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Journal articles on the topic 'Mathematical analysis'

To see the other types of publications on this topic, follow the link: Mathematical analysis.

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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1

Satriani, Dimas Hudda, Yuyu Yuhana, and Etika Khaerunnisa. "Analysis of Mathematics Literacy Ability in Solving PISA-type Questions viewed from Students’ Mathematical Disposition." PARADIKMA: JURNAL PENDIDIKAN MATEMATIKA 16, no. 1 (June 29, 2023): 80–90. http://dx.doi.org/10.24114/paradikma.v16i1.45514.

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The purpose of this research intended to described the qualities of students' mathematical dispositions and mathematical literacy in response to PISA-style questions. This research uses qualitative approaches and also incorporated within the qualitative descriptive research. The 39 students in class 10 MIPA who participated in the research were then reduced to three students to represent the low, medium, and high levels of disposition. The data were gathered using a questionnaire that measures students' mathematical disposition, a written essay test that measures students' mathematical literacy, and direct interviews. The outcome revealed that seven students fell into the low mathematical disposition category, 24 students had medium mathematical disposition, and eight students had high mathematical disposition. On the PISA scale of mathematical literacy, students with low mathematical disposition earn level 2, students with medium mathematical dsiposition achieved level 4 whereas those with strong mathematical disposition obtain level 6.

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2

Scott, D. B., and R. Maude. "Mathematical Analysis." Mathematical Gazette 71, no. 456 (June 1987): 170. http://dx.doi.org/10.2307/3616533.

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3

P, Balaganesan. "Mathematical Analysis of Virotherapy Treatment for Cancer." Chettinad Health City Medical Journal 12, no. 04 (December 30, 2023): 81–86. http://dx.doi.org/10.24321/2278.2044.202376.

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4

Hart, Mary, and H. Thurston. "Intermediate Mathematical Analysis." Mathematical Gazette 73, no. 466 (December 1989): 353. http://dx.doi.org/10.2307/3619334.

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5

Octaviani, Armelia Dwi, Ana Rahmawati, and Dian Novita Rohmatin. "Analysis of Students' Mathematical Communication Ability in Solving Problems Viewed from the Mathematical Disposition." International Journal of Research Publication and Reviews 4, no. 3 (March 10, 2023): 1609–13. http://dx.doi.org/10.55248/gengpi.2023.32739.

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6

Vasileva, Natalia, Vladimir Grigorev-Golubev, and Irina Evgrafova. "Mathematical programming in Mathcad and Mathematica." E3S Web of Conferences 419 (2023): 02007. http://dx.doi.org/10.1051/e3sconf/202341902007.

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An article generalizes the long-term work of authors with packages of applied mathematical programs. It discusses and demonstrates the features and methods of solution of mathematical tasks in mathematical package Mathcad and Mathematica: from the simplest ones, included in the set of typical problems of mathematical disciplines for training specialists for shipbuilding, to complex computational tasks and applied problems of professional orientation, which require the construction of a mathematical model and analysis of the results obtained. The examples show the solution of mathematical problems in symbolic form, mathematical studies in the Mathcad and Mathematica environment, and mathematical programming with these packages.

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7

Curran, W. S. "Mathematical proof." Journal of Interdisciplinary Mathematics 8, no. 1 (January 2005): 119–25. http://dx.doi.org/10.1080/09720502.2005.10700395.

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8

Juhász, Péter, Szilvia Béla, and Katalin Kopecskó. "Mathematical analysis of capillary elevation in porous limestone." Epitoanyag-Journal of Silicate Based and Composite Materials 65, no. 1 (2013): 2–5. http://dx.doi.org/10.14382/epitoanyag-jsbcm.2013.1.

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9

Maysarah, Siti, Sahat Saragih, and Dian Armanto. "Analysis of Students' Mathematical Literacy Ability in Solving Linear Equations of Two Variables." Logaritma : Jurnal Ilmu-ilmu Pendidikan dan Sains 11, no. 02 (December 31, 2023): 247–56. http://dx.doi.org/10.24952/logaritma.v11i02.10019.

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The purpose of this study was to analyze students' mathematical literacy ability in solving problems related to the material of a two-variable system of linear equations. This type of research is descriptive qualitative research. The results of this study are in the form of a description of indicators of mathematical literacy ability, namely: (1) identifying facts mathematically, (2) formulating problems mathematically, (3) using mathematical concepts to solve problems, (4) carrying out calculations based on certain procedures, and (5) draw conclusions. The sample in this study were 10 students of MTs Nurul Khairiyah Deli Serdang. Based on the results of the study, it was found that the average score of students' mathematical literacy abilities per indicator in solving linear equations of two variables, namely (1) identifying facts mathematically obtained 22.5%, (2) formulating problems mathematically obtained 90%, (3) using mathematical concepts to solve problems obtained 93.75%, (4) carrying out calculations based on certain procedures 92.5%, and (5) drawing conclusions obtained 83.75%.

