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Journal articles on the topic 'Mathematical Sciences'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

Thomas, Jan, Michelle Muchatuta, and Leigh Wood. "Mathematical sciences in Australia." International Journal of Mathematical Education in Science and Technology 40, no. 1 (January 15, 2009): 17–26. http://dx.doi.org/10.1080/00207390802597654.

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2

Ziegel, Eric. "Handbook of Mathematical Sciences." Technometrics 31, no. 2 (May 1989): 275. http://dx.doi.org/10.1080/00401706.1989.10488546.

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3

O'Leary, D. P., and S. T. Weidman. "The interface between computer science and the mathematical sciences." Computing in Science and Engineering 3, no. 3 (May 2001): 60–65. http://dx.doi.org/10.1109/mcise.2001.919268.

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4

Katz, Emily. "The Mixed Mathematical Intermediates." PLATO JOURNAL 18 (December 22, 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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5

Mazhukin, Vladimir Ivanovich, Žarkop Pavićević, Olga Nikolaevna Koroleva, and 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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6

Kim, K. H., F. W. Roush, and M. D. Intriligator. "Overview of Mathematical Social Sciences." American Mathematical Monthly 99, no. 9 (November 1992): 838. http://dx.doi.org/10.2307/2324119.

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7

Dr. Sumit Agarwal, Dr Sumit Agarwal. "Mathematical Modelling In Transportation Sciences." IOSR Journal of Mathematics 5, no. 6 (2013): 39–43. http://dx.doi.org/10.9790/5728-0563943.

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8

Kang, Zhou-Zheng, and Tie-Cheng Xia. "American Institute of Mathematical Sciences." Journal of Applied Analysis & Computation 10, no. 2 (2020): 729–39. http://dx.doi.org/10.11948/20190128.

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9

Pulleyblank, W. R. "Mathematical sciences in the nineties." IBM Journal of Research and Development 47, no. 1 (January 2003): 89–96. http://dx.doi.org/10.1147/rd.471.0089.

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10

Lewis, Hazel. "Mathematical Sciences Strand Outreach Work." MSOR Connections 11, no. 3 (September 2011): 52–56. http://dx.doi.org/10.11120/msor.2011.11030052.

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11

Kim, K. H., F. W. Roush, and M. D. Intriligator. "Overview of Mathematical Social Sciences." American Mathematical Monthly 99, no. 9 (November 1992): 838–44. http://dx.doi.org/10.1080/00029890.1992.11995938.

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12

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

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13

Bondar, Olha, and Olexiy Izvalov. "MATHEMATICAL MODELS IN COMPUTER SCIENCES." TECHNICAL SCIENCES AND TECHNOLOGIES, no. 1(35) (2024): 128–34. http://dx.doi.org/10.25140/2411-5363-2024-1(35)-128-134.

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14

Bastos, Nuno R. O., and Touria Karite. "Mathematical Methods in Applied Sciences." Axioms 13, no. 5 (May 15, 2024): 327. http://dx.doi.org/10.3390/axioms13050327.

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15

Allahverdiyeva, Vüsalə, Ziba Rəhimova, and Dilbər Qasımzadə. "APPLICATION OF TRIGONOMETRY TO SOLVE VARIOUS TYPES OF PROBLEMS." Scientific Works 91, no. 4 (August 9, 2024): 101–5. http://dx.doi.org/10.69682/arti.2024.91(4).101-105.

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The article shows the solution of some mathematical problems by the method of trigonometrical application. Ways of applying the concept of trigonometry to other sciences, including the measurement of geometric and mathematical quantities and calculations in many mathematically complex issues, have been investigated.

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16

KUSUOKA, Shigeo. "Science & Dream Roadmap in the Fields of Mathematical Sciences." TRENDS IN THE SCIENCES 20, no. 3 (2015): 3_16–3_19. http://dx.doi.org/10.5363/tits.20.3_16.

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17

Ratkó, I. "On special mathematical and computer science methods in medical sciences." Journal of Mathematical Sciences 92, no. 3 (November 1998): 3926–29. http://dx.doi.org/10.1007/bf02432365.

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18

Çetinkaya, Yalçın. "Ibn Khaldun and Music as a Science of Mathematical Sciences." Journal of Ibn Haldun Studies, Ibn Haldun University 2, no. 1 (January 15, 2017): 99–104. http://dx.doi.org/10.36657/ihcd.2017.23.

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19

Semenov-Tyan-Shanskiy, M. A. "From quantum field theory to the quantum method the inverse problem On the 90th anniversary of the birth of academician L.D. Faddeev." Вестник Российской академии наук 94, no. 4 (July 31, 2024): 366–77. http://dx.doi.org/10.31857/s0869587324040066.

