathematical modeling and organization of the computing process on high-performance multi-node hybrid computing clusters, and conduct research at the modern scientific and technical level.
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Abgaryan, Karine. "MATHEMATICAL MODELING OF NEUROMORPHIC SYSTEM." In Mathematical modeling in materials science of electronic component. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1518.mmmsec-2020/56-60.

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The paper deals with the creation of mathematical models for the development and optimization of the operation of neuromorphic systems. A multiscale approach based on set-theoretic representations is presented, which makes it possible to quickly develop software with a parallel computing mechanism for creating neuromorphic systems
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Chan, Kam Tong, Irwin King, and Man-Ching Yuen. "Mathematical Modeling of Social Games." In 2009 International Conference on Computational Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/cse.2009.166.

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Miao, Rong. "Applied Value of Mathematical Modeling Thought in Advanced Mathematics Teaching." In 6th International Conference on Social Science, Education and Humanities Research (SSEHR 2017). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/ssehr-17.2018.39.

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Kawata, Shigeo, Takayuki Teramoto, Hideaki Sugiura, Yuichi Saitoh, and Yoshikazu Hayase. "Mathematical Modeling Support in a Distributed Problem Solving Environment for Scientific Computing." In 2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06). IEEE, 2006. http://dx.doi.org/10.1109/e-science.2006.261182.

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"Innovative Teaching of Applied Higher Mathematics Curriculum Based on Mathematical Modeling Drive." In 2020 International Conference on Educational Science. Scholar Publishing Group, 2020. http://dx.doi.org/10.38007/proceedings.0000358.

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Kondrashev, Vadim, and Sergey Denisov. "METHODS AND ALGORITHMS FOR PARALLEL CALCULATIONS USING VIRTUALIZATION TECHNOLOGIES IN MATERIALS SCIENCE PROBLEMS." In Mathematical modeling in materials science of electronic component. LCC MAKS Press, 2021. http://dx.doi.org/10.29003/m2460.mmmsec-2021/26-30.

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The paper discusses methods and algorithms for the provision of high-performance computing resources in multicomputer systems in a shared mode for fundamental and applied research in the field of materials science. Approaches are proposed for the application of applied integrated software environments (frameworks) designed to solve material science problems using virtualization and parallel computing technologies.
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Abgaryan, Karine. "DESIGNING SOFTWARE SYSTEMS FOR MODELING IN THE MATERIAL SCIENCE OF ELECTRONIC COMPONENTS." In Mathematical modeling in materials science of electronic component. LCC MAKS Press, 2022. http://dx.doi.org/10.29003/m3069.mmmsec-2022/62-68.

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The paper considers current problems associated with the creation of new software systems in the field of material science of electronic components. Perspective approaches to construction of software systems in this field are considered. Relevance of using methods of multiscale computer modeling for studying material properties and construction of structure-property relations is noted. Main tendencies related to the development of digital modeling in materials science are listed. It is shown that development of intellectual systems in the field of material science of electronic components is one of the most important directions today. Software solutions under the management of ontologies may be used as a promising direction in the development of information support for their creation. It is noted that successes in this area will allow to achieve outstripping development not only in creation of new materials with required properties, but also in industrial production as a whole.
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Maminov, A. "MONITORING SYSTEM DESIGN IN HIGH PERFOMANCE COMPUTING CENTER FOR SOLVING MATERIAL SCIENCE PROBLEMS." In Mathematical modeling in materials science of electronic component. LCC MAKS Press, 2022. http://dx.doi.org/10.29003/m3063.mmmsec-2022/39-43.

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The paper considers methods for monitoring the workload of resources of a high-performance complex when setting computational problems of materials science in a common execution queue. Since materials science algorithms can be effectively run in parallel and are demanding on computing resources, there is a need to use supercomputer systems. However, inefficient use of resources significantly increases the estimated time of tasks. We propose to implement a monitoring system for subsequent analysis of allocated computing resources.
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Reports on the topic "Mathematical modeling - science"

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Markova, Oksana, Serhiy Semerikov, and Maiia Popel. СoCalc as a Learning Tool for Neural Network Simulation in the Special Course “Foundations of Mathematic Informatics”. Sun SITE Central Europe, May 2018. http://dx.doi.org/10.31812/0564/2250.

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The role of neural network modeling in the learning сontent of special course “Foundations of Mathematic Informatics” was discussed. The course was developed for the students of technical universities – future IT-specialists and directed to breaking the gap between theoretic computer science and it’s applied applications: software, system and computing engineering. CoCalc was justified as a learning tool of mathematical informatics in general and neural network modeling in particular. The elements of technique of using CoCalc at studying topic “Neural network and pattern recognition” of the special course “Foundations of Mathematic Informatics” are shown. The program code was presented in a CofeeScript language, which implements the basic components of artificial neural network: neurons, synaptic connections, functions of activations (tangential, sigmoid, stepped) and their derivatives, methods of calculating the network`s weights, etc. The features of the Kolmogorov–Arnold representation theorem application were discussed for determination the architecture of multilayer neural networks. The implementation of the disjunctive logical element and approximation of an arbitrary function using a three-layer neural network were given as an examples. According to the simulation results, a conclusion was made as for the limits of the use of constructed networks, in which they retain their adequacy. The framework topics of individual research of the artificial neural networks is proposed.
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Striuk, Andrii M., and Serhiy O. Semerikov. The Dawn of Software Engineering Education. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3671.

