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Статті в журналах з теми "Pattern sequence"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Xue, Linyan, Xiaoke Zhang, Fei Xie, Shuang Liu, and Peng Lin. "Frequent Patterns Algorithm of Biological Sequences based on Pattern Prefix-tree." International Journal of Computers Communications & Control 14, no. 4 (2019): 574–89. http://dx.doi.org/10.15837/ijccc.2019.4.3607.

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In the application of bioinformatics, the existing algorithms cannot be directly and efficiently implement sequence pattern mining. Two fast and efficient biological sequence pattern mining algorithms for biological single sequence and multiple sequences are proposed in this paper. The concept of the basic pattern is proposed, and on the basis of mining frequent basic patterns, the frequent pattern is excavated by constructing prefix trees for frequent basic patterns. The proposed algorithms implement rapid mining of frequent patterns of biological sequences based on pattern prefix trees. In e

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2

Ezeife, Christie I., Vignesh Aravindan, and Ritu Chaturvedi. "Mining Integrated Sequential Patterns From Multiple Databases." International Journal of Data Warehousing and Mining 16, no. 1 (2020): 1–21. http://dx.doi.org/10.4018/ijdwm.2020010101.

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Existing work on multiple databases (MDBs) sequential pattern mining cannot mine frequent sequences to answer exact and historical queries from MDBs having different table structures. This article proposes the transaction id frequent sequence pattern (TidFSeq) algorithm to handle the difficult problem of mining frequent sequences from diverse MDBs. The TidFSeq algorithm transforms candidate 1-sequences to get transaction subsequences where candidate 1-sequences occurred as (1-sequence, itssubsequenceidlist) tuple or (1-sequence, position id list). Subsequent frequent i-sequences are computed u

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3

Kotteeswaran, C., V. Khanaa, and A. Rajesh. "Pattern Based Matrix Insertion Deletion System for Efficient Bio Molecular Computing System." Journal of Computational and Theoretical Nanoscience 16, no. 2 (2019): 507–11. http://dx.doi.org/10.1166/jctn.2019.7759.

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The problem of bio molecular computing has been well studied and there are number of approaches discussed for the detection of false gene sequences. However, they suffer to achieve higher performance in the detection of false sequences. To improve the performance of detection of fake molecular patterns, an pattern based approach is discussed in this paper. As of the biomolecular strings a set of patterns, the method first identifies the list of sequences available and based on the set of patterns being maintained, the method identifies the list of patterns present in the gene sequence. Based o

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4

Kang, Yongyong, Xiaofei Yang, Jiadong Lin, and Kai Ye. "PVTree: A Sequential Pattern Mining Method for Alignment Independent Phylogeny Reconstruction." Genes 10, no. 2 (2019): 73. http://dx.doi.org/10.3390/genes10020073.

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Phylogenetic tree is essential to understand evolution and it is usually constructed through multiple sequence alignment, which suffers from heavy computational burdens and requires sophisticated parameter tuning. Recently, alignment free methods based on k-mer profiles or common substrings provide alternative ways to construct phylogenetic trees. However, most of these methods ignore the global similarities between sequences or some specific valuable features, e.g., frequent patterns overall datasets. To make further improvement, we propose an alignment free algorithm based on sequential patt

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5

Melchior, Jan, Aya Altamimi, Mehdi Bayati, Sen Cheng, and Laurenz Wiskott. "A neural network model for online one-shot storage of pattern sequences." PLOS ONE 19, no. 6 (2024): e0304076. http://dx.doi.org/10.1371/journal.pone.0304076.

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Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation process. In our model, CA3 provides a pre-trained sequence that is hetero-associated with the input sequence, rather than storing a sequence in CA3. That is, plasticity on a short timescale only occurs in the incoming and outgoing connections of CA3, not in its recurrent connections. We use a single learning rule named Hebbian descent to train all pla

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6

Gumulka, M., E. Kapkowska, and D. Maj. "Laying pattern parameters in broiler breeder hens and intrasequence changes in egg composition." Czech Journal of Animal Science 55, No. 10 (2010): 428–35. http://dx.doi.org/10.17221/1698-cjas.

