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25 results for “pattern matching”
Explaining human mobility predictions through a pattern matching algorithm
<p>The name of the file indicate information:<br> {type of sequence}_{type of measure}_{sequence properites}_{additional information}.csv</p> <p>{type of sequence} - 'synth' for synthetic or 'london' for real mobility data from London, UK.<br> {type of measure} - 'r2' for R-squared measure or 'corr' for Spearman's correlation<br> {sequence properties} - for synthetic data there are three types of sequences, described in the research article (random, markovian, nonstationary). For real mobility data this part includes information about data processing parameters: (...)_london_{type of mobility sequence}_{DBSCAN epsilon value}_{DBSCAN min_pts value}. {type of mobility sequence} is 'seq' for next-place sequences and '30min' or '1H' for the next time-bin sequences and indicate the size of the time-bin.<br> Files with 'predictability' at the end of the file contain R-squared and Spearman's correlation of measures calculated in relation to the predictability measure.</p> <p>R2 files include values of R-squared for all types of modelled regression functions.<br> 'line' indicates {y = ax + b} for single variable and {y = ax + by + c} for two variables.<br> 'expo' indicates {y = a*x^b + c} for single variable and {y = a*x^b + c*y^d + e} for two variables<br> 'log' indicates {y = a*log(x*b) + c} for single variable and {y = a * x + c * log(y) + e + d*x * log(y)} for two variables.<br> 'logf' indicates {y = a*log(x) + c * log(y) + e + b*log(x) * log(y)} for two variables</p>
Matching Network of Ontologies: a Pattern Recognition Approach
<p>Networks of Ontologies research deals with the need to combine several ontologies at the same time. In a world of integrated systems (system of systems), isolated systems are increasingly rare in the near future, and their integration creates opportunities to change, validate information and add more value to an information system. This system of systems can contain ontologies to support the corresponding knowledge model. Consequently, new integration requirements may have to deal with network alignment rather than single ontologies. This work delves into the area of network alignment and proposes new ways to approach a particular case of alignment of large ontologies. The contribution of the work is the use of algebraic operations on networks to eliminate candidates before alignment and to use a stochastic search method to discover the relevant nodes. These nodes should be retained as they increase accuracy and final alignment retrieval even though they are identical and removed by the algebraic operation. To find out the particular relevance of each node, we propose a random walk combined with a frequent itemsets approach that overcomes the force brute approaches in processing time, as the size of networks grows, and have close precision. The approach was validated using networks of ontologies created from the OAEI ontologies. The approach selected the entities to send to the matcher without losing significant preexisting alignments. Finally, two different matchers were used to get metrics and compare the results with the pairwise force brute approach.</p>
Supplementary Data: Mapping of local lattice parameter ratios by projective Kikuchi pattern matching
<p>This is the experimental dataset which was analyzed in:</p> <p>"Mapping of local lattice parameter ratios by projective Kikuchi pattern matching"<br> Aimo Winkelmann, Gert Nolze, Grzegorz Cios, and Tomasz Tokarski<br> Phys. Rev. Materials <strong>2</strong> (2018) 123803<br> https://doi.org/10.1103/PhysRevMaterials.2.123803</p> <p>We describe a lattice-based crystallographic approximation for the analysis of distorted crystal structures via electron backscatter diffraction (EBSD) in the scanning electron microscope. EBSD patterns are closely linked to local lattice parameter ratios via Kikuchi bands that indicate geometrical lattice plane projections. Based on the transformation properties of points and lines in the real projective plane, we can obtain continuous estimations of the local lattice distortion based on projectively transformed Kikuchi diffraction simulations for a reference structure. By quantitative image matching to a projective transformation model of the lattice distortion in the full solid angle of possible scattering directions, we enforce a crystallographically consistent approximation in the fitting procedure of distorted simulations to the experimentally observed diffraction patterns. As an application example, we map the locally varying tetragonality in martensite grains of steel.</p>
New Ideas for Brain Modelling 4-Figure 4. LHS relates to neuron binding ensemble mass, with central column activated. RHS relates to hierarchy, with a direct mapping. The two red lines show where the ensemble is missing and so it needs to be learned. The blue lines show extra neurons from the hierarchy back to the ensemble, but can be removed as error. The other paired black squares represent where the patterns match and can oscillate together.
