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Journal articles on the topic 'Computing Mathematics'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Bitter, Gary G., and Mary M. Hatfield. "COMPUTING AND MATHEMATICS." Journal of Reading, Writing, and Learning Disabilities International 5, no. 1 (1989): 1–21. http://dx.doi.org/10.1080/0748763890050102.

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2

Saiedian, Hossein. "Mathematics of Computing." Computer Science Education 3, no. 3 (1992): 203–21. http://dx.doi.org/10.1080/0899340920030302.

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3

Gordon, Neil. "Mathematics and Computing." MSOR Connections 4, no. 2 (2004): 10–13. http://dx.doi.org/10.11120/msor.2004.04020010.

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4

Lax, Peter D. "Mathematics and computing." Journal of Statistical Physics 43, no. 5-6 (1986): 749–56. http://dx.doi.org/10.1007/bf02628302.

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5

Hatfield, Larry L. "Instructional Computing." Arithmetic Teacher 32, no. 6 (1985): 27–30. http://dx.doi.org/10.5951/at.32.6.0027.

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One of the most important goals of mathematics education is the development of students' abilities to think and reason in numerical and spatial situations. How might we use computers as tools for stimulating and guiding the construction of the child's mathematical thinking? The approaches taken by two elementary school teacher are briefly described. Although the uses of the computer by the teacher differ, both adopt a problematic approach to teaching to emphasize the child's mathematical thinking.

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6

Taylor, John, John E. Munro, and Chapman and Hall. "Discrete Mathematics for Computing." Mathematical Gazette 77, no. 480 (1993): 383. http://dx.doi.org/10.2307/3619796.

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7

Ho, Diem. "Financial mathematics and computing." Applied Stochastic Models and Data Analysis 8, no. 3 (1992): 135–36. http://dx.doi.org/10.1002/asm.3150080303.

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8

MASCARI, G. F. "TOWARDS NONCOMMUTATIVE COMPUTING." International Journal of Modern Physics B 14, no. 22n23 (2000): 2451–54. http://dx.doi.org/10.1142/s0217979200001965.

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This paper presents first steps of an approach to quantum information processing in the framework of higher category theory from a noncommutative mathematics perspective. The aim is to provide a unifying theory for the structure and dynamics of composite quantum information processing systems, such that states, evolution, entanglement, decoherence are modeled by abstract categorical constructions and vice versa new mathematical structures arising from higher dimensional algebra could be "tested" as computational schemes and possibly realized by physical experiments.

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9

Iserles, A., and J. C. Diaz. "Mathematics for Large Scale Computing." Mathematical Gazette 74, no. 469 (1990): 324. http://dx.doi.org/10.2307/3619869.

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10

Rowell, Eric C., and Zhenghan Wang. "Mathematics of topological quantum computing." Bulletin of the American Mathematical Society 55, no. 2 (2018): 183–238. http://dx.doi.org/10.1090/bull/1605.

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11

Scott, R., and J. C. Diaz. "Mathematics for Large Scale Computing." Mathematics of Computation 57, no. 195 (1991): 447. http://dx.doi.org/10.2307/2938690.

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12

I., E., David Kincaid, and Ward Cheney. "Numerical Analysis--Mathematics of Scientific Computing." Mathematics of Computation 59, no. 199 (1992): 297. http://dx.doi.org/10.2307/2152998.

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13

COOPER, S. BARRY, BENEDIKT LÖWE, and DAG NORMANN. "Mathematics of computing at CiE 2005." Mathematical Structures in Computer Science 16, no. 05 (2006): 735. http://dx.doi.org/10.1017/s0960129506005433.

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14

Walker, Henry M. "Mathematics with computing and computational science." ACM SIGCSE Bulletin 45, no. 2 (2013): 7. http://dx.doi.org/10.1145/2490868.2490871.

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15

Gregory, Peggy. "Motivating Computing Students to Learn Mathematics." MSOR Connections 4, no. 3 (2004): 26–28. http://dx.doi.org/10.11120/msor.2004.04030026.

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16

Karl, Lila. "DNA computing: Arrival of biological mathematics." Mathematical Intelligencer 19, no. 2 (1997): 9–22. http://dx.doi.org/10.1007/bf03024425.

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17

Ivanek, J. "Mathematics for data processing and computing." European Journal of Operational Research 23, no. 3 (1986): 414–15. http://dx.doi.org/10.1016/0377-2217(86)90314-0.