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The aim of the study was to analyze the pattern of oviposition time in laying sequences in broiler breeder hens and to determine a relationship between egg position in the sequence and egg quality. The sequences were described using mean oviposition time (hour) within a sequence, mean lag of oviposition time between successive ovipositions, and mean and cumulative lag of oviposition for a sequence. Egg weight, percentage of egg components and shape index were determined for successive eggs in a sequence. The 2-, 3-, 4-, 5- to 6- and 7- to 9-egg sequences were considered. The light/dark regime

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7

Alghar, Muhammad Zia, Elly Susanti, and Marhayati Marhayati. "ETHNOMATHEMATICS: ARITHMETIC SEQUENCE PATTERNS OF MINANGKABAU CARVING ON SINGOK GONJONG." Jurnal Pendidikan Matematika (JUPITEK) 5, no. 2 (2022): 145–52. http://dx.doi.org/10.30598/jupitekvol5iss2pp145-152.

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This study aimed to explore the arithmetic sequence pattern found in Minangkabau carvings mounted on singok gonjong. The method used is a qualitative method with an ethnographic approach. Data was collected by observation, interviews, literature studies, and documentation. The object of this study is Minangkabau carving on singok gonjong. The data obtained in this study came fromdirect observation, results of interviews with Minang carving craftsmen, documentation, and literature studies. The results showed three kinds of arithmetic sequence patterns in Minang carvings in singok gonjong. The f

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8

KEMPE, STEFFEN, JOCHEN HIPP, CARSTEN LANQUILLON, and RUDOLF KRUSE. "MINING FREQUENT TEMPORAL PATTERNS IN INTERVAL SEQUENCES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 16, no. 05 (2008): 645–61. http://dx.doi.org/10.1142/s0218488508005546.

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Recently a new type of data source came into the focus of knowledge discovery from temporal data: interval sequences. In contrast to event sequences, interval sequences contain labeled events with a temporal extension. However, existing algorithms for mining patterns from interval sequences proved to be far from satisfying our needs. In brief, we missed an approach that, at the same time, defines support as the number of pattern instances, allows input data that consists of more than one sequence, implements time constraints on a pattern instance, and counts multiple instances of a pattern wit

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9

Rexie, J. A. M., Kumudha Raimond, Mythily Murugaaboopathy, D. Brindha, and Henock Mulugeta. "Lightweight Pattern Matching Method for DNA Sequencing in Internet of Medical Things." Computational Intelligence and Neuroscience 2022 (September 8, 2022): 1–16. http://dx.doi.org/10.1155/2022/6980335.

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An area of medical science, that is, gaining prominence, is DNA sequencing. Genetic mutations responsible for the disease have been detected using DNA sequencing. The research is focusing on pattern identification methodologies for dealing with DNA-sequencing problems relating to various applications. A few examples of such problems are alignment and assembly of short reads from next generation sequencing (NGS), comparing DNA sequences, and determining the frequency of a pattern in a sequence. The approximate matching of DNA sequences is also well suited for many applications equivalent to the

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10

Dr., E. Elakkiya*1 &. Dr. S. Ravichandran2. "MAX-CLOSED SPAMBY USING DIRECT BIT POSITION METHOD." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 9 (2019): 17–23. https://doi.org/10.5281/zenodo.3461151.

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This paper is Max-Closed SPAM by using Direct Bit Position (Maximal Closed sequential pattern mining). This algorithm is to acquire the maximal Closed Sequential Pattern from Sequence Database. The sequence pattern mining gives more numbers of patterns, closed sequential pattern obtains little number of patterns and maximal closed attain very few sequence patterns. According to the closed Sequential Patterns is long sequence database, the maximal closed pattern is influential by memory and performance. Experimental evaluation has done on UCI Repository Datasets, that shows the algorithm Max Cl

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11

Coons, Michael, and Jeffrey Shallit. "A pattern sequence approach to Stern’s sequence." Discrete Mathematics 311, no. 22 (2011): 2630–33. http://dx.doi.org/10.1016/j.disc.2011.07.029.

