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Journal articles on the topic 'Pattern'

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Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Tanno, Tomohiro, Kazumasa Horie, Takaaki Kobayashi, and Masahiko Morita. "Effect of Patten Coding on Pattern Classification Neural Networks." International Journal of Machine Learning and Computing 5, no. 4 (August 2015): 339–43. http://dx.doi.org/10.7763/ijmlc.2015.v5.531.

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OH, Ibewuike, Olotu EJ, and Paul JN. "Dermatoglyphic Digital Patterns and Pattern Intensity Index in Uterine Leiomyoma." International Journal of Pharma Research and Health Sciences 7, no. 2 (2019): 2923–27. http://dx.doi.org/10.21276/ijprhs.2019.02.01.

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3

Short, Nicholas. "Patterns of pattern formation." Nature 378, no. 6555 (November 1995): 331. http://dx.doi.org/10.1038/378331a0.

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4

Sze-To, Antonio, and Andrew K. C. Wong. "Discovering Patterns From Sequences Using Pattern-Directed Aligned Pattern Clustering." IEEE Transactions on NanoBioscience 17, no. 3 (July 2018): 209–18. http://dx.doi.org/10.1109/tnb.2018.2845741.

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Erwig, Martin, and Simon Peyton Jones. "Pattern Guards and Transformational Patterns." Electronic Notes in Theoretical Computer Science 41, no. 1 (August 2001): 3. http://dx.doi.org/10.1016/s1571-0661(05)80540-7.

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6

S., Sivaranjani. "Detecting Congestion Patterns in Spatio Temporal Traffic Data Using Frequent Pattern Mining." Bonfring International Journal of Networking Technologies and Applications 5, no. 1 (March 30, 2018): 21–23. http://dx.doi.org/10.9756/bijnta.8372.

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7

Peng, Hui. "Non-Interference Pattern Evolving to Interference Pattern; Non-Diffraction Pattern Evolving to Diffraction Pattern; Two Non-Diffraction Patterns Evolving to Interference-Pattern-Embedded-in-Diffraction Patterns--- Wave-Wave Interference to Photon-Photon Interaction." International Journal of Physics 12, no. 1 (February 4, 2024): 40–64. http://dx.doi.org/10.12691/ijp-12-1-4.

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8

Han, Jiawei, and Jian Pei. "Mining frequent patterns by pattern-growth." ACM SIGKDD Explorations Newsletter 2, no. 2 (December 2000): 14–20. http://dx.doi.org/10.1145/380995.381002.

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Humphrey, G. Keith, Peter C. Dodwell, and Victor F. Emerson. "Pattern-contingent color aftereffects on noninduced patterns." Perception & Psychophysics 45, no. 2 (March 1989): 97–109. http://dx.doi.org/10.3758/bf03208044.

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Zhou, Jianjun, Jorg Sander, and Guohui Lin. "Efficient composite pattern finding from monad patterns." International Journal of Bioinformatics Research and Applications 3, no. 1 (2007): 86. http://dx.doi.org/10.1504/ijbra.2007.011836.

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Ma, Qian, and Jingfeng Guo. "Mining Multi-Patterns in Pattern-Based Clustering." Procedia Engineering 29 (2012): 3179–83. http://dx.doi.org/10.1016/j.proeng.2012.01.462.

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Huang, Hao, Xindong Wu, and Richard Relue. "Mining frequent patterns with the pattern tree." New Generation Computing 23, no. 4 (December 2005): 315–37. http://dx.doi.org/10.1007/bf03037636.

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Poirson, Allen B., and Brian A. Wandell. "Appearance of colored patterns: pattern–color separability." Journal of the Optical Society of America A 10, no. 12 (December 1, 1993): 2458. http://dx.doi.org/10.1364/josaa.10.002458.

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14

Koyama, Motoaki. "Pattern recognition apparatus with retrieval reference patterns." Journal of the Acoustical Society of America 95, no. 1 (January 1994): 592. http://dx.doi.org/10.1121/1.408283.

