Relevant bibliographies by topics / Mathematical pattern

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Mathematical pattern'

Author: Grafiati
Published: 28 May 2022
Last updated: 29 May 2022

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Journal articles on the topic "Mathematical pattern"

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SATO, Atsushi. "Mathematical Methods for Pattern Recognition." IEICE ESS FUNDAMENTALS REVIEW 5, no. 4 (2012): 302–11. http://dx.doi.org/10.1587/essfr.5.302.

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Washburn, Dorothy. "Mathematical Symmetries for Pattern Analysis." Anthropology News 40, no. 3 (March 1999): 26–27. http://dx.doi.org/10.1111/an.1999.40.3.26.3.

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Sanchez, A., A. del Rio, J. L. Valenzuela, and L. Romero. "Mathematical pattern of diagnosis: Muskmelon." Communications in Soil Science and Plant Analysis 23, no. 17-20 (November 1992): 2763–70. http://dx.doi.org/10.1080/00103629209368771.

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Kodituwakku, Saluka R. "Mathematical structures in pattern organizations." Journal of Science of the University of Kelaniya Sri Lanka 4 (January 17, 2011): 46. http://dx.doi.org/10.4038/josuk.v4i0.2697.

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Milton, Graeme W., and Ornella Mattei. "Field patterns: a new mathematical object." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 473, no. 2198 (February 2017): 20160819. http://dx.doi.org/10.1098/rspa.2016.0819.

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Field patterns occur in space–time microstructures such that a disturbance propagating along a characteristic line does not evolve into a cascade of disturbances, but rather concentrates on a pattern of characteristic lines. This pattern is the field pattern. In one spatial direction plus time, the field patterns occur when the slope of the characteristics is, in a sense, commensurate with the space–time microstructure. Field patterns with different spatial shifts do not generally interact, but rather evolve as if they live in separate dimensions, as many dimensions as the number of field patterns. Alternatively one can view a collection as a multi-component potential, with as many components as the number of field patterns. Presumably, if one added a tiny nonlinear term to the wave equation one would then see interactions between these field patterns in the multi-dimensional space that one can consider them to live, or between the different field components of the multi-component potential if one views them that way. As a result of P T -symmetry many of the complex eigenvalues of an appropriately defined transfer matrix have unit norm and hence the corresponding eigenvectors correspond to propagating modes. There are also modes that blow up exponentially with time.
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Trautmann, Laura, and Attila Piros. "A New Mathematical Method for Pattern Development." Periodica Polytechnica Mechanical Engineering 63, no. 1 (November 21, 2018): 44–51. http://dx.doi.org/10.3311/ppme.12648.

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The specialty of the patterns is that they are present in many disciplines, even our world is organized by them. The application of a regular structure in the field of product design may also open new possibilities. An automatized pattern can be used in many industries, such as interior design, paper industry, and so on. In this article we can see an example for utilization in electronic industry. The innovation is the pattern applied to the product, which was created with a new mathematical method. The goal was to develop a fully automatized general method. The description of the Generalized Design Pattern Vector (GDPV) which contains the functions of geometric transformations is also included.
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Chichilnisky, Eduardo J. "A mathematical model of pattern formation." Journal of Theoretical Biology 123, no. 1 (November 1986): 81–101. http://dx.doi.org/10.1016/s0022-5193(86)80237-5.

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Rodrigues, Fátima, and Pedro J. Freitas. "TILES AND IDENTITY BY PATTERN CLASSIFICATION." ARTis ON, no. 8 (December 30, 2018): 69–80. http://dx.doi.org/10.37935/aion.v0i8.218.

