Communications

Five users aged 23, 25, 31, 42, and 46 participated in the experiment. The users sat comfortably in a chair. A green LED of 1 cm diameter was placed at a distance of about 1 meter from a person's eyes. EEG signals were recorded using g.USBAmp with 16 active electrodes. The users were stimulated with flickering LED lights with frequencies: 5 Hz, 6 Hz, 7 Hz, and 8 Hz. The stimulation lasted 30 seconds. The recorded signals were divided into the data used for training, the first 20 seconds, and the data used for testing, the next 10 seconds, for each signal.

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In the digital era of the Industrial Internet of Things (IIoT), the conventional Critical Infrastructures (CIs) are transformed into smart environments with multiple benefits, such as pervasive control, self-monitoring and self-healing. However, this evolution is characterised by several cyberthreats due to the necessary presence of insecure technologies. DNP3 is an industrial communication protocol which is widely adopted in the CIs of the US. In particular, DNP3 allows the remote communication between Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA).

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81 Views

Aiming the analytical modeling of Age of Information (AoI) and Peak-AoI, uploaded codes construct and solve analytical models for Non-preemptive Bufferless, Probabilistic Generate-at-will (GAW) and Random Arrival with Single Buffer (RA-SB) servers using the theory of absorbing Markov Chains. In particular, they output per-source PAoI/AoI distributions in a setting with general number of sources where the sources may have different (i) general phase-type service time distributions, (ii) packet error probabilities and (iii) arrival rates.

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Recently, unmanned aerial vehicles (UAVs) have been receiving significant attention due to the wide range of potential application areas. To support UAV use cases with beyond visual line of sight (BVLOS) and autonomous flights,  cellular networks can provide connectivity points to UAVs and provide remote control and payload communications. However, there are limited datasets to study the coverage of cellular technologies for UAV flights at different altitudes.

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106 Views

A synthetic laser reliability dataset generated using generative  adversarial networks (GANs) is provided. The data includes normalized current measurements estimated at the following times: 2, 20, 40, 60, 80, 100, 150, 500, 1000, and 1500 hours. The data can be used to train machine learning models to solve different predictive maintenance tasks such as prediction of performance degradation, remainng useful prediction, and so on. 

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A monitoring data, which includes several OTDR traces incorporating various types of fiber events (e.g. reflective, non-reflective, merged events) induced along an optical fiber link, is provided. Different fiber faults such as fiber cut, and fiber bend are modeled using optical components such as connectors and variable optical attenuators (VOAs). The data can be used to train machine learning models for solving fiber fault diagnosis problems. 

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This data is the Federal Communication Commission (FCC) F(50,50) signal strength variation curves for the Very High Frequency (VHF) Channel 7-13 and the Ultra High Frequency (UHF) Channel 14-69. The signal strength for both curves is in dBuV/m for an Effective Radiated Power (ERP) per dipole of 1 kW. All data are based on a 9 m mobile antenna height measurement for 30 m to 600 m antenna heights within a transmitter-receiver separation ranging from 1.5 km to 100 km.

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The monitored data is obtained using the optical time domain reflectometry (OTDR) principle, which is commonly used for troubleshooting fiber optic cables or links. The data set contains raw OTDR traces that include one or two reflective events caused by the placement of one or two reflectors and/or an open physical contact (PC) at the end of the monitored optical fiber link.

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88 Views

This dataset provides wireless measurements from two industrial testbeds: iV2V (industrial Vehicle-to-Vehicle) and iV2I+ (industrial Vehicular-to-Infrastructure plus sensor).

iV2V covers 10h of sidelink communication scenarios between 3 Automated Guided Vehicles (AGVs), while iV2I+ was conducted for around 16h at an industrial site where an autonomous cleaning robot is connected to a private cellular network.

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190 Views

The dataset provides data to develop wireless sensing applications -- namely activity recognition, people identification and people counting -- leveraging Wi-Fi devices. Human movements cause modifications to the multi-path propagation of Wi-Fi signals. Such modifications reflect on the channel frequency response and, in turn, wireless sensing can be performed by analyzing the channel state information (CSI) of the Wi-Fi channel when the person/people move within the propagation environment.

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297 Views

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