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HAYASHI, S., J. KATADA, R. SAKAMOTO, T. KOBAYASHI, and M. SAEKI. "Design Pattern Detection by Using Meta Patterns." IEICE Transactions on Information and Systems E91-D, no. 4 (April 1, 2008): 933–44. http://dx.doi.org/10.1093/ietisy/e91-d.4.933.

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Hill, Andrea A., and Gretchen E. Diehl. "Identifying the Patterns of Pattern Recognition Receptors." Immunity 49, no. 3 (September 2018): 389–91. http://dx.doi.org/10.1016/j.immuni.2018.08.027.

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Mikhailov, Alexei. "Indexing-Based Pattern Recognition." Advanced Materials Research 403-408 (November 2011): 5254–59. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.5254.

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The paper discusses the mathematics of pattern indexing and its applications to recognition of visual patterns and classification of objects that are represented by objects-properties matrices. It is shown that (a) pattern indexes can be represented by collections of inverted patterns, (b) solutions to pattern classification problems can be found as intersections of inverted patterns and, thus, matching of original patterns avoided.

18

Thakur, Ramjeevan Singh, and Vivek Tiwari. "Pattern Retrieval through Classification from Pattern Warehouse." International Journal of Business Intelligence Research 5, no. 3 (July 2014): 1–10. http://dx.doi.org/10.4018/ijbir.2014070101.

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The pattern is special kinds of data which are created through various data mining techniques and stored in the pattern warehouse through a specialized pattern management system (PMS). Pattern warehouse makes the pattern non-volatile or persists. Now a day's persistent pattern retrieval is a very new and important issue. This paper focuses on problems and challenges with pattern retrieval. One can see the applicability of classification in pattern retrieval as an opportunity and trying to bring attention to probable issues and challenges behind the physical implementation of this concept. This paper concluded that the applicability of classification in pattern retrieval is well feasible. It has also discussed that how of pattern classification is different with data's classification. Classification method should be defined in such a way that it can handle pattern efficiently. So far, little emphasis has been posed on developing an overall classification system for pattern retrieval. This paper concerns only association kinds of patterns. It has presented some issues regarding (i) Decision boundary of pattern classes. (ii) Problem of calculating a reliable estimate of pattern classes. (iii) How to define class boundary (iv) How to handle overlapping of pattern classes (v) Parameter selection for pattern classes estimation (v) Preprocessing of patterns (vi) How to handle classification on demand. (vii) Updating of pattern classes (vii) Finding optimal test conditions.

19

Ramdan, Deden. "MANAGEMENT FAMILY COMMUNICATION PATTERNS OF FEMALE TEACHERS AT STATE SECONDARY SCHOOL WEST JAVA." Jurnal Riset Bisnis dan Manajemen 15, no. 2 (August 13, 2022): 142–46. http://dx.doi.org/10.23969/jrbm.v15i2.9973.

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This study entitled “Family Communication Patterns Of Female Teachers At State Secondary School 15 Bandung City District West Java Province”. Female teachers who become informants are those whor are married and have children. The purpose of this study was to find out how or the pattern of communication carried out by a female teachers in childcare. And which family communication pattern will they use in parenting. The method used in this study is a qualitative research method with the theory of family communication pattern. With qualitative methods, researchers can obtain data using in-depth interview techniques so that the it is hoped that the data obtained will be able to complement and produce comprehensive qualitative descriptive data. The results obtained from this study are the communication patters that exist between female teachers and their families, where a pluralistic pattern is chosen from the four patterns contained in the concept of family communication, as a result of this entire research.

20

Darapureddy, Nagadevi, Nagaprakash Karatapu, and Tirumala Krishna Battula. "Local Derivative Vector Pattern: Hybrid Pattern for Content-Based Medical Image Retrieval." Review of Computer Engineering Studies 7, no. 4 (December 31, 2020): 79–86. http://dx.doi.org/10.18280/rces.070401.