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Walled tiles can be figurative or patterned. Whereas the figurative tiles can better be described by theme or author, tile patterns are traditionally classified using more abstract rules that describe either the motif or the pattern itself. In this paper, we present a traditional mathematical classification of plane patterns, the Washburn and Crowe Algorithm, and use it to identify or distinguish tile patterns. We present a complete mathematical classification of the tile patterns present in all places of public access in the Almada region and show how this classification can help recover damaged tiled walls and floors, in order to preserve our heritage. We extend this mathematical analysis to 20th century patterns and quasipatterns, hoping to show that this classification can add to our knowledge of the identity of these patterns.
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Puspasari, Ratih, Setyo Hartanto, Mohamad Gufron, Pradnyo Wijayanti, and Mega Teguh Budiarto. "Frieze Pattern on Shibori Fabric." Journal of Medives : Journal of Mathematics Education IKIP Veteran Semarang 6, no. 1 (January 21, 2022): 67. http://dx.doi.org/10.31331/medivesveteran.v6i1.1904.

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Mathematics and culture are two things that are closely related to the activities of daily human life. Because Mathematics is a form of culture that is integrated in all people's lives. This means that, in culture we can find various kinds of mathematical concepts called ethnomathematics. Shibori is a technique of manipulating cloth originating from Japan, to create patterns through a dyeing method that has been around since the 8th century. The patterns created in Shibori generally depict an asymmetrical shape. In the Shibori motif there are several mathematical elements, one of which is the Frieze Group pattern. The Frieze Group is a subgroup of a symmetry group that is constructed by translation in one direction. The Frieze pattern has 7 (seven) types of patterns consisting of isometric combinations and can be classified as cyclic or dihedral groups. This study is an ethnographic study, with exploration and documentation of Shibori. The data analysis technique chosen is interview, observation and documentation. The research subjects were Shibori fabric craftsmen in Tulungagung district, East Java. The purpose of this research is to further examine the cultural patterns of Shibori Traditional cloth into Frieze patterns, as a way to understand mathematics through culture. The results of the research conducted have shown that there are mathematical concepts (geometry) in the Shibori motif, namely the Frieze pattern F1, F2, F3, F5, F6, F7. Keywords: Group Frizes; Ethnomathematics; Shibori
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Smith, Margaret S., Amy F. Hillen, and Christy L. Catania. "Using Pattern Tasks to Develop Mathematical Understandings and Set Classroom Norms." Mathematics Teaching in the Middle School 13, no. 1 (August 2007): 38–44. http://dx.doi.org/10.5951/mtms.13.1.0038.

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The capacity to reason algebraically is critical in shaping students' future opportunities and, as such, is a central theme of K–12 education (NCTM 2000). One component of algebraic reasoning is “the capacity to recognize patterns and organize data to represent situations in which input is related to output by well-defined functional rules” (Driscoll 1999, p. 2). Geometric pattern tasks can be a useful tool for helping students develop algebraic reasoning, because the tasks provide students with opportunities to build patterns with materials such as toothpicks or pattern blocks. These materials help students “focus on the physical changes and how the pattern is being developed” (Friel, Rachlin, and Doyle 2001, p. 10). Such work might help bridge students' earlier mathematical experiences and lay the foundation for more formal work in algebra (English and Warren 1998; Ferrini-Mundy, Lappan, and Phillips 1997; NCTM 2000). Finally, the relationships between the quantities in pattern tasks can be expressed using symbols, tables, and graphs, as well as words. Thus, pattern tasks can also give students opportunities to make connections among representations—a key component in developing an understanding of function (Knuth 2000).
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Dissertations / Theses on the topic "Mathematical pattern"

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Yang, Xige. "MATHEMATICAL MODELS OF PATTERN FORMATION IN CELL BIOLOGY." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1542236214346341.

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Hunt, Gordon S. "Mathematical modelling of pattern formation in developmental biology." Thesis, Heriot-Watt University, 2013. http://hdl.handle.net/10399/2706.