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12

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 p

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13

AKITAYA, Hugo, Jun MITANI, Yoshihiro KANAMORI, and Yukio FUKUI. "819 Finding a folding sequence for an origami crease pattern using graph pattern matching." Proceedings of the Dynamics & Design Conference 2012 (2012): _819–1_—_819–8_. http://dx.doi.org/10.1299/jsmedmc.2012._819-1_.

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14

Alkan, Altug, Nathan Fox, and O. Ozgur Aybar. "On Hofstadter Heart Sequences." Complexity 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/2614163.

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The Hofstadter Q-sequence and the Hofstadter-Conway $10000 sequence are perhaps the two best known examples of meta-Fibonacci sequences. In this paper, we explore an unexpected connection between them. When the Q-sequence is subtracted from the Conway sequence, a chaotic pattern of heart-shaped figures emerges. We use techniques of Pinn and Tanny et al. to explore this sequence. Then, we introduce and analyze an apparent relative of the Q-sequence and illustrate how it also generates heart patterns when subtracted from the Conway sequence.

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15

Gowda, Karna, Yuxin Chen, Sarah Iams, and Mary Silber. "Assessing the robustness of spatial pattern sequences in a dryland vegetation model." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2187 (2016): 20150893. http://dx.doi.org/10.1098/rspa.2015.0893.

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A particular sequence of patterns, ‘gaps→labyrinth→spots’, occurs with decreasing precipitation in previously reported numerical simulations of partial differential equation dryland vegetation models. These observations have led to the suggestion that this sequence of patterns can serve as an early indicator of desertification in some ecosystems. Because parameter values in the vegetation models can take on a range of plausible values, it is important to investigate whether the pattern sequence prediction is robust to variation. For a particular model, we find that a quantity calculated via bi

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16

Zhou, Cheng, Boris Cule, and Bart Goethals. "Pattern Based Sequence Classification." IEEE Transactions on Knowledge and Data Engineering 28, no. 5 (2016): 1285–98. http://dx.doi.org/10.1109/tkde.2015.2510010.

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17

Han, Shui’Er, David Alais, and Randolph Blake. "Battle of the Mondrians: Investigating the Role of Unpredictability in Continuous Flash Suppression." i-Perception 9, no. 4 (2018): 204166951879293. http://dx.doi.org/10.1177/2041669518792930.

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In continuous flash suppression (CFS), a dynamic sequence of Mondrian patterns presented to one eye suppresses a static target in the other eye for several seconds at a time. Its effectiveness has been linked to low-level properties such as spatial frequency and orientation, but the role of higher order influences remains unstudied. Here, using a tracking paradigm, we asked if the spatial and temporal predictability of the Mondrian sequence affects CFS dynamics. Predictable temporal sequences were regularly updated every 100 ms or modulated sinusoidally in pixel luminance at 2 Hz. Unpredictabl

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18

Oyekunle, Victoria Oluwatoyin, Mercy Nwanyanwu, and Mercy Azibaye Ide. "Efficient Method of Mining Sequential pattern in retail database." Journal of Scientific and Engineering Research 8, no. 5 (2021): 65–74. https://doi.org/10.5281/zenodo.10590173.

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<strong>Abstract</strong> There is difficulty in detecting repetitive behavior for a company in order to identify regularities in businesses and inability to determine meta patterns as a group of events that lead to particular deviations in customers’ behavior. However, a sequential pattern mining mechanism has been developed to discover all sequences and subsequences that are repetitive in a meta data. Percussive method of pattern growth algorithms of Sequential Pattern Mining (SPM) has been used for finding frequent patterns from a huge data set. It first scans the sequence database an

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19

Mansour, Toufik, and Mark Shattuck. "Pattern avoidance in inversion sequences." Pure Mathematics and Applications 25, no. 2 (2015): 157–76. http://dx.doi.org/10.1515/puma-2015-0016.

