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16 results for “Map matching”
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>
Ground truth matches between maps with high disparity
<p>File describing the correct matches between the region of sketch maps and their model map, or between partial sensor built maps.</p> <p>The region were built using MAORIS segmentation algorithm</p>
Dataset for testing and training map-matching methods
<p>We present a dataset for testing, bench-marking, and offline learning of map-matching algorithms. For the first time, a large enough dataset is available to prove or disprove map-matching hypotheses on a world-wide scale. There are several hundred map-matching algorithms published in literature, each tested only on a limited scale due to difficulties in collecting truly large scale data. Our contribution aims to provide a convenient gold standard to compare various map-matching algorithms between each other. Moreover, as many state-of-the-art map-matching algorithms are based on techniques that require offline learning, our dataset can be readily used as the training set. Because of the global coverage of our dataset, learning does not have to be be biased to the part of the world where the algorithm was tested.</p>
Lung-MAP: Nivolumab With or Without Ipilimumab as Second-Line Therapy in Treating Patients With Recurrent Stage IV Squamous Cell Lung Cancer and No Matching Biomarkers
ClinicalTrials.gov study NCT02785952. IPD Sharing: Not stated. Countries: 2. Publications: 2.
Gridded maps of global population scaled to match the 2023 Wittgenstein Center (WIC) Population projections
<p>The gridded population data used for calculating exposed populations is based on the population projections from the original SSPs (KC and Lutz, 2017) which were subsequently gridded (Jones and O’Neill, 2016). These gridded projections were aggregated to 0.5 ° spatial resolution and then scaled to match the latest available projections for population in line with the updated SSPs, v3.0 (KC <em>et al.</em>, 2024). The scaling is done on a country basis for all countries included in the latest SSP projections. Countries, which are not included in these projections, remain unchanged. The scaling process is done on a country-level basis using the following step:<br> </p> <ol> <li>The total population for the original gridded data is calculated using the ISIMIP fractional country raster (Perrette, 2023), excluding border cells containing contributions from more than one country.</li> <li>The population of the fractional border cells is subtracted from the total population of the SSP population projections and the required scalar to match the population from the gridded data to the SSP population projections is calculated.</li> <li>This scalar is applied to all non-fractional cells. </li> </ol> <p>While it is possible to calculate the scalar for each country including the proportion of the population in the fractional border cells, this would require the scalar to also be applied to that proportion of the population in the border cells to match the overall population number for each country. Applying different scalars to the population proportions for each country in the same cell would, however, change the ratios of the population in the fractional border cells and subsequently lead to skewed results when reapplying the fractional country raster to the scaled data for the aggregation to country level. For small countries, where more population lives in fractional border cells than in non-border cells, and for countries that only consist of border cells with contributions from more than one country, all cells were used in the scaling process. <br><br>It should be noted that some smaller countries cannot be scaled properly and that the latest SSP population projections do not contain values for all countries. Since there has been no release of updated gridded population projections yet, the gridded population data created using this approach still provide the closest match to the latest SSP population projections currently available.</p>
Figure S1. Fusion map of propensity score matching for high-risk and very high-risk patient.
<p>Figure S1. Fusion map of propensity score matching for high-risk and very high-risk patient.</p>
New Ways of Mapping Knowledge Organization Systems. Using a SemiAutomatic MatchingProcedure for Building Up Vocabulary Crosswalks
<p>Abstract: Crosswalks between different vocabularies are an indispensable prerequisite for integrated and high­quality search scenarios in distributed data environments. Offered through the web and linked with each other they act as a central link so that users could move back and forth between different data sources being online available.<br> In the past, crosswalks between different thesauri have been primarily developed manually. In the long run the intellectual updating of such crosswalks requires huge personnel expenses. Therefore, an integration of automatic matching procedures, as for example Ontology Matching Tools, seems pretty obvious.<br> On the basis of computer­generated correspondences between the Thesaurus for Economics (STW) and the Thesaurus for the Social Sciences (TheSoz) our contribution will explore cross­border approaches between IT­assisted tools and procedures on the one hand<br> and external quality measurements via domain experts on the other hand. Thus, we will present techniques to semi­automatically perform vocabulary crosswalks. Due to intellectually evaluated results of multiple matching tools in the forerun, quality statements concerning the reliability of further computer­generated crosswalks can be made. This way, the application of various tools and procedures gradually contributes to an increase in quality. Moreover, on the long­term it facilitates a continuous update of high­quality vocabulary crosswalks.</p>
Lung-MAP: Durvalumab as Second-Line Therapy in Treating Patients With Recurrent Stage IV Squamous Cell Lung Cancer and No Matching Biomarkers
ClinicalTrials.gov study NCT02766335. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Ramucirumab and Pembrolizumab Versus Standard of Care in Treating Patients With Stage IV or Recurrent Non-small Cell Lung Cancer (A Lung-MAP Non-Match Treatment Trial)
ClinicalTrials.gov study NCT03971474. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Lung-MAP: Taselisib as Therapy in Treating Patients With Stage IV Squamous Cell Lung Cancer and Positive Biomarker Matches
ClinicalTrials.gov study NCT02785913. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Lane-level localization and map matching for advanced CAV applications
Open the record for dataset details and reuse information.
Genome-wide maps of H3K36me3 in ccRCC and RNA-seq of matched nephrectomy samples
GEO Series GSE69198. Homo sapiens. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Genome-wide chromatin interaction maps of enhancer-promoter and promoter-promoter contacts in 5 leiomyoma (MED12 G44 mutant) and 5 matched normal myometrium (WT) patient tissue samples.
GEO Series GSE128234. Homo sapiens. 10 samples. Type: Other.
Genome-wide maps of chromatin state, transcription factor and cofactor occupancy in 5 leiomyoma (MED12 G44 mutant) and 5 matched normal myometrium (WT) patient tissue samples.
GEO Series GSE128230. Homo sapiens. 80 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Genome-wide maps of H3K27ac and H3K4me1 in primary normal fibroblasts and matched cancer-associated fibroblasts
GEO Series GSE196348. Homo sapiens. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.