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The transformation from a single cell to the adult form is one of the remarkable wonders of nature. However, the fundamental mechanisms and interactions involved in this metamorphic change still remain elusive. Due to the complexity of the process, researchers have attempted to exploit simpler systems and, in particular, have focussed on the emergence of varied and spectacular patterns in nature. A number of mathematical models have been proposed to study this problem with one of the most well studied and prominent being the novel concept provided by A.M. Turing in 1952. Turing's simple yet elegant idea consisted of a system of interacting chemicals that reacted and di used such that, under certain conditions, spatial patterns can arise from near homogeneity. However, the implicit assumption that cells respond to respective chemical levels, di erentiating accordingly, is an oversimpli cation and may not capture the true extent of the biology. Here, we propose mathematical models that explicitly introduce cell dynamics into pattern formation mechanisms. The models presented are formulated based on Turing's classical mechanism and are used to gain insight into the signi cance and impact that cells may have in biological phenomena. The rst part of this work considers cell di erentiation and incorporates two conceptually di erent cell commitment processes: asymmetric precursor di erentiation and precursor speci cation. A variety of possible feedback mechanisms are considered with the results of direct activator upregulation suggesting a relaxation of the two species Turing Instability requirement of long range inhibition, short range activation. Moreover, the results also suggest that the type of feedback mechanism should be considered to explain observed biological results. In a separate model, cell signalling is investigated using a discrete mathematical model that is derived from Turing's classical continuous framework. Within this, two types of cell signalling are considered, namely autocrine and juxtacrine signalling, with both showing the attainability of a variety of wavelength patterns that are illustrated and explainable through individual cell activity levels of receptor, ligand and inhibitor. Together with the full system, a reduced two species system is investigated that permits a direct comparison to the classical activator-inhibitor model and the results produce pattern formation in systems considering both one and two di usible species together with an autocrine and/or juxtacrine signalling mechanism. Formulating the model in this way shows a greater applicability to biology with fundamental cell signalling and the interactions involved in Turing type patterning described using clear and concise variables.
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Vemulapalli, Smita. "Audio-video based handwritten mathematical content recognition." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45958.

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Recognizing handwritten mathematical content is a challenging problem, and more so when such content appears in classroom videos. However, given the fact that in such videos the handwritten text and the accompanying audio refer to the same content, a combination of video and audio based recognizer has the potential to significantly improve the content recognition accuracy. This dissertation, using a combination of video and audio based recognizers, focuses on improving the recognition accuracy associated with handwritten mathematical content in such videos. Our approach makes use of a video recognizer as the primary recognizer and a multi-stage assembly, developed as part of this research, is used to facilitate effective combination with an audio recognizer. Specifically, we address the following challenges related to audio-video based handwritten mathematical content recognition: (1) Video Preprocessing - generates a timestamped sequence of segmented characters from the classroom video in the face of occlusions and shadows caused by the instructor, (2) Ambiguity Detection - determines the subset of input characters that may have been incorrectly recognized by the video based recognizer and forwards this subset for disambiguation, (3) A/V Synchronization - establishes correspondence between the handwritten character and the spoken content, (4) A/V Combination - combines the synchronized outputs from the video and audio based recognizers and generates the final recognized character, and (5) Grammar Assisted A/V Based Mathematical Content Recognition - utilizes a base mathematical speech grammar for both character and structure disambiguation. Experiments conducted using videos recorded in a classroom-like environment demonstrate the significant improvements in recognition accuracy that can be achieved using our techniques.
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Zhu, Jia Jun. "A language for financial chart patterns and template-based pattern classification." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950603.

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Ren, Xiaojing, and 任晓晶. "Modeling pattern formation of swimming E.coli." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B43704001.

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Sangster, Margaret. "An exploration of pattern in primary school mathematics." Thesis, University of Surrey, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326524.