<p>This paper continues the research that considers a new cognitive model based strongly on the human brain, last updated in Greer (2016). In particular, it considers figure 4 of that paper (Figure below) and how it might be useful in practice. The paper also describes some new methods in the areas of image processing and behaviour simulation. The image processing introduces a most classical form of pattern cross-referencing, while the behaviour equations used feedback for a memory-type of cross-referencing. The work is all based on earlier research by the author and the new additions are intended to fit in with the overall design. For image processing, a grid-like structure is used with ‘full linking’, if you like. Each cell in the classifier grid stores a list of all other cells it gets associated with and this is used as the learned image that new input is compared with. For the behaviour metric, a new prediction equation is suggested, as part of a simulation, that uses feedback and history to dynamically determine its current state and course of action. While the new methods are from widely different topics, both can be compared with the binary-analog type of interface that is the main focus of the paper. Sensory input may be static and binary, but cross- references result in variable comparisons that make the input more dynamic. It is suggested that the simplest of linking between a tree and ensemble can explain neural binding and variable signal strengths.</p>
Latitudinal pattern in community-wide herbivory does not match the pattern in herbivory averaged across common plant species
<p>1. The latitudinal herbivory hypothesis (LHH) predicts that plant losses to herbivores decrease from low to high latitudes. Although the LHH is a community-level hypothesis, it has been rarely tested with data on community-wide herbivory, i.e. the percentage of annual production of foliar biomass consumed by insects from all plant species at a given site. Therefore, we asked whether community-wide leaf herbivory follows the same latitudinal pattern as observed for an unweighted average of herbivory across common plant species.</p> <p>2. We selected ten study sites in boreal forests from 60°N to 69°N along 1000 km long latitudinal gradient in NW Russia. We measured relative foliar losses to insect herbivores in seven woody plant species (jointly comprising over 95% of the community-wide aboveground biomass) and estimated their current-year foliar biomass. We averaged leaf herbivory for all seven species and calculated community-wide leaf herbivory by weighting the relative foliar losses of each plant species against the contribution of that species to the annual foliar biomass production.</p> <p>3. Leaf herbivory was five-fold higher in deciduous species than in conifers. Latitudinal patterns in herbivory varied from a significant poleward decrease in all deciduous species to a significant poleward increase in Norway spruce. Herbivory values, averaged across seven plant species, decreased with latitude and followed the pattern observed in deciduous plants due to their higher foliar losses compared with conifers. By contrast, community-wide herbivory did not change with latitude. This discrepancy emerged because the proportion of deciduous plant foliage in the community increased with increasing latitude, and this increase counterbalanced the simultaneous poleward decrease in losses of these species to insects.</p> <p>4. Synthesis The herbivory measured by averaging relative losses of individual plant species and the community-wide herbivory are likely to show different latitudinal patterns in various plant communities. The contributions of plant species to the total foliar biomass production should be taken into account in studies of spatial patterns of herbivory which test community-level hypotheses. This approach may provide new insight into macroecological research on biotic interactions and improve our understanding of the role of insect herbivores in ecosystem-level processes.</p>
King Rail and Common Moorhen egg pattern matching data
