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Artículos de revistas sobre el tema "Mathematical Sciences"

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Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 31 de enero de 2023

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1

Thomas, Jan, Michelle Muchatuta y Leigh Wood. "Mathematical sciences in Australia". International Journal of Mathematical Education in Science and Technology 40, n.º 1 (15 de enero de 2009): 17–26. http://dx.doi.org/10.1080/00207390802597654.

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2

Ziegel, Eric. "Handbook of Mathematical Sciences". Technometrics 31, n.º 2 (mayo de 1989): 275. http://dx.doi.org/10.1080/00401706.1989.10488546.

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3

O'Leary, D. P. y S. T. Weidman. "The interface between computer science and the mathematical sciences". Computing in Science and Engineering 3, n.º 3 (mayo de 2001): 60–65. http://dx.doi.org/10.1109/mcise.2001.919268.

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4

Zhao, Weijie. "Predicament and outlook of China's math education". National Science Review 7, n.º 9 (17 de abril de 2020): 1513–17. http://dx.doi.org/10.1093/nsr/nwaa070.

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Abstract Mathematics is the foundation of science and rational thinking. Math education for the younger generation is the fundamental project to upgrade the mathematical literacy and the creativity of the whole society. China's education system has long been different from that of Western countries. China has fostered many gold medal winners of the International Mathematics Olympiad, but is also criticized as lacking creativity. In this NSR forum on math education in China, educators of high schools and universities as well as researchers of different scientific fields gather to talk about the current predicaments and future developments of China's math education. Zenghu Li Mathematician; Professor of the School of Mathematical Sciences, Beijing Normal University, Beijing, China Chao Tang Quantitative biologist; Director of the Center for Quantitative Biology, Peking University, Beijing, China Zhihong Xia Mathematician; Professor of Mathematics, Northwestern University, Evanston, USA and the Founding Chair of the Department of Mathematics, Southern University of Science and Technology, Shenzhen, China Jinlong Yang Computational chemist; Professor of the School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, China Huawei Zhu Headmaster of Shenzhen Middle School, Shenzhen, China; Former leader and head coach of the national team of China for the International Mathematics Olympiad, China Gang Tian (Chair) Mathematician; Professor of the School of Mathematical Sciences, Peking University, Beijing, China

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5

Kim, K. H., F. W. Roush y M. D. Intriligator. "Overview of Mathematical Social Sciences". American Mathematical Monthly 99, n.º 9 (noviembre de 1992): 838. http://dx.doi.org/10.2307/2324119.

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6

Dr. Sumit Agarwal, Dr Sumit Agarwal. "Mathematical Modelling In Transportation Sciences". IOSR Journal of Mathematics 5, n.º 6 (2013): 39–43. http://dx.doi.org/10.9790/5728-0563943.

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7

Kang, Zhou-Zheng y Tie-Cheng Xia. "American Institute of Mathematical Sciences". Journal of Applied Analysis & Computation 10, n.º 2 (2020): 729–39. http://dx.doi.org/10.11948/20190128.

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8

Pulleyblank, W. R. "Mathematical sciences in the nineties". IBM Journal of Research and Development 47, n.º 1 (enero de 2003): 89–96. http://dx.doi.org/10.1147/rd.471.0089.

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9

Lewis, Hazel. "Mathematical Sciences Strand Outreach Work". MSOR Connections 11, n.º 3 (septiembre de 2011): 52–56. http://dx.doi.org/10.11120/msor.2011.11030052.

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10

Kim, K. H., F. W. Roush y M. D. Intriligator. "Overview of Mathematical Social Sciences". American Mathematical Monthly 99, n.º 9 (noviembre de 1992): 838–44. http://dx.doi.org/10.1080/00029890.1992.11995938.

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11

Calvetti, Daniela y Erkki Somersalo. "Life sciences through mathematical models". Rendiconti Lincei 26, S2 (6 de mayo de 2015): 193–201. http://dx.doi.org/10.1007/s12210-015-0422-5.

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12

KUSUOKA, Shigeo. "Science & Dream Roadmap in the Fields of Mathematical Sciences". TRENDS IN THE SCIENCES 20, n.º 3 (2015): 3_16–3_19. http://dx.doi.org/10.5363/tits.20.3_16.

