d3-smartphone-walking | dimensional data and found some interesting sets
kandi X-RAY | d3-smartphone-walking Summary
kandi X-RAY | d3-smartphone-walking Summary
d3-smartphone-walking is a JavaScript library. d3-smartphone-walking has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
I wanted to try and visualize some multi-dimensional data and found some interesting sets at the UCI Machine Learning Repository, from an academic study on user verification using biometric walking patterns. The x, y and z dimension accelerometer outputs can be displayed with three graphs and by using a heat-trace over time a distinct signature for each user is plotted. The smartphone in your pocket can do more than just register your position with GPS or wifi (and send it back to who knows who?), most these days have built in accelerometers that can measure change in movement in three axes. In the study visualized below mobile phones were placed in the users' breastpockets and a simple course followed while data from the phone's accelerometers was recorded. The red, green and blue dots show a heat-trace for three individuals of accelerometer output over the time-trial, clearly showing their individual 'walking signature'.
I wanted to try and visualize some multi-dimensional data and found some interesting sets at the UCI Machine Learning Repository, from an academic study on user verification using biometric walking patterns. The x, y and z dimension accelerometer outputs can be displayed with three graphs and by using a heat-trace over time a distinct signature for each user is plotted. The smartphone in your pocket can do more than just register your position with GPS or wifi (and send it back to who knows who?), most these days have built in accelerometers that can measure change in movement in three axes. In the study visualized below mobile phones were placed in the users' breastpockets and a simple course followed while data from the phone's accelerometers was recorded. The red, green and blue dots show a heat-trace for three individuals of accelerometer output over the time-trial, clearly showing their individual 'walking signature'.
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Support
d3-smartphone-walking has a low active ecosystem.
It has 15 star(s) with 8 fork(s). There are 3 watchers for this library.
It had no major release in the last 6 months.
d3-smartphone-walking has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of d3-smartphone-walking is current.
Quality
d3-smartphone-walking has 0 bugs and 0 code smells.
Security
d3-smartphone-walking has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
d3-smartphone-walking code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
d3-smartphone-walking does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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d3-smartphone-walking releases are not available. You will need to build from source code and install.
Installation instructions are not available. Examples and code snippets are available.
d3-smartphone-walking saves you 24 person hours of effort in developing the same functionality from scratch.
It has 67 lines of code, 0 functions and 4 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of d3-smartphone-walking
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of d3-smartphone-walking
d3-smartphone-walking Key Features
No Key Features are available at this moment for d3-smartphone-walking.
d3-smartphone-walking Examples and Code Snippets
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Vulnerabilities
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