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This paper examines a hybrid pattern i.e. Local derivative Vector pattern and comparasion of this pattern over other different patterns for content-based medical image retrieval. In recent years Pattern-based texture analysis has significant popularity for a variety of tasks like image recognition, image and texture classification, and object detection, etc. In literature, different patterns exist for texture analysis. This paper aims at forming a hybrid pattern compared in terms of precision, recall and F1-score with different patterns like Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Completed Local Binary Pattern (CLBP), Local Tetra Pattern (LTrP), Local Vector Pattern (LVP) and Local Anisotropic Pattern (LAP) which were applied on medical images for image retrieval. The proposed method is evaluated on different modalities of medical images. The results of the proposed hybrid pattern show biased performance compared to the state-of-the-art. So this can further extended with other pattern to form a hybrid pattern.

21

Li, Yun, and Saihua Cai. "Detecting Outliers in Data Streams Based on Minimum Rare Pattern Mining and Pattern Matching." Information Technology and Control 51, no. 2 (June 23, 2022): 268–82. http://dx.doi.org/10.5755/j01.itc.51.2.30524.

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Outliers are the major factors to influence the accuracy of data-based processing, thus, they must be discovered from collected datasets to guarantee data security. With the widely use of sensors and other monitoring equipment, data streams are becoming the main form of data. However, the huge scale of data streams results in the number of mined rare patterns very large, which makes it hard to effectively detect outliers through pattern-based outlier detection methods. Since minimal rare patterns (MRPs) can represent rare patterns and the number is much smaller, therefore, the use of MRPs on outlier detection can short the time consumption. Based on this idea, this paper proposes an outlier detection approach based on minimal rare pattern, called ODMRP, which is composed of pattern mining phase and pattern matching phase. Specifically, in the pattern mining phase, an improved minimal rare pattern mining algorithm, namely MRPM, is proposed to mine the MRPs from data streams; It first constructs two matrix structures to store information of transactions and frequent 2-patterns, and then apply “pattern extension” operations to extend frequent 2-patterns to longer patterns, at the same time, rare patterns are removed to prevent them participating into “pattern extension” operation to reduce meaningless time cost; In the pattern matching phase, we use the IM-Sunday algorithm to match the mined MRPs with the patterns stored in outlier pattern library, to find potential outliers. Extensive experimental studies show that the proposed ODMRP method can accurately detect outliers from data streams in less overhead.

22

Lou, Bu Ye, and Shuo Weng. "Improvement of PRG Pattern by Using Ajax Technology." Applied Mechanics and Materials 336-338 (July 2013): 1992–96. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.1992.

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The study discusses the fusion technology of PRG pattern and Ajax and its applications. After analyzing the natures and shortcomings of PRG pattern, it introduces improvement of PRG pattern by using Ajax technology, and proposes three patterns: A-P pattern, A-PRG pattern and A-PG pattern. These patterns can make full use of the characteristics of Ajax technology, which can send asynchronous requests to the server and partially update page, and solve the shortcomings of PRG pattern. Finally, the implementation technology of the patterns in JSF application is presented; the applicable scenarios and constraints of the patterns are elaborated.

23

Eschenbach, Carolyn A., Frank J. Hall, and Zhongshan Li. "From real to complex sign pattern matrices." Bulletin of the Australian Mathematical Society 57, no. 1 (February 1998): 159–72. http://dx.doi.org/10.1017/s0004972700031518.

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This paper extends some fundamental concepts of qualitative matrix analysis from sign pattern classes of real matrices to sign pattern classes of complex matrices. A complex sign pattern and its corresponding sign pattern class are defined in such a way that they generalize the definitions of a (real) sign pattern and its corresponding sign pattern class. A survey of several qualitative results on complex sign patterns is presented. In particular, sign nonsingular complex patterns are investigated. The type of region in the complex plane representing the distribution of the determinants of the matrices in the sign pattern class of a sign nonsingular complex pattern is identified. Cyclically nonnegative complex patterns and complex patterns that are signature similar to nonnegative patterns are characterized. Extensions of sign stable and sign semistable patterns from the real to the complex case are given. Results on ray patterns are also obtained. Finally, many open questions are mentioned.

24

Huang, K. Y., K. S. Fu, S. W. Cheng, and Z. S. Lin. "Syntactic pattern recognition and Hough transformation for reconstruction of seismic patterns." GEOPHYSICS 52, no. 12 (December 1987): 1612–20. http://dx.doi.org/10.1190/1.1442278.