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13

Ratkó, I. "On special mathematical and computer science methods in medical sciences". Journal of Mathematical Sciences 92, n.º 3 (noviembre de 1998): 3926–29. http://dx.doi.org/10.1007/bf02432365.

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14

Çetinkaya, Yalçın. "Ibn Khaldun and Music as a Science of Mathematical Sciences". Journal of Ibn Haldun Studies, Ibn Haldun University 2, n.º 1 (15 de enero de 2017): 99–104. http://dx.doi.org/10.36657/ihcd.2017.23.

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15

Hayati, Tri Rahmah y Kamid Kamid. "Analysis of Mathematical Literacy Processes in High School Students". International Journal of Trends in Mathematics Education Research 2, n.º 3 (19 de octubre de 2019): 116. http://dx.doi.org/10.33122/ijtmer.v2i3.70.

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The results of the Programme for International Students Assessment (PISA) survey published by the Organization for Economic Cooperation and Development (OECD) show that Indonesia is still a country with low mathematical literacy skills. The ability of mathematical literacy is closely related to interpreting contextual problems into mathematical language. In modern times like today, what is needed is not only mathematics as arithmetic, but also mathematical literacy is needed related to mathematical reasoning and problem solving. The government has included contextual aspects of the curriculum applied in schools. However, in reality many schools still do not have contextual abilities that are in line with the still low literacy abilities of students in Indonesia. The purpose of this study is to describe the mathematical literacy process in senior high schools which in this study were students with majoring in science and students with majoring in social studies. This type of research is descriptive qualitative research. The research subjects were grade X students majoring in science and majoring in social studies. The instruments used in this study were the authors themselves, math literacy questions sheets, and interview guidelines. The results showed that the mathematics literacy process of high school students obtained was both students with majoring in Natural Sciences and students with majoring in Social Sciences are 1) The social science students have been able to reasoning and planning to solve the problem well, even though there still mistakes. The natural science students well in calculation and use formula. However, the natural science students are unable not to argue mathematically and express opinions. 2) the social science students are not good at reasoning and planning to solve the problem, however well in express what students thought verbally. For diagrams translate and solve to math language, the students from social science still difficult. Use of formula in natural science students still not right.

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16

PAVELKO, VIKTORIYA. "MATHEMATICS IN NATURAL SCIENCES AND EDUCATION: THEORETICAL ASPECT". Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University. Series: pedagogy 1, n.º 2 (11 de enero de 2023): 106–13. http://dx.doi.org/10.25128/2415-3605.22.2.13.

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The need to modernize modern education in order to increase the level of students' interest in studying subjects, mathematical and natural sciences, was noted. The role of mathematics and natural sciences for the versatile development of the personality in general, their necessity from the first years of education is defined and integration as an important condition for unification and mutual use in the educational process of mathematical and natural knowledge. The relevance of the problem of using mathematics both in the learning process and for various areas of scientific knowledge is substantiated. The article describes general historical information about mathematics as a science and gives examples of the interpretation of its content by scientists of both the past and the present. The factors determining the importance of the role of mathematics are determined. Its general aspects are characterized from the point of view of mathematical language, its elements, namely, sign, symbol, model, mathematical modeling. The important role of the language of mathematics both in the cognitive activity of a person and in the research of natural sciences at various stages of their development is substantiated. As a result of the analysis of scientific and pedagogical literature and generalizations of the use of mathematical methods and tools, examples of the interpretation of the concept of "mathematization of scientific knowledge" are given. The main aspects of the mathematization of sciences and, in particular, its necessity in the formation and development of natural sciences are theoretically substantiated. The necessary conditions for the effectiveness of the application of the concepts and methods of mathematics and the strengthening of the mathematization of knowledge have been identified. Examples of the application of mathematical methods for such sciences as astronomy and chemistry are given. The need for mathematization in natural science is also mentioned in the context of biological sciences, and the stages of this process are characterized. The degree of reality of mathematical concepts and structures in natural science has been clarified; of mutual dependence, bilateral connection of mathematics and natural sciences are clarified. That is, that natural science is necessary for modern mathematics, just as it is necessary for it. The significance of mathematization in the integration of natural knowledge in today's conditions is indicated. The author also drew attention to the issue of mathematization of natural sciences in the context of the educational process, i.e., that for the subjects of the study, it involves the penetration of mathematics into natural science; on the problem of conditioning the integration of mathematics with science subjects. It was emphasized that science and mathematics education is gaining importance today and the need for active implementation of STEM education in the New Ukrainian School and, in particular, in the primary level.