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10

Lorig, Matthew, Zhou Zhou, and Bin Zou. "A Mathematical Analysis of Technical Analysis." Applied Mathematical Finance 26, no. 1 (January 2, 2019): 38–68. http://dx.doi.org/10.1080/1350486x.2019.1588136.

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11

Chorlton, F., and Hans Triebel. "Analysis and Mathematical Physics." Mathematical Gazette 72, no. 459 (March 1988): 70. http://dx.doi.org/10.2307/3618017.

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12

Nugent, S. M., and Rod Haggarty. "Fundamentals of Mathematical Analysis." Mathematical Gazette 74, no. 467 (March 1990): 83. http://dx.doi.org/10.2307/3618884.

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13

Lord, Nick, Piotr Biler, and Alfred Witkowski. "Problems in Mathematical Analysis." Mathematical Gazette 75, no. 471 (March 1991): 125. http://dx.doi.org/10.2307/3619029.

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14

Whittaker, Douglas, and R. Haggarty. "Fundamentals of Mathematical Analysis." Mathematical Gazette 79, no. 484 (March 1995): 221. http://dx.doi.org/10.2307/3620100.

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15

Shiu, P., and David S. G. Stirling. "Mathematical Analysis and Proof." Mathematical Gazette 82, no. 493 (March 1998): 148. http://dx.doi.org/10.2307/3620189.

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16

Srivastava, Hari. "Mathematical Analysis and Applications." Axioms 7, no. 4 (November 12, 2018): 82. http://dx.doi.org/10.3390/axioms7040082.

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17

Dykstra, Richard L., Judah Rosenblatt, Stoughton Bell, Douglas Mooney, and Randall Swift. "Mathematical Analysis for Modeling." Journal of the American Statistical Association 95, no. 451 (September 2000): 1017. http://dx.doi.org/10.2307/2669502.

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18

&NA;. "Mathematical Analysis in Engineering." Journal of Clinical Engineering 20, no. 4 (July 1995): 268–71. http://dx.doi.org/10.1097/00004669-199507000-00011.

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19

Bains, Raghpat. "Fundamentals of Mathematical Analysis." Engineering Analysis with Boundary Elements 7, no. 3 (September 1990): 150. http://dx.doi.org/10.1016/0955-7997(90)90045-b.

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20

Watanabe, Hiroshi. "Mathematical construction of chiral anomaly." Journal of Functional Analysis 97, no. 2 (May 1991): 327–50. http://dx.doi.org/10.1016/0022-1236(91)90005-p.

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21

Kézi, Csaba. "Teaching the Analysis of Newton’s Cooling Model to Engineering Students." International Journal of Engineering and Management Sciences 8, no. 2 (June 30, 2023): 63–68. http://dx.doi.org/10.21791/ijems.2023.2.7.

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To apply mathematical methods to physical or other real life problem, we have to formulate the problem in mathematical terms. It means that, we have to construct the mathematical model for the problem. Many physical problems shows the relationships between changing quantities. The rates of change are represented mathematically by derivatives. In this case the mathematical models involve equations relating an unknown function and one or more of its derivatives. These equations are the differential equations. In this article, teaching the analysis of Newton's cooling model to engineering students is presented as one of the applications of separable differential equations.

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22

Yokoi, Keisuke, Minh-Quoc Nghiem, Yuichiroh Matsubayashi, and Akiko Aizawa. "Contextual Analysis of Mathematical Expressions for Advanced Mathematical Search." Polibits 43 (June 30, 2011): 81–86. http://dx.doi.org/10.17562/pb-43-11.

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23

Wagino, Wagino, and Andriani Andriani. "Analysis of Mathematical Connection Skills Using Realistic Mathematical Education." Indo-MathEdu Intellectuals Journal 2, no. 2 (October 20, 2021): 83–91. http://dx.doi.org/10.54373/imeij.v2i2.20.