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Hierarchical syntactic pattern recognition and the Hough transformation are proposed for automatic recognition and reconstruction of seismic patterns in seismograms. In the first step, the patterns are hierarchically decomposed or recognized into single patterns, straight‐line patterns, or hyperbolic patterns, using syntactic pattern recognition. In the second step, the Hough transformation technique is used for reconstruction, pattern by pattern. The system of syntactic seismic pattern recognition includes envelope generation, a linking process in the seismogram, segmentation, primitive recognition, grammatical inference, and syntax analysis. The seismic patterns are automatically recognized and reconstructed.

25

ASMAWATI, ASMAWATI, MURSIDAH MURSIDAH, and SYARIFAH AIDA. "PENENTUAN POLA PRODUKSI MEMINIMALISASI BIAYA PADA USAHA PENGOLAHAN DODOL BANDOL DI KECAMATAN SAMBUTAN KOTA SAMARINDA (The Determination of Production Pattern to Minimize Cost at Processing Business of Dodol Bandol in Sambutan Subcity, Samarinda City)." JURNAL AGRIBISNIS DAN KOMUNIKASI PERTANIAN (Journal of Agribusiness and Agricultural Communication) 3, no. 1 (December 21, 2019): 1. http://dx.doi.org/10.35941/jakp.3.1.2020.2985.1-8.

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Processing business of dodol Bandol is an agroindustry which processes raw materials from agricultural products. The different of production patterns will cause the different of production cost. The purposes of this research were to know the production patterns of dodol Bandol, incremental costs of every production pattern of dodol Bandol, the minimum production cost of dodol Bandol. Methods of data analysis were descriptive and quantitative. Incremental cost was calculated for every production pattern and then it was determined the production pattern with minimum cost. Production pattern that used is a bumpy production pattern. Incremental costs of every production patterns were constant production pattern of IDR583,120.00, bumpy production pattern of IDR117,000.00, and moderat production pattern of IDR357,560.00. The right production pattern that could be applied on processing of dodol Bandol is bumpy production pattern because it has the lowest incremental cost among the third production patterns.

26

Nenojata, Yohanes J., Gratiana Sama, and Yuliana M. D. K. Kara. "SENTENCE PATTERN USED IN CALUM SCOTT’S SONG LYRICH." Lantern: Journal of Language and Literature 9, no. 2 (September 1, 2023): 72–81. http://dx.doi.org/10.37478/lantern.v9i2.3965.

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Sentence patterns and sentence types are an inseparable unit where each type of sentence contains several sentence patterns. In general, some researchers analyzed sentence patterns in a short story, speech text, news text and others. But in this study will analyze sentence patterns and sentence types in two song lyrics by Calum Scott. Usually in a song lyrics consists of phrases, clauses, and sentences, but the study will analyze how many sentences are there. This study aims to find sentence patterns and sentence types in the two song lyrics. This study uses a qualitative method. The results of the study show that there are six sentence patterns and six types of sentences found in the two songs. No Matter What's first song with details as follows; pattern I (S+VT+DO), pattern II (S+int.V), pattern, pattern IV (S+intr.V+SP), pattern V (S+com.V+DO+OP), and pattern IV (S+pre.V+PC). The second song is Dancing on My Own with the following details; pattern I (S+VT+DO), pattern II (S+int.V), pattern III (S+dist.V+DO+IO), pattern IV (S+intr.V+SP), pattern V (S+com.V+DO+OP), and pattern VI (S+pre.V+PC). While the types of sentences from the two songs, No Matter What and Dancing on My Own there are four types. They are simple sentence, compound sentence, complex sentence, and compound complex sentence.

27

Liu, Qian, and Ming Chen. "Frequent Pattern Mining Based on Pattern Space Division in Map/Reduce Cluster." Advanced Materials Research 588-589 (November 2012): 2038–41. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.2038.