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18

Stark, W. Richard. "Amorphous computing: examples, mathematics and theory." Natural Computing 12, no. 3 (2013): 377–92. http://dx.doi.org/10.1007/s11047-013-9370-0.

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19

Melnikov, Yury, and Yelena Ivukina. "Relevance factors of mathematical education for sustainable development." E3S Web of Conferences 295 (2021): 05009. http://dx.doi.org/10.1051/e3sconf/202129505009.

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Education system is viewed as an important constituent of sustainable development of a society. The spread of information technology reduces the need for mastering the computing apparatus of mathematics. On the other hand, firstly, the role of mathematics is not limited at least to its computing apparatus, the other components of the mathematical apparatus (for example, conceptual, methodological, etc.) and other aspects of mathematics (historical, activity, education of “intellectual honesty”, the formation of specific types of thinking, for example, geometric, ampect, linked with modelling,

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20

Serkan, Christopher G. "The Integration Of Computing Technology Into Undergraduate Mathematics Classes." International Journal for Innovation Education and Research 3, no. 5 (2015): 149–62. http://dx.doi.org/10.31686/ijier.vol3.iss5.371.

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This study investigated different calculus professors’ conceptions about mathematics and mathematical learning, calculus teaching with or without the use of computing technology, and the experiences in which those conceptions were grounded. Six college professors were purposefully selected and studied. The results showed the professors’ perceptions of the effects of technology use on pedagogy and students’ learning; their perceptions of barriers and challenges to the adoption and use of technology for teaching and learning calculus; and their experience, knowledge, and motivation for adopting

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21

Woods, Damien, and Thomas J. Naughton. "Optical computing." Applied Mathematics and Computation 215, no. 4 (2009): 1417–30. http://dx.doi.org/10.1016/j.amc.2009.04.061.

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22

Kemp, A. W., D. Brown, and P. Rothery. "Models in Biology: Mathematics, Statistics and Computing." Biometrics 51, no. 2 (1995): 792. http://dx.doi.org/10.2307/2532967.

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23

Pentecost, A., D. Brown, and P. Rothery. "Models in Biology: Mathematics, Statistics and Computing." Journal of Ecology 83, no. 1 (1995): 167. http://dx.doi.org/10.2307/2261161.

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24

Coulson, Tim, D. Brown, and P. Rothery. "Models in Biology: Mathematics, Statistics and Computing." Journal of Animal Ecology 64, no. 6 (1995): 793. http://dx.doi.org/10.2307/5868.

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25

Tucker, J. V., J. G. Kemeny, T. E. Kurtz, and J. L. Snell. "Computing for a Course in Finite Mathematics." Mathematical Gazette 71, no. 458 (1987): 333. http://dx.doi.org/10.2307/3617091.

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26

Hatfield, Larry L. "Psychological Perspectives for Instructional Computing in Mathematics." Education and Urban Society 17, no. 4 (1985): 463–74. http://dx.doi.org/10.1177/0013124585017004009.

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27

Kelly, Sarah. "Resource Guide for Engineering, Mathematics and Computing." MSOR Connections 3, no. 2 (2003): 37–38. http://dx.doi.org/10.11120/msor.2003.03020037.

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28

Walker, Henry M. "Mathematics for/with computing and computational science." ACM Inroads 4, no. 2 (2013): 32–34. http://dx.doi.org/10.1145/2465085.2465094.

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29

Kidwell, Peggy Aldrich. "Computing devices, mathematics education and mathematics: Sexton’s omnimetre in its time." Historia Mathematica 36, no. 4 (2009): 395–404. http://dx.doi.org/10.1016/j.hm.2009.06.001.

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30

Yakovlev, Alex. "Energy current and computing." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 376, no. 2134 (2018): 20170449. http://dx.doi.org/10.1098/rsta.2017.0449.

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In his seminal Electrical papers , Oliver Heaviside stated ‘We reverse this …' referring to the relationship between energy current and state changes in electrical networks. We explore implications of Heaviside's view upon the state changes in electronic circuits, effectively constituting computational processes. Our vision about energy-modulated computing that can be applicable for electronic systems with energy harvesting is introduced. Examples of analysis of computational circuits as loads on power sources are presented. We also draw inspiration from Heaviside's way of using and advancing

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31

Brinn, L. W. "Computing Topologies." Mathematics Magazine 58, no. 2 (1985): 67. http://dx.doi.org/10.2307/2689890.

