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Journal articles on the topic 'Patterns'

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Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

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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2

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

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3

Desli, Despoina, and Dimitra Gaitaneri. "Η κατανόηση των μαθηματικών μοτίβων από παιδιά Γ’ και Δ’ δημοτικού και οι στρατηγικές σκέψης τους." Preschool and Primary Education 5, no. 1 (March 6, 2017): 63. http://dx.doi.org/10.12681/ppej.10216.

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The aim of the present study was to examine how children attending the middle years of the primary school understand and extend mathematical patterns. A total of 90 students coming from grades C (N=48) and D (N=42) were asked 21 pattern tasks that were designed on the basis of two main categories (visual patterns and number patterns) and were further divided into: a) repeating visual and repeating number patterns, and b) growing visual and growing number patterns. Participants were asked to identify the pattern rules and extend the patterns by filling the missing steps. They also had to make a pattern on their own. Overall results showed similarly high performance on visual and number pattern tasks. However, the majority of the participants had a higher rate of success in repeating visual patterns and repeating number patterns compared to growing visual patterns and growing number patterns. The analysis of the strategies that children implemented in patterning revealed a great differentiation between their use and the type of pattern. More specifically, students mainly justified their pattern extensions by making reasonable connections within successive steps in the growing pattern tasks, whereas they tended to use techniques related to random predictions following repetitions of the pattern’s parts in the repeating pattern tasks. Last, participants’ preference for repeating visual patterns was found when making their own patterns.

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4

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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5

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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6

Lei, Shuangyan, and Song Zhang. "Digital sinusoidal fringe pattern generation: Defocusing binary patterns VS focusing sinusoidal patterns." Optics and Lasers in Engineering 48, no. 5 (May 2010): 561–69. http://dx.doi.org/10.1016/j.optlaseng.2009.12.002.

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7

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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8

Collins, Tom, Robin Laney, Alistair Willis, and Paul H. Garthwaite. "Modeling Pattern Importance in Chopin's Mazurkas." Music Perception 28, no. 4 (April 1, 2011): 387–414. http://dx.doi.org/10.1525/mp.2011.28.4.387.

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This study relates various quantifiable characteristics of a musical pattern to subjective assessments of a pattern's salience. Via score analysis and listening, twelve music undergraduates examined excerpts taken from Chopin's mazurkas. They were instructed to rate already discovered patterns, giving high ratings to patterns that they thought were noticeable and/or important. Each undergraduate rated thirty specified patterns and ninety patterns were examined in total. Twenty-nine quantifiable attributes (some novel but most proposed previously) were determined for each pattern, such as the number of notes a pattern contained. A model useful for relating participants' ratings to the attributes was determined using variable selection and cross-validation. Individual participants were much poorer than the model at predicting the consensus ratings of other participants. While the favored model contains only three variables, many variables were identified as having some predictive value if considered in isolation. Implications for music psychology, analysis, and information retrieval are discussed.

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Minemoto, Takumi, and Junzo Narano. "Hybrid pattern recognition by features extracted from object patterns and Fraunhofer diffraction patterns." Applied Optics 24, no. 18 (September 15, 1985): 2914. http://dx.doi.org/10.1364/ao.24.002914.

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10

Marcus, Aaron. "Patterns within patterns." Interactions 11, no. 2 (March 2004): 28–34. http://dx.doi.org/10.1145/971258.971268.

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11

Hui, S., and S. H. Żak. "Discrete Fourier transform based pattern classifiers." Bulletin of the Polish Academy of Sciences: Technical Sciences 62, no. 1 (March 1, 2014): 15–22. http://dx.doi.org/10.2478/bpasts-2014-0002.