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17

Distelzweig, Peter M. "The Intersection of the Mathematical and Natural Sciences: The Subordinate Sciences in Aristotle". Apeiron 46, n.º 2 (abril de 2013): 85–105. http://dx.doi.org/10.1515/apeiron-2011-0008.

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Abstract Aristotle is aware of the mathematical treatment of natural phenomena constitutive of Greek astronomy, optics, harmonics, and mechanics. Here I provide an account of Aristotle’s understanding of these ‘subordinate sciences’, drawing on both his methodological discussions and his optical treatment of the rainbow in Meteorology III 5. This account sheds light on the de Caelo, in which Aristotle undertakes a natural investigation of the heavens distinct from, but closely related to, astronomical (thus mathematical) investigations. Although Aristotle insists that such subordinate sciences belong to mathematical and not natural science, he sees them as essential to complete scientific knowledge of the sensible world.

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18

Ram, Mangey, Vijay Kumar y G. S. Ladde. "Computational and mathematical approach for recent problems in mathematical sciences". International Journal for Computational Methods in Engineering Science and Mechanics 22, n.º 3 (4 de mayo de 2021): 169. http://dx.doi.org/10.1080/15502287.2021.1916172.

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19

Bhadane, Mr Sandip, Mrs Megha Kishor Kothawade, Dr Mahendra D. Shinde y Dr Vishal Sulakhe. "Applications of Mathematical in Computer Science". International Journal for Research in Applied Science and Engineering Technology 11, n.º 1 (31 de enero de 2023): 705–9. http://dx.doi.org/10.22214/ijraset.2023.48667.

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Abstract: Mathematics (The QUEEN’s mother of all Sciences), is the foundation of Computer Science. Mathematics can be perceived in our garden or park from symmetry of leaves, flowers, fruits etc. and by so many examples of Geometry and symmetry can be seen in nature. Scientists and researchers cannot ideally accomplish their work without the inclusion of mathematics. Mathematics is sociable for analytical skills needed in Computer Disciplines like; Concepts of binary number system, Boolean algebra, Calculus, Discrete mathematics, linear algebra, number theory, and graph theory are the most applicable to the subject of computer science with the accessional emergence of new concepts like machine learning, artificial intelligence, virtual reality and augmented reality make the future of mathematics grow endless. Mathematics has been an important intellectual preoccupation of man for a long time. Computer Science as a formal discipline is about seven decades young. Is the almost spontaneous use of computing? In this article, this paper convey to the frontage the many close connections and parallels between the Mother and daughter sciences. The paper underscores the strong interplay and interactions by looking at some exciting contemporary results from number theory and combinatorial mathematics and algorithms of computer science.

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20

Svoboda, David y Prokop Sousedík. "The Emergence of (Instrumental) Formalism and a New Conception of Science". Studia Neoaristotelica 16, n.º 2 (2019): 307–29. http://dx.doi.org/10.5840/studneoar201916210.

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According to formalism, a mathematician is not concerned with mysterious metaphysical entities but with mathematical symbols. As a result, mathematical entities become simply sensible signs. However, the price that has to be paid for this move seems to be too high, for mathematics, at present considered to be the queen of sciences, turns out to be a to a contentless game. That is why it seems absurd to regard numbers and all mathematical entities as mere symbols. The aim of our paper is to show the reasons that have led some philosophers and mathematicians to adopt the view that mathematical terms in the proper sense refer to nothing and mathematical propositions have no real content. At the same time we want to explain how formalism helped to overcome the traditional concept of science.