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TITONELI, LUANA MIRANDA BALTAZAR. "THE PATTERN OBSERVATION: MATHEMATICAL MODELING THROUGH NUMERICAL SEQUENCES AND GEOMETRIC OBJECTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33077@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE MESTRADO PROFISSIONAL EM MATEMÁTICA EM REDE NACIONAL
Este trabalho é uma análise de padrões que são modelados matematicamente através de conceitos que envolvem as sequências numéricas bem como aspectos geométricos. São consideradas algumas aplicações práticas de conteúdos trabalhados na educação básica, muitas vezes estudados de forma mecânica através de fórmulas que tornam a Matemática enfadonha e até sem sentido para os discentes. O objetivo é mostrar que a Matemática transpõe os limites das salas de aula e que sua beleza pode ser vista em áreas diversas. As ideias e conceitos que envolvem as Progressões Aritméticas e Geométricas, por exemplo, são úteis na resolução de várias situações. A arte musical que está envolta em conhecimentos matemáticos desde os primórdios de seu desenvolvimento. Os estudos desenvolvidos com a sequência de Fibonacci e como está relacionada com a razão áurea e com fenômenos naturais que aparentemente nada teriam em comum. Além disso, a presença tão marcante na natureza das características dos fractais que traçam um padrão de formação para certos elementos naturais. É possível fazer com que o processo ensino- aprendizagem de Matemática torne-se efetivo através da abordagem dos conteúdos de forma prática, o que desperta no aluno o desejo de compreender o que é proposto. Este trabalho é inspirado na frase de Pitágoras: A Matemática é o alfabeto com o qual Deus escreveu o Universo e o que pretende-se é mostrar que esta ciência de fato está em toda a parte e que seu aprendizado pode ser significativo e interessante.
This work is an analysis of patterns that are modeled mathematically through concepts involving numerical sequences as well as geometric aspects. Some practical applications of content worked in basic education are considered, often mechanically studied through formulas that make Mathematics boring and even meaningless to students. The goal is to show that Mathematics transposes the boundaries of classrooms and that its beauty can be seen in several areas. The ideas and concepts that involve Arithmetic and Geometric Progressions, for example, are useful in solving various situations. The musical art that is shrouded in mathematical knowledge from the beginnings of its development. The studies developed with the Fibonacci sequence and how it is related to the golden ratio and with natural phenomena that apparently would have nothing in common. In addition, the presence so striking in the nature of the characteristics of the fractals that lay out a pattern of formation for certain natural elements. It is possible to make the teaching-learning process of Mathematics become effective by approaching the contents in a practical way, which awakens in the student the desire to understand what is proposed. This work is inspired by the phrase of Pythagoras: Mathematics is the alphabet with which God wrote the Universe and what is intended is to show that this science is indeed everywhere and that its learning can be meaningful and interesting.
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Lewis, Mark A. "Analysis of dynamic and stationary biological pattern formation." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276976.

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Crawford, David Michael. "Analysis of biological pattern formation models." Thesis, University of Oxford, 1989. http://ora.ox.ac.uk/objects/uuid:aaa19d3b-c930-4cfa-adc6-8ea498fa5695.

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In this thesis we examine mathematical models which have been suggested as possibile mechanisms for forming certain biological patterns. We analyse them in detail attempting to produce the requisite patterns both analytically and numerically. A reaction diffusion system in two spatial dimensions with anisotropic diffusion is examined in detail and the results compared with certain snakeskin patterns. We examine two other variants to the standard reaction diffusion system: a system where the reaction kinetics and the diffusion coefficients depend upon the cell density suggested as a possible model for the segmentation sequence in Drosophila and a system where the model parameters have one dimensional spatial gradients. We also analyse a model derived from known cellular processes used to model the branching behaviour in bryozoans and show that, in one dimension, such a model can, in theory, give all the required solution behaviour. A genetic switch model for pattern elements on butterfly wings is also briefly examined to obtain expressions for the solution behaviour under coldshock.
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Dabbah, Mohammad A. "Non-reversible mathematical transforms for secure biometric face recognition." Thesis, University of Newcastle upon Tyne, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548002.

