Artificial Intelligence

This work presents a dataset based on multiple metrics namely KQIs, which provide the E2E conditions of different services. Particularly, the dataset considers video streaming and cloud gaming (CG) services. 

 

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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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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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A real-world radio frequency (RF) fingerprinting dataset for commercial off-the-shelf (COTS) Bluetooth and WiFi emitters under challenging testbed setups is presented in this dataset. The chipsets within the devices (2 laptops and 8 commercial chips) are WiFi-Bluetooth combo transceivers. The emissions are captured with a National Instruments Ettus USRP X300 radio outfitted with a UBX160 daughterboard and a VERT2450 antenna. The receiver is tuned to record a 66.67 MHz bandwidth of the spectrum centered at the 2.414 GHz frequency.

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Synthetic Digitally Modulated Signal Datasets for Automatic Modulation Classification contain CSPB.ML.2018 and CSPB.ML.2022, two high-quality communication signal datasets with eight modulation types: BPSK, QPSK, 8-PSK, pi/4-DQPSK, MSK, 16-QAM, 64-QAM, and 256-QAM. There are 14,000 signals of each modulation type in each dataset for a total of 112,000 signals per dataset. The two datasets are useful for signal processing testing, neural network (NN) training, initial NN testing, and out-of-distribution NN testing as signal generation parameters differ between the two datasets.

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Wireless Intelligence Channel (WIC) is a realistic channel data set, which is designed for deep learning research work in MIMO as well as other applications. The WIC data set is obtained directly through commercial BSs and a device capable of data acquisition that is similar to a commercial terminal. The scene selection and parameter configuration involved in the experiment are based on the characteristics of realistic scenarios and the existing configurations in commercial BSs, without assumptions and restrictions on the ideal experimental conditions.

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The integration of communication and artificial intelligence has become a development trend, one of the applications is semantic communication, but the current research lacks the support of comprehensive datasets. To solve this problem, we built a new image and video dataset, named SCO dataset, for the researches on semantic communication and computing. First, we introduce the peculiarities of the dataset, which contains 5100 images and 138 video clips. Secondly, we we give the data generation and processing methods of the dataset, including images and videos.

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Rainfall Runoff _ Mahaweli River

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KDD-CUP99 standard intrusion detection dataset

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Sign languages are the most common mode of communication with and between hearing-impaired individuals. In the Arab world, Arabic sign language is used with different dialects supporting a distinct set of rules for the gestures used. With research on natural language processing advancing, models have been developed to translate sign language to spoken language and vice versa. However, Arabic sign language has rarely been studied due to the lack of availability of datasets dealing with Arabic sign language.

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