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Abstract A permutation of length n may be represented, equivalently, by a sequence a1a2 • • • an satisfying 0 < ai < i for all z, which is called an inversion sequence. In analogy to the usual case for permutations, the pattern avoidance question is addressed for inversion sequences. In particular, explicit formulas and/or generating functions are derived which count the inversion sequences of a given length that avoid a single pattern of length three. Among the sequences encountered are the Fibonacci numbers, the Schröder numbers, and entry A200753 in OEIS. We make use of both algebraic

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20

Mulawakkan, Andi, Wasilatul Murtafiah*, Marheny Lukitasari, Nurcholif Diah, Tias Ernawati, and Sri Adi. "Generalization of Patterns Drawing of High-Performance Students Based on Action, Process, Object, and Schema Theory." European Journal of Educational Research 12, no. 1 (2023): 421–33. http://dx.doi.org/10.12973/eu-jer.12.1.421.

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<p style="text-align: justify;">This study is qualitative with descriptive and aims to determine the process of generalizing the pattern image of high performance students based on the action, process, object, and schema (APOS) theory. The participants in this study were high performance eighth-grade Indonesian junior high school. Assignments and examinations to gauge mathematical aptitude and interviews were used to collect data for the study. The stages of qualitative analysis include data reduction, data presentation, and generating conclusions. This study showed that when given a seq

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21

Thiet, Pham Thi. "APPLYING THE ATTRIBUTED PREFIX TREE FOR MINING CLOSED SEQUENTIAL PATTERNS." Vietnam Journal of Science and Technology 54, no. 3A (2018): 106. http://dx.doi.org/10.15625/2525-2518/54/3a/11964.

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Mining closed sequential patterns is one of important tasks in data mining. It is proposed to resolve difficult problems in mining sequential pattern such as mining long frequent sequences that contain a combinatorial number of frequent subsequences or using very low support thresholds to mine sequential patterns is usually both time- and memory-consuming. This paper applies the characteristics of closed sequential patterns and sequence extensions into the prefix tree structure to mine closed sequential patterns from the sequence database. The paper uses the parent–child relationship on prefix

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22

Peng, He. "CFSP: a collaborative frequent sequence pattern discovery algorithm for nucleic acid sequence classification." PeerJ 8 (April 20, 2020): e8965. http://dx.doi.org/10.7717/peerj.8965.

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Background Conserved nucleic acid sequences play an essential role in transcriptional regulation. The motifs/templates derived from nucleic acid sequence datasets are usually used as biomarkers to predict biochemical properties such as protein binding sites or to identify specific non-coding RNAs. In many cases, template-based nucleic acid sequence classification performs better than some feature extraction methods, such as N-gram and k-spaced pairs classification. The availability of large-scale experimental data provides an unprecedented opportunity to improve motif extraction methods. The p

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23

Ouyang, Wei Min, and Qin Hua Huang. "Mining Indirect Temporal Sequential Patterns in Large Transaction Databases." Applied Mechanics and Materials 385-386 (August 2013): 1362–65. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.1362.

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Sequential pattern is an important research topic in data mining and knowledge discovery. Traditional algorithms for mining sequential patterns focus on the frequent sequences, which do not consider the infrequent sequences and lifespan of each sequence. On the one hand, some infrequent patterns can provide very useful insight view into the data set, on the other hand, without taking lifespan of each sequence into account, not only some discovered patterns may be invalid, but also some useful patterns may not be discovered. So, we extend the sequential patterns to the indirect temporal sequent

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24

Mrazek, J., and S. Xie. "Pattern locator: a new tool for finding local sequence patterns in genomic DNA sequences." Bioinformatics 22, no. 24 (2006): 3099–100. http://dx.doi.org/10.1093/bioinformatics/btl551.

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25

Brick, Tim. "SEQUENCE MINING FOR COMPLEX PATTERN FINDING." Innovation in Aging 3, Supplement_1 (2019): S377. http://dx.doi.org/10.1093/geroni/igz038.1383.

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Abstract The processes of aging play out across multiple variables and multiple timescales, with patterns of daily, and weekly behavior that may be influenced by each other and by changes across the aging process. Further, many of these patterns do not fit neatly into the linear modeling approaches common in the field. Sequence mining, an approach from the data mining literature, provides a means of identifying commonalities and differences in these sequences in ways that can begin to handle the multivariate and multi-timescale nature of behaviors in aging. In this talk, I present an example o

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26

Schulz, Reiner, and James A. Reggia. "Temporally Asymmetric Learning Supports Sequence Processing in Multi-Winner Self-Organizing Maps." Neural Computation 16, no. 3 (2004): 535–61. http://dx.doi.org/10.1162/089976604772744901.