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As the demand for higher and more sophisticated security solutions has dramatically increased, a trustworthy and a more intelligent authentication technology has to takeover. That is biometric authentication. Although biometrics provides promising solutions, it is still a pattern recognition and artificial intelligence grand challenge. More importantly, biometric data in itself are vulnerable and requires comprehensive protection that ensures their security at every stage of the authentication procedure including the processing stage. Without this protection biometric authentication cannot replace traditional authentication methods. This protection however cannot be accomplished using conventional cryptographic methods due to the nature of biometric data, its usage and inherited dynamical changes. The new protection method has to transform the biometric data into a secure domain where original information cannot be reversed or retrieved. This secure domain has also to be suitable for accurate authentication performance. In addition, due to the permanence characteristic of the biometric data and the limited number of valid biometrics for each individual, the transform has to be able to generate multiple versions of the same original biometric trait. This to facilitate the replacement and the cancellation of any compromised transformed template with a newer one without compromising the security of the system. Hence the name of the transform that is best known as cancellable biometric. Two cancellable face biometric transforms have been designed, implemented and analysed in this thesis, the Polynomial and Co-occurrence Mapping (PCoM) and the Randomised Radon Signatures (RRS). The PCoM transform is based on high-order polynomial function mappings and co-occurrence matrices derived from the face images. The secure template is formed by the Hadamard product of the generated metrics. A mathematical framework of the two-dimensional Principal Component Analysis (2DPCA) recognition is established for accuracy performance evaluation and analysis. The RRS transform is based on the Radon Transform (RT) and the random projection. The Radon Signature is generated from the parametric Radon domain of the face and mixed with the random projection of the original face image. The transform relies on the extracted signatures and the Johnson-Lindenstrauss lemma for high accuracy performance. The Fisher Discriminant Analysis (FDA) is used for evaluating the accuracy performance of the transformed templates. Each of the transforms has its own security analysis besides a comprehensive security analysis for both. This comprehensive analysis is based on a conventional measure for the Exhaustive Search Attack (ESA) and a new derived measure based on the lower-bound guessing entropy for Smart Statistical Attack (SSA). This entropy measure is shown to be greater than the Shannon lower-bound of the guessing entropy for the transformed templates. This shows that the transforms provide greater security while the ESA analysis demonstrates immunity against brute force attacks. In terms of authentication performance, both transforms have either maintained or improved the accuracy of authentication. The PCoM has maintained the recognition rates for the CMU Advance Multimedia Processing Lab (AMP) and the CMU Pose, Illumination & Expression (PIE) databases at 98.35% and 90.13% respectively while improving the rate for the Olivetti Research Ltd (ORL) database to 97%. The transform has achieved a maximum recognition performance improvement of 4%. Meanwhile, the RRS transform has obtained an outstanding performance by achieving zero error rates for the ORL and PIE databases while improving the rate for the AMP by 37.50%. In addition, the transform has significantly enhanced the genuine and impostor distributions separations by 263.73%, 24.94% and 256.83% for the ORL, AMP and PIE databases while the overlap of these distributions have been completely eliminated for the ORL and PIE databases.
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Books on the topic "Mathematical pattern"

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Pattern puzzles. London: Franklin Watts, 2015.

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1932-, Dutta Majumder D., ed. Fuzzy mathematical approach to pattern recognition. New York: Wiley, 1986.

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Maini, Philip K., and Hans G. Othmer, eds. Mathematical Models for Biological Pattern Formation. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0133-2.

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General pattern theory: A mathematical study of regular structures. Oxford: Clarendon, 1993.

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Lewis, Robert Michael. Why pattern search works. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1998.

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Bowen, Lynda. Pattern block activities. Barrie, Ontario: Exclusive Educational Products, 1989.

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Latorre Carmona, Pedro, J. Salvador Sánchez, and Ana L. N. Fred, eds. Mathematical Methodologies in Pattern Recognition and Machine Learning. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5076-4.

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Wei, Juncheng, and Matthias Winter. Mathematical Aspects of Pattern Formation in Biological Systems. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5526-3.

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Misha, Gromov, Harel-Bellan Annick, Morozova Nadya, Pritchard Linda Louise, and SpringerLink (Online service), eds. Pattern Formation in Morphogenesis: Problems and Mathematical Issues. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Kinetic theory of living pattern. Cambridge: Cambridge University Press, 1993.

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Book chapters on the topic "Mathematical pattern"

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Herman, Gabor T. "Mathematical Background." In Advances in Pattern Recognition, 259–76. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84628-723-7_15.

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Li, Stan Z. "Mathematical MRF Models." In Advances in Pattern Recognition, 1–28. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-279-1_2.

