mni12 - Slashdot User

Submission + - Alexa, launch moon lander (amazon.com)

Submitted by mni12 on Tuesday September 25, 2018 @08:04PM

mni12 writes: Anybody interested to try out this "retro game" Amazon Alexa skill I created?
Just say "Alexa, enable moon lander".

DESCRIPTION:
Your mission is to land the Apollo 11 Lunar Module to the surface of the Moon.Alexa will help you by reading out your altitude and velocity. Houston Mission Control is also monitoring your descend using telemetry. The telemetry data is shown on your Alexa companion app or website.

HOW TO PLAY:
You control the descent by throttling the rocket engine burn."Burn 100" will give maximum 100% thrust and "Burn 0" will give you no thrust.You can use any value between 0 and 100 to control the descent velocity.

The game starts at 1000 meters with descent velocity of -50 meters/second.The maximum landing velocity is 5 meters/second and you have 75 seconds to complete the mission.If you make a successful landing, you will be added on the Leader board with your score and ranking.

TIPS:
Negative velocity means you are going down, positive velocity means you are gaining altitude

Moon's gravity on the surface is 1.625 m/s^2 — with zero burn your descent will accelerate by this amount each second

At successful landing your score = (8200 — fuel left) + 100*(75 — seconds) + 1000. * abs(velocity)

You can minimize your score by making a soft landing, and by optimizing your fuel and time usage to minimum.

Example successful landing: "Burn 100" until you reach 220 meter altitude, then "Burn 50" until 35 meters altitude, then "Burn 35" until you touch the surface.

Submission + - Ask Slashdot: How to build Morse code audio library for machine learning? (blogspot.com)

Submitted by mni12 on Thursday December 26, 2013 @11:04AM

mni12 writes: I have been working on a Bayesian Morse decoder for a while. My goal is to have a CW decoder that adapts well to different ham radio operators rhythm, sudden speed changes, signal fluctuations, interference and noise and has ability to decode Morse code accurately. While this problem is not as complex as speaker independent speech recognition there is still a lot of human variation where machine learning algorithms such as Bayesian probabilistic methods can help.

I posted first alpha release yesterday and despite all the bugs first brave ham reported success.
I would like to collect thousands of audio samples (WAV files) of real world CW traffic captured by hams via some sort of online system that would allow hams not only to upload captured files but also provide relevant details such as their callsign, date & time, frequency, radio / antenna used, software version, comments etc. I would then use these audio files to build a test library for automated tests to improve the Bayesian decoder performance.

Since my focus is on improving the decoder and not starting to build a digital audio archive service I would like to get suggestions of any open source (free) software packages, online services or any other ideas how to effectively collect large number of audio files and without putting much burden on alpha / beta testers to submit their audio captures. Many available services require registration and don't support metadata or aggregation of submissions.

Thanks in advance for your suggestions.

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