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Abstract A technique for pattern classification using the Fourier transform combined with the nearest neighbor classifier is proposed. The multidimensional fast Fourier transform (FFT) is applied to the patterns in the data base. Then the magnitudes of the Fourier coefficients are sorted in descending order and the first P coefficients with largest magnitudes are selected, where P is a design parameter. These coefficients are then used in further processing rather than the original patterns. When a noisy pattern is presented for classification, the pattern’s P Fourier coefficients with largest magnitude are extracted. The coefficients are arranged in a vector in the descending order of their magnitudes. The obtained vector is referred to as the signature vector of the corresponding pattern. Then the distance between the signature vector of the pattern to be classified and the signature vectors of the patterns in the data base are computed and the pattern to be classified is matched with a pattern in the data base whose signature vector is closest to the signature vector of the pattern being classified.

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12

Xie, Shiyong, and Long Zhao. "An Efficient Algorithm for Mining Stable Periodic High-Utility Sequential Patterns." Symmetry 14, no. 10 (September 28, 2022): 2032. http://dx.doi.org/10.3390/sym14102032.

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Periodic high-utility sequential pattern mining (PHUSPM) is used to extract periodically occurring high-utility sequential patterns (HUSPs) from a quantitative sequence database according to a user-specified minimum utility threshold (minutil). A sequential pattern’s periodicity is determined by measuring when the frequency of its periods (the time between two consecutive happenings of the sequential pattern) exceed a user-specified maximum periodicity threshold (maxPer). However, due to the strict judgment threshold, the traditional PHUSPM method has the problem that some useful sequential patterns are discarded and the periodic values of some sequential patterns fluctuate greatly (i.e., are unstable). In frequent itemset mining (FIM), some researchers put forward some strategies to solve these problems. Because of the symmetry of frequent itemset pattern (FIPs), these strategies cannot be directly applied to PHUSPM. In order to address these issues, this work proposes the stable periodic high-utility sequential pattern mining (SPHUSPM) algorithm. The contributions made by this paper are as follows. First, we introduce the concept of stability to overcome the abovementioned problems, mine sequential patterns with stable periodic behavior, and propose the concept of stable periodic high-utility sequential patterns (SPHUSPs) for the first time. Secondly, we design a new data structure named the PUL-list to record the periodic information of sequential patterns, thereby improving the mining efficiency. Thirdly, we propose the maximum lability pruning strategy in sequential pattern (MLPS), which can prune a large number of unstable sequential patterns in advance. To assess the algorithm’s effectiveness, we perform many experiments. It turns out that the algorithm can not only mine patterns that are ignored by traditional algorithms, but also ensure that the discovered patterns have stable periodic behavior. In addition, after using the MLPS pruning strategy, the algorithm can prune 46.5% of candidates in advance on average in six datasets. Pruning a large number of candidates in advance not only speeds up the mining process, but also greatly reduces memory usage.

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13

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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14

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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15

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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16

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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17

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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18

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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19

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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20

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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21

SALLES-COSTA, Rosana, Gabriela dos Santos BARROSO, Maria CABRAL, and Maria Beatriz Trindade de CASTRO. "Parental dietary patterns and social determinants of children's dietary patterns." Revista de Nutrição 29, no. 4 (August 2016): 483–93. http://dx.doi.org/10.1590/1678-98652016000400004.