<p>This dataset is a combination of egg images and processed output on pattern matching of eggshell surfaces from the images using NaturePatternMatch (NPM), additional data extracted from NPM, and field data. The data are separated into four folders based on species and analyses performed. There are two folders of scaled single egg images, one for King Rails, Rallus elegans, and one for Common Moorhens, Gallinula chloropus chloropus. Each photograph is identified by year, clutch and egg identity. Most of the Common Moorhen eggs are numbered in the order of their laying sequence, and they are further identified by laying hen. The NMDS folder includes NPM matching output and clutch identities needed to perform NMDS and PERMANOVA analyses. It includes consolidated and organized output from NPM for each species as well as files with clutch names needed to create merged datasets for graphing. These data were used to perform non-metric multidimensional scaling (NMDS) and permutational analysis of variance (PERMANOVA). The Linear Discriminant Analyses folder includes field data (egg length, width, and identity), pattern data extracted from NPM, as well as the estimated proportion of pigment measured within a scaled oval on binary images of eggs. This was used as a proxy for the relative amount of pigmentation on each egg. These data were used to conduct linear discriminant analyses for each species.</p>
Appendix for "Don't DIY: Automatically transform legacy Python code to support structural pattern matching"
<p>This is the appendix for paper "Don’t DIY: Automatically transform legacy Python code to support structural pattern matching" presented in SCAM 2022.</p> <p><strong>Abstract</strong></p> <p><em>As data becomes more and more complex as technology evolves, the need to support more complex data types in programming languages has grown. However, without proper storage and manipulation capabilities, handling such data can result in hard-to-read, difficult-to-maintain code. Therefore, programming languages continuously evolve to provide more and more ways to handle complex data. Python 3.10 introduced structural pattern matching, which serves this exact purpose: we can split complex data into relevant parts by examining its structure, and store them for later processing. Previously, we could only use the traditional conditional branching, which could have led to long chains of nested conditionals. Maintaining such code fragments can be cumbersome. In this paper, we present a complete framework to solve the aforementioned problem. Our software is capable of examining Python source code and transforming relevant conditionals into structural pattern matching. Moreover, it is able to handle nested conditionals and it is also easily extensible, thus the set of possible transformations can be easily increased.</em></p>
King Rail and Common Moorhen egg pattern matching data
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Perch choice and substrate matching to the dorsal patterns of Amphibolurus muricatus lizards
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Latitudinal pattern in community-wide herbivory does not match the pattern in herbivory averaged across common plant species
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Directed labeled multigraphs and directed labeled multigraphs enriched with information about which graph patterns match a graph and how they match a graph
<p>This dataset contains all directed labeled multigraphs that consist of one or two triples and that were generated from a set of 5 terms.</p> <p>The graphs are represented as RDF data in ntriples format.</p> <p>The graphs 1-125 consist of a single triple. The graphs 126-4625 consist of two triples.</p> <p>Each graph also exists in an enriched version, where each graph pattern that matches the graph is made explicit in the graph and it is also made explicit how it matches the graph.</p> <p>Enrichment means that for each graph pattern that matches a graph, a node is introduced that is labeled with the name of that graph pattern. Each term that occurs in that graph pattern is linked to that graph pattern node with an edge labeled "occurs-in". For each term t in the graph that can be bound to a variable v according to a match of that graph pattern an edge will be created from the node t to the graph pattern node where the edge is labeled with "bound-to-v".</p> <p>The generation of the dataset and the enrichment procedure is described in more detail in a paper that is currently under double-blind submission. We will link to the paper once it is accepted for publication.</p> <p> </p> <p>Example: the graph #100 (file 100.nt)</p> <p><http://ex.org/term/4> <http://ex.org/term/5> <http://ex.org/term/5> .</p> <p>Example: the graph #2000 (file 2000.nt)</p> <p><http://ex.org/term/2> <http://ex.org/term/2> <http://ex.org/term/3> .<br><http://ex.org/term/2> <http://ex.org/term/3> <http://ex.org/term/1> .</p> <p>Example: the enriched graph #100 (file 100-extended.nt)</p> <p><http://ex.org/term/4> <http://ex.org/term/5> <http://ex.org/term/5> .<br><http://ex.org/term/5> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-v1-t5-v2> .<br><http://ex.org/term/4> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-v1-t5-v2> .<br><http://ex.org/term/5> <http://ex.org/pattern/bound-to-v2> <http://ex.org/pattern/p-v1-t5-v2> .<br><http://ex.org/term/4> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-t4-v1-v1> .