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We examine the extent to which modified Kohonen self-organizing maps (SOMs) can learn unique representations of temporal sequences while still supporting map formation. Two biologically inspired extensions are made to traditional SOMs: selection of multiple simultaneous rather than single “winners” and the use of local intramap connections that are trained according to a temporally asymmetric Hebbian learning rule. The extended SOM is then trained with variable-length temporal sequences that are composed of phoneme feature vectors, with each sequence corresponding to the phonetic transcription

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27

Krishna, J., and M. Haritha. "An Efficient Closed Maximal Pattern Sequences Mining on High Dimensional Datasets." Asian Journal of Computer Science and Technology 8, S3 (2019): 50–53. http://dx.doi.org/10.51983/ajcst-2019.8.s3.2088.

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Previous methods have presented convincing arguments that mining complete set of patterns is huge for effective usage. A compact but high quality set of patterns, such as closed patterns and maximal patterns is needed. Most of the previously maximal pattern sequences mining algorithms on high dimensional sequence, such as biological data set, work under the same support. In this paper, an efficient algorithm Closed Maximal Pattern Sequences (CMPS-Mine) for mining closed maximal patterns based on multi-support is suggested. Careful exhibitions once Beta-globin gene sequences have exhibited that

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28

Van, Trang Thien Thi. "Survey on Sequential Pattern Mining based on User - Constraints." Journal of Development and Integration, no. 73 (December 25, 2023): 68–77. http://dx.doi.org/10.61602/jdi.2023.73.09.

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Sequence data mining, also known as sequential pattern mining, is to find all frequent sub-sequences (called sequential patterns) in a sequence database, the threshold of frequency is specified by the user. In recent years, with the explosion growth of information and big data, this problem trends toward mining with constraints to overcome both effectiveness and efficiency challenges since that the constraints represent for the user’s interest. This paper presents a detailed survey of recent studies on mining sequential pattern and the categories of the constraints. Moreover, it also classifie

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29

Soroushnia, Shima, Masoud Daneshtalab, Juha Plosila, Tapio Pahikkala, and Pasi Liljeberg. "High Performance Pattern Matching on Heterogeneous Platform." Journal of Integrative Bioinformatics 11, no. 3 (2014): 88–98. http://dx.doi.org/10.1515/jib-2014-253.

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Summary Pattern discovery is one of the fundamental tasks in bioinformatics and pattern recognition is a powerful technique for searching sequence patterns in the biological sequence databases. Fast and high performance algorithms are highly demanded in many applications in bioinformatics and computational molecular biology since the significant increase in the number of DNA and protein sequences expand the need for raising the performance of pattern matching algorithms. For this purpose, heterogeneous architectures can be a good choice due to their potential for high performance and energy ef

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30

Bergeson, Tonya R., and Sandra E. Trehub. "Infants Perception of Rhythmic Patterns." Music Perception 23, no. 4 (2006): 345–60. http://dx.doi.org/10.1525/mp.2006.23.4.345.

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We explored 9-month-old infants perception of auditory temporal sequences in a series of three experiments. In Experiment 1, we presented some infants with tone sequences that were expected to induce a strongly metric framework and others with a sequence that was expected to induce a weakly metric framework or no such framework. Infants detected a change in the context of the former sequences but not in the latter sequence. In Experiment 2, infants listened to a tone sequence with temporal cues to duple or triple meter. Infants detected a change in the pattern with duple meter but not in the p

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31

Khan, Hussain Ali, and Syed H. Masood. "Placement Sequence Methodology in Pallet Pattern Formation in Robotic Palletisation." Advanced Materials Research 383-390 (November 2011): 6347–51. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6347.