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21

Abiad, Fouad. "Mathematical Modeling of the Strategy of the Early Islamic Wars". International Journal of Social Science Research and Review 3, n.º 1 (10 de marzo de 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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22

Mazhukin, Vladimir Ivanovich, Žarkop Pavićević, Olga Nikolaevna Koroleva y Alexander Vladimirovich Mazhukin. "To the 80th anniversary from the birth of A.A. Samokhin, doctor of physical and mathematical sciences, chief researcher of the Prokhorov General Physics Institute of the Russian Academy of Sciences". Mathematica Montisnigri 49 (2020): 111–20. http://dx.doi.org/10.20948/mathmontis-2020-49-9.

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The article is dedicated to the 80th anniversary of the birth of the Soviet and Russian theoretical physicist, Doctor of Physical and Mathematical Sciences A.A. Samokhin, Chief Researcher of the Theoretical Department of the Institute of Prokhorov General Physics Institute of the RAS, a regular contributor to Mathematica Montisnigri and a long-term active participant in the international scientific seminar "Mathematical Models and Modeling in Laser-Plasma Processes and Advanced Scientific Technologies" (LPpM3), one of the founders of which is Mathematica Montisnigri.

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23

Katz, Emily. "The Mixed Mathematical Intermediates". PLATO JOURNAL 18 (22 de diciembre de 2018): 83–96. http://dx.doi.org/10.14195/2183-4105_18_7.

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In Metaphysics B.2 and M.2, Aristotle gives a series of arguments against Platonic mathematical objects. On the view he targets, mathematicals are substances somehow intermediate between Platonic forms and sensible substances. I consider two closely related passages in B2 and M.2 in which he argues that Platonists will need intermediates not only for geometry and arithmetic, but also for the so-called mixed mathematical sciences (mechanics, harmonics, optics, and astronomy), and ultimately for all sciences of sensibles. While this has been dismissed as mere polemics, I show that the argument is given in earnest, as Aristotle is committed to its key premises. Further, the argument reveals that Annas’ uniqueness problem (1975, 151) is not the only reason a Platonic ontology needs intermediates (according to Aristotle). Finally, since Aristotle’s objection to intermediates for the mixed mathematical sciences is one he takes seriously, so that it is unlikely that his own account of mathematical objects would fall prey to it, the argument casts doubt on a common interpretation of his philosophy of mathematics.

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24

Wang, Yingxu. "On the Mathematical Theories and Cognitive Foundations of Information". International Journal of Cognitive Informatics and Natural Intelligence 9, n.º 3 (julio de 2015): 42–64. http://dx.doi.org/10.4018/ijcini.2015070103.

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A recent discovery in computer and software sciences is that information in general is a deterministic abstract quantity rather than a probability-based property of the nature. Information is a general form of abstract objects represented by symbolical, mathematical, communication, computing, and cognitive systems. Therefore, information science is one of the contemporary scientific disciplines collectively known as abstract sciences such as system, information, cybernetics, cognition, knowledge, and intelligence sciences. This paper presents the cognitive foundations, mathematical models, and formal properties of information towards an extended theory of information science. From this point of view, information is classified into the categories of classic, computational, and cognitive information in the contexts of communication, computation, and cognition, respectively. Based on the three generations of information theories, a coherent framework of contemporary information is introduced, which reveals the nature of information and the fundamental principles of information science and engineering.

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25

Davison, R., Paul Doucet y Peter B. Sloep. "Mathematical Modelling in the Life Sciences". Mathematical Gazette 78, n.º 482 (julio de 1994): 220. http://dx.doi.org/10.2307/3618594.

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26

Cheney, Margaret y Charles W. Groetsch. "Inverse Problems in the Mathematical Sciences." Mathematics of Computation 63, n.º 208 (octubre de 1994): 820. http://dx.doi.org/10.2307/2153303.

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27

Abrahams, David. "Isaac Newton Institute for Mathematical Sciences". EMS Newsletter 2019-6, n.º 112 (6 de junio de 2019): 36–38. http://dx.doi.org/10.4171/news/112/9.

