Remote sensing of environment research has explored the benefits of using synthetic aperture radar imagery systems for a wide range of land and marine applications since these systems are not affected by weather conditions and therefore are operable both daytime and nighttime. The design of image processing techniques for  synthetic aperture radar applications requires tests and validation on real and synthetic images. The GRSS benchmark database supports the desing and analysis of algorithms to deal with SAR and PolSAR data.

Last Updated On: 
Tue, 11/12/2019 - 10:38
Citation Author(s): 
Nobre, R. H.; Rodrigues, F. A. A.; Rosa, R.; Medeiros, F.N.; Feitosa, R., Estevão, A.A., Barros, A.S.

The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances.

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This paper introduces a low profile wideband Planar Inverted-F antenna (PIFA) for vehicular applications in the 5G systems (below 6GHz) and Vehicle-to-Everything (V2X) communications. The antenna covers a wide range of bandwidth that operates from 617MHz to 6GHz while having an acceptable filtering on the GNSS bands. This design’s physical dimensions and electrical performance makes it suitable for low profile wireless applications in the automotive field.

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These datasets contain bulk BTE simulation results for GaAs, InP, GaSb and InAs as a function of electric field at 300 K.

Instructions: 

To read the data we suggest to

1. un-zip the data

2. read it with e.g. the pandas library for Python or any *csv reader

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This is a large Chinese taxonomic knowledge base, which is translated from Probase by the neural network.

It has 11,292,493 IsA pairs with an accuracy of 86.6%.

 

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This is a large Chinese commonsense knowledge base, which is translated from ConceptNet 5.6, with around 2 million triples and an accuracy of 89.6%.

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This file contains the supplementary materials of the paper entitled "Meta-Path Based Gene Ontology Profiles for Predicting Drug-Disease Associations".

Instructions: 

This file contains three supplementary material files including

1. Supplementary material S1 contains the list of known drug-disease association data (*.csv).

2. Supplementary material S2 contains the supplementary figures and tables (*.pdf).

3. Supplementary material S3 contains the list of the inferred drug-disease associations (*.xlsx).

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This dataset presents the results obtained for Ingestion and Reporting layers of a Big Data architecture for processing performance management (PM) files in a mobile network. Flume was used in the Ingestion layer. Flume collected PM files from a virtual machine that replicates PM files from a 5G network element (gNodeB). Flume transferred PM files to High Distributed File System (HDFS) in XML format. Hive was used in the Reporting layer. Hive queries the raw data from HDFS. Hive queries a view from HDFS.

 

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The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at-sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, we present a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks.

Instructions: 

This repository contains the AURORA dataset, a multi sensor dataset for robotic ocean exploration.

It is accompanied by the report "AURORA, A multi sensor dataset for robotic ocean exploration", by Marco Bernardi, Brett Hosking, Chiara Petrioli, Brian J. Bett, Daniel Jones, Veerle Huvenne, Rachel Marlow, Maaten Furlong, Steve McPhail and Andrea Munafo.

Exemplar python code is provided at https://github.com/noc-mars/aurora.

 

The dataset provided in this repository includes data collected during cruise James Cook 125 (JC125) of the National Oceanography Centre, using the Autonomous Underwater Vehicle Autosub 6000. It is composed of two AUV missions: M86 and M86.

  • M86 contains a sample of multi-beam echosounder data in .all format. It also contains CTD and navigation data in .csv format.

  • M87 contains a sample of the camera and side-scan sonar data. The camera data contains 8 of 45320 images of the original dataset. The camera data are provided in .raw format (pixels are ordered in Bayer format). The size of each image is of size 2448x2048. The side-scan sonar folder contains a one ping sample of side-scan data provided in .xtf format.

  • The AUV navigation file is provided as part of the data available in each mission in .csv form.

 

The dataset is approximately 200GB in size. A smaller sample is provided at https://github.com/noc-mars/aurora_dataset_sample and contains a sample of about 200MB.

Each individual group of data (CTD, multibeam, side scan sonar, vertical camera) for each mission (M86, M87) is also available to be downloaded as a separate file. 

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This dataset is a set of eighteen directed networks that represents message exchanges among Twitter accounts during eighteen crisis events. The dataset comprises 645,339 anonymized unique user IDs and 1,396,709 edges that are labeled with respect to Plutchik's basic emotions (anger, fear, sadness, disgust, joy, trust, anticipation, and surprise) or "neutral" (if a tweet conveys no emotion).

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