*.csv
This dataset has been measured from the User Equipment (UE) using an Automated Guided Vehicle (AGV). The collected metrics include the radio information measured by the modem, and the localization information obtained from the AGV's navigation system based on LiDAR technology.
The AGV is configured to follow a loop movement from the south to the north of the laboratory at 1 m/s speed. The BTS is a commercial cell publicly available on mmWave, but no external users were connected to mmWave during the experiments.
- Categories:
150 Views
Data Collection Period: Both datasets cover the period from July 1, 2022, to July 31, 2023. This one-year span captures a full cycle of seasonal variations, which are critical for understanding and forecasting air quality trends.
Data Characteristics
- Temporal Resolution: The data is recorded at 15-minute intervals, offering detailed temporal resolution.
- Missing Data: Both datasets contain missing values due to sensor malfunctions or communication issues. These missing values were handled using imputation techniques as part of the preprocessing phase.
- Categories:
350 Views
This csv provides the following:
- NeighbourNrInfo which indicates the RSSI recevied from the UE of the 5G stations (AP) 50, 51 or 52.
- RttInfo which indicates the RSSI recevied from the UE of the routers (AP) '3c:28:6d:b2:e2:0b', '3c:28:6d:b2:c9:1f' or '08:b4:b1:70:47:df'
- groundTruth indicates the position of the UE in that case
- Categories:
63 Views
The "Multilabel Extremism Classification Tweets Dataset" dataset contains user comments annotated with labels including toxic, severe toxic, obscene, threat, insult, and identity hate. Designed for multi-label classification, this dataset is valuable for researchers focused on detecting online extremism and toxicity across multiple languages. It enables the development of NLP models for content moderation, hate speech detection, and extremism identification.
- Categories:
178 Views
The "Multi-Label Extremism and Jihadism Classification Tweets Dataset" dataset is a multilingual resource designed for multi-label classification of online extremism and toxic behavior, including extremism and jihadism. Each comment is annotated with labels indicating the presence of various extremism traits: toxic, severe toxic, obscenity, threats, insults, identity hate, and jihadi content.
- Categories:
108 Views
The accurate distinction between line-of-sight (LOS) and non-line-of-sight (NLOS) propagation channels is paramount for precise distance measurement within ultra-wideband (UWB) indoor localization systems. In complex and dynamic environments, such as those encountered in the indoor positioning of autonomous mobile robots or vehicles, UWB signal propagation is particularly susceptible to NLOS conditions.
- Categories:
453 Views
In this paper, two datasets for text classification were primarily used in the experiments: AG News and IMDB. The AG News dataset is a widely used four-class news dataset, including four categories: World News, Sports News, Business News, and Technology News. The dataset contains a total of 120,000 samples, with 114,000 samples in the training set and the remaining 6,000 samples in the test set. The IMDB dataset is a movie review dataset used for sentiment analysis, primarily for binary classification tasks, i.e., positive and negative reviews.
- Categories:
46 Views
- Categories:
459 Views
The "Burn Depression Checklist Dataset" is a comprehensive dataset designed to aid in the analysis and understanding of depressive symptoms. The dataset is comprised of 2,600 entries, each corresponding to a unique individual, with 25 features that encapsulate various dimensions of depression, ranging from emotional and psychological symptoms to behavioral patterns.
- Categories:
799 Views
This dataset presents real measurements of radio frequency signals in a railway corridor within the Atlantic Forest in the state of São Paulo, Brazil. A transmitter antenna fixed on a pole inside the corridor was used together with an RF generator transmitting a CW signal in the 460 MHz band. A mobile receiving antenna was installed on the roof of a locomotive and connected to a spectrum analyzer, a laptop and software for data reading were used together, coupled to a GPS antenna. Thus, the measured signal was geographically recorded as the train traveled along the corridor.
- Categories:
141 Views