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The Pallet Loading Problem (PLP) in packaging industry usually deals with generating optimal pallet patterns of placing boxes on a rectangular pallet. For a given pattern, the boxes can be placed in different set of sequences each affecting efficiency and productivity of robotic palletisation. Therefore, getting an optimal pallet pattern does not guarantee an optimal pattern placement strategy. Therefore, there is a need to develop a methodology that considers the palletisers physical characteristics and limitations in robotic palletising systems. This paper presents development of a methodolo

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32

Gottlob-McHugh, S. G., M. Lévesque, K. MacKenzie, M. Olson, O. Yarosh, and D. A. Johnson. "Organization of the 5S rRNA genes in the soybean Glycine max (L.) Merrill and conservation of the 5S rDNA repeat structure in higher plants." Genome 33, no. 4 (1990): 486–94. http://dx.doi.org/10.1139/g90-072.

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The 5S rRNA gene of the soybean Glycine max (L.) Merr. has been cloned on a 556-bp fragment of DNA and sequenced. This fragment contains two copies of the soybean 5S rDNA sequence, one intact and one truncated, separated by noncoding DNA. We have used this clone to investigate the organization of the 5S genes within the soybean genome and the extent of their methylation. Our results demonstrate that soybean 5S genes are clustered, organized into tandem repeats of 330 bp, and extensively methylated. Hybridization of the 5S sequence to Southern transfers of soybean DNA digested with BamHI reveal

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33

Kretzler, M., G. Fan, D. Rose, L. J. Arend, J. P. Briggs, and L. B. Holzman. "Novel mouse embryonic renal marker gene products differentially expressed during kidney development." American Journal of Physiology-Renal Physiology 271, no. 3 (1996): F770—F777. http://dx.doi.org/10.1152/ajprenal.1996.271.3.f770.

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Investigators approaching the problem of renal organogenesis have been hampered by a paucity of suitable molecular markers that specify distinct developmental phenotypes. To identify such markers, differential display-polymerase chain reaction (DD-PCR) was used to survey the temporal pattern of gene expression in mouse kidney at 11.5, 13.5, 15.5, and 17.5 days after conception and in the adult kidney. Twenty-two differentially expressed amplification products were identified, isolated, and sequenced. Seventeen clones showed no significant similarity with previously reported nucleotide sequence

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34

Oh, Sukyoon, Zhe Sun, Tong Tian, and Christian Spielmann. "Improvements of Computational Ghost Imaging by Using Sequenced Speckle." Applied Sciences 13, no. 12 (2023): 6954. http://dx.doi.org/10.3390/app13126954.

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This study presents a computational ghost imaging (GI) scheme that utilizes sequenced random speckle pattern illumination. The primary objective is to develop a speckle pattern/sequence that improves computational time without compromising image quality. To achieve this, we modulate the sequence of speckle sizes and design experiments based on three sequence rules for ordering the random speckle patterns. Through theoretical analysis and experimental validation, we demonstrate that our proposed scheme achieves a significantly better contrast-to-noise rate (CNR) compared to traditional GI at a

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35

Sabeti, Elyas, Sehong Oh, Peter Song, and Alfred Hero. "A Pattern Dictionary Method for Anomaly Detection." Entropy 24, no. 8 (2022): 1095. http://dx.doi.org/10.3390/e24081095.

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In this paper, we propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. The proposed method is capable of learning complex patterns in a training data sequence, using these learned patterns to detect potentially anomalous patterns in a test data sequence. The proposed pattern dictionary method uses a measure of complexity of the test sequence as an anomaly score that can be used to perform stand-alone anomaly detection. We also show that when combined with a universal source coder, the proposed pattern dictionary yields a powerful at

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Yang, Ming Shi, He Jiang, Hong Jun Yu, Xiu Fang Li, and Da Ding. "An Algorithm for Mining Weighted Negative Sequence Pattern." Applied Mechanics and Materials 644-650 (September 2014): 1717–20. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1717.

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.For the purpose of showing the importance of certain items in the negative sequences and make negative sequences have more practicality, this paper presents a method for mining weighted negative sequence pattern. Set the weight value to calculate the weighted support and prune the weighted negative sequences which don’t meet conditions. We use IRIS data set which belongs to UCI data sets to verify the new algorithm. Comparing with Neg-GSP algorithm, showing the benefit of the weighted concept.

