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This dataset contain the pulse responses of the Sallen-Key bandpass filter circuit and the amplifier board circuit. The test excitation is a 10 us pulse signal with an amplitude of 5 V and a frequency of 5 kHZ that exhibits abundant frequency components. By observing the pulse response, the sampling frequency is set to 5 MHz and the number of sampling points for each sample is fixed at 1000 in Case 1. PSPICE is applied for circuit simulation to set up the circuit fault according to the range of fault component parameter values.
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The scope of this challenge is development of signal processing methods for localizing a gas source using in-situ wind speed and gas concentrations measurements. The methods are designed to advance robotic olfaction and associated autonomous robotic exploration techniques -- highly relevant yet challenging problems in the context of gas source localization, environmental monitoring, and civil security, to name only a few.

Last Updated On: 
Thu, 11/28/2024 - 06:35
Citation Author(s): 
D. Shutin, A.J. Lilienthal, C. Munoz, P. Hinsen,T. Wiedemann, V. Prieto Ruiz, S. Zhang, H. Fan

The terahertz communications band in the 252 to325 GHz range has been recently explored for its potential to meet the stringent requirements for the emerging sixth generation of wireless communications. However, there are several challenges including noise and nonlinearity that hinder efficient implementations. We aim to address this limitation in terahertz communications through convolutional neural networks (CNN) enhanced by the domain knowledge from traditional Volterra filters.

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288 Views

The dataset contains Game stats for all matches in the League of Legends LEC Spring Playoffs 2024. It has 81 columns and 420 rows. Here is the description of the columns.

 

Dataset Contents:

●       Player: Name of the player.

●       Role: Role of the player (e.g., TOP, JUNGLE, MID, ADC, SUPPORT)

●       Team: Name of the player's team

●       Opponent_Team: Name of the opposing team

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405 Views

This dataset contains:

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407 Views

The dataset was gathered from a virtual learning environment course at Constantine the Philosopher University in Nitra. It includes online activity logs of 152 university students enrolled in a blended Computer Science course during the winter semester from September 25, 2023, to December 21, 2023. This course combined traditional lectures and lab sessions with online interactions and digital access to course materials via the Learning Management System Moodle platform. 

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523 Views

Seismocardiography (SCG) Signal Processing Dataset is a comprehensive collection of data samples to simulate the real-world application of the advanced technique in cardiac health monitoring. The dataset has been collected in different medical conditions of the patient in a real-time medical environment at varying timestamps. This dataset contains 1,000 samples collected over a period from 10 November 2023 to 10 January 2024, providing a robust timeframe in various conditions.

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680 Views

This dataset includes channel delay data for 5G and TSN networks.The 5G and TSN channel delay dataset includes a training set and a test set, with 600 sets of data in the training set and 200 sets of data in the test set, which are used for channel model prediction. The data in these datasets are real, collected in real-time from the running 5G-TSN system using network testers and data packet capture tools.

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667 Views

The dataset includes Pakistan most popular YouTube videos for each category from year 2021- 2023. There are two kinds of data files, one includes video statistics and other one related to comments on those videos. They are linked by the unique video_id field. Both datasets are merged in final videos file which contains all videos statistics and sentiment extracted from comments. Here’s a breakdown of each column:

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319 Views

The massive damage caused by COVID-19 worldwide over the past two years has highlighted the importance of predicting the spread of infectious diseases. Therefore, with advances in deep learning, numerous and diverse methods have been considered for predicting the spread of infectious diseases. However, these studies have shown that the long-term prediction abilities of deep learning models are insufficient to predict the course and propagation of COVID-19 outbreaks.

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