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. Sharing Twitter data other than Tweet ids publicly violates Twitter regulation policies.    

Instructions: 

The script to load data is written in documentation.

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686 Views

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. Sharing Twitter data other than Tweet ids publicly violates Twitter regulation policies.    

Instructions: 

Use the code snippet provided written in python to load data.

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389 Views

Motion platforms have been widely used in Virtual Reality (VR) systems for decades to simulate motion in virtual environments. Currently, the development of new VR immersive systems faces unique challenges to respond to user’s requirements, such as introducing high resolution 360° panoramic images and videos. This new visual information lacks the possibility of calculating the motion properties (acceleration) and makes traditional control systems for motion platforms fail.

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This data set contains all relevant 3D mold files for modeling a pancreatic phantom described in the publication:

Benjamin Eigl et al.: A Multimodal Pancreas Phantom for Computer-Assisted Surgery Training.

https://ieeexplore.ieee.org/document/9107339

Instructions: 

Please refer to the _README.txt file for further Documentation

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144 Views

The SPICE model of a ferroelectric negative capacitance - electrostatic MEMS hybrid actuator is presented. The model is validated for static pull-in and release characteristics. The simulation results are in agreement with the analytical predictions available in the literature. The model could be used for investigating the static, dynamic and load-line analysis of the hybrid actuator. The SPICE model being circuit compatible could be used along with other standard device models to evaluate various CMOS-MEMS hybrid circuits.

Instructions: 

1. Refer "Modeling Hybrid MEMS Actuator.pdf" for detailed implementation of the SPICE model in the circuit simulator.

2. Go through the "README.txt" for the instructions to simulate the hybrid actuator SPICE model in the circuit simulator using the SPICE netlist.

3. Go through the "README_Dataset.txt" for the instructions to plot the hybrid actuator characteristics using the dataset.

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138 Views

Improving performance and safety conditions on industrial sites remains a key element of the company's strategy. The major challenges require, the ability to dynamically locate people and goods on the site. Security and regulation of access to areas with different characteristics (types of tasks, level of risk or confidentiality...) are often ensured by doors or badge barriers. These means have several weaknesses when faced with inappropriate movements of people, but also an inappropriate use of objects or tools.

Instructions: 

Dataset of each position of person.

We provide two modalities :

-A motion capture system called Mocap with an millimetric accuracy -An Ultra Wide Band system (The MDEK1001 from Decawave) with a centimeter accuracy.

The dataset is composed of two '.zip' :

  1. Raw_datas_UWB_Mocap.zip : Raw datas of both UWB and Mocap in the same frame of reference. It contains each person (Rig1 to Rig6).

  2. Filtered_datas_UWB.zip : UWB datas filtered.

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The dataset is for twitter spam detection.

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226 Views

Experimental evaluation of test-driven development with interns working on a real industrial project:

   - raw experimental data: unit test, integration tests results and coverage,

   - R statistical analysis script,

   - processing scripts.

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47 Views

The Costas condition on a permutation matrix, expressed as row indices as elements of a vector c, can be expressed as A*c=b, where b is a vector of integers in which no element is zero.  A particular formulation of the matrix A allows a singular value decomposition in which the eigenvalues are squared integers and the eigenvalues may be scaled to vectors with all integer elements.  This is a database of the Costas constraint matrices A, the scaled eigenvectors, and the squared eigenvalues for orders 3 through 100.

Instructions: 

Please refer to the file CC_SVD_Database_Readme.pdf for instructions on the format of the database, and its use.  The database contains one file for each order.  The files are CSV files in which each line ends with a comma, then a plain text remark that explains that line.

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190 Views

104 participants  (54 female and 50 male) walked over a treadmill. Gait data based on 25 joint trajectories was recorded using a single Kinect V2 depth sensor placed in frontal view. We gradually increased the speed of the motorized treadmill from 0m/s to 1.2m/s. All recordings start once 1.2m/s speed is reached. After approximately 30 seconds of continuous walking, the recording stops and then the slowdown starts.

Instructions: 

The .zip file contains:

1) A .xlsx file containing important information about each participant (age,sex,height and weight)

2) A .jpg file containing an overview of the workspace.

3) 104 walking recordings (54 female and 50 male recordings) .

 Each recording has the identification code "K3"+"the participant reference number". Each recording is a time series vector organized as follows:

0.Time 

1.Shoulder Right (x,y,z)

2.Elbow Right (x,y,z)

3.Wrist Right (x,y,z)

4.Hand Right (x,y,z)

5.Hand tip Right (x,y,z)

6.Thumb Right (x,y,z)

7.Hip Right (x,y,z)

8.Knee Right (x,y,z)

9.Ankle Right (x,y,z)

10.Foot Right (x,y,z)

11.Shoulder Left (x,y,z)

12.Elbow Left (x,y,z)

13.Wrist Left (x,y,z)

14.Hand Left (x,y,z)

15.Hand tip Left (x,y,z)

16.Thumb Left (x,y,z)

17.Hip Left (x,y,z)

18.Knee Left (x,y,z)

19.Ankle Left (x,y,z)

20.Foot Left (x,y,z)

21.Head (x,y,z)

22.Neck (x,y,z)

23.Spine Shoulder (x,y,z)

24.Spine mid (x,y,z)

25.Spine Base (x,y,z)

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334 Views

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