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Journal articles on the topic 'Discrete approach'

Author: Grafiati

Published: 10 March 2023

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1

Dias-da-Costa, D., J. Alfaiate, L. J. Sluys, and E. Júlio. "A discrete strong discontinuity approach." Engineering Fracture Mechanics 76, no. 9 (2009): 1176–201. http://dx.doi.org/10.1016/j.engfracmech.2009.01.011.

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2

Djadja, M., A. Naamane, and N. Giambiasi. "Approach for discrete event simulation." Electronics Letters 34, no. 16 (1998): 1615. http://dx.doi.org/10.1049/el:19981112.

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3

Kantelhardt, Jan W., H. Eduardo Roman, and Martin Greiner. "Discrete wavelet approach to multifractality." Physica A: Statistical Mechanics and its Applications 220, no. 3-4 (1995): 219–38. http://dx.doi.org/10.1016/0378-4371(95)00267-b.

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4

Khosiyono, Banun Havifah cahyo. "DISCRETE AND INTEGRATED APPROACH AND THE IMPLICATIONS ON LANGUAGE TEACHING LEARNING MANAGEMENT." Prominent 4, no. 1 (2021): 19–29. http://dx.doi.org/10.24176/pro.v4i1.5755.

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This paper describes discrete and integrated approach and the implication on language teaching learning management. Discrete approach emphasizes on the teaching and learning a language discretely, whereas integrated approach emphasizes on the whole language, namely speaking, writing, listening, reading, pronunciation, grammar, and vocabulary. In fact, both are interrelated since discrete learning is the basis for integrated learning. Both should be implemented in the teaching learning process in the classroom so that students are able to use the language well. Therefore, the curriculum or the syllabus, teaching materials, teachers’ qualification, and classroom management should be prepared well.

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5

do Nascimento, Roberto Quirino, Ana Flávia Uzeda dos Santos Macambira, Lucidio dos Anjos Formiga Cabral, and Renan Vicente Pinto. "The discrete ellipsoid covering problem: A discrete geometric programming approach." Discrete Applied Mathematics 164 (February 2014): 276–85. http://dx.doi.org/10.1016/j.dam.2012.10.016.

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6

Prasuna, P. M., Dr Y. Ramadevi, and Dr A. Vinay Babu. "A two level approach to discretize cosmetic data using Rough set theory." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 10 (2015): 6147–52. http://dx.doi.org/10.24297/ijct.v14i10.1826.

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Discrete values play a very prominent role in extracting knowledge. Most of the machines learning algorithms use discrete values. It is also observed that the rules discovered through discrete values are shorter and precise. The predictive accuracy is more when discrete values are used. Cosmetic industry extracts the features from the face images of the customers to analyze their facial skin problems. These values are continuous in nature. A predictive model with high accuracy is required to determine the cosmetic problems of the customers and suggest suitable cosmetic. Existing traditional discretization techniques are not sufficient for deriving discretized data from continuous valued cosmetic data as it has to balance the loss of information intrinsic to process adapted and generating a reasonable number of cut points, that is, a reasonable search space. This paper proposes a two level discretization method which is a combination of traditional k means clustering technique and rough set theory to discretize continuous features of cosmetic data.

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7

Zhukovskiy, V., and L. Smirnova. "UNCERTAINTY AND DISCRETE MAXIMIN." TAURIDA JOURNAL OF COMPUTER SCIENCE THEORY AND MATHEMATICS, no. 1 (November 25, 2022): 7–31. http://dx.doi.org/10.29039/1729-3901-2021-20-1-7-31.

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The article consists of two parts. The ﬁrst part is devoted to general questions that are related to uncertainty: causes and sources of uncertainties appearance, classiﬁcation of uncertainties in economic systems and approach to their assessment. In the second part the concept of maximin, based on the principle of guaranteed result (Wald’s principle) is considered. In this case, maximin is interpreted from viewpoint of two-level hierarchical game. On the basis of the maximin concept, a guaranteed solution in outcomes for K-stage positional single-criterion linear quadratic problem under uncertainty is formalized. An explicit form of the guaranteed solution for this problem is found

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8

Blachowski, Bartlomiej, and Witold Gutkowski. "A hybrid continuous-discrete approach to large discrete structural optimization problems." Structural and Multidisciplinary Optimization 41, no. 6 (2009): 965–77. http://dx.doi.org/10.1007/s00158-009-0466-1.