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Zhu, You Chan, and Juan Hua Bai. "A Study of Push-Based Sequence Authorization Mechanism for Grid Security." Applied Mechanics and Materials 63-64 (June 2011): 59–63. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.59.

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Grid security is one of the core issues of grid computing, and the authorization issue of grid security is a hot topic of current research. This paper describes three sequence patterns of the authorization, and focuses on the architecture of push sequence model and application example-Community Authorization Service (CAS). It analyzes and compares the push sequence pattern and pull sequence pattern. Authorization mechanism based on push sequence pattern solves the scalability issue of GSI quite well in some extent and improves the flexibility of the system.

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Degadwala, Dr Sheshang, and Dhairya Vyas. "Data Mining Approch for Amino Acid Sequence Classification." International Journal of New Practices in Management and Engineering 10, no. 04 (2021): 01–08. http://dx.doi.org/10.17762/ijnpme.v10i04.124.

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Computerized applications are employed all around the world, an enormous amount of data is collected. The essential information contained in large amounts of data is attracting scholars from a variety of disciplines to examine how to extract the hidden knowledge inside them. The technique of obtaining or mining usable and valuable knowledge from enormous amounts of data is known as data mining. Text mining, picture mining, sequential pattern mining, web mining, and so on are all examples of data mining fields. Sequencing mining is one of the most important technologies in this field, as it aid

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Yang, Songbai, Tianxing Zhang, Yingchun Zhai, et al. "Frequent Alarm Pattern Mining of Industrial Alarm Flood Sequences by an Improved PrefixSpan Algorithm." Processes 11, no. 4 (2023): 1169. http://dx.doi.org/10.3390/pr11041169.

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Alarm systems are essential to the process safety and efficiency of complex industrial facilities. However, with the increasing size of plants and the growing complexity of industrial processes, alarm flooding is becoming a serious problem and posing challenges to alarm systems. Extracting alarm patterns from an alarm flood database can assist with an alarm root cause analysis, decision support, and the configuration of an alarm suppression model. However, due to the large size of the alarm database and the problem of sequence ambiguity in the alarm sequence, existing algorithms suffer from ex

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Okolica, James S., Gilbert L. Peterson, Robert F. Mills, and Michael R. Grimaila. "Sequence Pattern Mining with Variables." IEEE Transactions on Knowledge and Data Engineering 32, no. 1 (2020): 177–87. http://dx.doi.org/10.1109/tkde.2018.2881675.

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Wang, Chun-Sheng, Ying-Ho Liu, and Kuo-Chung Chu. "Closed inter-sequence pattern mining." Journal of Systems and Software 86, no. 6 (2013): 1603–12. http://dx.doi.org/10.1016/j.jss.2013.02.010.

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Haji, Amir Hossein. "Sequence, symmetry and pattern formation." Mathematical and Computer Modelling 52, no. 9-10 (2010): 1639–43. http://dx.doi.org/10.1016/j.mcm.2010.06.029.

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Silsbee, P. L., A. C. Bovik, and Dapang Chen. "Visual pattern image sequence coding." IEEE Transactions on Circuits and Systems for Video Technology 3, no. 4 (1993): 291–301. http://dx.doi.org/10.1109/76.257218.

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Na, Zhang, Chen Feng, Wang Jianpo, and Zhu Yadi. "Travel pattern recognition of urban rail passengers based on spatiotemporal sequence similarity." Insights of Automation in Manufacturing 1, no. 2 (2024): 30–42. http://dx.doi.org/10.59782/iam.v1i2.224.

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Understanding passenger travel patterns is helpful for the allocation of passenger resources in urban rail transit. Based on rail transit smart card data, this paper proposes a method to identify travel patterns by modeling individual spatiotemporal sequences. First, all the stations visited by individual passengers are extracted, and the similarity of the stations is calculated by the frequency of inter-station travel, the distance between stations and the activity duration of the stations. The main spatial activity area of the individual is divided using a hierarchical clustering algorithm.

