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Dataset results
150 results for “Cube”
CASSINI ORBITER SATURN UVIS SPATIAL SPECTRAL IMAGE CUBE 1.0
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
CASSINI ORBITER SATURN UVIS SPATIAL SPECTRAL IMAGE CUBE V1.3
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
CASSINI ORBITER SATURN UVIS SPATIAL SPECTRAL IMAGE CUBE 1.1
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
CASSINI SATURN CIRS CUBES RECORDS V2.0
This data set comprises uncalibrated and calibrated data from the Cassini Composite Infrared Spectrometer (CIRS) instrument. The basic data is comprised of uncalibrated raw spectra, along with along with pointing and geometry information, and housekeeping information. Also included are calibrated power spectra, and documentation.
CASSINI ORBITER SATURN UVIS SPATIAL SPECTRAL IMAGE CUBE 1.2
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
Efficient Keyword-Based Search for Top-K Cells in Text Cube
Previous studies on supporting free-form keyword queries over RDBMSs provide users with linked-structures (e.g.,a set of joined tuples) that are relevant to a given keyword query. Most of them focus on ranking individual tuples from one table or joins of multiple tables containing a set of keywords. In this paper, we study the problem of keyword search in a data cube with text-rich dimension(s) (so-called text cube). The text cube is built on a multidimensional text database, where each row is associated with some text data (a document) and other structural dimensions (attributes). A cell in the text cube aggregates a set of documents with matching attribute values in a subset of dimensions. We define a keyword-based query language and an IR-style relevance model for coring/ranking cells in the text cube. Given a keyword query, our goal is to find the top-k most relevant cells. We propose four approaches, inverted-index one-scan, document sorted-scan, bottom-up dynamic programming, and search-space ordering. The search-space ordering algorithm explores only a small portion of the text cube for finding the top-k answers, and enables early termination. Extensive experimental studies are conducted to verify the effectiveness and efficiency of the proposed approaches. Citation: B. Ding, B. Zhao, C. X. Lin, J. Han, C. Zhai, A. N. Srivastava, and N. C. Oza, “Efficient Keyword-Based Search for Top-K Cells in Text Cube,” IEEE Transactions on Knowledge and Data Engineering, 2011.
Topic Modeling for OLAP on Multidimensional Text Databases: Topic Cube and its Applications
As the amount of textual information grows explosively in various kinds of business systems, it becomes more and more desirable to analyze both structured data records and unstructured text data simultaneously. Although online analytical processing (OLAP) techniques have been proven very useful for analyzing and mining structured data, they face challenges in handling text data. On the other hand, probabilistic topic models are among the most effective approaches to latent topic analysis and mining on text data. In this paper, we study a new data model called topic cube to combine OLAP with probabilistic topic modeling and enable OLAP on the dimension of text data in a multidimensional text database. Topic cube extends the traditional data cube to cope with a topic hierarchy and stores probabilistic content measures of text documents learned through a probabilistic topic model. To materialize topic cubes efficiently, we propose two heuristic aggregations to speed up the iterative Expectation-Maximization (EM) algorithm for estimating topic models by leveraging the models learned on component data cells to choose a good starting point for iteration. Experimental results show that these heuristic aggregations are much faster than the baseline method of computing each topic cube from scratch. We also discuss some potential uses of topic cube and show sample experimental results.
GALILEO NIMS SPECTRAL IMAGE CUBES: JUPITER OPERATIONS
The natural form of imaging spectrometer data is the spectral image cube. It is normally in band sequential format, but has a dual nature. It is a series of 'images' of the target, each in a different wavelength, in ascending order. It is also a set of spectra, each at a particular line and sample, over the target area. Each spectrum describes a small portion of the area. When transformed into cubes, the data may be analyzed spatially, an image at a time, or spectrally, a spectrum at a time, or in more complex spatial-spectral fashion.
CASSINI ORBITER N/A UVIS SPATIAL SPECTRAL IMAGE CUBE 1.0
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
CASSINI ORBITER JUPITER UVIS SPATIAL SPECTRAL IMAGE CUBE 1.0
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [Cube_TiO2_NP]
GEO Series GSE157853. Mus musculus. 38 samples. Type: Expression profiling by array.
NIMS SPECTRAL IMAGE CUBES OF THE EARTH: E1 & E2 ENCOUNTERS
Unknown
NIMS SPECTRAL IMAGE CUBES OF VENUS
Unknown
NIMS SPECTRAL IMAGE CUBES OF THE EARTH: E1 & E2 ENCOUNTERS
Unknown
CASSINI ORBITER SATURN UVIS SPATIAL SPECTRAL IMAGE CUBE 1.2
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
GALILEO NIMS SPECTRAL IMAGE CUBES: JUPITER OPERATIONS
The natural form of imaging spectrometer data is the spectral image cube. It is normally in band sequential format, but has a dual nature. It is a series of 'images' of the target, each in a different wavelength, in ascending order. It is also a set of spectra, each at a particular line and sample, over the target area. Each spectrum describes a small portion of the area. When transformed into cubes, the data may be analyzed spatially, an image at a time, or spectrally, a spectrum at a time, or in more complex spatial-spectral fashion.
CASSINI ORBITER SATURN UVIS SPATIAL SPECTRAL IMAGE CUBE 1.0
Spectrographic observations of Jupiter, Saturnian rings, satellites, atmospheres and the interplanetary medium in the far and extreme ultraviolet.
CASSINI SATURN CIRS SPECTRAL CUBES RECORDS V1.0
This data set comprises uncalibrated and calibrated data from the Cassini Composite Infrared Spectrometer (CIRS) instrument. The basic data is comprised of uncalibrated raw spectra, along with along with pointing and geometry information, and housekeeping information. Also included are calibrated power spectra, and documentation.
HIRES NIMS GASPRA SPECTRAL IMAGE CUBE
This data volume contains a 17 channel spectral image cube of asteroid 951 Gaspra ranging from 0.7 to 5.2 micrometers in wavelength in cgs units of radiance. The spatial resolution of this data is 1.28 km/pixel. This data set was obtained by the Galileo spacecraft Near Infrared Mapping Spectrometer on October 29, 1991. It was radiometrically calibrated using calibration measurements obtained by the Near Infrared Mapping Spectrometer during its observations of Earth on December 9, 1990.
Workforce Information Cubes for NASA
Workforce Information Cubes for NASA, sourced from NASA's personnel/payroll system, gives data about who is working where and on what. Includes records for every civil service employee in NASA, snapshots of workforce composition as of certain dates, and data on personnel transactions, such as hires, losses and promotions. Updates occur every 2 weeks.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.