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28

HAGIWARA, Ichiro, Luis DIAGO y Hiroe ABE. "Mathematical Sciences for Self-Driving Car". Proceedings of Mechanical Engineering Congress, Japan 2021 (2021): W011–01. http://dx.doi.org/10.1299/jsmemecj.2021.w011-01.

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29

Dlab, V. y L. L. Scott. "New Books: Mathematical and Physical Sciences". Physics Essays 11, n.º 4 (diciembre de 1998): 613. http://dx.doi.org/10.4006/1.3025348.

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30

Cargal, James. "On Teaching in the Mathematical Sciences". Humanistic Mathematics Network Journal 1, n.º 6 (mayo de 1991): 86–89. http://dx.doi.org/10.5642/hmnj.199101.06.18.

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31

Fowler, A. C. "Mathematical Models in the Applied Sciences." Biometrics 54, n.º 4 (diciembre de 1998): 1684. http://dx.doi.org/10.2307/2533707.

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32

Vogelius, Michael y Henry Warchall. "DMS Mathematical Sciences Research Institutes Update". Notices of the American Mathematical Society 62, n.º 11 (1 de diciembre de 2015): 1375–78. http://dx.doi.org/10.1090/noti1322.

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33

Rankin, Samuel M. "Mathematical Sciences in the FY2013 Budget". Notices of the American Mathematical Society 59, n.º 10 (1 de noviembre de 2012): 1. http://dx.doi.org/10.1090/noti913.

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34

Davies, Penny. "The Scottish Mathematical Sciences Training Centre". MSOR Connections 8, n.º 4 (noviembre de 2008): 8–10. http://dx.doi.org/10.11120/msor.2008.08040008.

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35

Collins, Harry. "Mathematical understanding and the physical sciences". Studies in History and Philosophy of Science Part A 38, n.º 4 (diciembre de 2007): 667–85. http://dx.doi.org/10.1016/j.shpsa.2007.09.001.

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36

Hadlock, Charles R. "Service-Learning in the Mathematical Sciences". PRIMUS 23, n.º 6 (mayo de 2013): 500–506. http://dx.doi.org/10.1080/10511970.2012.736453.

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37

Mishra, Satya N. y Mark Carpenter. "Preface: Confluence of the Mathematical Sciences". American Journal of Mathematical and Management Sciences 28, n.º 3-4 (febrero de 2008): 231–33. http://dx.doi.org/10.1080/01966324.2008.10737726.

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38

Turok, Neil. "The African Institute for Mathematical Sciences". Annales Henri Poincaré 4, S2 (diciembre de 2003): 977–82. http://dx.doi.org/10.1007/s00023-003-0977-2.

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39

Berger, James. "Statistical and Applied Mathematical Sciences Institute". Wiley Interdisciplinary Reviews: Computational Statistics 1, n.º 1 (julio de 2009): 123–27. http://dx.doi.org/10.1002/wics.11.

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40

Witkovský, Viktor y Ivan Frollo. "Measurement Science is the Science of Sciences - There is no Science without Measurement". Measurement Science Review 20, n.º 1 (1 de febrero de 2020): 1–5. http://dx.doi.org/10.2478/msr-2020-0001.

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AbstractOmnia in mensura et numero et pondere disposuisti is a famous Latin phrase from Solomon’s Book of Wisdom, dated to the mid first century BC, meaning that all things were ordered in measure, number, and weight. Naturally, the wisdom is appearing in its relation to man. The Wisdom of Solomon is understood as the perfection of knowledge of the righteous as a gift from God showing itself in action. Consequently, a natural and obvious conjecture is that measurement science is the science of sciences. In fact, it is a basis of all experimental and theoretical research activities. Each measuring process assumes an object of measurement. Some science disciplines, such as quantum physics, are still incomprehensible despite complex mathematical interpretations. No phenomenon is a real phenomenon unless it is observable in space and time, that is, unless it is a subject to measurement. The science of measurement is an indispensable ingredient in all scientific fields. Mathematical foundations and interpretation of the measurement science were accepted and further developed in most of the scientific fields, including physics, cosmology, geology, environment, quantum mechanics, statistics, and metrology. In this year, 2020, Measurement Science Review celebrates its 20th anniversary and we are using this special opportunity to highlight the importance of measurement science and to express our faith that the journal will continue to be an excellent place for exchanging bright ideas in the field of measurement science. As an illustration and motivation for usage and further development of mathematical methods in measurement science, we briefly present the simple least squares method, frequently used for measurement evaluation, and its possible modification. The modified least squares estimation method was applied and experimentally tested for magnetic field homogeneity adjustment.