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The article is dedicated to the life and work of a theoretical physicist and mathematician, a full member of the USSR Academy of Sciences and RAS L.D. Faddeev (1934−2017), the formation of his scientific school. Faddeev’s works on scattering theory, quantum field theory, classical and quantum theory of integrable systems were included in the golden fund of world science and largely determined the face of modern mathematical physics. The author of the article is an employee of the Laboratory of Mathematical Problems of Physics created by L.D. Faddeev at the St. Petersburg Department of the V.A. Steklov Mathematical Institute of the Russian Academy of Sciences since its foundation.

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20

Ram, Mangey, Vijay Kumar, and G. S. Ladde. "Computational and mathematical approach for recent problems in mathematical sciences." International Journal for Computational Methods in Engineering Science and Mechanics 22, no. 3 (May 4, 2021): 169. http://dx.doi.org/10.1080/15502287.2021.1916172.

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21

Kashchenko, Ilya, and Sergey Glyzin. "On the anniversary of Sergei A. Kashchenko." Izvestiya VUZ. Applied Nonlinear Dynamics 31, no. 2 (March 31, 2023): 125–27. http://dx.doi.org/10.18500/0869-6632-003035.

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22

Ağayarov, Mətləb, Mehman Sadiqov, and Fəxrəddin Əliyev. "SOLUTION OF IRRATIONAL INEQUALITIES BY DIFFERENT METHODS." Scientific Works 91, no. 4 (August 9, 2024): 92–96. http://dx.doi.org/10.69682/arti.2024.91(4).92-96.

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The article presents the solution of different types of irrational equations using different methods. The author showed the solution of some mathematical problems using the trigonometric method. Explores ways to apply the concept of trigonometry to other sciences, including the measurement of geometric and mathematical quantities and calculations in many mathematically complex issues.

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23

Witkovský, Viktor, and Ivan Frollo. "Measurement Science is the Science of Sciences - There is no Science without Measurement." Measurement Science Review 20, no. 1 (February 1, 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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24

Khadka, Shree Ram, Santosh Ghimire, and Durga Jang K.C. "Some Fundamental Research Tools in Mathematical Sciences." Journal of Nepal Mathematical Society 6, no. 1 (August 22, 2023): 70–73. http://dx.doi.org/10.3126/jnms.v6i1.57434.

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Research in mathematical sciences either builds up the insight or breaks the boundary of the literature of the pertaining mathematical research area. A mathematical research technique is an attentive, persistent and systematic approach based on the logical rules of inference and mathematical rules of inference to find something new. Mathematical modeling, construction of theorems with the proofs, design of algorithms, data with simulation could be considered as the fundamental tools in mathematical research. In this paper, we discuss some fundamental research tools which are useful to do research in mathematical sciences.

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25

Babenko, V. F., R. O. Bilichenko, M. B. Vakarchuk, O. V. Kovalenko, S. V. Konareva, V. O. Kofanov, T. Yu Leskevych, et al. "In memoriam: Lilia Georgiivna Boitsun, a mathematician and bright person." Researches in Mathematics 29, no. 1 (July 5, 2021): 3. http://dx.doi.org/10.15421/242101.

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26

Editorial Board, ADM. "Fedir Mykolayovych Lyman (22.02.1941–13.06.2020)." Algebra and Discrete Mathematics 30, no. 1 (2020): C—E. http://dx.doi.org/10.12958/adm1749.

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27

Davison, R., Paul Doucet, and Peter B. Sloep. "Mathematical Modelling in the Life Sciences." Mathematical Gazette 78, no. 482 (July 1994): 220. http://dx.doi.org/10.2307/3618594.

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28

Cheney, Margaret, and Charles W. Groetsch. "Inverse Problems in the Mathematical Sciences." Mathematics of Computation 63, no. 208 (October 1994): 820. http://dx.doi.org/10.2307/2153303.

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29

Abrahams, David. "Isaac Newton Institute for Mathematical Sciences." EMS Newsletter 2019-6, no. 112 (June 6, 2019): 36–38. http://dx.doi.org/10.4171/news/112/9.

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30

HAGIWARA, Ichiro, Luis DIAGO, and 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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31

Dlab, V., and L. L. Scott. "New Books: Mathematical and Physical Sciences." Physics Essays 11, no. 4 (December 1998): 613. http://dx.doi.org/10.4006/1.3025348.