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9

Antoine, J. P., Y. B. Kouagou, D. Lambert, and B. Torrésani. "An algebraic approach to discrete dilations. Application to discrete wavelet transforms." Journal of Fourier Analysis and Applications 6, no. 2 (2000): 113–41. http://dx.doi.org/10.1007/bf02510656.

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10

Hager, Kevin, and Richard Balling. "New Approach for Discrete Structural Optimization." Journal of Structural Engineering 114, no. 5 (1988): 1120–34. http://dx.doi.org/10.1061/(asce)0733-9445(1988)114:5(1120).

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11

Rioul, O. "Regular wavelets: a discrete-time approach." IEEE Transactions on Signal Processing 41, no. 12 (1993): 3572–79. http://dx.doi.org/10.1109/78.258100.

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12

Das, Ashish, and Rakhi Singh. "Discrete choice experiments—A unified approach." Journal of Statistical Planning and Inference 205 (March 2020): 193–202. http://dx.doi.org/10.1016/j.jspi.2019.07.003.

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13

Garc�a-Cutr�n, Javier, and Carlos Herv�s-Beloso. "A discrete approach to continuum economies." Economic Theory 3, no. 3 (1993): 577–83. http://dx.doi.org/10.1007/bf01209704.

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14

Baez, John C., and James W. Gilliam. "An algebraic approach to discrete mechanics." Letters in Mathematical Physics 31, no. 3 (1994): 205–12. http://dx.doi.org/10.1007/bf00761712.

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15

Nedjalkov, Mihail, and Dragica Vasileska. "Semi-discrete 2D Wigner-particle approach." Journal of Computational Electronics 7, no. 3 (2008): 222–25. http://dx.doi.org/10.1007/s10825-008-0197-3.

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16

Hall, Peter, and Peihua Qiu. "Discrete-transform approach to deconvolution problems." Biometrika 92, no. 1 (2005): 135–48. http://dx.doi.org/10.1093/biomet/92.1.135.

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17

Cufí, Julià, Agustí eventós, and Carlos J. Rodríguez. "A discrete approach to Wirtinger's inequality." Journal of Mathematical Inequalities, no. 3 (2019): 737–46. http://dx.doi.org/10.7153/jmi-2019-13-50.

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18

Sarkar, Prasanta. "Discrete-time Systems—A Unified Approach." IETE Journal of Research 52, no. 6 (2006): 471–79. http://dx.doi.org/10.1080/03772063.2006.11416487.

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19

Miller, Russ. "A modern approach to discrete structures." International Journal of Teaching and Case Studies 9, no. 1 (2018): 33. http://dx.doi.org/10.1504/ijtcs.2018.090194.

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20

Miller, Russ. "A modern approach to discrete structures." International Journal of Teaching and Case Studies 9, no. 1 (2018): 33. http://dx.doi.org/10.1504/ijtcs.2018.10011119.

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21

Bossavit, Alain. "Discrete Magneto-Elasticity: A Geometrical Approach." IEEE Transactions on Magnetics 46, no. 8 (2010): 3485–91. http://dx.doi.org/10.1109/tmag.2010.2043346.

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22

Large, M. C. J., D. R. McKenzie, and M. I. Large. "Incoherent reflection processes: a discrete approach." Optics Communications 128, no. 4-6 (1996): 307–14. http://dx.doi.org/10.1016/0030-4018(95)00761-x.

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23

Melnikov, B. F. "Multiheuristic approach to discrete optimization problems." Cybernetics and Systems Analysis 42, no. 3 (2006): 335–41. http://dx.doi.org/10.1007/s10559-006-0070-y.

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24

LIU, WEI YI, JIN LI, KUN YUE, NING SONG, and HONG YAO. "AN APPROACH FOR SOLVING FUZZY GAMES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, no. 03 (2006): 277–92. http://dx.doi.org/10.1142/s0218488506004011.

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This paper is to compute a Nash equilibrium in a fuzzy environment, which is represented by a fuzzy approximate Nash equilibrium in a space of discrete mixed strategies. For discrete mixed strategies, the relationship between the discrete degree and the approximate degree is discussed. Based on the fuzzy regret degree, a genetic algorithm for computing a fuzzy Nash equilibrium is given.