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41

Martinez, Luciana. "Kant on mathematical axioms". Estudos Kantianos [EK] 10, n.º 1 (15 de julio de 2022): 213. http://dx.doi.org/10.36311/2318-0501.2022.v10n1.p213.

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This article is intended to explain the notion of “mathematical axioms” presented in Kant’s Critique of Pure Reason.This notion is developed mainly within the framework of a justification of the thesis of the methodological dualism of the rational sciences (mathematics and metaphysics). We argue that there are significant differences between the critical notion of mathematical axioms, the pre-critical developments and the Wolffian definitions. The notion of “axiom” that Kant intends to take from mathematical procedures is inscribed in his peculiar way of thinking this science. This paper studies the considerations of (i) Wolff’s mathematical texts, (ii) the pre-critical texts and (iii) the Critique of Pure Reason, and mentions the differences between them in the conclusion.

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42

Shields, Brit. "Mathematics, Peace, and the Cold War". Historical Studies in the Natural Sciences 46, n.º 5 (1 de noviembre de 2016): 556–91. http://dx.doi.org/10.1525/hsns.2016.46.5.556.

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This paper seeks to combine studies of émigré scientists, Cold War American science, and cultural histories of mathematical communities by analyzing Richard Courant’s participation in the National Academy of Sciences interacademy exchange program with the Soviet Union in the 1960s. Following his dismissal by the Nazi government from his post as Director of the Göttingen Mathematics Institute in 1933, Courant spent a year at the University of Cambridge, and then immigrated to the United States where he developed the Courant Institute of Mathematical Sciences at New York University. Courant’s participation with the National Academy of Sciences interacademy exchange program at the end of his career highlights his ideologies about the mathematics discipline, the international mathematics community, and the political role mathematicians could play in contributing to international peace through scientific diplomacy. Courant’s Cold War scientific identity emerges from his activities as an émigré mathematician, institution builder, and international “ambassador.”

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43

Merriam, Daniel y Richard Howarth. "Pioneers in Mathematical Geology". Earth Sciences History 23, n.º 2 (1 de enero de 2004): 314–24. http://dx.doi.org/10.17704/eshi.23.2.j422754m21177430.

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Statistical and mathematical techniques have been used in the earth sciences for about one-hundred years, but only after the introduction of the electronic computer in the mid-Twentieth Century did a revolution in the science take place. The story of the quantification of geology is best told through the works of those who fostered the dramatic change. Here is chronicled the contributions of six pioneers in numerical geology in short exposés by authors close to, and knowledgeable of, the people and their work. The pioneers include F. Chayes (American), J. C. Griffiths (American/Welsh), W. C. Krumbein (American/German), G. Matheron (French), R. A. Reyment (Australian/Swede), and A. B. Vistelius (Russian). These magnificent six also played a major role in forming the International Association for Mathematical Geology in 1968 at the International Geological Congress in Prague, Czechoslovakia.

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44

Turner, Peter R., Rachel Levy y Kathleen Fowler. "Collaboration in the Mathematical Sciences Community on Mathematical Modeling Across the Curriculum". CHANCE 28, n.º 4 (2 de octubre de 2015): 12–18. http://dx.doi.org/10.1080/09332480.2015.1120122.

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45

Levin, Simon A. "Mathematical Ecology, Evolution and the Social Sciences". Ecology, Economy and Society–the INSEE Journal 4, n.º 1 (28 de enero de 2021): 5–12. http://dx.doi.org/10.37773/ees.v4i1.401.