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32

Brinn, L. W. "Computing Topologies." Mathematics Magazine 58, no. 2 (1985): 67–77. http://dx.doi.org/10.1080/0025570x.1985.11977153.

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33

Álvarez, Alonso, Narcisa Salazar, and José Tinajero. "Scientific Computing and the Huygens' Principle." KnE Engineering 1, no. 2 (2018): 44. http://dx.doi.org/10.18502/keg.v1i2.1485.

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Abstract. Mathematics has been present in the development of society since time immemorial; great figures have dedicated their entire life to analysis and research in various branches of this broad science. Scientific Computing is closely related to the design and construction of mathematical models aimed at solving scientific, social and engineering problems. There are several applications of this discipline, for example for mathematical simulations of differential equations in partial derivatives that describe the propagation of a variety of waves such as sound waves, or heat conduction prob

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34

Yu, Ker-Wei, Yang Xu, and Jer-Guang Hsieh. "Mathematical Tools of Soft Computing." Mathematical Problems in Engineering 2014 (2014): 1–3. http://dx.doi.org/10.1155/2014/904014.

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35

Deshpande, Amogh. "Financial computing literacy: 10 steps." MSOR Connections 16, no. 1 (2017): 45. http://dx.doi.org/10.21100/msor.v16i1.504.

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It is often the case that in a financial engineering/mathematics master's curriculum, computer programming if taught, is before the start of an important course typically titled ‘Numerical analysis of financial derivatives’. Typically in this computer programming course, C++ is taught, and the material spans from basic constructs to an introduction to advanced programming such as design patterns. A major reason for its early introduction is that students would subsequently be able to use the skills to computationally solve problems occurring in numerics. We believe this curriculum strategy to

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36

Lu, Liping, and Jing Zhou. "Research on Mining of Applied Mathematics Educational Resources Based on Edge Computing and Data Stream Classification." Mobile Information Systems 2021 (March 25, 2021): 1–8. http://dx.doi.org/10.1155/2021/5542718.

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Facing the massive data of higher education institutions, data mining technology is an intelligent information processing technology that can effectively discover knowledge from the massive data and can discover important information that people have previously ignored from the huge data information. This article is dedicated to the development of applied mathematics education resource mining technology based on edge computing and data stream classification. First of all, this article establishes a resource system architecture suitable for existing applied mathematics education through edge co

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37

Sun, Hong, Qian Wei Tu, Xiao Wan Wang, Jian Hong Zhang, Qian Zhong Wu, and Shou Wen Qin. "The Pricing and Charging of Cloud Computing SaaS." Advanced Materials Research 798-799 (September 2013): 703–7. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.703.

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In this paper, different mathematics models are applied to research the reasonable pricing of the cloud computing software products on the SaaS platform and explore the sales price of the cloud computing software products with the maximum total profits. These information can be the reference for decision-makers to determine the pricing strategy. The aim of this paper is for the cloud computing company to provide the majority of users with the inexpensive and excellent softwares and services, which can make the company dominate the cloud computing market quickly, gain the huge profits in the su

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38

Rodrigues, H., A. C. dos Santos, and A. Soares. "Parachutes: a crossroads between physics, mathematics and computing." Physics Education 55, no. 6 (2020): 065009. http://dx.doi.org/10.1088/1361-6552/aba47c.

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39

Thompson, D. "Book ReviewModels in biology: mathematics, statistics and computing." Journal of Chemical Technology & Biotechnology 67, no. 1 (1996): 105–6. http://dx.doi.org/10.1002/(sici)1097-4660(199609)67:1<105::aid-jctb2534>3.0.co;2-5.

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40

Greenleaf, Newcomb. "Algorithms and proofs: mathematics in the computing curriculum." ACM SIGCSE Bulletin 21, no. 1 (1989): 268–72. http://dx.doi.org/10.1145/65294.65313.

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41

Billstein, Rick, and Johnny W. Lott. "The Turtle Deserves a Star." Arithmetic Teacher 33, no. 7 (1986): 14–16. http://dx.doi.org/10.5951/at.33.7.0014.

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The National Council of Teachers of Mathematics recently published “The lmpact of Computing Technology on School Mathematics: Report of an NCTM Conference” (NCTM 1985). This report addresses the need for mathematics curricula and instructional methods to respond to the influence of computing technology. This report states that “the major influence of technology on mathematics education is its potential to shift the focus of instruction from an emphasis on manipulative skills to an emphasis on developing concepts, relationships, structures, and problem-solving skills.” The use of the computer l

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42

Dubbs, Clyde, and David Siegel. "Computing Determinants." College Mathematics Journal 18, no. 1 (1987): 48. http://dx.doi.org/10.2307/2686317.