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25

Stefanov, Stefan M. "On the Application of Iterative Methods of Nondifferentiable Optimization to Some Problems of Approximation Theory." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/165701.

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We consider the data fitting problem, that is, the problem of approximating a function of several variables, given by tabulated data, and the corresponding problem for inconsistent (overdetermined) systems of linear algebraic equations. Such problems, connected with measurement of physical quantities, arise, for example, in physics, engineering, and so forth. A traditional approach for solving these two problems is the discrete least squares data fitting method, which is based on discretel2-norm. In this paper, an alternative approach is proposed: with each of these problems, we associate a nondifferentiable (nonsmooth) unconstrained minimization problem with an objective function, based on discretel1- and/orl∞-norm, respectively; that is, these two norms are used as proximity criteria. In other words, the problems under consideration are solved by minimizing the residual using these two norms. Respective subgradients are calculated, and a subgradient method is used for solving these two problems. The emphasis is on implementation of the proposed approach. Some computational results, obtained by an appropriate iterative method, are given at the end of the paper. These results are compared with the results, obtained by the iterative gradient method for the corresponding “differentiable” discrete least squares problems, that is, approximation problems based on discretel2-norm.

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26

Salari, Amjad, Giuseppe Caristi, David Barilla, and Alfio Puglisi. "A Variational Approach to Perturbed Discrete Anisotropic Equations." Abstract and Applied Analysis 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/5676138.

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We continue the study of discrete anisotropic equations and we will provide new multiplicity results of the solutions for a discrete anisotropic equation. We investigate the existence of infinitely many solutions for a perturbed discrete anisotropic boundary value problem. The approach is based on variational methods and critical point theory.

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27

Ricker, S. L., N. Sarkar, and K. Rudiet. "A discrete-event systems approach to modeling dextrous manipulation." Robotica 14, no. 5 (1996): 515–25. http://dx.doi.org/10.1017/s0263574700020002.

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SUMMARYTo perform dextrous manipulation efficiently, it is necessary to coordinate the interactions of many component processes. This paper investigates one approach to coordination: discrete-event systems. The applicability of discrete-event systems to the modeling of dextrous manipulation tasks is studied. Discrete-event control theory offers formal methods for determining whether a coordinator of the components can be generated. A representative dextrous manipulation task, the planar Grasp-Lift-Replace task of Howe and Cutkosky, is presented as a discrete-event process. The task is extended to include two-fingered exploratory procedures. The effectiveness of the discrete-event system approach is illustrated through simulations of several test cases.

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28

Barton, P. M., and A. M. Tobias. "Discrete Quantity Approach to Continuous Simulation Modelling." Journal of the Operational Research Society 51, no. 4 (2000): 485. http://dx.doi.org/10.2307/254176.

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29

Sinuany-Stern, Zilla, and Abraham Mehrez. "Discrete Multiattribute Utility Approach to Project Selection." Journal of the Operational Research Society 38, no. 12 (1987): 1133. http://dx.doi.org/10.2307/2582750.

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30

Larkin, E. V., A. N. Privalov, and A. V. Bogomolov. "Discrete Approach to Simulating Synchronized Relay Races." Automatic Documentation and Mathematical Linguistics 54, no. 1 (2020): 43–51. http://dx.doi.org/10.3103/s0005105520010082.

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31

Bobenko, Alexander, and Felix Günther. "Discrete complex analysis – the medial graph approach." Actes des rencontres du CIRM 3, no. 1 (2013): 159–69. http://dx.doi.org/10.5802/acirm.65.

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32

Kucera, V. "Discrete linear control: The polynomial equation approach." IEEE Transactions on Systems, Man, and Cybernetics SMC-15, no. 4 (1985): 595–96. http://dx.doi.org/10.1109/tsmc.1985.6313430.

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33

Tsironis, G. P. "An algebraic approach to discrete breather construction." Journal of Physics A: Mathematical and General 35, no. 4 (2002): 951–57. http://dx.doi.org/10.1088/0305-4470/35/4/307.

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34

G. KULKARNI, ANANT, DR M. F. QURESHI, and DR MANOJ JHA. "Discrete Fourier Transform: Approach To Signal Processing." International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 03, no. 10 (2014): 12341–48. http://dx.doi.org/10.15662/ijareeie.2014.0310005.