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Connection ability is the ability to associate between topics in mathematics, associate mathematics in other sciences, and with everyday life. This research aims to find out the ability of mathematical connections by using the realistic mathematical education of the concept of Social Arithmetic in class VII of SMP Negeri 209 Jakarta. This type of research is qualitative descriptive with the selection of subjects based on the results of interviews. The main instrument in the study was the researchers themselves. Instruments for discovering mathematical connection skills are tests and interviews. Data collection techniques with observation guidelines, tests, interviews, and documentation. Data analysis used is qualitative analysis i.e. data collection, presentation of data, and withdrawal of conclusions. The results of the analysis showed that subjects included students who had the ability of mathematical connections that met 4 indicators of mathematical connections, namely recognizing the equivalent representation of the same concept, recognizing the relationship of a mathematical procedure of a representation to an equivalent representation procedure, using and assessing the relationship between topics with other disciplines, using mathematics in everyday life

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24

Abdullah, Saeed Ahmad, Saud Owyed, Abdel-Haleem Abdel-Aty, Emad E. Mahmoud, Kamal Shah, and Hussam Alrabaiah. "Mathematical analysis of COVID-19 via new mathematical model." Chaos, Solitons & Fractals 143 (February 2021): 110585. http://dx.doi.org/10.1016/j.chaos.2020.110585.

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25

Al-Hanifah, Jihan Azizah, Yus Mochamad Cholily, and Siti Khoiruli Ummah. "Analysis of Students' Analytical Thinking Ability and Mathematical Communication Using Online Group Investigation Learning Model." Mathematics Education Journal 7, no. 1 (March 1, 2023): 100–113. http://dx.doi.org/10.22219/mej.v7i1.23342.

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Analytical thinking and mathematical communication are abilities included in the learning process objectives. This study aims to describe students' analytical thinking skills and mathematical communication using the online group investigation cooperative learning model. The subjects of this research were 30 students of class VIII-C. The type of research used is descriptive qualitative. The data to determine the implementation of learning and the ability to think analytically and communicate mathematically are observations, documentation, and tests. The study results show that the online group investigation type cooperative learning model implementation takes place following the steps of group investigation learning. The results of the ability to think analytically and communicate mathematically meet all indicators. The distinguishing indicator of analytical thinking ability is the most widely achieved, and the one that has yet to be completed much is the attributing indicator. So that students' analytical thinking skills have an analytical category. The most widely conducted indicator of mathematical communication ability is the indicator of expressing mathematical ideas in writing. What has yet to be widely achieved is the indicator of analyzing and evaluating mathematical concepts. So that students' mathematical communication skills have a mathematical category.

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26

Lutovac, Miroslav, and Dejan Tosic. "Symbolic signal processing and system analysis." Facta universitatis - series: Electronics and Energetics 16, no. 3 (2003): 423–31. http://dx.doi.org/10.2298/fuee0303423l.

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We present new software in MATLAB and Mathematica for symbolic signal processing and system analysis. Our mission is to encapsulate high-tech engineering and sophisticated mathematical knowledge into easy-to-use software that effectively solves practical problems.

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27

Mikelić, A. "Mathematical theory of stationary miscible filtration." Journal of Differential Equations 90, no. 1 (March 1991): 186–202. http://dx.doi.org/10.1016/0022-0396(91)90167-8.

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28

Furuichi, Shigeru, Kenjiro Yanagi, and Hamid Reza Moradi. "Mathematical inequalities on some weighted means." Journal of Mathematical Inequalities, no. 2 (2023): 447–57. http://dx.doi.org/10.7153/jmi-2023-17-30.

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29

Hardianti, Siti, Thamrin Tayeb, Fitriani Nur, Ahmad Farham Majid, and Baharuddin Baharuddin. "THE ANALYSIS OF MATHEMATICAL PROOF ABILITY." MATEMATIKA DAN PEMBELAJARAN 8, no. 2 (December 31, 2020): 102–11. http://dx.doi.org/10.33477/mp.v8i2.1528.

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The ability to prove mathematically is one of the important abilities in learning mathematics. This study aims to determine students' mathematical proof ability. This type of research is a qualitative descriptive study, which involved 38 sixth semester students of the Mathematics Education Department, Tarbiyah and Teacher Training College, Alauddin Makassar State Islamic University with 3 of them being interview subjects. The instruments and data collection techniques used were researchers using diagnostic tests and interview guides. The analysis techniques used are data reduction, display data, and conclusion drawing / verification. The result of this research is that the students' mathematical proving ability in working on the questions is not optimal. In the indicator of the ability to construct evidence, students are less able to make connections between known facts and the elements to be proven. Furthermore, on the indicator of the ability to read a proof, students are less able to use definitions as a basis for providing arguments.