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Designing a mobile-oriented environment for professional and practical training requires determining the stable (fundamental) and mobile (technological) components of its content and determining the appropriate model for specialist training. In order to determine the ratio of fundamental and technological in the content of software engineers’ training, a retrospective analysis of the first model of training software engineers developed in the early 1970s was carried out and its compliance with the current state of software engineering development as a field of knowledge and a new the standard of higher education in Ukraine, specialty 121 “Software Engineering”. It is determined that the consistency and scalability inherent in the historically first training program are largely consistent with the ideas of evolutionary software design. An analysis of its content also provided an opportunity to identify the links between the training for software engineers and training for computer science, computer engineering, cybersecurity, information systems and technologies. It has been established that the fundamental core of software engineers’ training should ensure that students achieve such leading learning outcomes: to know and put into practice the fundamental concepts, paradigms and basic principles of the functioning of language, instrumental and computational tools for software engineering; know and apply the appropriate mathematical concepts, domain methods, system and object-oriented analysis and mathematical modeling for software development; put into practice the software tools for domain analysis, design, testing, visualization, measurement and documentation of software. It is shown that the formation of the relevant competencies of future software engineers must be carried out in the training of all disciplines of professional and practical training.
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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM). Instats Inc., 2023. http://dx.doi.org/10.61700/kwigtxevhohxk469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta-Analysis (CoTiMA) using results from multiple studies. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECTS Equivalent points for European PhD students.
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Kelic, Andjelka, and Aldo A. Zagonel. Science, Technology, Engineering, and Mathematics (STEM) career attractiveness system dynamics modeling. Office of Scientific and Technical Information (OSTI), December 2008. http://dx.doi.org/10.2172/1177094.

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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM) + 1 Free Seminar. Instats Inc., 2022. http://dx.doi.org/10.61700/am2g78fjl1gx5469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta-Analysis (CoTiMA) using results from multiple studies. To frame the seminar content, a free background seminar is provided when enrolling: Longitudinal SEM in R. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECTS Equivalent points for European PhD students.
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Perdigão, Rui A. P. New Horizons of Predictability in Complex Dynamical Systems: From Fundamental Physics to Climate and Society. Meteoceanics, October 2021. http://dx.doi.org/10.46337/211021.

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Discerning the dynamics of complex systems in a mathematically rigorous and physically consistent manner is as fascinating as intimidating of a challenge, stirring deeply and intrinsically with the most fundamental Physics, while at the same time percolating through the deepest meanders of quotidian life. The socio-natural coevolution in climate dynamics is an example of that, exhibiting a striking articulation between governing principles and free will, in a stochastic-dynamic resonance that goes way beyond a reductionist dichotomy between cosmos and chaos. Subjacent to the conceptual and operational interdisciplinarity of that challenge, lies the simple formal elegance of a lingua franca for communication with Nature. This emerges from the innermost mathematical core of the Physics of Coevolutionary Complex Systems, articulating the wealth of insights and flavours from frontier natural, social and technical sciences in a coherent, integrated manner. Communicating thus with Nature, we equip ourselves with formal tools to better appreciate and discern complexity, by deciphering a synergistic codex underlying its emergence and dynamics. Thereby opening new pathways to see the “invisible” and predict the “unpredictable” – including relative to emergent non-recurrent phenomena such as irreversible transformations and extreme geophysical events in a changing climate. Frontier advances will be shared pertaining a dynamic that translates not only the formal, aesthetical and functional beauty of the Physics of Coevolutionary Complex Systems, but also enables and capacitates the analysis, modelling and decision support in crucial matters for the environment and society. By taking our emerging Physics in an optic of operational empowerment, some of our pioneering advances will be addressed such as the intelligence system Earth System Dynamic Intelligence and the Meteoceanics QITES Constellation, at the interface between frontier non-linear dynamics and emerging quantum technologies, to take the pulse of our planet, including in the detection and early warning of extreme geophysical events from Space.
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Semerikov, Serhiy, Viacheslav Osadchyi, and Olena Kuzminska. Proceedings of the 1st Symposium on Advances in Educational Technology - Volume 2: AET. SciTePress, 2022. http://dx.doi.org/10.31812/123456789/7011.

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Symposium on Advances in Educational Technology (AET) is a peer-reviewed international conference focusing on research advances and applications of combined use of computer hardware, software, and educational theory and practice to facilitate learning. Today, AET is the premier interdisciplinary forum for learning scientists, academicians, researchers, professionals, policymakers, postgraduate students, and practitioners to present their latest research results, ideas, developments, and applications. AET topics of interest are: • Artificial intelligence in education • Augmented reality in education • Cloud-based learning environments • Cloud technologies for mathematics learning • Cloud technologies for informatics learning • Computer simulation in science and mathematics learning • ICT in primary and secondary education • ICT in higher education • Learning environments • Learning technology • Professional training in the digital space • Massive open online courses • Methodology of informatization in education • Modelling systems in education • Psychological safety in the digital educational environment • Soft skills development • STEM education • Virtualization of learning This volume represents the proceedings of the Symposium on Advances in Educational Technology, held in Kyiv, Ukraine, on November 12-13, 2020. It comprises 110 contributed papers that were carefully peer-reviewed and selected from 282 submissions. Each submission was reviewed by at least 3, and on the average 3.1, program committee members. The accepted papers present a state-of-the-art overview of successful cases and provide guidelines for future research. We are thankful to all the authors who submitted papers and the delegates for their participation and their interest in AET as a platform to share their ideas and innovation. Also, we are also thankful to all the program committee members for providing continuous guidance and efforts taken by peer reviewers contributed to improve the quality of papers provided constructive critical comments, improvements and corrections to the authors are gratefully appreciated for their contribution to the success of the workshop. Moreover, we would like to thank the developers of HotCRP, who made it possible for us to use the resources of this excellent and comprehensive conference management system, from the call of papers and inviting reviewers, to handling paper submissions, communicating with the authors, and creating the volume of the workshop proceedings.
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