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By means of pattern space division and based on Map/Reduce, the problem of processing the many-to-many corresponding relationship between the data set and the patterns set is converted to the problem of processing the many-to-many corresponding relationship between the data subsets and the pattern subspaces associated with the frequent 1-itemsets. Thus, the scale of the intermediate key/value pairs set is reduced so dramatically that the problem of single Map node bottleneck which results from combinatorial explosion of candidate patterns space is avoided. Over three rounds of Map/Reduce tasks, the pattern space is constructed and divided, the filtering rules is established and employed, father more, the mining of frequent patterns is realized in each pattern subspace independently. By making the best of both the universal trait of the entire pattern space and the individuality of each pattern subspace, the optimized non-recursive algorithm is designed and implemented to improve the efficiency of mining phase.

28

Dence, Thomas. "Pattern Busting." Mathematics Teacher 98, no. 4 (November 2004): 254–59. http://dx.doi.org/10.5951/mt.98.4.0254.

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Even though sequences of numbers may follow an apparent pattern for a long period, that doesn't mean the pattern will continue forever. Geometric and algebraic sequences are used in examples as well as trig functions and prime number patterns.

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Chai, Xin, Dan Yang, Jingyu Liu, Yan Li, and Youxi Wu. "Top-k sequence pattern mining with non-overlapping condition." Filomat 32, no. 5 (2018): 1703–10. http://dx.doi.org/10.2298/fil1805703c.

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Pattern mining has been widely applied in many fields. Users often mine a large number of patterns. However, most of these are difficult to apply in real applications. Top-k pattern mining, which involves finding the most frequent k patterns, is an effective strategy, because the more frequently a pattern occurs, the more likely they are to be important for users. However, top-k mining can only mine short patterns in mining applications with the Apriori property. It is well-known that short patterns contain less information than long patterns. In this paper, we focus on mining top-k sequence patterns of each pattern length. We propose an effective algorithm, named NOSTOPK (non-overlapping sequence pattern mining for top-k). The algorithm calculates the support of a pattern using a Nettree data structure, which has been introduced to tackle various types of pattern matching and sequence pattern mining issues. We find the top k patterns of length len, and calculate the supports of the corresponding k x |?| super-patterns of length len + 1 to discover the new top k super-patterns with len + 1. Experimental results demonstrate that the algorithm achieves a better performance than comparable algorithms.

30

P., Prathamesh, Shreya Bondre, and Neha Gavankar. "Honey-patterns: Recognizing Pattern based Attacks on Websites." International Journal of Computer Applications 161, no. 9 (March 15, 2017): 8–11. http://dx.doi.org/10.5120/ijca2017913202.

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31

Sagar, Sai, Nikhil Srivastava, and Nitin Arora. "Browsing Pattern Analysis: What user browsing Patterns Indicate." International Journal of Computer Applications 180, no. 2 (December 15, 2017): 16–20. http://dx.doi.org/10.5120/ijca2017915937.

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32

Ellaway, Rachel H., and Joanna Bates. "Exploring patterns and pattern languages of medical education." Medical Education 49, no. 12 (November 27, 2015): 1189–96. http://dx.doi.org/10.1111/medu.12836.

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Poonam Sharma and Gudla Balakrishna. "PreﬁxSpan: Mining Sequential Patterns by Preﬁx-Projected Pattern." International Journal of Computer Science & Engineering Survey 2, no. 4 (November 30, 2011): 111–22. http://dx.doi.org/10.5121/ijcses.2011.2408.

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Wyse, Gordon A. "Central pattern generation underlying Limulus rhythmic behavior patterns." Current Zoology 56, no. 5 (October 1, 2010): 537–49. http://dx.doi.org/10.1093/czoolo/56.5.537.

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Abstract Many behavioral activities of the horseshoe crab Limulus are rhythmic, and most of these are produced in large part by central pattern generators within the CNS. The chain of opisthosomal ('abdominal') ganglia controls gill movements of ventilation and gill cleaning, and the prosomal ring of fused ganglia (brain and segmental 'thoracic' ganglia) controls generation of feeding and locomotor movements of the legs. Both the opisthosomal CNS and the prosomal CNS can generate behaviorally appropriate patterns of motor output in isolation, without movements or sensory input. Preparations of the isolated opisthosomal CNS generate rhythmic output patterns of motor activity characterized as fictive ventilatory and gill cleaning rhythms. Moreover, CNS preparations also express longer-term patterns, such as intermittent ventilation or sequential bouts of ventilation and gill cleaning. Such longer-term patterns are commonly observed in intact animals. The isolated prosomal CNS does not spontaneously generate the activity patterns characteristic of walking, swimming, and feeding. However, perfusion of octopamine in the isolated prosomal CNS activates central pattern generators underlying rhythmic chewing movements, and injection of octopamine into intact Limulus promotes the chewing pattern of feeding, whether or not food is presented. Our understanding of the ability of neuromodulators such as octopamine to elicit or alter central motor programs may help to clarify the central neural circuits of pattern generation that produce and coordinate these rhythmic behaviors.