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The last few decades have seen an enhanced partnership between ecologists and social scientists, especially economists, in addressing the environmental challenges facing societies. Not only do ecology and economics, in particular, need each other; but also the challenges they face are similar and can benefit from cross-fertilization. At the core are scaling from the micro- to the macro, the development of appropriate statistical mechanics to facilitate scaling, features underlying the resilience and robustness of systems, the anticipation of critical transitions and regime shifts, and addressing the conflicts of interest between individual agents and the common good through exploration of cooperation, prosociality and collective decision-making. Confronting these issues will be crucial in the coming years for all nations, especially those in South Asia that will suffer in major ways from the consequences of overpopulation, climate change and other environmental threats.

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46

Mahony, John. "Some mathematical appreciations in the physical sciences". Mathematical Gazette 105, n.º 562 (17 de febrero de 2021): 4–15. http://dx.doi.org/10.1017/mag.2021.3.

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According to reports in the media, there is a dearth of practical examples that students of mathematics en route to their qualification can feast upon, at either sixth form level or an undergraduate level. Despite these alleged shortages, it is this author’s opinion that there are numerous examples that can be drawn from the literature and it is the purpose of this article to address the issue by providing examples from the realms of antenna reflector theory and the use therein of conic sections. Some students will be familiar with conic sections and others might not, but the numerous instances of their manifestation in the real world would suggest that they are a force to be reckoned with, and this is certainly true from a mathematical perspective.

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47

Folland, Gerald B., Nicholas J. Higham y Steven G. Krantz. "Handbook of Writing for the Mathematical Sciences." American Mathematical Monthly 105, n.º 8 (octubre de 1998): 779. http://dx.doi.org/10.2307/2589013.

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48

Graham, Chris y Christian Lawson-Perfect. "E-Assessment in Mathematical Sciences (EAMS) Conference". MSOR Connections 15, n.º 2 (26 de enero de 2017): 5. http://dx.doi.org/10.21100/msor.v15i2.495.

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The inaugural E-Assessment in Mathematical Sciences (EAMS) conference was held in September2016 at Newcastle University. This two-day conference brought together researchers andpractitioners in the field of mathematical e-assessment and was attended by over 70 delegates fromall corners of the globe. Motivated by a desire to bring together projects and bubbles of developmentaround the world, around 25 speakers gave a mixture of presentations and workshops.

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49

Abbott, Steve y Nicholas J. Higham. "Handbook of Writing for the Mathematical Sciences". Mathematical Gazette 83, n.º 497 (julio de 1999): 335. http://dx.doi.org/10.2307/3619085.

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50

Mahony, John D. "A mathematical approximation in the physical sciences". Mathematical Gazette 106, n.º 566 (22 de junio de 2022): 220–32. http://dx.doi.org/10.1017/mag.2022.62.

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The business of making mathematical approximations in the physical sciences has a long and noble history. For example, in the earliest days of pyramid construction in ancient Egypt it was necessary to approximate lengths required in construction, especially when they involved irrational numbers. Similarly, surveyors in early Greece seeking to lay out profiles of right-angle triangles or circles on the ground invariably ended up making approximations regarding measurements of required lengths, as indeed is the case today. Practitioners have always faced the problem of having to decide when parameters in theory have been met satisfactorily in the practice of measurement. Further, before the advent of hand-held calculators, students in schools in the UK would have been very familiar with the approximation 22/7 for the transcendental number π, obtained perhaps by comparing (as this author did) the measured circumferences of many laboriously drawn circles of different sizes with their diameters. Despite the advent of sophisticated calculating devices and facilities, such as computers and spreadsheets, the practice of making approximations is still much in evidence in theoretical work in fields associated with physical phenomena. Such approximations often result in formulae that are easy to use and remember, and moreover can produce theoretical results that support directly, or otherwise, results from measurements. In this respect, the practical mathematician does not have to seek results to many decimal places when measurement facilities allow for accuracy to only a few. The purpose of this Article is to illustrate this point by discussing an example drawn from the realms of antenna theory, relating to the performance of a dipole antenna. It is not the purpose here to delve into the derivation of dipole theory, but to extract the relevant information and show how useful mathematical approximations can be employed to simplify a relationship between parameters of interest to an antenna engineer. To this end, it will first be necessary to introduce some antenna concepts that might be new to the reader.

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