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Silversides, Katherine L. "Pattern Classification." In Encyclopedia of Mathematical Geosciences, 1–3. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_242-1.

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Thakur, Sanchari, LakshmiKanthan Muralikrishnan, Bijal Chudasama, and Alok Porwal. "Pattern Analysis." In Encyclopedia of Mathematical Geosciences, 1–4. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_241-1.

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Negri, Rogério G. "Pattern Recognition." In Encyclopedia of Mathematical Geosciences, 1–3. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_244-1.

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Pach, János, and Micha Sharir. "Extremal combinatorics: Repeated patterns and pattern recognition." In Mathematical Surveys and Monographs, 133–46. Providence, Rhode Island: American Mathematical Society, 2008. http://dx.doi.org/10.1090/surv/152/06.

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Murray, James D. "Neural Models of Pattern Formation." In Mathematical Biology, 481–524. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-662-08539-4_16.

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Murray, James D. "Neural Models of Pattern Formation." In Mathematical Biology, 481–524. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-08542-4_16.

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Stoyan, Dietrich. "Point Pattern Statistics." In Encyclopedia of Mathematical Geosciences, 1–7. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-26050-7_404-1.

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Fink, Gernot A. "Foundations of Mathematical Statistics." In Markov Models for Pattern Recognition, 35–49. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6308-4_3.

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Conference papers on the topic "Mathematical pattern"

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Mohamed, Marina, Nazihah Ismail, Syafiza Saila Samsudin, and Noor Azimah Ibrahim. "Mathematical nature’s pattern in Zinnia Peruviana." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041579.

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Buslaev, Alexander, Marina Yashina, Ruslan Abushov, and Igor Kotovich. "Mathematical Problems of Pattern Recognition for Traffic." In 2010 Seventh International Conference on Information Technology: New Generations. IEEE, 2010. http://dx.doi.org/10.1109/itng.2010.245.

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Takagi, Noboru. "A pattern recognition method of mathematical graphs." In 2010 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2010. http://dx.doi.org/10.1109/icsmc.2010.5642470.

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Gokeri, A. M. "A Mathematical Model For Representing Patterns And Pattern Classes Using Semantic Nets." In 1984 Cambridge Symposium, edited by David P. Casasent and Ernest L. Hall. SPIE, 1985. http://dx.doi.org/10.1117/12.946181.

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Bouchoffra, D., and F. Ykhlef. "Mathematical models for machine learning and pattern recognition." In 2013 8th InternationalWorkshop on Systems, Signal Processing and their Applications (WoSSPA). IEEE, 2013. http://dx.doi.org/10.1109/wosspa.2013.6602331.

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Jia, Qi, Xitong Yang, Weidong Xu, Xuliang Lv, and Jianghua Hu. "Design of Camouflage Pattern Based on Mathematical Morphology." In 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/ammsa-17.2017.35.

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Das, Monidipa, and Soumya K. Ghosh. "Modeling Spatio-temporal Change Pattern using Mathematical Morphology." In CODS '16: IKDD Conference on Data Science, 2016. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2888451.2888458.

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Cotogni, Marco, Claudio Cusano, and Antonino Nocera. "Recursive Recognition of Offline Handwritten Mathematical Expressions." In 2020 25th International Conference on Pattern Recognition (ICPR). IEEE, 2021. http://dx.doi.org/10.1109/icpr48806.2021.9413076.

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Mansor, Mohd Asyraf, Saratha Sathasivam, and Mohd Shareduwan Mohd Kasihmuddin. "Enhanced metaheuristic approach in pattern satisfiability problem." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041557.

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HALL, B. D. "THE GUM TREE DESIGN PATTERN FOR UNCERTAINTY SOFTWARE." In Advanced Mathematical and Computational Tools in Metrology. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702647_0017.

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Reports on the topic "Mathematical pattern"

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Bilous, Vladyslav V., Volodymyr V. Proshkin, and Oksana S. Lytvyn. Development of AR-applications as a promising area of research for students. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4409.

