This dataset is very vast and contains tweets related to COVID-19. There are 226668 unique tweet-ids in the whole dataset that ranges from December 2019 till May 2020 . The keywords that have been used to crawl the tweets are 'corona', , 'covid ' , 'sarscov2 ', 'covid19', 'coronavirus '. For getting the other 33 fields of data drop a mail at "avishekgarain@gmail.com". Twitter doesn't allow public sharing of other details related to tweet data( texts,etc.) so can't upload here.
This dataset is very vast and contains Bengali tweets related to COVID-19. There are 36117 unique tweet-ids in the whole dataset that ranges from December 2019 till May 2020 . The keywords that have been used to crawl the tweets are 'corona', , 'covid ' , 'sarscov2 ', 'covid19', 'coronavirus '. For getting the other 33 fields of data drop a mail at "avishekgarain@gmail.com". Code snippet is given in Documentation file.
This dataset is very vast and contains Spanish tweets related to COVID-19. There are 18958 unique tweet-ids in the whole dataset that ranges from December 2019 till May 2020 . The keywords that have been used to crawl the tweets are 'corona', , 'covid ' , 'sarscov2 ', 'covid19', 'coronavirus '. For getting the other 33 fields of data drop a mail at "avishekgarain@gmail.com". Code snippet is given in Documentation file.
100 Speakers each consisting of 5 voice samples for training data and 1 voice sample for testing data. Total of 600 voice samples collected in different audio formats like mpeg, mp4, mp3, ogg etc. These samples were than preprocessed and converted into .wav format. Each voice sample has a time duration of 5-10 seconds due to different lengths tuning of parameters should be done before usage. Whole Dataset size is 600mb and duration is 1 hour 40 minutes. This dataset can be used for speech synthesis, speaker identification.
100 Speakers each consisting of 5 voice samples for training data and 1 voice sample for testing data. Total of 600 voice samples collected in different audio formats like mpeg, mp4, mp3, ogg etc. These samples were than preprocessed and converted into .wav format. Each voice sample has a time duration of 5-10 seconds due to different lengths tuning of parameters should be done before usage. Whole Dataset size is 600mb and duration is 1 hour 40 minutes. This dataset can be used for speech synthesis, speaker identification.
Dataset used for "A Machine Learning Approach for Wi-Fi RTT Ranging" paper (ION ITM 2019). The dataset includes almost 30,000 Wi-Fi RTT (FTM) raw channel measurements from real-life client and access points, from an office environment. This data can be used for Time of Arrival (ToA), ranging, positioning, navigation and other types of research in Wi-Fi indoor location. The zip file includes a README file, a CSV file with the dataset and several Matlab functions to help the user plot the data and demonstrate how to estimate the range.
A Indústria enfrenta desafios graves e fracassa sem competitividade. Atacando esta problemática, conferiu-se o oferecimento de maior eficiência a processos industriais para promover a produtividade, elevar a qualidade e impulsionar mudanças. A solução desenvolvida incluiu dispositivos com sensores não invasivos, simples de instalar, que contabilizam os itens sendo transportados em linhas de produção.
This repository introduces a novel dataset for the classification of Chronic Obstructive Pulmonary Disease (COPD) patients and Healthy Controls. The Exasens dataset includes demographic information on 4 groups of saliva samples (COPD-HC-Asthma-Infected) collected in the frame of a joint research project, Exasens (https://www.leibniz-healthtech.de/en/research/projects/bmbf-project-exasens/), at the Research Center Borstel, BioMaterialBank Nord (Borstel, Germany).
The dataset is for twitter spam detection.
Imagine you just moved to your brand-new home and hired your energy provider. They tell you that based on the provided information they will set up a direct debit of €50/month. However, at the end of the year, that prediction was not quite accurate, and you end up paying a settlement amount of €300, or if you are lucky, they give you back some money. Either way, you will probably be disappointed with your energy provider and might consider moving on to another one. Predicting energy consumption is currently a key challenge for the energy industry as a whole.