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35

Shukla, Ratnesh K., Vattipalli Sameera, Arvind Chaturvedi, and Indu Kapoor. "Videolaryngoscopy: A Discrete Approach to Awake Intubation!" Journal of Neuroanaesthesiology and Critical Care 06, no. 01 (2019): 048. http://dx.doi.org/10.1055/s-0038-1677643.

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36

Pokrovski, Vladimir N. "Extended thermodynamics in a discrete-system approach." European Journal of Physics 26, no. 5 (2005): 769–81. http://dx.doi.org/10.1088/0143-0807/26/5/009.

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37

Blanco, Philip R. "A discrete, energetic approach to rocket propulsion." Physics Education 54, no. 6 (2019): 065001. http://dx.doi.org/10.1088/1361-6552/ab315b.

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38

Danh Le, Ba, Georg Koval, and Cyrille Chazallon. "Discrete element approach in brittle fracture mechanics." Engineering Computations 30, no. 2 (2013): 263–76. http://dx.doi.org/10.1108/02644401311304881.

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39

Djerdir, A., P. Hiebel, E. Voisin, and J. M. Kauffmann. "Discrete approach for 3D magnetic field profiling." IEEE Transactions on Appiled Superconductivity 10, no. 1 (2000): 1360–63. http://dx.doi.org/10.1109/77.828490.

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40

Gugushvili, Shota, Ester Mariucci, and Frank Meulen. "Decompounding discrete distributions: A nonparametric Bayesian approach." Scandinavian Journal of Statistics 47, no. 2 (2019): 464–92. http://dx.doi.org/10.1111/sjos.12413.

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41

Mokni, Karima, Saber Elaydi, Mohamed CH-Chaoui, and Amina Eladdadi. "Discrete evolutionary population models: a new approach." Journal of Biological Dynamics 14, no. 1 (2020): 454–78. http://dx.doi.org/10.1080/17513758.2020.1772997.

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42

Sinuany-Stern, Zilla, and Abraham Mehrez. "Discrete Multiattribute Utility Approach to Project Selection." Journal of the Operational Research Society 38, no. 12 (1987): 1133–39. http://dx.doi.org/10.1057/jors.1987.194.

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43

Marchand-Maillet, Ste´phane. "Binary Digital Image Processing: A Discrete Approach." Journal of Electronic Imaging 10, no. 2 (2001): 576. http://dx.doi.org/10.1117/1.1326456.

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44

Joshi, N., A. Ramani, and B. Grammaticos. "A bilinear approach to discrete Miura transformations." Physics Letters A 249, no. 1-2 (1998): 59–62. http://dx.doi.org/10.1016/s0375-9601(98)00624-0.

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45

Barton, P. M., and A. M. Tobias. "Discrete quantity approach to continuous simulation modelling." Journal of the Operational Research Society 51, no. 4 (2000): 485–89. http://dx.doi.org/10.1057/palgrave.jors.2600880.

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46

Zhaoxia, Leng, Liu Qingfeng, Sun Jinkun, and Wang Huamin. "A Discrete Modeling Approach for Buck Converter." Physics Procedia 24 (2012): 710–16. http://dx.doi.org/10.1016/j.phpro.2012.02.105.

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47

Ben Boubaker, B., B. Haussy, and J. F. Ganghoffer. "Discrete models of woven structures. Macroscopic approach." Composites Part B: Engineering 38, no. 4 (2007): 498–505. http://dx.doi.org/10.1016/j.compositesb.2006.01.007.

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48

WILLIAMS, RUTH M. "DISCRETE QUANTUM GRAVITY: THE REGGE CALCULUS APPROACH." International Journal of Modern Physics B 06, no. 11n12 (1992): 2097–108. http://dx.doi.org/10.1142/s0217979292001043.

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After a brief introduction to Regge calculus, some examples of its application in quantum gravity are described. In particular, the earliest such application, by Ponzano and Regge, is discussed in some detail and it is shown how this leads naturally to current work on invariants of three-manifolds.

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49

Deya, Aurélien. "A Discrete Approach to Rough Parabolic Equations." Electronic Journal of Probability 16 (2011): 1489–518. http://dx.doi.org/10.1214/ejp.v16-919.

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50

Klishin, S. V., and A. F. Revuzhenko. "3D discrete element approach to Janssen’s problem." Journal of Mining Science 50, no. 3 (2014): 417–22. http://dx.doi.org/10.1134/s1062739114030028.

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