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The article substantiates the importance of using augmented reality in the educational process, in particular, in the study of natural and mathematical disciplines. The essence of AR (augmented reality), characteristics of AR hardware and software, directions and advantages of using AR in the educational process are outlined. It has proven that AR is a unique tool that allows educators to teach the new digital generation in a readable, comprehensible, memorable and memorable format, which is the basis for developing a strong interest in learning. Presented the results of the international study on the quality of education PISA (Programme for International Student Assessment) which stimulated the development of the problem of using AR in mathematics teaching. Within the limits of realization of research work of students of the Borys Grinchenko Kyiv University the AR-application on mathematics is developed. To create it used tools: Android Studio, SDK, ARCore, QR Generator, Math pattern. A number of markers of mathematical objects have been developed that correspond to the school mathematics course (topic: “Polyhedra and Functions, their properties and graphs”). The developed AR tools were introduced into the process of teaching students of the specialty “Mathematics”. Prospects of research in development of a technique of training of separate mathematics themes with use of AR have been defined.
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Markova, Oksana, Serhiy Semerikov, and Maiia Popel. СoCalc as a Learning Tool for Neural Network Simulation in the Special Course “Foundations of Mathematic Informatics”. Sun SITE Central Europe, May 2018. http://dx.doi.org/10.31812/0564/2250.

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The role of neural network modeling in the learning сontent of special course “Foundations of Mathematic Informatics” was discussed. The course was developed for the students of technical universities – future IT-specialists and directed to breaking the gap between theoretic computer science and it’s applied applications: software, system and computing engineering. CoCalc was justified as a learning tool of mathematical informatics in general and neural network modeling in particular. The elements of technique of using CoCalc at studying topic “Neural network and pattern recognition” of the special course “Foundations of Mathematic Informatics” are shown. The program code was presented in a CofeeScript language, which implements the basic components of artificial neural network: neurons, synaptic connections, functions of activations (tangential, sigmoid, stepped) and their derivatives, methods of calculating the network`s weights, etc. The features of the Kolmogorov–Arnold representation theorem application were discussed for determination the architecture of multilayer neural networks. The implementation of the disjunctive logical element and approximation of an arbitrary function using a three-layer neural network were given as an examples. According to the simulation results, a conclusion was made as for the limits of the use of constructed networks, in which they retain their adequacy. The framework topics of individual research of the artificial neural networks is proposed.
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Bednar, Amy. Topological data analysis : an overview. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/40943.

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A growing area of mathematics topological data analysis (TDA) uses fundamental concepts of topology to analyze complex, high-dimensional data. A topological network represents the data, and the TDA uses the network to analyze the shape of the data and identify features in the network that correspond to patterns in the data. These patterns extract knowledge from the data. TDA provides a framework to advance machine learning’s ability to understand and analyze large, complex data. This paper provides background information about TDA, TDA applications for large data sets, and details related to the investigation and implementation of existing tools and environments.
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Duch, Michael. Performing Hanne Darboven's Opus 17a and long duration minimalist music. Norges Musikkhøgskole, August 2018. http://dx.doi.org/10.22501/nmh-ar.481276.

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Hanne Darboven’s (1941-2009) Opus 17a is a composition for solo double bass that is rarely performed due to the physical and mental challenges involved in its performance. It is one of four opuses from the composers monumental 1008 page Wünschkonzert (1984), and was composed during her period of making “mathematical music” based on mathematical systems where numbers were assigned to certain notes and translated to musical scores. It can be described as large-scale minimalism and it is highly repetitive, but even though the same notes and intervals keep repeating, the patterns slightly change throughout the piece. This is an attempt to unfold the many challenges of both interpreting, preparing and performing this 70 minute long solo piece for double bass consisting of a continuous stream of eight notes. It is largely based on my own experiences of preparing, rehearsing and performing Opus 17a, but also on interviews I have conducted with fellow bass players Robert Black and Tom Peters, who have both made recordings of this piece as well as having performed it live. One is met with few instrumental technical challenges such as fingering, string crossing and bowing when performing Opus 17a, but because of its long duration what one normally would take for granted could possibly prove to be challenging.
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Nelson, Gena, Angela Crawford, and Jessica Hunt. A Systematic Review of Research Syntheses for Students with Mathematics Learning Disabilities and Difficulties. Boise State University, Albertsons Library, January 2022. http://dx.doi.org/10.18122/sped.143.boisestate.