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30

Kurz, Terri L., and Barbara Bartholomew. "Mathematical Explorations: Rethinking Dr. Seuss's The Lorax—Mathematically." Mathematics Teaching in the Middle School 18, no. 3 (October 2012): 180–87. http://dx.doi.org/10.5951/mathteacmiddscho.18.3.0180.

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31

Azlan, Noor Akmar, and Mohd Faizal Nizam Lee Abdullah. "Komunikasi matematik : Penyelesaian masalah dalam pengajaran dan pembelajaran matematik." Jurnal Pendidikan Sains Dan Matematik Malaysia 7, no. 1 (April 27, 2017): 16–31. http://dx.doi.org/10.37134/jsspj.vol7.no1.2.2017.

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Based on the study of mathematic problems created by Clements in 1970 and 1983 in Penang, it was found that students in Malaysia do not have a problem of serious thought. However, the real problem is related to read, understand and make the right transformation when solving mathematical problems, especially those involving mathematical word problem solving. Communication is one of the important elements in the process of solving problems that occur in the teaching and learning of mathematics. Students have the opportunities to engage in mathematic communication such as reading, writing and listening and at least have two advantages of two different aspects of communication which are to study mathematics and learn to communicate mathematically. Most researchers in the field of mathematics education agreed, mathematics should at least be studied through the mail conversation. The main objective of this study is the is to examine whether differences level of questions based on Bloom’s Taxonomy affect the level of communication activity between students and teachers in the classroom. In this study, researchers wanted to see the level of questions which occur with active communication and if not occur what is the proper strategy should taken by teachers to promote the effective communication, engaging study a group of level 4 with learning disabilities at a secondary school in Seremban that perform mathematical tasks that are available. The study using a qualitative approach, in particular sign an observation using video as the primary method. Field notes will also be recorded and the results of student work will be taken into account to complete the data recorded video. Video data are primary data for this study. Analysis model by Powell et al., (2013) will was used to analyze recorded video. Milestones and critical during this study will be fully taken into account.

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32

Al Nazer, Safaa, Carole Rosier, and Munkhgerel Tsegmid. "Mathematical analysis of a Dupuit-Richards model." Electronic Journal of Differential Equations 2022, no. 01-87 (January 17, 2022): 06. http://dx.doi.org/10.58997/ejde.2022.06.

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This article concerns an alternative model to the 3D-Richards equation to describe the flow of water in shallow aquifers. The model couples the two dominant types of flow existing in the aquifer. The first is described by the classic Richards problem in the upper capillary fringe. The second results from Dupuit's approximation after vertical integration of the conservation laws between the bottom of the aquifer and the saturation interface. The final model consists of a strongly coupled system of parabolic-type partial differential equations that are defined in a time-dependent domain. First, we show how taking the low compressibility of the fluid into account eliminates the nonlinearity in the time derivative of the Richards equation. Then, the general framework of parabolic equations is used in non-cylindrical domains to give a global in time existence result to this problem.

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33

Buikis, A., J. Cepitis, H. Kalis, A. Reinfelds, A. Ancitis, and A. Salminš. "Mathematical Models of Papermaking." Nonlinear Analysis: Modelling and Control 6, no. 1 (April 1, 2001): 9–19. http://dx.doi.org/10.15388/na.2001.6.1.15221.

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The mathematical model of wood drying based on detailed transport phenomena considering both heat and moisture transfer have been offered in article. The adjustment of this model to the drying process of papermaking is carried out for the range of moisture content corresponding to the period of drying in which vapour movement and bound water diffusion in the web are possible. By averaging as the desired models are obtained sequence of the initial value problems for systems of two nonlinear first order ordinary differential equations.

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34

Lazareva, G. G., V. V. Mironova, N. A. Omelyanchuk, I. V. Shvab, V. A. Vshivkov, D. N. Gorpinchenko, S. V. Nikolaev, and N. A. Kolchanov. "Mathematical modeling of plant morphogenesis." Numerical Analysis and Applications 1, no. 2 (April 2008): 123–34. http://dx.doi.org/10.1134/s1995423908020043.

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35

Sinan, Muhammad, and Nadiyah Hussain Alharthi. "Mathematical Analysis of Fractal-Fractional Mathematical Model of COVID-19." Fractal and Fractional 7, no. 5 (April 27, 2023): 358. http://dx.doi.org/10.3390/fractalfract7050358.

