Three well-known Border Gateway Anomalies (BGP) anomalies Slammer, Nimda, and Code Red I occurred in January 2003, September 2001, and July 2001, respectively. The Reseaux IP Europeens (RIPE) BGP update messages are publicly available from the Network Coordination Centre (NCC)and contain Slammer, Nimda, Code Red I, and regular data: https://www.ripe.net/analyse/.

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Since there is no image-based personality dataset, we used the ChaLearn dataset for creating a new dataset that met the characteristics we required for this work, i.e., selfie images where only one person appears and his face is visible, labeled with the person's apparent personality in the photo.

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683 Views

These datasets are used to detect Intrusions in Controller Area Network (CAN) bus. Intrusions are detected using various Machine Learning and Deep Learning algorithms.

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The data made available are the simulations of a time-resolved Monte Carlo model for use in quantitative as well as qualitative analysis of different types of particle atmospheres.

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These CSV files contain the wearable sensor data (RIP and IMU )collected from forty subjects during multiple cigarette smoking sessions.

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BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer participants), and (2) Emotiv based Dataset (collected from 27 volunteer participants over several months in 2019). 

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A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.

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This dataset was used in the article "Dias-Audibert FL, Navarro LC, de Oliveira DN, Delafiori J, Melo CFOR, Guerreiro TM, Rosa FT, Petenuci DL, Watanabe MAE, Velloso LA, Rocha AR and Catharino RR (2020) Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers. Front. Bioeng. Biotechnol. 8:6. doi: 10.3389/fbioe.2020.00006", open access available at: https://doi.org/10.3389/fbioe.2020.00006.

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Normal
0

false
false
false

EN-US
X-NONE
AR-SA

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The dataset contains measurement results of Radar Cross Section of different Unmanned Aerial Vehicles at 26-40 GHz. The measurements have been performed fro quasi-monostatic case (when the transmitter and receiver are spatially co-located) in the anechoic chamber. The data shows how radio waves are scattered by different UAVs at the specified frequency range.

 

 

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