This dataset consists of measurements from a foot-mounted inertial measurement unit (IMU). In total, we provide data from five different test subjects travelling over more than 7.6 km. The data are combined with various forms of ground truth positioning information that can be used to evaluate the accuracy of a zero-velocity-aided, foot-mounted inertial navigation system (INS).
This dataset gives a cursory glimpse at the overall sentiment trend of the public discourse regarding the COVID-19 pandemic on Twitter. The live scatter plot of this dataset is available as The Overall Trend block at https://live.rlamsal.com.np. The trend graph reveals multiple peaks and drops that need further analysis. The n-grams during those peaks and drops can prove beneficial for better understanding the discourse.
Data are collected before and after percutaneous transluminal angiography (PTA) for dialysis patients.
Each sample is labeled as a-b-before.wav or a-b-after.wav and the associated txt, where a is the patient id and b is the location id.
The first position was the arterial-venous junction, and the second point was 3 cm from the first position along the vein.
The distances between the adjacent positions were also about 3 cm.
Considering the ongoing works in Natural Language Processing (NLP) with the Nepali language, it is evident that the use of Artificial Intelligence and NLP on this Devanagari script has still a long way to go. The Nepali language is complex in itself and requires multi-dimensional approaches for pre-processing the unstructured text and training the machines to comprehend the language competently. There seemed a need for a comprehensive Nepali language text corpus containing texts from domains such as News, Finance, Sports, Entertainment, Health, Literature, Technology.
The data are used to identify the kinematic parameters deviation of Cartesian robot, train Gaussian Process Regression (GPR) model, record the compensation result of four calibration methods under different loading conditions.
Four groups of wind speed series
Long-term 3DC Dataset as described in
Virtual Reality to Study the Gap Between Offline and Real-Time EMG-based Gesture Recognition
The dataset corresponds to the variables that affect the process of passing the sheet between rodsizer and the spooner section for a paper machine.
This data is related to the article “On the Spectral Quality of Time-Resolved CMOS SPAD-Based Raman Spectroscopy with High Fluorescence Backgrounds” that have been submitted to the IEEE Sensors Journal.
This dataset was used in the article "Dias-Audibert FL, Navarro LC, de Oliveira DN, Delafiori J, Melo CFOR, Guerreiro TM, Rosa FT, Petenuci DL, Watanabe MAE, Velloso LA, Rocha AR and Catharino RR (2020) Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers. Front. Bioeng. Biotechnol. 8:6. doi: 10.3389/fbioe.2020.00006", open access available at: https://doi.org/10.3389/fbioe.2020.00006.