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In this work, we modified a dynamical system that addresses COVID-19 infection under a fractal-fractional-order derivative. The model investigates the psychological effects of the disease on humans. We establish global and local stability results for the model under the aforementioned derivative. Additionally, we compute the fundamental reproduction number, which helps predict the transmission of the disease in the community. Using the Carlos Castillo-Chavez method, we derive some adequate results about the bifurcation analysis of the proposed model. We also investigate sensitivity analysis to the given model using the criteria of Chitnis and his co-authors. Furthermore, we formulate the characterization of optimal control strategies by utilizing Pontryagin’s maximum principle. We simulate the model for different fractal-fractional orders subject to various parameter values using Adam Bashforth’s numerical method. All numerical findings are presented graphically.

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36

Chen, Zhangxin, and Richard Ewing. "Mathematical Analysis for Reservoir Models." SIAM Journal on Mathematical Analysis 30, no. 2 (January 1999): 431–53. http://dx.doi.org/10.1137/s0036141097319152.

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37

Khanmamedova, E. "MATHEMATICAL MODEL ANALYSIS OF GRAPHENE OXIDE THERMAL DEVELOPMENT." Grail of Science, no. 26 (April 24, 2023): 283–85. http://dx.doi.org/10.36074/grail-of-science.14.04.2023.050.

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The thermal processing mathematical model of graphene oxide is a model that mathematically describes the changes that the material undergoes during thermal processing. This model takes into account the changes in the crystal structure of the material during thermal treatment and the effects of these changes on the properties of the material.

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38

Rose, H. E. "LECTURES ON CONSTRUCTIVE MATHEMATICAL ANALYSIS (Translations of Mathematical Monographs, 60)." Bulletin of the London Mathematical Society 17, no. 6 (November 1985): 623. http://dx.doi.org/10.1112/blms/17.6.623.

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39

Tyagi, Tarun Kumar. "Mathematical Creativity and Mathematical Aptitude: A Cross-Lagged Panel Analysis." Creativity Research Journal 28, no. 3 (July 2, 2016): 328–33. http://dx.doi.org/10.1080/10400419.2016.1195654.

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40

Emeira, G., Hapizah, and Scristia. "Mathematical proof analysis using mathematical induction of grade XI students." Journal of Physics: Conference Series 1480 (March 2020): 012044. http://dx.doi.org/10.1088/1742-6596/1480/1/012044.

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41

Ray, W. D., and F. Y. M. Wan. "Mathematical Models and Their Analysis." Journal of the Operational Research Society 41, no. 12 (December 1990): 1173. http://dx.doi.org/10.2307/2583116.

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42

Middleton, D., and John A. Rice. "Mathematical Statistics and Data Analysis." Mathematical Gazette 72, no. 462 (December 1988): 330. http://dx.doi.org/10.2307/3619963.

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43

Buffa, Annalisa, Thomas Hughes, Angela Kunoth, and Carla Manni. "Mathematical Foundations of Isogeometric Analysis." Oberwolfach Reports 16, no. 3 (September 9, 2020): 1981–2032. http://dx.doi.org/10.4171/owr/2019/33.

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44

Ziegel, Eric R., and John Rice. "Mathematical Statistics and Data Analysis." Technometrics 37, no. 1 (February 1995): 127. http://dx.doi.org/10.2307/1269179.

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45

Srivastava, Hari M. "Mathematical Analysis and Applications II." Axioms 9, no. 1 (February 6, 2020): 16. http://dx.doi.org/10.3390/axioms9010016.

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46

Козлов, Н. Н., and N. N. Kozlov. "Mathematical analysis of genetic codes." Mathematical Biology and Bioinformatics 1, no. 1 (March 29, 2006): 70–96. http://dx.doi.org/10.17537/2006.1.70.

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47

Leonard, Tom, and John A. Rice. "Mathematical Statistics and Data Analysis." Journal of the American Statistical Association 84, no. 406 (June 1989): 625. http://dx.doi.org/10.2307/2289973.

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48

LuValle, Michael, Flemming Topsoe, and John Stillwell. "Spontaneous Phenomena: A Mathematical Analysis." Journal of the American Statistical Association 86, no. 415 (September 1991): 824. http://dx.doi.org/10.2307/2290424.

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49

AA and John A. Rice. "Mathematical Statistics and Data Analysis." Journal of the American Statistical Association 90, no. 429 (March 1995): 398. http://dx.doi.org/10.2307/2291188.

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50

Zwirner, Walter W. "Mathematical Programming in Statistical Analysis." Calcutta Statistical Association Bulletin 44, no. 3-4 (September 1994): 229–38. http://dx.doi.org/10.1177/0008068319940310.

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