<br><http://ex.org/term/5> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-t4-v1-v1> .<br><http://ex.org/term/4> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-t4-t5-v1> .<br><http://ex.org/term/5> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-t4-t5-v1> .<br><http://ex.org/term/5> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-t4-t5-v1> .<br><http://ex.org/term/5> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-t4-v1-t5> .<br><http://ex.org/term/4> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-t4-v1-t5> .<br><http://ex.org/term/5> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-t4-v1-t5> .<br><http://ex.org/term/5> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-v1-t5-t5> .<br><http://ex.org/term/4> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-v1-t5-t5> .<br><http://ex.org/term/4> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-v1-v2-v2> .<br><http://ex.org/term/5> <http://ex.org/pattern/bound-to-v2> <http://ex.org/pattern/p-v1-v2-v2> .<br><http://ex.org/term/5> <http://ex.org/pattern/occurs_in> <http://ex.org/pattern/p-v1-v2-t5> .<br><http://ex.org/term/4> <http://ex.org/pattern/bound-to-v1> <http://ex.org/pattern/p-v1-v2-t5> .<br><http://ex.org/term/5> <http://ex.org/pattern/bound-to-v2> <http://ex.org/pattern/p-v1-v2-t5> .<br><br></p> <p>For each graph pattern exists a CSV file that lists the IDs of all graphs that are matched by that pattern.For example, the file target-p-t3-t4-v1=v1-t1-t2-graph_size_2.csv lists all those graphs that are matched by the pattern t3-t4-v1=v1-t1-t2.</p> <p>Finally, there are four JSON files:</p> <p>plain-graphs_of_size_1.json, plain-graphs_of_size_2.json, enriched-graphs_of_size_1.json, enriched-graphs_of_size_2.json </p> <p>These files contain the same graphs that are also stored in the .nt-files, but allow to conveniently read in a set of graphs at once.</p> <p> </p>
Incremental Model Transformations with Triple Graph Grammars for Multi-version Models and Multi-version Pattern Matching Evaluation Data
<p>Java abstract syntax graphs for two software development projects in non-recreating multi-version model encoding.</p>
Data for 'Indexing electron backscatter diffraction patterns with a refined template matching approach'
<p>Data for 'Indexing electron backscatter diffraction patterns with a refined template matching approach'</p> <p>Alexander Foden, T Ben Britton<br> Department of Materials, Imperial College London, Prince Consort Road, London, SW7 2AZ, UK</p> <p>For more information please contact: b.britton@imperial.ac.uk (Ben Britton) or a.foden16@imperial.ac.uk (Alex Foden)</p> <p>---</p> <p>File contains:</p> <p>High resolution image for Figures 1 - 11</p> <p>CSV data files for Figures 2, 3, 4, 5, 7 and 8. Figures 1 and 6 are illustrative and contain no data.</p> <p>EBSD data for figures 9, 10 and 11 can be found here <a href="https://zenodo.org/record/3459415#.XYym9C5KhaQ">https://zenodo.org/record/3459415#.XYym9C5KhaQ</a></p>
Data from: Colour pattern variation forms local background matching camouflage in a leaf-mimicking toad
<p>Optimal camouflage can, in principle, be relatively easily achieved in simple, homogeneous, environments where backgrounds always have the same color, brightness, and patterning. Natural environments are, however, rarely homogenous and species often find themselves viewed against varied backgrounds where the task of concealment is more challenging. One result of variable backgrounds is the evolution of intraspecific phenotypic variation which may either be generalized, with multiple similarly cryptic patterns, or specialized, with each discrete color form maximizing concealment against a single component of the background. We investigated the role of phenotypic variation in a highly variable population of the Neotropical toad <em>Rhinella margaritifera</em> using visual modeling and a computer-based detection task. We found that phenotypic variation was not divided into discrete color morphs and all toads were well camouflaged against the forest floor. However, although the whole population may appear to consist of random samples from the background, the toads were a particularly close match to the leaf litter, suggesting that they masquerade as dead leaves, which are themselves variable. Furthermore, rather than each color form being equally effective against a single background, each toad was specialized towards its own particular local surroundings, as suggested by a specialist strategy. Taken together, these data highlight the importance of background matching to a nominally masquerading species, as well as how habitat heterogeneity at multiple spatial scales may affect the evolution of camouflage and phenotypic variation.</p>