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ABSTRACT Objective To identify dietary patterns in children up to thirty months of age and verify whether they are associated with parental dietary patterns, and socioeconomic and demographic characteristics. Methods This is a cross-sectional study with baseline data from a population-based study composed of 1,085 households from a representative sample of a metropolitan region in Rio de Janeiro, Brazil. The children's food intake was evaluated by two 24-hour recalls, and the dietary patterns were identified by principal component analysis stratified into two groups according to the children's age: 6 to 17 months; and 18 to 30 months. The explanatory variables collected by a structured questionnaire were socioeconomic and demographic characteristics, age at introduction of complementary foods, and parental dietary pattern. A Food Frequency Questionnaire was administered to assess parental dietary pattern, which was determined by principal component analysis. Multivariate linear regression estimated the effect of each explanatory variable on the children's dietary patterns. Results Three dietary patterns were identified in children aged 6-17 months (basic-mixed; mixed-plus; and milk-flours) and two dietary patterns were identified in children aged 18-30 months: basic-mixed and mixed-plus. Multivariate linear regression showed that complementary feeding (b=0.108; p=0.004) was positively associated with the basic-mixed dietary pattern, and family income (b=0.002; p£0.01), with the mixed-plus dietary pattern. A negative association was found between the traditional parental dietary pattern and children's mixed-plus pattern in children aged 6-17 months (b=0.152; p=0.006) and in children aged 18-30 months (b=0.152; p=0.016). In children aged up to 18 months, parental education level (b=0.368; p£0.01) was positively associated with the mixed-plus dietary pattern. Conclusion Family income, parental education level, and parental dietary patterns are associated with children's dietary patterns.

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22

Holmes, Michelle D., Shona Dalal, Vikash Sewram, Megan B. Diamond, Sally N. Adebamowo, Ikeoluwapo O. Ajayi, Clement Adebamowo, et al. "Consumption of processed food dietary patterns in four African populations." Public Health Nutrition 21, no. 8 (February 1, 2018): 1529–37. http://dx.doi.org/10.1017/s136898001700386x.

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AbstractObjectiveTo identify predominant dietary patterns in four African populations and examine their association with obesity.DesignCross-sectional study.Setting/SubjectsWe used data from the Africa/Harvard School of Public Health Partnership for Cohort Research and Training (PaCT) pilot study established to investigate the feasibility of a multi-country longitudinal study of non-communicable chronic disease in sub-Saharan Africa. We applied principal component analysis to dietary intake data collected from an FFQ developed for PaCT to ascertain dietary patterns in Tanzania, South Africa, and peri-urban and rural Uganda. The sample consisted of 444 women and 294 men.ResultsWe identified two dietary patterns: the Mixed Diet pattern characterized by high intakes of unprocessed foods such as vegetables and fresh fish, but also cold cuts and refined grains; and the Processed Diet pattern characterized by high intakes of salad dressing, cold cuts and sweets. Women in the highest tertile of the Processed Diet pattern score were 3·00 times more likely to be overweight (95 % CI 1·66, 5·45; prevalence=74 %) and 4·24 times more likely to be obese (95 % CI 2·23, 8·05; prevalence=44 %) than women in this pattern’s lowest tertile (both P<0·0001; prevalence=47 and 14 %, respectively). We found similarly strong associations in men. There was no association between the Mixed Diet pattern and overweight or obesity.ConclusionsWe identified two major dietary patterns in several African populations, a Mixed Diet pattern and a Processed Diet pattern. The Processed Diet pattern was associated with obesity.

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23

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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24

Schulz, Eric, Francisco Quiroga, and Samuel J. Gershman. "Communicating Compositional Patterns." Open Mind 4 (August 2020): 25–39. http://dx.doi.org/10.1162/opmi_a_00032.

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How do people perceive and communicate structure? We investigate this question by letting participants play a communication game, where one player describes a pattern, and another player redraws it based on the description alone. We use this paradigm to compare two models of pattern description, one compositional (complex structures built out of simpler ones) and one noncompositional. We find that compositional patterns are communicated more effectively than noncompositional patterns, that a compositional model of pattern description predicts which patterns are harder to describe, and that this model can be used to evaluate participants’ drawings, producing humanlike quality ratings. Our results suggest that natural language can tap into a compositionally structured pattern description language.

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25

Tanguay, Liane. "Patterns behind the Patterns." American Book Review 41, no. 1 (2019): 17–29. http://dx.doi.org/10.1353/abr.2019.0133.

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26

JAY, BARRY, and DELIA KESNER. "First-class patterns." Journal of Functional Programming 19, no. 2 (March 2009): 191–225. http://dx.doi.org/10.1017/s0956796808007144.