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Sikdar, B. K., N. Ganguly, and P. P. Chaudhuri. "Generation of Test Patterns Without Prohibited Pattern Set." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 23, no. 12 (December 2004): 1650–60. http://dx.doi.org/10.1109/tcad.2004.837730.

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Chen, Chien-Chung, and John M. Foley. "Pattern detection: interactions between oriented and concentric patterns." Vision Research 44, no. 9 (April 2004): 915–24. http://dx.doi.org/10.1016/j.visres.2003.11.017.

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JANSON, SVANTE. "Patterns in Random Permutations Avoiding the Pattern 132." Combinatorics, Probability and Computing 26, no. 1 (May 18, 2016): 24–51. http://dx.doi.org/10.1017/s0963548316000171.

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We consider a random permutation drawn from the set of 132-avoiding permutations of lengthnand show that the number of occurrences of another pattern σ has a limit distribution, after scaling bynλ(σ)/2, where λ(σ) is the length of σ plus the number of descents. The limit is not normal, and can be expressed as a functional of a Brownian excursion. Moments can be found by recursion.

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Kiran, T. Ravi, Ch Sai Priyanka Rani, K. Bhoomika, K. Madhuri, and L. Naresh. "An Efficient Pattern Discovery Over Long Text Patterns." International Journal of Engineering Trends and Technology 10, no. 9 (April 25, 2014): 470–73. http://dx.doi.org/10.14445/22315381/ijett-v10p290.

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Tlidi, M., M. Haelterman, and P. Mandel. "3D patterns and pattern selection in optical bistability." Europhysics Letters (EPL) 42, no. 5 (June 1, 1998): 505–10. http://dx.doi.org/10.1209/epl/i1998-00275-y.

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Abdollahifard, Mohammad J., and Karim Faez. "Stochastic simulation of patterns using Bayesian pattern modeling." Computational Geosciences 17, no. 1 (October 5, 2012): 99–116. http://dx.doi.org/10.1007/s10596-012-9319-x.

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Janson, Svante. "Patterns in random permutations avoiding the pattern 321." Random Structures & Algorithms 55, no. 2 (November 14, 2018): 249–70. http://dx.doi.org/10.1002/rsa.20806.

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Van, Trang, Atsuo Yoshitaka, and Bac Le. "Mining web access patterns with super-pattern constraint." Applied Intelligence 48, no. 11 (May 2, 2018): 3902–14. http://dx.doi.org/10.1007/s10489-018-1182-6.

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Helfman, Jonathan. "Dotplot patterns: A literal look at pattern languages." Theory and Practice of Object Systems 2, no. 1 (1996): 31–41. http://dx.doi.org/10.1002/(sici)1096-9942(1996)2:1<31::aid-tapo3>3.0.co;2-a.

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Manossoh, Jeniver R., Nurmin Samola, and Sanerita T. Olii. "A SYNTACTICAL ANALYSIS ON SENTENCE PATTERNS USED IN BARACK OBAMA SPEECH." Journal of English Culture, Language, Literature and Education 10, no. 1 (June 10, 2022): 201–25. http://dx.doi.org/10.53682/eclue.v10i1.4172.