Caffeine Supplementation on Movement Patterns and Reactive Agility in Rugby Sevens Matches
ClinicalTrials.gov study NCT06612463. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Colour pattern variation forms local background matching camouflage in a leaf-mimicking toad
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Spatial and temporal variation in prey colour patterns for background-matching across a continuous heterogeneous environment
<p>In heterogeneous habitats, camouflage via background-matching can be challenging because visual characteristics can vary dramatically across small spatial scales. Additionally, temporal variation in signalling functions of colouration can affect crypsis, especially when animals use colouration seasonally for intraspecific signalling (e.g. mate selection). We currently have a poor understanding of how wild prey optimise background-matching within continuously heterogeneous habitats, and whether this is affected by requirements of intraspecific signalling across biological seasons. Here, we quantified colour patterns of a wild population of shore skink (<i>Oligosoma smithi</i>), a variably coloured lizard endemic to New Zealand, to 1) investigate whether background-matching varies across a vegetation gradient; 2) assess potential signalling functions of colour; and 3) to determine whether there is a trade-off between requirements for crypsis and intraspecific signalling in colouration across seasons. Although all pattern types occurred throughout the vegetation gradient, we found evidence for background-matching in skinks across the vegetation gradient, where dorsal brightness and pattern complexity corresponded with the proportion of vegetation cover. There was also a significant disparity between ventral colour (saturation) of juveniles and adults, and also between sexes, suggestive of sex recognition. However, there was little indication that colour was condition-dependent in adults. Despite some evidence for a potential role in signalling, crypsis did not greatly differ across seasons. Our study suggests that selection favours a mix of generalist and specialist background-matching strategies across continuously heterogeneous habitats.</p>
Data from: Accuracy of background matching and prey detection: predation by blue tits (Cyanistes caeruleus) indicates intense selection for highly matching prey colour pattern
1. Although background matching decreases prey detectability, resemblance between camouflaged prey and their visual background is seldom perfect. This could be because even a moderate resemblance might provide sufficient protection, and additional adjustment of colour pattern might give little benefit. Alternatively, close resemblance to background may not be attained due to trade-offs or constraints. To understand selection on colour patterns of camouflaged prey and the existence of inaccurate background matching, it is necessary to investigate how detectability of a colour pattern varies with its resemblance to the background. 2. We trained wild-caught blue tits (Cyanistes caeruleus) to search for artificial prey. We manipulated the resemblance of the artificial prey items to the visual backgrounds. 3. For the first half of the twelve repeated prey presentations we found a non-linear relationship between resemblance and detectability, such that for prey that had high background matching, a change in resemblance resulted in a larger change in detectability than an equal change in resemblance did for prey with lower background matching. However, for the second half of the presentations this relationship was linear. Moreover, in a two-patch-type habitat a prey pattern that was a compromise between the two different backgrounds did after few initial presentations equally well as the prey pattern that matched highly one of the backgrounds. 4. Our results indicate an intense selection for close matching in a single background. Yet, in the heterogeneous environment that consisted of two backgrounds the compromise, which only loosely resembled either background, provided good protection. Therefore, we conclude that cryptic colour patterns that bear only a loose resemblance to a given background, and thus represent inaccurate background matching, may be adaptive outcomes.
Data from: Accuracy of background matching and prey detection: predation by blue tits (Cyanistes caeruleus) indicates intense selection for highly matching prey colour pattern
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Spatial and temporal variation in prey colour patterns for background-matching across a continuous heterogeneous environment
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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