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AbstractPure pattern calculus supports pattern-matching functions in which patterns are first-class citizens that can be passed as parameters, evaluated and returned as results. This new expressive power supports two new forms of polymorphism. Path polymorphism allows recursive functions to traverse arbitrary data structures. Pattern polymorphism allows patterns to be treated as parameters which may be collected from various sources or generated from training data. A general framework for pattern calculi is developed. It supports a proof of confluence that is parameterised by the nature of the matching algorithm, suitable for the pure pattern calculus and all other known pattern calculi.

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27

ASO, HIROMOTO, and NAMIO HONDA. "REPRESENTATION OF ITERATIVE PATTERNS." International Journal of Pattern Recognition and Artificial Intelligence 03, no. 03n04 (December 1989): 479–95. http://dx.doi.org/10.1142/s021800148900036x.

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Iterative patterns can be described by the component pattern of iteration and their way of connection for iteration. It is shown that the shape of the component pattern can be a rectangle for any iterative pattern, which is called a tile. The tile is related to the basis of the parallel translation group of the iterative pattern. The component pattern itself is identified by a "tessera" which is defined by a non-degenerate colored tile. The tessera is a compact representation of iterative patterns. Some natures of tesseras and tiles are also discussed. The number of the kinds of distinct iterative patterns for each way of iteration is evaluated.

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28

Goh, Ryan, and Arnd Scheel. "Growing patterns." Nonlinearity 36, no. 10 (September 6, 2023): R1—R51. http://dx.doi.org/10.1088/1361-6544/acf265.

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Abstract Pattern forming systems allow for a wealth of states, where wavelengths and orientation of patterns varies and defects disrupt patches of monocrystalline regions. Growth of patterns has long been recognized as a strong selection mechanism. We present here recent and new results on the selection of patterns in situations where the pattern-forming region expands in time. The wealth of phenomena is roughly organised in bifurcation diagrams that depict wavenumbers of selected crystalline states as functions of growth rates. We show how a broad set of mathematical and numerical tools can help shed light into the complexity of this selection process.

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29

Demertzi, A., E. Tagliazucchi, S. Dehaene, G. Deco, P. Barttfeld, F. Raimondo, C. Martial, et al. "Human consciousness is supported by dynamic complex patterns of brain signal coordination." Science Advances 5, no. 2 (February 2019): eaat7603. http://dx.doi.org/10.1126/sciadv.aat7603.

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Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern’s implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain’s ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.

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30

Sakoe, Hiroaki. "Device for recognizing an input pattern with approximate patterns used for reference patterns on mapping." Journal of the Acoustical Society of America 77, no. 3 (March 1985): 1288. http://dx.doi.org/10.1121/1.392072.

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31

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.

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32

Guerrero-García, Josefina, Juan Manuel González-Calleros, and Jean Vanderdonckt. "Workflow User Interfaces Patterns." Acta Universitaria 22 (March 1, 2012): 62–68. http://dx.doi.org/10.15174/au.2012.343.

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A collection of user interface design patterns for workflow information systems is presented that contains forty three resource patterns classified in seven categories. These categories and their corresponding patterns have been logically identified from the task life cycle based on offering and allocation operations. Each Workflow User Interface Pattern (WUIP) is characterized by properties expressed in the PLML markup language for expressing patterns and augmented by additional attributes and models attached to the pattern: the abstract user interface and the corresponding task model. These models are specified in a User Interface Description Language. All WUIPs are stored in a library and can be retrieved within a workflow editor that links each workflow pattern to its corresponding WUIP, thus giving rise to a user interface for each workflow pattern.

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33

Torgerson, C. S., M. J. Gdovin, and J. E. Remmers. "Fictive Gill and Lung Ventilation in the Pre- and Postmetamorphic Tadpole Brain Stem." Journal of Neurophysiology 80, no. 4 (October 1, 1998): 2015–22. http://dx.doi.org/10.1152/jn.1998.80.4.2015.