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The purpose of this document is to provide readers with the coding protocol that authors used to code 36 research syntheses (including meta-analyses, evidence-based reviews, and quantitative systematic reviews) focused on mathematics interventions for students with learning disabilities (LD), mathematics learning disabilities (MLD), and mathematics difficulties (MD). The purpose of the systematic review of mathematics intervention syntheses was to identify patterns and gaps in content areas, instructional strategies, effect sizes, and definitions of LD, MLD, and MD. We searched the literature for research syntheses published between 2000 and 2020 and used rigorous inclusion criteria in our literature review process. We evaluated 36 syntheses that included 836 studies with 32,495 participants. We coded each synthesis for variables across seven categories including: publication codes (authors, year, journal), inclusion and exclusion criteria, content area focus, instructional strategy focus, sample size, methodological information, and results. The mean interrater reliability across all codes using this coding protocol was 90.3%. Although each synthesis stated a focus on LD, MLD, or MD, very few students with LD or MLD were included, and authors’ operational definitions of disability and risk varied. Syntheses predominantly focused on word problem solving, fractions, computer- assisted learning, and schema-based instruction. Syntheses reported wide variation in effectiveness, content areas, and instructional strategies. Finally, our results indicate the majority of syntheses report achievement outcomes, but very few syntheses report on other outcomes (e.g., social validity, strategy use). We discuss how the results of this comprehensive review can guide researchers in expanding the knowledge base on mathematics interventions. The systematic review that results from this coding process is accepted for publication and in press at Learning Disabilities Research and Practice.
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Wallach, Rony, Tammo Steenhuis, Ellen R. Graber, David DiCarlo, and Yves Parlange. Unstable Flow in Repellent and Sub-critically Repellent Soils: Theory and Management Implications. United States Department of Agriculture, November 2012. http://dx.doi.org/10.32747/2012.7592643.bard.

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Water repellency causes unstable wetting fronts that result in water moving in preferential flowpaths through homogeneous soils as well in structured soils where macropores enhance the preferential flow pattern. Water repellency is typically associated with extended water ponding on the soil surface, but we have found that repellency is important even before the water ponds. Preferential flow fingers can form under conditions where the contact angle is less than 90o, but greater than 0o. This means that even when the soil is considered wettable (i.e., immediate penetration of water), water distribution in the soil profile can be significantly non-uniform. Our work concentrated on various aspects of this subject, with an emphasis on visualizing water and colloid flow in soil, characterizing mathematically the important processes that affect water distribution, and defining the chemical components that are important for determining contact angle. Five papers have been published to date from this research, and there are a number of papers in various stages of preparation.
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Patel, Reena. Complex network analysis for early detection of failure mechanisms in resilient bio-structures. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41042.

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Bio-structures owe their remarkable mechanical properties to their hierarchical geometrical arrangement as well as heterogeneous material properties. This dissertation presents an integrated, interdisciplinary approach that employs computational mechanics combined with flow network analysis to gain fundamental insights into the failure mechanisms of high performance, light-weight, structured composites by examining the stress flow patterns formed in the nascent stages of loading for the rostrum of the paddlefish. The data required for the flow network analysis was generated from the finite element analysis of the rostrum. The flow network was weighted based on the parameter of interest, which is stress in the current study. The changing kinematics of the structural system was provided as input to the algorithm that computes the minimum-cut of the flow network. The proposed approach was verified using two classical problems three- and four-point bending of a simply-supported concrete beam. The current study also addresses the methodology used to prepare data in an appropriate format for a seamless transition from finite element binary database files to the abstract mathematical domain needed for the network flow analysis. A robust, platform-independent procedure was developed that efficiently handles the large datasets produced by the finite element simulations. Results from computational mechanics using Abaqus and complex network analysis are presented.
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