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This study focuses on 9 basic sentence patterns that used in Barack Obama speech which he delivered when visited Universitas Indonesia Jakarta. The aim of the study is to find out how many sentence patterns that used in Barack Obama Speech. This study used qualitative research which the researcher analyzed through the script. The results of the study showed that there were 8 sentence patterns in the speech as follows, they were pattern 1 (9 sentences), pattern 2 (2 sentences), pattern 3 (26 sentences), pattern 4 (1 sentence), pattern 6 (20 sentences), pattern 7 (103 sentences), pattern 8 (1 sentence), pattern 9 (2 sentences). Based on the result, it can be concluded that the pattern 7 were most dominant of the other pattern, then there was 1 pattern was not found, pattern 5. In this research there were various kinds of sentences pattern in 1 speech that can be used to help you improve writing skill, for English learners especially for the future researchers

45

Huang, Hua, Yi Lai Zhang, and Yu Ming Zhai. "Analysis of Ceramic Pattern Case." Advanced Materials Research 186 (January 2011): 41–45. http://dx.doi.org/10.4028/www.scientific.net/amr.186.41.

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By analyzing and summarizing a large number of ceramic patterns, the paper introduces a so-called “pattern case” concept. A reusable component is extracted from a pattern, forms a pattern primitive, and is stored in the library of pattern primitives. Such a pattern abstract structure that doesn’t depend on any concrete data is referred to as a “case”. The paper gives a detailed analysis of several common ceramic patterns cases. Our work places a certain theoretical foundation for achieving intelligence of computerized ceramic pattern design.

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Yun, Unil, Gwangbum Pyun, and Eunchul Yoon. "Efficient Mining of Robust Closed Weighted Sequential Patterns Without Information Loss." International Journal on Artificial Intelligence Tools 24, no. 01 (February 2015): 1550007. http://dx.doi.org/10.1142/s0218213015500074.

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Sequential pattern mining has become one of the most important topics in data mining. It has broad applications such as analyzing customer purchase data, Web access patterns, network traffic data, DNA sequencing, and so on. Previous studies have concentrated on reducing redundant patterns among the sequential patterns, and on finding meaningful patterns from huge datasets. In sequential pattern mining, closed sequential pattern mining and weighted sequential pattern mining are the two main approaches to perform mining tasks. This is because closed sequential pattern mining finds representative sequential patterns which show exactly the same knowledge as the complete set of frequent sequential patterns, and weight-based sequential pattern mining discovers important sequential patterns by considering the importance of each sequential pattern. In this paper, we study the problem of mining robust closed weighted sequential patterns by integrating two paradigms from large sequence databases. We first show that the joining order between the weight constraints and the closure property in sequential pattern mining leads to different sets of results. From our analysis of joining orders, we suggest robust closed weighted sequential pattern mining without information loss, and present how to discover representative important sequential patterns without information loss. Through performance tests, we show that our approach gives high performance in terms of efficiency, effectiveness, memory usage, and scalability.

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Heather, McLeod. "Artist Statement: Pattern on Pattern." Canadian Review of Art Education / Revue canadienne d’éducation artistique 47, no. 1 (December 30, 2020): i. http://dx.doi.org/10.26443/crae.v47i1.109.

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Mueller, Bernardo, and Marcos Paulo R. Correia. "Pattern making and pattern breaking." Revista Brasileira de Inovação 21 (September 13, 2022): e022015. http://dx.doi.org/10.20396/rbi.v21i00.8667409.

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How do new ideas emerge in academic contexts and what forces determine which ideas get selected and which are forgotten? We analyze all papers presented at the ANPEC Brazilian Economics National Meetings from 2013 to 2019 using topic modeling and Kullback-Leibler divergence to measure novelty and resonance. In contrast to simply counting citations or reference combinations, these methods explore the Shannon information in the actual texts to detect the rise of new patterns and whether these patterns persist once they have been established. We find that novelty is highly correlated with transience so that most new ideas are quickly forgotten. However, of the ideas that persist, those that are more novel have higher impact. We show that our text-based measure of impact is correlated with subsequent citations.

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Cheeney, R. F. "Pattern recognition and pattern analysis." Geological Magazine 122, no. 2 (March 1985): 203–4. http://dx.doi.org/10.1017/s0016756800031150.

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Câmpeanu, Cezar, and Sheng Yu. "Pattern expressions and pattern automata." Information Processing Letters 92, no. 6 (December 2004): 267–74. http://dx.doi.org/10.1016/j.ipl.2004.09.007.

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