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32

Cargal, James. "On Teaching in the Mathematical Sciences." Humanistic Mathematics Network Journal 1, no. 6 (May 1991): 86–89. http://dx.doi.org/10.5642/hmnj.199101.06.18.

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33

Fowler, A. C. "Mathematical Models in the Applied Sciences." Biometrics 54, no. 4 (December 1998): 1684. http://dx.doi.org/10.2307/2533707.

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34

Vogelius, Michael, and Henry Warchall. "DMS Mathematical Sciences Research Institutes Update." Notices of the American Mathematical Society 62, no. 11 (December 1, 2015): 1375–78. http://dx.doi.org/10.1090/noti1322.

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35

Rankin, Samuel M. "Mathematical Sciences in the FY2013 Budget." Notices of the American Mathematical Society 59, no. 10 (November 1, 2012): 1. http://dx.doi.org/10.1090/noti913.

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36

Davies, Penny. "The Scottish Mathematical Sciences Training Centre." MSOR Connections 8, no. 4 (November 2008): 8–10. http://dx.doi.org/10.11120/msor.2008.08040008.

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37

Collins, Harry. "Mathematical understanding and the physical sciences." Studies in History and Philosophy of Science Part A 38, no. 4 (December 2007): 667–85. http://dx.doi.org/10.1016/j.shpsa.2007.09.001.

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38

Hadlock, Charles R. "Service-Learning in the Mathematical Sciences." PRIMUS 23, no. 6 (May 2013): 500–506. http://dx.doi.org/10.1080/10511970.2012.736453.

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39

Mishra, Satya N., and Mark Carpenter. "Preface: Confluence of the Mathematical Sciences." American Journal of Mathematical and Management Sciences 28, no. 3-4 (February 2008): 231–33. http://dx.doi.org/10.1080/01966324.2008.10737726.

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40

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

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41

Berger, James. "Statistical and Applied Mathematical Sciences Institute." Wiley Interdisciplinary Reviews: Computational Statistics 1, no. 1 (July 2009): 123–27. http://dx.doi.org/10.1002/wics.11.

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42

Nakiyingi, Winnie. "African Institute for Mathematical Sciences (AIMS)." European Mathematical Society Magazine, no. 132 (June 19, 2024): 48–52. http://dx.doi.org/10.4171/mag/193.

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43

Nishant, Juneja*. "MATHEMATICAL MODELS IN ECOLOGY." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 4, no. 3 (March 31, 2017): 43–45. https://doi.org/10.5281/zenodo.838569.

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Mathematical modelling is the process of translating the real word problem into the mathematical problem, solving mathematical problem to get some useful results, and then these results are interpreted in the language of real world. Modelling consists of writing in mathematical terms what is first expressed in words, using variables where necessary. Mathematical models are used in the natural sciences , engineering as well as in the social sciences. Statisticians, operations research analysts, and economists use mathematical models hugely. A model may help to explain a system and to study the effects of different components, and to make predictions about the problem. In this paper we shall discuss about the mathematical modelling and its use in ecology..

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44

Mendelsohn, Joshua. "Aristotle on the Objects of Natural and Mathematical Sciences." Ancient Philosophy Today 5, no. 2 (October 2023): 98–122. http://dx.doi.org/10.3366/anph.2023.0092.

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In a series of recent papers, Emily Katz has argued that on Aristotle's view mathematical sciences are in an important respect no different from most natural sciences: They study sensible substances, but not qua sensible. In this paper, I argue that this is only half the story. Mathematical sciences are distinctive for Aristotle in that they study things ‘from’, ‘through’ or ‘in’ abstraction, whereas natural sciences study things ‘like the snub’. What this means, I argue, is that natural sciences must study properties as they occur in the subjects from which they are originally abstracted, even where they reify these properties and treat them as subjects. The objects of mathematical sciences, on the other hand, can be studied as if they did not really occur in an underlying subject. This is because none of the properties of mathematical objects depend on their being in reality features of the subjects from which they are abstracted, such as bodies and inscriptions. Mathematical sciences are in this way able to study what are in reality non-substances as if they were substances.

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45

Morze, Nataliia V., Iryna V. Mashkina, and Mariia A. Boiko. "Experience in training specialists with mathematical computer modeling skills, taking into account the needs of the modern labor market." CTE Workshop Proceedings 9 (March 21, 2022): 95–196. http://dx.doi.org/10.55056/cte.106.

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Today in most countries there is a lack of qualifications in areas, which require specialists with mathematical competencies, despite the high unemployment rate in many countries. At the same time, it is generally recognized that most likely those sciences are developing, the fundamental results of which can be formulated mathematically. Using mathematical methods, researchers draw important conclusions that could hardly be obtained otherwise. Digital transformation of all industries requires specialists with a sufficient level of mathematical competence and skills in ICT tools, including computer modeling using the approach called Inquiry-Based Mathematics Education (IBME).