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SHAN, YING, HARPREET S. SAWHNEY, and ART POPE. "CLUSTERING MULTIPLE IMAGE SEQUENCES WITH A SEQUENCE-TO-SEQUENCE SIMILARITY MEASURE." International Journal of Pattern Recognition and Artificial Intelligence 19, no. 04 (2005): 551–64. http://dx.doi.org/10.1142/s0218001405004149.

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We propose a novel similarity measure of two image sequences based on shapeme histograms. The idea of shapeme histogram has been used for single image/texture recognition, but is used here to solve the sequence-to-sequence matching problem. We develop techniques to represent each sequence as a set of shapeme histograms, which captures different variations of the object appearances within the sequence. These shapeme histograms are computed from the set of 2D invariant features that are stable across multiple images in the sequence, and therefore minimizes the effect of both background clutter,

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Feng, Shanshan, Ting Chen, Yunlong Zhang, and Changrui Lu. "mRNA Fragmentation Pattern Detected by SHAPE." Current Issues in Molecular Biology 46, no. 9 (2024): 10249–58. http://dx.doi.org/10.3390/cimb46090610.

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The success of messenger RNA (mRNA) vaccines in controlling COVID-19 has warranted further developments in new technology. Currently, their quality control process largely relies on low-resolution electrophoresis for detecting chain breaks. Here, we present an approach using multi-primer reverse transcription sequencing (MPRT-seq) to identify degradation fragments in mRNA products. Using this in-house-made mRNA containing two antigens and untranslated regions (UTRs), we analyzed the mRNA completeness and degradation pattern at a nucleotide resolution. We then analyzed the sensitive base sequen

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Pavlova, V. V. "The Study of Age-Related Variability of Pigmentation Patterns of the Shells of Dreissena Polymorpha (Bivalvia, Dreissenidae) from Different Parts of It's Range." Vestnik Zoologii 48, no. 2 (2014): 137–48. http://dx.doi.org/10.2478/vzoo-2014-0014.

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Abstract The Study of Age-Related Variability of Pigmentation Patterns of the Shells Dreissena polymorpha (Bivavia, Dreissenidae) from Different Parts of it's Range. Pavlova, V. V. - Traditionally, shells of Dreissena polymorpha Pallas, 1771 mussels are studied as a whole by the investigation of population variability of coloration. However, shell surface is divided into zones by the lines of growth delay called annual rings, and mussel shell coloration is an array of patterns in the consequent age zones. In the present paper traditional term “pattern type” is expanded by its relation to defin

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TORSHIN, Ivan. "Direct and reversed amino acid sequence pattern analysis: structural reasons for activity of reversed sequence sites and results of kinase site mutagenesis." Biochemical Journal 345, no. 3 (2000): 733–40. http://dx.doi.org/10.1042/bj3450733.

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During studies of kinase phosphorylation, not all functional kinase phosphorylation may be found using consensus sequence patterns. This type of phosphorylation is termed ‘non-consensus’ or ‘cryptic’ phosphorylation. Results presented here based on molecular dynamics of short peptides show that protein kinases may phosphorylate not only established consensus sequences (reading a sequence from N-terminus to C-terminus) but also reversed consensus sequences (reading from C- to N-terminus). Several protein sequences were analysed and corresponding biochemical data were presented. Similarity of mo

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Ali Khan, Hussain, Syed Hasan Masood, and Adrian Giecco. "An Algorithm to Determine Placement Sequence in Robotic Pallet Pattern Formation." Advanced Materials Research 403-408 (November 2011): 3953–58. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3953.

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In automated manufacturing palletising operations, the Pallet Loading Problem (PLP) usually deals with generating optimal pallet patterns of placing boxes on a rectangular pallet. For a given pattern, the boxes can be placed in different set of sequences each affecting efficiency and productivity of robotic palletisation. Therefore, merely getting an optimal pallet pattern does not guarantee an optimal pattern placement strategy. Very few published literature is available to address this problem, and so there is a need to develop a methodology that considers the palletisers physical characteri

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Ramavathy, N., and V. Priyadarshini . "User Behavior Patterns in Social Networks Using Generalized Sequence Pattern." International Journal of Computer Sciences and Engineering 6, no. 7 (2018): 1392–97. http://dx.doi.org/10.26438/ijcse/v6i7.13921397.

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