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43

Temirgaliyev, N. "Scientific, scientific-methodological and organizational report “The Institute of theoretical mathematics and scientific computing (ITMSC) L.N.Gumilyov Eurasian National University in 2019 year (Part II)”." BULLETIN of L.N. Gumilyov Eurasian National University. MATHEMATICS. COMPUTER SCIENCE. MECHANICS Series 132, no. 3 (2020): 31–69. http://dx.doi.org/10.32523/2616-7182/2020-132-31-69.

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The article is the written on the constantly actual problem of \textit{understanding mathematic} which is even confessed by G.H. Hardy: "\textit{I learnt for the first time as I read it} ("Course of Mathematical Analysis" by Jordan - N.T.). Therefore, it is devoted to the question "\textit{To what extent and in what relation are the scientific environment and basic textbooks important for understanding mathematics?}". Although Hardy's case refutes, in any case does not make it unconditional, it is obvious that "\textit{A qualified environment makes up for the omissions of the textbook"}. This

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44

Mainzer, Klaus. "The Digital and the Real Universe. Foundations of Natural Philosophy and Computational Physics." Philosophies 4, no. 1 (2019): 3. http://dx.doi.org/10.3390/philosophies4010003.

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In the age of digitization, the world seems to be reducible to a digital computer. However, mathematically, modern quantum field theories do not only depend on discrete, but also continuous concepts. Ancient debates in natural philosophy on atomism versus the continuum are deeply involved in modern research on digital and computational physics. This example underlines that modern physics, in the tradition of Newton’s Principia Mathematica Philosophiae Naturalis, is a further development of natural philosophy with the rigorous methods of mathematics, measuring, and computing. We consider fundam

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45

Chen, Feng Xin. "Research of Scientific Computing in the Engineering Linear Algebra Teaching." Applied Mechanics and Materials 333-335 (July 2013): 2218–21. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.2218.

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In this paper, we use some examples to discuss the necessity of using computer software to convert mathematical theory into numerical computations, which can combine classical theory with modern computing and make the abstract concept visualized, then give the future engineer a good foundation for further studies in mathematics as well as other subjects.

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46

Li, Xiao Yi, and Zhao Di Xu. "Based on Mathematical Modeling and Mathematical Experiment Course Platform Enhancing Students Innovative Ability." Applied Mechanics and Materials 513-517 (February 2014): 3034–37. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3034.

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This paper describes the positive significance of the creation of mathematical modeling and experimental mathematics curriculum for students scientific computing and applied mathematics to solve practical problems, it analysis the mathematical modeling and mathematical experimental course, it proposes colleges in mathematical modeling and experimental mathematics teaching,we can take many forms of teaching and different levels of teaching content, thus, to raise and train studentss ability of solving practical problems by applying mathematical knowledge and innovative ability, in order to cult

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47

Zhang, L. H., and M. T. Chu. "Computing absolute maximum correlation." IMA Journal of Numerical Analysis 32, no. 1 (2011): 163–84. http://dx.doi.org/10.1093/imanum/drq029.

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48

Heid, M. Kathleen. "Implementing the Standards: Uses of Technology in Prealgebra and Beginning Algebra." Mathematics Teacher 83, no. 3 (1990): 194–98. http://dx.doi.org/10.5951/mt.83.3.0194.

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The NCTM's Curriculum and Evaluation Standards for School Mathematics (Stan dards) (1989) designates four standards that apply to all students at all grade levels: mathematics as problem solving, mathematics as communication, mathematics as reasoning, and mathematical connections. These and NCTM's other standards are embedded in a vision of technologically rich school mathematics classrooms in which students and teachers have constant access to appropriate computing devices and in which students use computers and calculators as tools for the investigation and exploration of problems.

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49

McKay, John. "On Computing Discriminants." American Mathematical Monthly 94, no. 6 (1987): 523. http://dx.doi.org/10.2307/2322843.

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50

Zak, Michail. "Quantum Analog Computing." Chaos, Solitons & Fractals 10, no. 10 (1999): 1583–620. http://dx.doi.org/10.1016/s0960-0779(98)00215-x.

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