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46

Distelzweig, Peter M. "The Intersection of the Mathematical and Natural Sciences: The Subordinate Sciences in Aristotle." Apeiron 46, no. 2 (April 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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47

Turner, Peter R., Rachel Levy, and Kathleen Fowler. "Collaboration in the Mathematical Sciences Community on Mathematical Modeling Across the Curriculum." CHANCE 28, no. 4 (October 2, 2015): 12–18. http://dx.doi.org/10.1080/09332480.2015.1120122.

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48

Nurfitriani, Cut Devy, and Abd Qohar. "ANALISIS KEMAMPUAN KONEKSI MATEMATIS SISWA SMP DALAM MENYELESAIKAN MASALAH KONTEKSTUAL HIMPUNAN." Jurnal Kajian Pembelajaran Matematika 5, no. 2 (October 30, 2021): 38. http://dx.doi.org/10.17977/um076v5i22021p38-45.

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Mathematical connections are connecting mathematical concepts and mathematical concepts with other sciences and problems of everyday life. Mathematical contextual problems can be used to view and build students' mathematical connections. The purpose of this study was to describe how the mathematical connection abilities of junior high school students when solving contextual problems on set material. The type of research used is qualitative descriptive research. Research data obtained through mathematical connection tests and interviews. Analysis of mathematical connection ability is divided into modeling connections, concepts, representations, and procedures. The results of this study indicate that high mathematical ability students make modeling connections by making mathematical models, conceptual connections by connecting many members of each set, and procedural connections by operating algebraic forms correctly, representation connections are not carried out because students rarely use Venn diagrams. Students who are mathematically capable are not making modeling connections, concept connections, representation connections, and procedural connections. Students with low mathematical ability do not make modeling connections, concept connections, representation connections and procedural connections

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49

Siti Norhidayah. "Mathematical Reasoning Ability as a Tool to improve Mathematical Literacy." Hipotenusa: Journal of Mathematical Society 5, no. 2 (December 17, 2023): 147–58. http://dx.doi.org/10.18326/hipotenusa.v5i2.565.

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Mathematical reasoning is one of the competencies needed to improve mathematical literacy. Mathematical reasoning is very influential in relation to other sciences and in daily life. This research is a descriptive research with the purpose of describing mathematical reasoning ability of Semester 1 students of Mechanical Engineering Study Program of Balikpapan University. The result of the research shows that there is a good mathematical reasoning in Mechanical Engineering 1st Semester Class A1 Academic Year 2023/2024. With good mathematical reasoning, it can be said that their mathematical literacy is also good enough. Mechanical Engineering students who have good mathematical reasoning will be very supportive in understanding other sciences, especially science in the field of Mechanical Engineering. The problems that arise in the process of mathematical reasoning of Mechanical Engineering Semester 1 students include not understanding the meaning of the problem command, difficulty starting the work steps, lack of accuracy when operating numbers, inability to use certain theories / formulas / rules in solving problems, inability to conclude answers, usually the answer only stops at the calculation result without concluding the results. For students whose achievement of mathematical reasoning ability indicators is still low, it can be helped by often practicing working on problems that require mathematical reasoning. This is one way for teachers to improve their students' mathematical reasoning skills.

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50

Masomi, Hayatullah. "The Application of Mathematical Series in Sciences." Journal of Mathematics and Statistics Studies 4, no. 4 (November 8, 2023): 76–83. http://dx.doi.org/10.32996/jmss.2023.4.4.8.

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Mathematical series and sequences are crucial in scientific disciplines to identify patterns, make predictions, and deduce mathematical correlations between variables. Chemistry, biology and physics rely heavily on mathematical series to model complex systems, make precise predictions, and identify fundamental principles of chemical and biological processes. The study used a qualitative approach to identify mathematical series used in scientific research and evaluate their application in chemistry and biology. A comprehensive literature review was conducted to gather pertinent papers and articles from credible scientific databases, followed by a thematic analysis strategy to examine the content. The findings of the study revealed that mathematical series are widely used in various fields, including chemistry, biology, and physics. The Taylor series, power series expansion, Fibonacci series, power series and binomial series are some of the most commonly used series. They approximate functions, express reaction rates, solve linear equations, depict spiral patterns, study population growth, and analyze genetics and molecular biology. They are crucial tools in physics, quantum mechanics, and natural phenomena description.

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