Machine Learning

This article presents the details of the Cardinal RF (CardRF) dataset. CardRF is acquired to foster research in RF- based UAV detection and identification or RF fingerprinting. RF signals were collected from UAV controllers, UAV, Bluetooth, and Wi-Fi devices. Signals are collected at both visual line-of-sight and beyond-line-of-sight. The assumptions and procedure for the data acquisition are presented. A detailed explanation of how the data can be utilized is discussed. CardRF is over 65 GB in storage memory.

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Solar Insecticidal Lamp, as a professional device for smart phytoprotection, can kill the insects to calculate the insect density, further guiding the famers to spray pesticide accurately. Various experiments were performed by a testbed, combined Solar Insecticidal Lamp with two cameras, to get the dataset including time, Pulse Number of Insecticidal Sounds, Pulse Number of Insecticidal Discharges, insecticidal status, abnormal value, and insecticidal quantity. The dataset can be used for a variety of methods related to the research of insecticidal counting.

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This dataset is Bill Proposal History of the Republic of Korea 20th National Assembly(2016-2020) Lawmakers. This dataset consists of 21,594 rows with 37 columns. Contents are mainly written in korean, so translation will be needed for foreign researchers. If any further instruction or information is needed, contact by minhan.nick.cho@gmail.com.

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Please cite the following paper when using this dataset:

N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049

Abstract

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According to recent statistics released by the California Department of Forestry and Fire Protection (CAL FIRE), in the year 2020, 8112 fire incidents were reported, resulting in damaging approximately 1.4 million acres of land in California

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Glacial lake outburst floods (GLOFs) are a major threat to the local communities and important infrastructures in the high mountain regions. Early detection of glacial lakes can prevent these disastrous events. Towards this end, we collected Sentinel 2 true color scenes of High-Mountain Asia (HMA) region using glacial lakes inventory of this region. It covers an area of 2080.12 km2 with nearly 30,121 glacial lakes. After data collection, we retained 1200 cloud free true color images and manually generated their ground truth masks.

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This dataset contains pipe images straight, right and left curves to support AUV navigation based on image.

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Please cite the following paper when using this dataset:

N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109

Abstract

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In this study, a primary IMU-based gait dataset has been collected from 30 participants using a MOTI goniometer. This device collects movement data related to specific joints depending on the location of the device. The MOTI sensor contains an IMU consisting of an accelerometer, gyroscope, and magnetometer. Accelerometers measure acceleration the acceleration of the device, gyroscopes measure angular velocity of the device, and magnetometers measure the magnetic field of the Earth. In our study, the device was attached to arm and leg (thigh) positions.

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# Datasets

The datasets were collected from a software based simulation environment simulating a small scale IEC 61850 compliant substation with both the primary plant and the process bus.

 

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