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Torgerson, C. S., M. J. Gdovin, and J. E. Remmers. Fictive gill and lung ventilation in the pre- and postmetamorphic tadpole brain stem. J. Neurophysiol. 80: 2015–2022, 1998. The pattern of efferent neural activity recorded from the isolated brain stem preparation of the tadpole Rana catesbeiana was examined to characterize fictive gill and lung ventilations during ontogeny. In vitro recordings from cranial nerve (CN) roots V, VII, and X and spinal nerve (SN) root II of premetamorphic tadpoles showed a coordinated sequence of rhythmic bursts occurring in one of two patterns, pattern1, high-frequency, low-amplitude bursts lacking corresponding activity in SN II and pattern 2, low-frequency, high-amplitude bursts with coincident bursts in SN II. These two patterns corresponded to gill and lung ventilatory burst patterns, respectively, recorded from nerve roots of decerebrate, spontaneously breathing tadpoles. Similar patterns were observed in brain stem preparations from postmetamorphic tadpoles except that they showed a greater frequency of lung bursts and they expressed fictive gill ventilation in SN II. The laryngeal branch of the vagus (Xl) displayed efferent bursts in phase with gill and lung activity, suggesting fictive glottal constriction during gill ventilation and glottal dilation during lung ventilation. The fictive gill ventilatory cycle of pre- and postmetamorphic tadpoles was characterized by a rostral to caudal sequence of CN bursts. The fictive lung ventilatory pattern in the premetamorphic animal was initiated by augmenting CN VII discharge followed by synchronous bursts in CN V, X, SN II, and Xl. By contrast, postmetamorphic patterns of fictive lung ventilation were characterized by lung burst activity in SN II that preceded burst onset in CN V and followed the lead burst in CN VII. We conclude that recruitment and timing of pattern 1 and pattern 2 rhythmic bursts recorded in vitro closely resemble that recorded during spontaneous respiratory behavior, indicating that the two patterns are the neural equivalent of gill and lung ventilation, respectively. Further, fictive gill and lung ventilatory patterns in postmetamorphic tadpoles differ in burst onset latency from premetamorphic tadpole patterns and resemble fictive oropharyngeal and pulmonary burst cycles in adult frogs.

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Sapaty, P. S. "Managing distributed systems with spatial grasp patterns." Mathematical machines and systems 4 (2023): 11–25. http://dx.doi.org/10.34121/1028-9763-2023-4-11-25.

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The pattern is everything around us. It can represent the world’s regularity, a human-made design, a model, plan, diagram, a standard way of modeling, acting and thinking, a distinctive style or form, a combination of qualities and tendencies, etc. That is why the theory, research, and practical works on patterns are so important for different scientific and technological fields, having also stimulated the preparation and writing of the current paper. The paper reviews existing works on patterns, grouping them by different categories, and briefs the developed Spatial Grasp Model and Technology (SGT) and its Spatial Grasp Language (SGL) with the distributed networked implementation, which provide effective distributed solutions in systems management, control, and simulation by active self-spreading patterns. The article shows how practical patterns can be expressed in SGL, including regular patterns, patterns of concrete objects, and different pattern-based management solutions like coordinating transport columns, finding distributed zone coordinates, and spatial tracking of mobile objects. It also gives network examples of distributed pattern recognition and matching with the use of self-propagating active network templates reflecting images to be found. The paper provides a classified summary of the investigated use of SGL for pattern operations in different areas, which includes descriptive patterns, creative patterns, patterns as spatial processes, pattern recognition, self-matching patterns, combined patterns, cooperating and conflicting patterns, psychological patterns, and recursive patterns. The work concludes with the belief that SGL can be used as a real, very effective, and compact language for pattern representation and operations, and SGT should contribute to the pattern theory and resultant technologies.

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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.

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36

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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37

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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38

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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39

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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40

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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41

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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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.

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